The aim of this document is to provide practical guidance on the choice of target difference used in the sample size calculation of a randomised controlled trial (RCT). Guidance is provided with a definitive trial, one that seeks to provide a useful answer, in mind and not those of a more exploratory nature. The term “target difference” is taken throughout to refer to the difference that is used in the sample size calculation (the one that the study formally “targets”). Please see the glossary for definitions and clarification with regards other relevant concepts. In order to address the specification of the target difference, it is appropriate, and to some degree necessary, to touch on related statistical aspects of conducting a sample size calculation. Generally the discussion of other aspects and more technical details is kept to a minimum, with more technical aspects covered in the appendices and referencing of relevant sources provided for further reading.The main body of this guidance assumes a standard RCT design is used; formally, this can be described as a two-arm parallel-group superiority trial. Most RCTs test for superiority of the interventions, that is, whether or not one of the interventions is superior to the other (See Box 1 for a formal definition of superiority, and of the two most common alternative approaches). Some common alternative trial designs are considered in Appendix 3. Additionally, it is assumed in the main body of the text that the conventional (Neyman-Pearson) approach to the sample size calculation of an RCT is being used. Other approaches (Bayesian, precision and value of information) are briefly considered in Appendix 2 with reference to the specification of the target difference.

Nanopeening treatment was applied to the AISI 420 steel to decrease its sensitivity to the tribocorrosion damage. Microstructural investigation highlighted that the Nanopeening treatment led to a high plastic deformation and nanostructured surface layer with 110 µm depth. . In order to study the combined effect of corrosion and mechanical wear, tribocorrosion tests were performed on non–treated and nanopeened samples in boric acid and lithium hydroxide solution, considering both continuous and intermittent sliding. It was found that the AISI 420 steel is sensitive the synergism between mechanical friction and electrochemical corrosion with a domination of abrasive wear. Adhesive wear was also detected in the wear track. Indeed, the mechanical wear was pronounced under intermittent sliding because of hard wear debris generation from the repassivated layer during rotating time. The Nanopeening treatment led to enhance mechanical performance and corrosion properties. Such improvement could be explained by the high plastic deformation resulting in the nano-structuration of grains and increasing hardness of AISI 420 steel.

Although researchers have proposed various indentation size effect (ISE) models, these models often involve different form and number of parameters that can make our wonder which is the best in existed ISE models. Three types of ISE test data, namely, normal ISE, reverse ISE and transition of normal to reverse ISE, are used to evaluate the sixteen ISE models. The comparatively study indicates that H-J, N-G-Fs, N-G-H, N-G-A and N-G-Qs models can accurately predict the normal ISE. The reason for this is that the friction stress that is not related to dislocation activities or the indentation size effect of plastic zone has been introduced into these models. Therefore, these two factors should be considered in future ISE models. The sixteen ISE models are originally proposed to describe the normal ISE of different materials. However, to our surprise, some of these models are able to capture the reverse ISE and the transition of normal to reverse ISE of different materials. The determination coefficients (DC) of the sixteen ISE models are also determined for different materials. For reverse ISE, the highest DC value for NiCSi, TC4 and PED Ni are given by the EXP, N-G-Fs and N-G-A models, respectively. For the transition of normal to reverse ISE, the N-G-YC, N-G-Fs, and N-G-H models produce the maximum DC for ZrO2, Cu and Y2O3-ZrO2, respectively. Moreover, the mean DC of the N-G-Fs model is the maximum among the sixteen ISE models, followed by the N-G-H model, but they cannot accurately predict the reverse ISE. Therefore, the N-G-Fs and N-G-H models should be further modified to accurately predict the reverse ISE.

In this study, the model proposed by Yang et al. to generalize the stress–strain model for unconfined concrete with consideration of the size effect is expanded. Sim et al.’s compressive strength model that is based on the function of specimen width and aspect ratio was used for the maximum stress. In addition, a strain at the maximum stress was formulated as a function of compressive strength by considering the size effect using the regression analysis of datasets compiled from a wide variety of specimens. The descending branch after the peak stress was formulated with consideration of less dissipated area of fracture energy with the increase in specimen width and aspect ratio in the compression damage zone (CDZ) model. The key parameter for the slope of the descending branch was formulated as a function of specimen width and aspect ratio, concrete density, and compressive strength of concrete considering the size effect. Consequently, a rational stress–strain model for unconfined concrete was proposed. This model explains the trends of the peak stress and strain at the peak stress to decrease and the slope of the descending branch to increase, as the specimen width and aspect ratio increase. The proposed model agrees well with the test results, irrespective of the compressive strength of concrete, concrete type, specimen width and aspect ratio. In particular, the proposed model for the stress–strain curve rationally considered the effect of decreasing peak stress and increasing the descending branch slope, with the increase in specimen width and aspect ratio.

The fast spread of COVID-19 constitutes a worldwide challenge to the public health, educational, and trade systems, affecting the overall wellbeing of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Thus, it is of general interest to consider the validity of the proposal for keeping a social distancing of at least 2 m from other persons to avoid the spread of COVID-19. The exposure to the bioaerosol can result in the deposition of the pathogen in the respiratory tract of the host causing disease and an immunological response. In the atmospheric context, the work evaluates the effect of aerodynamic diameter (size) of particles in carrying RNA copies of the novel coronavirus. A SARS-CoV-2 carrier person talking, sneezing, or coughing at distance of 2 m can still provide a pathogenic bioaerosol load with submicron particles that remain viable in air for up to 3 hours for exposure of healthy persons near and far from the source in a stagnant environment. The deposited bioaerosol creates contaminated surfaces, which if touched can act as a path to introduce the pathogen by mouth, nose, or eyes and cause disease.

Thermal shape memory polymers (SMPs) find increasing applications in biology and medicine due to their promising potential for improved biocompatibility. In such applications, the inevitable penetration of small molecules from the ambient fluid into the polymer influences the shape recovery process and often leads to a reduction of the temperature, at which shape recovery takes place. We show here via molecular dynamics simulations that the size of additive molecules plays a key role for this process. While the effect of concentration on the recovery rate is monotonic in the investigated range, a non-monotonic dependence on the size of additive molecules emerges at temperatures close to the glass transition. This work thus identifies the additives’ size to be a qualitatively novel parameter for switching the recovery process in polymer-based shape memory materials.

The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. In order to achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.

In this work, TiO₂ QDs modifed NiO nanosheets was employed to imporve the room-temperature NO₂ sensing properties of NiO. The gas-sensing studies showed that the response of nanocomposites with the optimal ratio to 60 ppm NO₂ was nearly 10 times larger than that of bare NiO, exhibiting potential application in gas-sensing. Considering the commonly reported immature mechanism that the effective charge transfer between two phases contribute to enhanced sensitivity, QDs sensitization mechanism was further detailed by designing a seirs of contrast experiments. First, the important role of QDs size effect was revealed by comparing a little enhanced sensitivity of TiO₂ particle-modified NiO with largely enhanced senstivity of TiO₂ QDs-NiO. Second, and more important, the direct evidence of heterointerface charge transfer efficiency was detailed by extracted interface bond (Ti-O-Ni) using XPS peak fitting. We hope this work can provide guideline to design more QDs-modified nanocomposites with the higher sensitivty for practical application.

Silver nanoparticles (AgNPs) have been demonstrated to restrain bacterial growth while maintaining the minimal risk in development of bacterial resistance and human cell toxicity that conventional silver compounds exhibit. Several physical and chemical methods have been reported to synthesize AgNPs. However, these methods are expensive and involve heavy chemical reduction agents. An alternative approach to produce AgNPs in a cost-effective and environmentally friendly way employs a biological pathway using various plant extracts to reduce metal ions. The size control issue and the stability of nanoparticles remain some of the latest challenges in such methods. In this study, we used two different concentrations of fresh leaf extract of the plant Arbutus Unedo (LEA) as a reducing and stabilizing agent to produce two size variations of AgNPs. UV-Vis spectroscopy, Dynamic Light Scattering, Transmission Electron Microscopy and zeta potential were applied for the characterization of AgNPs. Both AgNP variations were evaluated for their antibacterial efficacy against the gram-negative species Escherichia coli and Pseudomonas aeruginosa, as well as the gram-positive species Bacillus subtilis and Staphylococcus epidermidis. Although significant differences have been achieved in the nanoparticles’ size by varying the plant extract concentration during synthesis, the antibacterial effect was almost similar.

This study aimed to decrease the particle size of ginseng by roasting and cryogenic milling to increase its water solubility and physiological activity. The samples were roasted for different times (9–21 min) and generated in different sizes (10–50, and > 50 μm). All roasted samples revealed significantly smaller particle sizes than did non-roasted samples based on Sauter mean diameter (D [3,2], p < 0.05). Further, the particle sizes of roasted samples decreased till roasting up to 15 min. In terms of the water solubility index (WSI), antioxidant activity, total polyphenol content (TPC), and total polysaccharides according to particle size, 10-20 μm-sized samples showed the highest values when compared with >50 μm-sized samples. Based on roasting time, WSI values of all samples roasted for up to 15 min were higher than those of the control (not roasted) (p < 0.05). Antioxidant activity and TPC also increased with increasing roasting time. Total polysaccharide content was the highest upon roasting for 15 min except for the 10-20 μm sample. Ginsenoside content of roasted samples >20 μm size was higher than that of the control (not roasted) except after 15 min of roasting. Therefore, roasting and cryogenic milling are effective in producing ginseng root powder.

In our previous works we have proposed design equations that can predict with reasonable accuracy the transition point from homogeneous to heterogeneous regime as well as the gas holdup and the mean Sauter diameter at the homogeneous regime. The validity of the proposed correlations was checked with data obtained using different geometrical configurations and several Newtonian and non-Newtonian liquids as well as the addition of surfactants. However, in all the experiments the gas phase was atmospheric air. This work investigates the effect of gas phase properties by conducting experiments employing various gases (i.e., air, CO₂, He) that cover a wide range of physical property values. Experiments revealed that only the use of low-density gas (He) has a measurable effect on bubble column performance. More precisely, when the low-density gas (He) is employed, the transition point shifts to higher gas flow rates and the gas holdup decreases, a fact attributed to the lower momentum force exerted by the gas. In view of the new data, the proposed correlations have been slightly modified to include the effect of gas phase properties and it is found that they can predict the aforementioned quantities with an accuracy of ±15%. It has been also proved that CFD simulations are an accurate means for assessing the flow characteristics inside a bubble column.

Exploring the effect of the sample size on the estimation accuracy of airborne LiDAR forest attributes in a large-scale area can help in optimizing the technical application scheme of operational ALS-based large-scale forest stand inventories. In our study, sample datasets composed of different sample plots were constructed by repeated sampling from 1003 sample plots in a subtropical study area covering 2376 × 103 km2. Sixteen multiplicative power models were built in each forest type consisting of four forest attributes. Through these models, the variations of standard deviation (SD) and coefficient of variation (CV) of R2 and rRMSE of forest attribute estimation models for different quantity levels of sample plots were also analyzed. The results showed that, first, when the sample size increased from 30 to the top limit, the SD of the forest attributes and LiDAR variables showed a decreasing trend. Second, as the sample size increased, the rRMSE of the 16 forest attribute estimation models gradually decreased, while the R2 gradually increased. Third, when the sample size was small, both the SD of R2 and rRMSE of the models were large, and the SD of R2 and rRMSE gradually decreased as the sample size increased. In 50 models conducted for each attribute at the same sample size, for the mean standard deviations of forest attributes, the ten best performing models were lower than those of the total 50 models, and the worst ten models were the opposite. When the sample size increased, the accuracy of each forest attribute estimation model for each forest type gradually improved. The variation of forest attributes and the LiDAR variable of the construction model are critical factors that affect the model’s accuracy. To efficiently apply airborne LiDAR in order to survey large-scale subtropical forest resources, the sample size of the Chinese fir forest, pine forest, eucalyptus forest, and broad-leaved forest should be 110, 80, 85, and 70, respectively.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

Loess is a special soil with high water sensitivity, which covers a large area in northwest China. Cracks are prone to generate in loess under the arid and semi-arid climate, which will provide the preferential channel for water and reduce the mechanical properties of soils. It is of great significance to understand the evolution characteristics and mechanisms of the cracks in loess areas. At present, the researches on cracks in soils are mainly concentrated in the characteristics of different cracking patterns. However, the spacing cracks are mostly discussed in materials like rock and concrete, rather than soils. The cracking characteristics and mechanisms of spacing cracks in loess is still inadequate. In this research, the drying tests of loess are carried out with different sizes of specimens. The parameters of spacing cracks and local strain distributions of the loess samples are obtained via PCAS and DIC methods during desiccation, respectively. The cracking modes, space cracking laws like insertion and saturation of spacing cracks are revealed. Finally, the size effect on the characteristics of spacing cracks is verified with a discrete element software MatDEM.

Size effect on plain concrete specimens is well known and can be correctly captured when performing numerical simulations by using a well characterised softening function, but in the case of fibre reinforced concrete this is not directly applicable, since an only diagram cannot capture the material behaviour on elements with different size due to dependence of the orientation factor of the fibres with the size of the specimen. In previous works, the use of a trilinear softening diagram proved to be very convenient for reproducing fracture of polyolefin fibre reinforced concrete elements, but only if it is previously adapted for each specimen size. In this work, a predictive methodology is used to reproduce fracture of polyolefin fibre reinforced concrete specimens of different sizes under three-point bending. Fracture is reproduced by means of a well known embedded cohesive model, with a trilinear softening function that is defined specifically for each specimen size. The fundamental points of these softening functions are defined a priori by using empirical expressions proposed in past works, based on an extensive experimental background. Therefore, the numerical results are obtained in a predictive manner, and then compared with a previous experimental campaign, showing that this approach properly captures the size effect, although some values of the fundamental points in the trilinear diagram could be defined more accurately.

To facilitate the computation of the uniaxial compressive strength value of the cemented paste backfill under the condition of high sand-cement ratio, and to analyze the size effect of the cemented paste backfill with high sand-cement ratio under varied aspect ratios, the cemented paste backfill specimens with sand-cement ratios of 8:1-24:1 and aspect ratios of 0.5, 1, and 2 were prepared. Through response surface experiments and finite element analysis, the influence of three aspect ratios on the cemented paste backfill strength was explored, and the failure characteristics and size effect mechanisms of cemented paste backfill with various aspect ratios were analyzed. The model of strength conversion between cemented paste backfill with different aspect ratios was established. The results show that the compressive strength of the cemented paste backfill decreases with the increase of the aspect ratio under the same mass concentration and sand-cement ratio. When the aspect ratio is 0.5 and 1, the splitting failure is the main factor; when the aspect ratio is 2, the shearing failure is the main factor. The three-dimensional stress caused by the end effect of the cemented paste backfill is the main reason for the high strength when the aspect ratio is 0.5. Due to the one-dimensional stress zone generated in the middle of the cemented paste backfill with an aspect ratio of 2 in the laboratory, its strength value is closer to the actual uniaxial compressive strength value of the cemented paste backfill. The strength values of the cemented paste backfill with aspect ratios of 0.5 and 1 were higher than the actual uniaxial compressive strength values in the laboratory. The rationality of the theoretical analysis was verified by the ABAQUS analysis results. According to the experimental results, a strength conversion model between different aspect ratios is established, which can provide a reference for the design of the uniaxial compressive strength of the cemented paste backfill.

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.

This study aims to model grinding of a Polish slag and evaluate the particle size distributions of the products obtained after different grinding times. Then, selected products were alkali activated in order to investigate the effect of particle size on the compressive strength of the produced alkali activated materials (AAMs). Other parameters affecting alkali activation, i.e. temperature, curing and ageing time were also examined. Among the different mathematical models used to simulate the particle size distribution, Rosin-Rammler (RR) was found to be the most suitable. When piecewise regression analysis was applied to experimental data it was found that the particle size distribution of the slag products exhibits multi fractal character. In addition, grinding of slag exhibits non-first-order behavior and the reduction rate of each size is time dependent. The grinding rate and consequently the grinding efficiency increases when the particle size increases, but drops sharply near zero after prolonged grinding periods. Regarding alkali activation, it is deduced that among the parameters studied, particle size (and the respective specific surface area) of the raw slag product and curing temperature have the most noticeable impact on the compressive strength of the produced AAMs.

A novel gas-phase electrocatalytic system based on a low-temperature proton exchange membrane (Sterion) was developed for the gas phase electrocatalytic conversion of CO2 to liquid fuels. This system achieved gas-phase electrocatalytic reduction of CO2 at low temperatures (below 90 ºC) over a Cu cathode by using water electrolysis-derived protons generated in-situ on an IrO2 anode. Three Cu-based cathodes with varying metal particle sizes were prepared by supporting this metal on an activated carbon at three loadings (50, 20, and 10 wt%; 50%Cu-AC, 20%Cu-AC, and 10%Cu-AC, respectively). The cathodes were characterized by N2 adsorption–desorption, temperature-programmed reduction (TPR), and X-ray diffraction (XRD) whereas their performance towards the electrocatalytic conversion of CO2 was subsequently studied. The membrane electrode assembly (MEA) containing the cathode with the largest Cu particle size (50%Cu-AC, 40 nm) showed the highest CO2 electrocatalytic activity per mole of Cu, with methyl formate being the main product. This higher electrocatalytic activity was attributed to the lower Cu–CO bonding strength over large Cu particles. Different product distributions were obtained over 20%Cu-AC and 10%Cu-AC, with acetaldehyde and methanol being the main reaction products, respectively. The CO2 consumption rate increased with the applied current and the reaction temperature.

The bimodal grain-size distribution 0.9KNbO₃-0.1BaTiO₃ ceramics, with a typical perovskite structure in tetragonal phase at room temperature, were successfully prepared by an induced abnormal grain growth (IAGG) method at a relatively low sintering temperature. In this bimodal grain-sized distribution structure, the extra-large grains (about 10‒50 μm) were evolved from the micron-sized filler powders and the fine grains (about 0.05‒0.35 μm) were derived from the sol precursor matrix. The 0.9KNbO₃-0.1BaTiO₃ ceramics exhibit relaxor-like behavior with the diffused phase transition near room temperature, and confirmed by the existence of the polar nanodomain regions (PNRs) using the HRTEM images. The large room-temperature electrocaloric (EC) effect was found, characterized by an adiabatic temperature drop of 1.5 K, an isothermal entropy change of 2.48 J kg^-1 K^-1, and high EC strengths of ïDT/DEï = 1.50×10^-6 KmV^-1 and DS/DE = 2.48×10^-6 Jmkg^-1K^-1V^-1directly measured under E = 1.0 MV/m. These excellent ECEs demonstrate that this simple IAGG method is highly appreciated for synthesizing high-performance EC materials for efficient cooling devices.

In this investigation, the impact of reducing agent concentration on the synthesis of zinc oxide nanoparticles was examined. During the synthesis, an assessment of ionic conductivity was carried out, revealing a significant increase in conductivity prior to the introduction of the reducing agent, followed by a sharp decrease upon its addition. Characterization of the ZnO NPs involved UV-visible spectroscopy, scanning electron microscopy, Fourier Infrared Spectroscopy, and X-Ray Diffraction analysis. The outcomes suggest that the characteristics of the ZnO NPs are influenced by the concentration of the reducing agent during the synthesis process. Notably, the ZnO NPs synthesized with a higher concentration of reducing agent exhibited a narrower optical band gap and increased surface energy. Furthermore, employing a concentration of 0.5 v/v resulted in the rapid production of nanoparticles with relatively uniform sizes. Conversely, concentrations below 0.5 v/v lead to slow formation, while concentrations exceeding 0.5 v/v yielded non-uniform nanoparticles.

Evidence-based medicine (EBM) is in crisis, in part due to bad methods, which are understood as misuse of statistics that is considered correct in itself. This article exposes two related common misconceptions in statistics, the effect size (ES) based on correlation (CBES) and a misconception of contingency tables (MCT). CBES is a fallacy based on misunderstanding of correlation and ES and confusion with 2 × 2 tables, which makes no distinction between gross crosstabs (GCTs) and contingency tables (CTs). This leads to misapplication of Pearson’s Phi, designed for CTs, to GCTs and confusion of the resulting gross Pearson Phi, or mean-square effect half-size, with the implied Pearson mean square contingency coefficient. Generalizing this binary fallacy to continuous data and the correlation in general (Pearson’s r) resulted in flawed equations directly expressing ES in terms of the correlation coefficient, which is impossible without including covariance, so these equations and the whole CBES concept are fundamentally wrong. MCT is a series of related misconceptions due to confusion with 2 × 2 tables and misapplication of related statistics. The misconceptions are threatening because most of the findings from contingency tables, including CBES-based meta-analyses, can be misleading. Problems arising from these fallacies are discussed and the necessary changes to the corpus of statistics are proposed resolving the problem of correlation and ES in paired binary data. Since exposing these fallacies casts doubt on the reliability of the statistical foundations of EBM in general, we urgently need to revise them.

The effect of filling velocity on positive macrosegregations in large size steel ingots was studied. Macrosegregation and macro-/micro-structure were characterized on the hot-tops and a portion of the upper section of two ingots. The measurements revealed that segregation features in the two ingots varied as a function of the alloying elements, and that the severity of positive macrosegregation in the casting body was reduced when the filling rate was increased. It was also found that at the higher filling rate, grain morphologies in the first solidified zones of the ingot changed from columnar to equiaxe, and secondary dendrite arm spacing (SDAS) became slightly smaller in the intermediate and final solidified zones. The experimental findings were analyzed in the framework of diffusion and convection controlled solidification, as well as liquid metal flow theories. The solute dependence of segregation features was related to the difference in solid-liquid partition coefficient and diffusion capability of each element in the liquid iron. Calculation of Reynolds numbers (Re) during the filling process, for both ingots, showed that higher filling velocity caused more instable movement of the liquid metal in the initial solidification stage, resulting in the modification of grain morphology, as well as accelerated solidification rate.

In the present work, three different atmospheric plasma sprayed (APS) alumina coatings were fabricated using three fused and crushed alumina powders of different particle size fine, medium and coarse. The influence of the particle size on thermal properties and micro-structural features of the produced coating were investigated by thermal insulation test and detailed image analysis technique, respectively. The analyzed micro-structural features include the total porosity, pore size (fine, medium, and large) and cracks. All types of cracks were considered in calculations as voids and were evaluated according to their sizes as pores. All spray parameters except the particle size were fixed throughout the spraying process. The results revealed that the fine starting powder has produced the densest coating with the lowest total porosity and that the total porosity increases with an increasing particle size. This was expected as powders of smaller particle size will reach a higher in-flight temperature and velocity than powders of bigger particle sizes as long as the same spray parameters are applied. However, a detailed image analysis investigation on the three produced coatings showed that the fraction of fine pores and cracks versus the total porosity is substantially higher in coatings produced by using fine starting powders than those produced using medium and coarse powders. In this work, a connection between the thermal insulation and the porosity fraction, which includes fine pores and cracks, was revealed.

Tree growth is under the combined influence of abiotic and biotic factors. Trees with different sizes may respond differently to these factors, implying that tree heterogeneity in tree size may also modulate the overall growth trend. To test this hypothesis, we focused on the radial growth trends of natural subalpine forests on the Tibetan Plateau. We first extended the iterative growth model (IGM) to the tree-ring scale (IGMR) to test the applicability of the generalized metabolic growth theory to tree growth. As predicted by the IGMR, the radial growth of trees at the aggregate scale is constrained by a unimodal pattern. Using the IGMR, we reconstructed the historical best growth trajectory (HBGT) of trees within the same community based on the tree with the largest radius and/or longest age in the community. From the average difference between the HBGT and the current radial growth rate of trees with different sizes, we constructed an indicator that can measure the overall variation in tree radial growth. Based on this indicator, we found a negative effect of tree size heterogeneity on the overall variability of tree growth across elevations. Further analysis also revealed that the radial growth rate of trees on the Tibetan Plateau has increased significantly compared to the past, where growing season average temperature and annual minimum temperature were negatively and positively correlated with tree growth below and above the treeline, respectively. Our study not only confirmed that the overall variability of tree growth depends on tree size heterogeneity but also proposed an indicator that reveals net changes in tree radial growth rate relative to the past. These theoretical advances facilitate the understanding of changes in the extent of subalpine forests.

Recently perovskite solar cells have been paying attention of researchers. This comes from their high efficiency and stability. In this work, the change of some Optical and Electrical Properties of BaxFe(1-x)TiO4 thin films due to the change of the nanocrystal spacing and size were studied. A simple theoretical model based on the string theory was utilized to explain some of these empirical relations. The empirical results obtained indicated that an increase in the efficiency of the nano solar cell requires the energy gap to be narrow. Decreasing the nanocrystal size and spacing caused the energy gap to become narrower. The energy gap decreases also upon increasing the absorption coefficient and decreasing the transmission. This also requires increasing the conductivity and the magnetic permeability. The increase of the nanocrystal spacing decreases the absorption coefficient, electrical conductivity, and magnetic permeability, while it causes the transmission to increase. All these changes are explained using a simple string model beside Newton's laws. The capability of the string theory to explain this Nano quantum behavior comes from the fact that the string theory, like quantum theory, recognizes both the particle and the wave nature of the Nano system.

The manipulation of participant allocation in randomized controlled trials to achieve equal groups sizes may introduce allocation bias potentially leading to larger treatment effect estimates. This study aimed to estimate the proportion of nursing trials that have precisely equal group sizes and examine if there was an association with trial outcome. Data were extracted from a sample of 148 randomized controlled trials published in nursing science journals in 2017. One hundred trials (68%) had precisely equal group sizes. Respectively, a positive outcome was reported in 70% and 58% of trials with equal/unequal groups. Trials from Asia were more likely to have equal group sizes than those from the rest of the world. Most trials reported a sample size calculation (n=105, 71%). In a third of trials (n=36, 34%), the number of participants recruited precisely matched the requirement of the sample size calculation; this was significantly more common in studies with equal group sizes. The high number of nursing trials with equal groups may suggest nurses con-ducting clinical trials are manipulating participant allocation to ensure equal group size increasing the risk of bias.

Introduction: The purposes of this study were to seek for overall ratio (OR) and anterior ratio (AR) patients data in normal occlusion and Angle’s malocclusion studies, and to assess if such results support Bolton’s standards as general references. Methods: Pubmed, Medline, CENTRAL and Scholar databases were searched up to February 2018 (CRD42018088438). Gray literature was explored through OpenGray. Non-randomized clinical studies, published in English and assessing Bolton’s OR and AR in normal occlusion and Angle’s malocclusion groups (Class I, Class II, Class II division 1, Class 2 division 2, Class III) patients were included. OR and AR means and standard deviations (SD) were collected. Potential covariates (study design, publication year, country where the study was conducted, number of cases, gender, mesiodistal measurement method, and calibration method) were also extracted. The National Health Heart Lung, and Blood Institute’s Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to assess each included studies quality. Pairwise Random-Effects and Multilevel Bayesian Network Meta-Analyses were used to synthesize available data. Results: Fifty-two observational studies were included (8872 participants; male/females 2674/3272; 16 studies lacked gender information). For normal occlusion, global pooled estimates for OR and AR means were 91.74% (95% CI: 91.37-92.10) and 78.24% (95% CI: 77.85-78.63), respectively. We could identify on Angle’s Class III patients meaningful OR and AR mean deviations from normal occlusion (0.89, 95% credible interval [CrI], 0.66-1.12, and 0.66, 95% CrI, 0.38-0.94, respectively), while on Class I patients we found a meaningful mean deviation from normal occlusion only for OR (0.25, 95% CrI, 0.03-0.47). Concerning gender impact, male patients presented higher OR (0.30, 95% CI 0.00-0.59) and AR (0.41, 95% CI 0.00-0.83) mean values than females in Class I. Conclusions: The results show that global pooled OR and AR mean values for normal occlusion patients are slightly above Bolton’s original values. Class I, for OR mean values, and Class III, for both OR and AR, are proportionally larger than normal occlusion patients. Gender had almost no impact on teeth mesiodistal proportion.

Biochar is a carbon-rich material that recently received attention due to its increasing agronomical potential. The agricultural utilization of biochar relates to its potential to act in the soil as a soil conditioner, nevertheless, the complex information on the direct dependence of biochar physical properties (texture, particle size) and corresponding leaching and availability of organic molecules (e.g. the polycyclic and heterocyclic organic compounds) and inorganic mineral salts (based on micro– and macroelements) are still not consistent. These aspects were addressed in our study. A multi-elemental analysis (ICP-OES) was used to access the information on the aqueous-extractable and total contents of inorganic macro- and macroelements in used commercial biochar samples (purchased from Sonnenerde GmbH, Novoterrra Sonnenerde GmbH, Biouhel.cz, s.r.o.). Potassium (K) was identified as the major macroelement, responsible for alkaline pH and the conductivity of biochar extract. Our results indicate an indirect relation between the size fraction of biochar and the content of extractable K, sodium (Na), and calcium (Ca) and a direct relation with the contents of phosphorus (P) and magnesium (Mg). As the total determined amounts of inorganic elements were significantly higher compared to aqueous-extractable amounts, we believe it could indicate the potential for repeated release to the surrounding soil. These findings were also confirmed by the analysis of biochar samples obtained after the cultivation (duration of 2 years) in selected representative soil samples from the Czech Republic (Cambisol, Fluvisol, Regosol, Chernozem). Moreover, gas chromatography (GC) coupled with mass spectroscopy (MS) was further used to reveal the concentrations of available polycyclic aromatic and heterocyclic compounds in biochar samples. The detected concentration of these types of organic compounds were far below the certified limits. We believe our in-depth analysis could provide the necessary insight into the description of biochar mineral content, its connection to biochar texture, corresponding physicochemical properties and potential availability to leach nutrients to the soil. These findings could help in further assessment of the potential applications of biochar in modern agriculture as a soil conditioner.

Concretizing the mechanisms of Bergmann rule, we found saw-tooth pattern in body size variation in ground beetle Pterostichus oblongopunctatus. We sampled beetles in 2010 – 2018 at the forest undisturbed plots on the broad territory in Russia. Investigating regions covered territory, extending to 3 degrees latitude and 19 degrees longitude. We measured six traits in every of 3294 caught individual. ANOVA showed that latitude, and sex affected significantly body size of the species studied. Mean values of each trait changed significantly from one studied region to another in females and males as well. Sexual size dimorphism in species was female-biased. We performed models in R to estimate the steepness of body size variation in both sexes. In overwhelming majority of cases that parameter was equal in both sexes. So the hypothesis, that male′s variation is steeper in latitude gradient was not confirmed.

This paper presents a new approach of eddy current methods for determining the size of the co-axial hole in the metallic circular disk. In recent decades, for the air-cored sensor probe, the impedance change due to the presence of an infinite metal plate can be calculated by the Dodd-Deeds model. However, in practical measurements, the sample cannot match with the condition required - ‘infinite’, thus the Dodd-Deeds model could not be applied to the disk with finite size and certainly not a co-axial hole in the center. In this paper, a dual-constraint analytical method is proposed. That is, the upper and lower limits of the integration are substituted with specific values instead of the original 0 and . Besides, it is found that, once the outer radius of the disk is fixed (i.e. the lower limit of integration is fixed), the upper limit reduces linearly as the size of the coaxial hole increases. Both the FEM simulation and experiments have been carried out to validate this method. The radius of the hole can be estimated based on the dual-constraint integration feature.

Scientists, politicians, and practitioners are debating the current structure of pig farms in Lithuania, as medium and small farms have almost disappeared over the past decade. The debated problem is whether the revitalization of medium and small pig farms would sustainably contribute to self-sufficiency in pork? Therefore, this research aims to determine which farms in terms of size could be the most perspective. In order to achieve this aim the multi-criteria evaluation method TOPSIS was used. The economic, production and environmental indicators of Lithuanian pig farms and pig farming sector in Lithuania and selected EU countries: Latvia, Estonia, Poland, Germany, and Denmark were analyzed in this research. The multi-criteria evaluation led to the conclusion that Danish pig farms were the best managed. Germany occupied the second place. The industrial large farms were found as dominated in those countries. Large pig farms (approximately two thousand sows) appeared most perspective in Lithuania: they took the first place in the years examined (2016–2021). The criterion estimate of their assessed indicators was much higher than of the medium (100 sows) and small (20 sows) farms. The main reasons: significantly higher labour productivity, lower cost, lower price, and better production indicators.

(1) Background: Stunting remains a challenge in Indonesia, where 30.8% of under-five children are stunted and may never reach full potential height and cognitive function. We aimed to investigate the risk factors of stunting in Nangapanda subdistrict, East Nusa Tenggara; (2) Methods: The design was cross-sectional study located in rural area as part of PINTERMIDI UI project. We collected quantitative data on social determinants, weight, height, hemoglobin, ferritin, serum zinc, CRP, worm infection, history of deworming, co-morbidity, food security, and nutrient intake; (3) Results: A total of 196 under-five children included and 74% households were food insecure. The prevalence of stunting was 29.9% in this population (31.8% worm infection, 30.3% iron deficiency, and 28.1% zinc deficiency). Multivariate analysis showed household with 5-8 members (AOR 3.076; 95% CI 1.132 – 8.356) and unsafe drinking water (AOR 1.702; 95% CI 0.825 – 3.512) were significant independent risk factors of stunting after adjusted by child’s gender, father’s occupation, caregiver’s education, monthly expenses, sanitary facilities, and food security status; (4) Conclusions: The number of household members is the only independent risk factor of stunting among children age 24-59 months in rural area of Eastern Indonesia. Development of nutrition sensitive intervention and promotion of family planning are needed in order to increase adequate child’s care and feeding practices in rural area of Eastern Indonesia.

Shark unprovoked attacks consist of fatal and non-fatal cases. Numerous cases have been reported involving shark species from Carcharhinus melanopterus with length of 145.5 cm to half-ton Carcharodon carcharias. Currently there are more (P < 0.05) unprovoked non-fatal cases with the average is 28.46 cases/shark species (95%CI: 3.86-53.1) than unprovoked fatal cases, which the average is 5.12 cases /shark species (95%CI: -0.075-10.3). Hence this paper seeks to select the best shark size model that correlates with the unprovoked fatal and non-fatal cases. The studied sharks consist of 24 shark species with the average length is 268.18 cm (95%CI: 230-306 cm) and the average weight is 225.42 kg (95%CI: 128-323 kg). Based on the model and as described by low values of AIC and the highest values of R² and adjusted R² , shark weight followed by combinations of shark weight and length produced unprovoked fatal and non-fatal cases best models. The model for explaining unprovoked fatal cases is the shark weight with high numbers of cases observed in large size shark (weight⁓fatal cases, AIC = 165.359, R² = 0.72, Adj. R = 0.71). While for non-fatal cases, the best model is also the shark weight (weight⁓non fatal cases, AIC = 246.93, R² = 0.63, Adj. R = 0.59).

In December 2012, DOAJ’s parent company, IS4OA, announced they would introduce new criteria for inclusion in DOAJ [1] and that DOAJ would collect vastly more information from journals as part of the accreditation process – and that journals already included, would need to reapply in order to be kept in the registry. My hypothesis was that the journals removed from DOAJ on May 9th 2016 would chiefly be journals from small publishers (mostly single journal publishers) and that DOAJ journal metadata information would reveal that they were journals with a lower level of publishing competence than those that would remain in the DOAJ. Among indicators of publishing competence could be the use of APCs, permanent article identifiers, journal licenses, article level metadata deposited with DOAJ, archiving policy/solutions and/or having a policy in SHERPA/RoMEO. The analysis shows my concerns to be correct.

In this paper, comprehensive analysis of combined effect of major influencing parameters on heat transfer in the single U-tube BHE (sBHE) and double U-tube BHE (dBHE) with two independent circuits was performed by using validated numerical heat transfer model. Geometrical parameters, such as shank spacing (with maximum, average and minimum values) and borehole diameter (large, medium and small borehole sizes) and borehole depth (shallow, average and deep borehole depths) as well as thermal conductivity of soil and grout which ranges from minimum to high value were considered. The combined impact of these parameters was included under four major cases: 1) combined effect of borehole depth, borehole size and shank spacing; 2) combined effect of borehole depth, and soil and grout thermal conductivity; 3) combined effect of soil and grout thermal conductivity and borehole size; and 4) combined effect of soil thermal conductivity, borehole size and shank spacing. Each of these major cases has nine different design options of both sBHE and dBHE. Series of results of heat transfer per unit borehole depth were generated for all the considered various cases. With the given parameters, the BHE case that provides highest heat transfer among the various cases of sBHE and dBHE were obtained.

Inbreeding depression is expected to be more pronounced in fitness-related traits, such as pig litter size. Recent studies have suggested that the genetic determinism of inbreeding depression may be heterogeneous across the genome. Therefore, the objective of this study is to conduct a genomic scan across the pig autosomal genome to detect the genomic regions that control inbreeding depression for litter size in two varieties of Iberian pigs (Entrepelado and Retinto). The datasets consist of 2,069 (338 sows) and 2,028 (327 sows) records for litter size (Total Number Born and Number Born Alive) for the Entrepelado and Retinto varieties. All sows were genotyped using the Geneseek GGP PorcineHD 70 K. We employed the Unfavorable Haplotype Finder software to extract runs of homozygosity (ROHs) and conducted a mixed model analysis to identify highly significant differences between homozygous and heterozygous sows for each specific ROH. A total of 8 genomic regions located on SSC2, SSC5, SSC7, SSC8, and SSC13, were significantly associated with inbreeding depression, housing some relevant genes such as FSHR, LHCGR, CORIN, AQP6, and CEP120.

Polyaniline or PANI is a conductive polymer (CPs) with flexibility in turning into conducting properties. The drawback is mainly in terms of limited mechanical properties improvement which attracted the interest in fabrication of PANI with other polymeric materials. PANI-PVL composites film was synthesized and fabricated in this work with chronological steps according to the objectives aligned in two different phases. The first phase determines the optimum parameters to synthesize nanosized PANI. The ideal initial molar ratio, r was 1, stirring speed of 600 rpm, purified by filtration, synthesis temperature of 25 oC, washed by dopant acid, acetone and distilled water. The usage of non-ionic surfactant, Triton X-100 (TX100) with 0.1 % concentration favours the formation of smaller particle size of PANI and good dispersibility compared to the usage of anionic sodium dodecyl sulphate (SDS). The synthesis of PANI in nanosized dimension has the potential to be applied for antimicrobial applications such as gloves and antimicrobial coating of frequent contact points in the near future.

Abstract: Ovulation failure was associated with a reduction in pre-mating concentrations of oestradiol-17β and prolactin (PRL). The present study aimed to evaluate whether pre-mating PRL levels have a role on the reproductive efficiency of doe rabbits. A total of 78 multiparous California does (2nd parity) were divided, according to plasma pre-mating PRL, into five categories, >20-25, >25-30, >30-35, >35-40, and >40-45 ng/ml. Does in all categories were naturally mated and kindled, then their reproductive measurements and progesterone (P4) levels were determined. Results show that pre-mating PRL averaged 23.60±0.78, 28.00±0.83, 33.46±0.43, 38.17±0.49 and 41.98±0.68 ng/ml in five categories (p < 0.05), respectively, representing the highest distribution (38.5%) in the 3rd-category. Live body weight of doe rabbits, at mating, pregnancy, and parturition increased (p < 0.05) with increasing pre-mating PRL level. The number of services, litter size, and pregnancy rate increased (p < 0.05) by increasing PRL levels. Reproductive traits and P4 level at mid-pregnancy of does, and average weight of kits at birth increased (p < 0.05) by increasing PRL levels. The pre-mating PRL profile is important for the identification of reproductive performance in doe rabbits.

Meganthropus palaeojavanicus was known very tall with body height of 8 feet and this made M. palaeojavanicus as the tallest hominid ever existed. This species was living in closed tropical woodland and hilly landscape as the fossil remains were found in a remote forest in Sangiran, central Java. Owing large body size, it may influence the foraging ecology of M. palaeojavanicus to cope with the terrain. In here, this study aimed to model the M. palaeojavanicus foraging ecology along terrain gradients. The model indicates that within 5 km home range radius, the most suitable foraging areas were in north east since these areas have more flat landscapes with slopes of <7.5%. While less suitable areas in north west and south west areas were characterized by hilly landscapes with rugged terrain and steep slopes with slopes of >62.8%.

The purpose of this paper is to analyze how Green Business Models (BMs) established by small and medium enterprises (SMEs) can incorporate product and process decarbonization in their components (value proposition, creation and capture) and to what extent this incorporation is affected by SME size. We use a database comprising 1,161 observations of SMEs, 466 in 2014 and 695 in 2016. The results show that SMEs’ value propositions give an intermediate valuation to both legally required and voluntary reduction of environmental impact, irrespective of SME size and the year analyzed. Regarding value creation, SMEs adopt practically no environmental practices, and there are significant differences according to size, with more difficulties than advantages stemming from small size. The study also shows that such environmental practices are not effective in reducing carbon. This diagnosis indicates that SMEs need help from the administration if they are to play a key role in the process of transformation toward a low-carbon economy. Legislative actions involving harsher environmental protection measures might help shape value propositions that place greater importance on reducing environmental impact, whereas training actions on available environmental techniques, promotion of research on how to adapt such techniques to SMEs and the development of specific practices for SMEs might enhance environmental value creation and capture in their BMs.

A picture is a powerful and convenient medium for inducing the illusion that one perceives a real three-dimensional scene. The relative invariance of picture perception across viewing positions has aroused the interest of painters, photographers and visual scientists. Many studies have been devoted to perceptual invariance when pictures are viewed from oblique directions. Invariance across viewing distances has received less attention. This study presents a computational analysis of pictures of perspective scenes taken from different distances between camera and physical objects. Distances and directions of pictorial objects were computed as function of viewing distance to the picture and compared with distances and directions of the physical objects as function of camera position. The computations show that pictorial distance and direction are determined by angular size of the depicted objects. Pictorial distance and direction are independent of camera position, focal length of the lens, and picture size. Ratios of pictorial distances, directions and sizes are constant as function of viewing distance. The constant ratios are proposed as the reason for invariance of picture perception over a range of viewing distances. Reanalysis of distance judgments obtained from the literature shows that perspective space, previously proposed as the model for visual space, is also a good model for pictorial space. The geometry of pictorial space contradicts some conceptions about picture perception.

The analysis of suspended particle size distribution in produced water for hydraulic fracturing and for water injection operations is vital for the effective development of tight reservoir formations like the Middle Bakken. Several reservoir engineering studies and industry guidelines recommend that particle sizes fall between 1/7th and 1/3rd of the square root of the formation permeability measured in millidarcies, to avoid pore throat clogging and subsequent formation damage. In the tight Bakken formation, with an average permeability of 0.04 millidarcies, the ideal particle size range for total suspended solids should fall within the 0.03 to 0.06 microns range. This study evaluates whether produced water used for hydraulic fracturing and enhanced oil recovery in the Middle Bakken meets this recommendation, as there are no established regulations in North Dakota addressing this issue. Using laser diffraction, particle size distribution was measured in treated and untreated produced water samples. The results show that current treatment methods do not reduce particle sizes to the recommended range. Treated water had particle diameters ranging from 8.5 to 40 μm, while untreated water had diameters ranging from 8.2 to 10 μm. None of the samples met the particle size requirements for safe use in hydraulic fracturing and water injection. This study highlights the inadequacy of current water recycling practices and offers empirical evidence that may guide future regulations on produced water reuse hydraulic fracturing and water injection in the Bakken.

Methyl Mercaptan is a sulfur-based chemical found as a co-product in produced natural gas and causes corrosion in pipelines, storage tanks, catalysts, and solid adsorption beds. To improve the quality of methane produced, researchers studied the use of metal oxides and aluminum silicates as catalysts for removing mercaptan. However, there are restricted limitations on the efficiency of metal oxides or aluminum silicates as adsorbents for this particular application. Therefore, this study investigated the performance of these materials in a fixed-bed reactor with simulated natural gas streams under various operating conditions. The testing procedure includes a detailed assessment of the adsorbent/catalysts by several techniques, such as Braeuer-Emmett-Teller (BET), Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectrometry (EDS), and X-ray Photoelectron Spectroscopy. The result revealed that metal oxides such as copper, manganese, and zinc performed well in methyl mercaptan elimination. The addition of manganese, copper, and zinc oxides to the aluminum silicate surface resulted in a sulfur capacity of 1226 mg S/g of catalyst. These findings provide critical insights for the development of catalysts that combine metal oxides to increase adsorption while reducing the production of byproducts like dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) during methyl mercaptan removal.

One of the most crucial attributes of emulsions is their particle size, which has implication on the stability, rheology as well as sensory properties in different food applications. Homogenization speed is an important parameter that disrupts fat globules into desirable particle sizes. The effect of emulsification composition and homogenization parameters on particle size distribution of palm stearin oil-in-water emulsion was investigated. A palm stearin oil-in-water emulsion was homogenized at different speed (10k-25k rpm) and the particle size distribution was investigated. When the homogenization speed was increased above >10k rpm, the particle size distribution decreased. Increasing concentration of surfactant from 1 wt.% to 3wt.%, in the emulsion showed a decrease in particle size distribution for all homogenisation speed. Oil droplet size could also be minimized by increasing the concentration of sugar in continuous phase.

Sample size using prevalence has been one of the most important medical research methodologies and has been used in original articles more often than any other statistical tool available. The simple formula consists of variables interdependent and it is as important to understand how they influence each other as it is to learn to use the formula to calculate the sample size. With the choice of different amounts of precision and levels of confidence available to a medical researcher, it should be of paramount importance to understand what a slight change in choosing the parameter would mean at the end of the research. Understanding of different Z values, Levels of precision, and ranging Prevalence is required to understand the effect on the sample size and subsequently on the research. Topological representation using parameter ranges can be used to demonstrate this relationship.

This study aimed to investigate the interactions between corn particle size (PS) and conditioning temperature (CT) on the performance, carcass traits, intestinal morphology, and immune responses in broilers fed a corn-soybean meal-based diet. A total of 360, one-day-old male broiler chicks (Ross 308) were randomly allocated into six dietary treatments in a 2×3 factorial arrangement, consisting of two corn PS (finely ground with geometric mean diameter (GMD) of 357 µm (PSF) vs. coarsely ground corn with GMD of 737 µm (PSC), and three CT [unconditioned (CTU), conditioned at 75◦C (CT75) and 90◦C (CT90)]. Birds accommodated in 30 pens with five replicates and 12 chicks per each. There was no interaction between corn PS and CT on growth performance and immune response of broilers at any growth phases. However, during the starter (0-10d) period, the average daily weight gain (ADWG) and feed conversion ratio (FCR) of PSF-fed birds were significantly improved compared to those fed PSC (P<0.05). During the starter (0-10d) and grower (11-24d) periods, increasing the conditioning temperature of corn increased the ADWG, while in the starter phase only the CT75 caused a lower FCR (P<0.05). Broilers fed PSF corn showed lowest FCR during the finisher (25-42d) period compared to those fed PSC (P<0.05). Conditioning corn at 75ºC reduced FCR during the finisher (25-42d) period compared to the birds fed CTU and CT90 corn (P<0.05). In whole experimental periods (1-42d), PSF and CT75 treatment increased the ADWG compared to the PSC and CTU (P<0.05). The CT75 treatment improved primary total anti-sheep red blood cell (SRBCs) titer (IgT) and IgM and secondary IgT and IgG responses compared to the other experimental groups (CTU and CT90) (P<0.05). No significant PS × CT interaction was found on Newcastle disease (ND) antibody titer of broiler chickens (P>0.05). Feeding CT75 corn reduced duodenum and jejunum relative length compared to the birds fed diets containing CTU corn. Significant PS×CT interactions (P<0.05) were observed for villus height, villus height to crypt depth, crypt depth, muscle thickness, and absorption surface area of jejunum. The highest carcass yield observed in PSF-CT75-group (P<0.05). In conclusion, the use of finely ground corn (PSF) conditioned at 75℃ (CT75) was beneficial to growth performance, development of the digestive tract, jejunum histomorphometry and the immune responses of broilers.

Remanufacturing is a way for product recovery initiative and maintaining sufficient production flow to satisfy customer demand through circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chain vulnerable to disruptions. Among the disruptions that usually occur is the shortage in spare parts supply, which causes unexpected delay in production and possible loss of sales. In the face of potential disruption, it is essential for remanufacturing facilities to manage their supply chains in an optimum manner as to decrease the adverse impact of disruptions to their business. In this study, a two-stage production-inventory system is analysed by developing a cost-minimisation model focusing on the recovery schedule after a disruption occurrence in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch and bound algorithm. Through numerical experiments, the results indicate that the optimal recovery schedule and the number of recovery cycles are significantly dependant on disruption time, lost sales and backorder costs. Moreover, a sensitivity analysis shows that the lost sales option seems to be more effective than the backorder option in optimising the system’s overall cost. The proposed model could assist managers in deciding the optimal production strategy while providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

The orchid market is a dynamic horticultural business in which novelty and beauty command high prices. The development of miniature to large and showy flowers, in addition to fragrance, is mainly of interest. Overall organ size might be modified by doubling the chromosome number, which can be accomplished by careful study of meiotic chromosome disjunction in hybrids or species. Meiosis is the process in which diploid (2n) pollen mother cells recombine their DNA sequences and then undergo two rounds of division to give rise to four haploid (n) cells called sporads. Thus, by interfering in chromosome segregation, one can induce the development of diploid recombinant sporads called dyads. These dyads may be used for breeding polyploid progenies with enhanced fertility and large flower size. This review gives an overview of developments in orchid breeding placed in the large context of ploidy breeding in higher plants to facilitate innovation

The feral mink population in Denmark consists of two groups of animals; mink born in the wild and mink that have recently escaped from farms. The aims of this study are; 1) to estimate the reproduction and mortality of wild-born and captive-born mink and 2) to estimate the age of mink based on the width of pulp cavity (% of tooth width) in the canine teeth. During 2018, 247 wild caught mink were sent for necropsy at the Danish National Veterinary Institute. Of these mink, 112 were determined as captive-born and 96 were determined wild-born. The mean litter size ± SE of wild-born females was 7.6 ± 0.9 (range: 5-11 kits) and for captive-born females 5.9 ± 0.9 (range: 1-10 kits). The best fitting regression line for mink age (in months) based on pulp width was y=0.42x2-11.52x+104.7, R² = 0.77, p&lt; 0.0001. Individuals with a pulp cavity width &lt;35% was found to be younger than one year. The turnover of mink caught in nature was estimated to 66% and the yearly mortality to 69%, therefore the population is slightly declining. In conclusion, a feral reproducing mink population in Denmark persists, besides the continues influx of captive-born mink escaped from farms.

The angular diameter is the angle subtended by a generic object – an apple or a star – to the eye of an observer, and it describes how large the object appears from a given viewpoint. The angular diameter represents a powerful tool for distance calculations starting from a directly measurable information and it finds application in several contexts varying from cosmography to architecture. In this article, the author proposes a novel equation to calculate the apparent diameter of whatever object. This equation defines the relationship between the object’s apparent diameter with respect to the travelled distance starting from the initial distance R₀ at which the observed object is located. Based on the preliminary tests conducted, the model seems to faithfully portray this relation with respect to measured values, also at the astronomical scale, thus considering the Earth-Moon distance, where, the absolute error detected is about 0.56%. Tests highlight also a dependency between the results accuracy and the measurement conditions suggesting a high level of sensibility linked to the initial magnification effect produced by the retina or the artificial lens employed.

Plastics are naturally hydrophobic materials so, in order to employ flotation for the separation of plastic mixtures, the use of appropriate wetting agents is mandatory. In this work, the effect of pretreatment with alkaline solutions of sodium hydroxide on the floatability of four plastics (PET, PS, PMMA and PVC) was studied. The influence of NaOH concentration, treatment time and temperature of the alkaline solution, and influence of particle size was analyzed. Results showed that alkaline treatment had a strong effect on PET floatability, some effect on floatability of PMMA and PVC and no effect on floatability of PS. Plastics floatability decreased with the increase of NaOH concentration, temperature and treatment time of the alkaline solution. Based on flotation behavior of simple plastics, flotation separation after alkaline treatment of bi-component mixtures of PET with PS and PVC was achieved efficiently. The best separation was obtained for PET/PS mixture, a floated with a grade of 98% in PS and a sunk with a grade of 100% in PET. PET/PMMA mixture led to the worst separation. For PET/PMMA and PET/PVC mixtures, flotation separation improved with the decrease of the particles size.

Aim: aim of this study is to evaluate the clinical and radiographic healing after repairing mechanical furcal perforations that occurred in primary molars by using MTA (Mineral Trioxide Aggregate) and search in some factors that may affect the prognosis of the treatment. Materials & Methods: we had 34 primary molars in 32 children aged 5–10 years, were treated by using MTA material after the occurrence of furcal perforation during pulpotomy procedure. Cases had been followed clinically and radiographically within 12 months. Statistical analyses were performed at p-value = 0.05. Results: All teeth were asymptomatic at the first week. Overall success rate was 79.3%. There was no significant statistically differences between overall-success rates according to the perforation size and continues bleeding in the furcation area (p-value > 0.05). Conclusions: Iatrogenic furcal perforations that may occur during pulpotomy in primary molars can be treated successfully by using MTA, and small sized-perforations may have more favorable prognosis than the large ones. Iatrogenic furcal perforations that may occur during pulpotomy in primary molars can be treated successfully by using MTA, and small sized- perforations may have more favorable prognosis than the large ones.

The present study set out to explore the option of developing food portion size for nutritional labelling purposes using two European Union (EU) dietary surveys. The surveys were selected as they differed in (a) methodologies (food diary v food frequency questionnaire), (b) populations (Irish National Adult Nutrition Survey: NANS) versus a seven-country based on the pan EU study Food4Me), (c) food quantification (multiple options v, solely photographic album) and (d) duration (4 consecutive days v recent month). Using data from these studies, portion size was determined for 15 test foods, where portion size was defined as the median intake of a target food when consumed. The median values of the portion sizes derived from both the NANS and Food4Me surveys were correlated (r = 0.823; P<0.00) and the mean of the two survey data sets were compared to US values from the Recognized as Customarily Consumed (RACC) database. There was very strong agreement across all food categories between the averaged EU and the US portion size (r = 0.947; P<0.00). It is concluded that notwithstanding the variety of approaches used for dietary survey data in the EU, the present data supports using a standardized approach to food portion size quantification for food labelling in the EU.

Extracellular vesicles (EVs) are cell-derived membranous particles secreted by all cell types into the extracellular milieu. EVs carry, protect, and transport a wide array of bioactive cargoes to recipient/target cells. EVs regulate physiological and pathophysiological processes in recipient cells and are important in therapeutics/drug delivery. Despite these great attributes of EVs, an efficient protocol for EV separation from biofluids is lacking. Numerous techniques have been adapted for the separation of EVs with size exclusion chromatography (SEC)-based methods being the most promising. Here, we review the SEC protocols used for EV separation, and discuss opportunities for significant improvements, such as the development of novel particle purification liquid chromatography (PPLC) system capable of tandem purification and characterization of biological and synthetic particles with near-single vesicle resolution. Finally, we identify future perspectives and current issues to make PPLC a tool capable of providing a unified, automated, adaptable, yet simple and affordable particle separation resource.

Electronic cigarette (ecig) use in pregnancy is common, but potential effects on fetal development are largely unknown. The study goal was to examine the association between ecig exposure and fetal growth. Data were extracted from medical charts in this single site retrospective study. The sample, excluding those with known tobacco, alcohol, illicit drug, opioid, and benzodiazepine use, contained women who used ecigs throughout pregnancy and non-ecig user controls. Fetal size measurements from second and third trimester ultrasounds and at birth were expressed as percentiles for gestational age. Following adjustment for confounding factors, in the second trimester, only femur length was significant, with an adjusted deficit of 11.5 percentile points for ecig exposed compared to controls. By the third trimester, femur length difference was 28.5 points, with fetal weight difference also significant (17.2 points). At birth, all three size parameter differences between groups were significant. Significant size deficits were predicted by prenatal ecig exposure, becoming larger and impacting more parameters with increasing gestation. While additional study is warranted to confirm and expand upon these findings, this study adds to emerging data pointing to specific harms following ecig exposure in pregnancy, and suggests that ecigs may not be a “safer” alternative to combustible cigarette smoking in pregnancy.

This paper examines the impact of random sample sizes on the extreme value theory of competing risks, a significant area in finance and environmental science. We capture limit distributions of two extreme types under random sampling sizes, known as accelerated mixed l-max and p-max stable type distributions. The study presents results for both maxima and minima in competing risks scenarios, addressing cases of independent and non-independent random sample sizes. Numerical examples validate our theoretical findings, demonstrating the applicability of our approach to various random sample size distributions, including time-shifted Poisson or binomial, geometric, and negative binomial distributions.

Cerebral aneurysms come in a wide range of shapes and sizes, they can evolve over time and present significant changes. It is generally accepted that large aneurysms are more prone to rupture, but the rupture of small aneurysms has also been observed, indicating the presence of additional risks factors. The aim of this study is to assess the effects of the aneurysm size and wall thickness on its rupture risk by using fluid-structure interaction simulations. Six patient-specific geometries were chosen, four were used for studying the size effect and two for studying the thickness effect. Additional cases where the aneurysm was removed were included. It was found that thinner walls suffer from significantly greater stresses, whereas an increment in size means, in general, lower wall shear stress and greater equivalent stress. By removing the aneurysm, it could be noted that at the rupture point, the reduction in the time-averaged wall shear stress was 75%. Although the size of an aneurysm has a great impact in its rupture risk, its wall thickness needs to be considered, since even maintaining its size, the aneurysm could suffer from a thin-ning of its walls that can lead to structural failure.

Our previous studies showed pure blue (B) spectra from LEDs can promote shade avoidance responses (SARs). However, it is unknown whether SARs vary among different peak wavelengths (λpeak) of B or how they compare with other photomorphologically-important wavebands, such as ultraviolet-A and far-red. To answer these questions, mustard (Brassica juncea, ‘Ruby Streaks’) and arugula (Brassica eruca, ‘Rocket’) seedlings, grown to the cotyledon unfolding stage under the following narrowband spectrum treatments: UVA (λpeak = 385 nm), B1 (λpeak = 404 nm), B2 (λpeak = 440 nm), B3 (λpeak = 455 nm), and FR (λpeak = 730 nm). Both red (R, λpeak = 660 nm) and dark (D) were used as control treatments. The spectrum treatments were provided at 50 μmol m−2 s−1 on a continuous basis. There were no differences among the B treatments except for reduced mustard fresh weight (FWt) in B3. Compared with R, the B treatments promoted hypocotyl elongation, reduced cotyledon size, and increased petiole length in arugula and B1 increased petiole length in mustard. Compared with the B treatments, UVA inhibited hypocotyl and petiole elongation, similar to or greater than R in both species. Compared with the other LED treatments, seedlings grown under FR generally had the lowest hypocotyl and petiole elongation and the smallest cotyledons. Compared to the LED treatments, D substantially promoted hypocotyl elongation and reduced cotyledon size, except compared to FR in arugula. Among the spectrum treatments, the three B treatments had the greatest SAR promotion effects in both species. Despite having the lowest phytochrome activity, FR inhibited SARs normally associated with high FR environments. Legacy parameters used to estimate SAR-promoting effects of spectrum treatments may not be appropriate for characterizing narrowband spectra from LEDs – new approaches must be developed.

Traditional camera sensors rely on human eyes for observation. However, the human eye 1 is prone to fatigue when observing targets of different sizes for a long time in complex scenes, and 2 human cognition is limited, which often leads to judgment errors and greatly reduces the efficiency. 3 Target recognition technology is an important technology to judge the target category in camera 4 sensor. In order to solve this problem, a small size target detection algorithm for special scenarios was 5 proposed by this paper. Its advantage is that this algorithm not only has higher precision for small 6 size target detection, but also can ensure that the detection accuracy of each size is not lower than the 7 existing algorithm. In this paper, a new down-sampling method was proposed, which could better 8 preserve the context feature information. The feature fusion network was improved to effectively 9 combine shallow information and deep information. A new network structure was proposed to 10 effectively improve the detection accuracy of the model. In terms of accuracy, it is better than: YOLOX, 11 YOLOXR, YOLOv3, scaled YOLOv5, YOLOv7-Tiny and YOLOv8.Three authoritative public data sets 12 were used in this experiment: a) On Visdron data sets (small size targets), DC-YOLOv8 is 2.5% more 13 accurate than YOLOv8. b) On Tinyperson data sets (minimal size targets), DC-YOLOv8 is 1% more 14 accurate than YOLOv8. c) On PASCAL VOC2007 data sets (Normal size target), DC-YOLOv8 is 0.5% 15 more accurate than YOLOv8.

Bayesian Maximum Entropy (BME) is increasingly used in predicting and mapping spatio-temporal data. However, studies that have fully evaluated its robustness empirically are rare. Therefore, this research examined empirically the effect of skewness, sample size and spatial dependency level using simulated data. We considered symmetric data, data positively skewed by 1, 3, 6 and 9, data with weak, moderate, and strong spatial dependency levels, and sample sizes from 100 to 500 at the interval length of 50. The results showed that the variation of sample sizes and spatial dependency levels do not affect the Mean Square Error (MSE) and bias of BME prediction. However, skewness affects the MSE of prediction but does not affect the bias. This result indicates that BME is robust to sample size and is unbiased. Despite the significant difference due to skewness, a graphical plot showed values of MSE close to zero, suggesting that BME can be considered robust to skewness.

The Eastern Mediterranean is a highly populated area with air quality problems as well where climate change already is noticed by higher temperatures and changing precipitation pattern. The anthropogenic aerosol affects health and changing concentra-tions and properties of the atmospheric aerosol affect radiation balance and clouds. Continuous long-term observations are essential in assessing the influence of anthro-pogenic aerosols on climate and health. We present 6 years of observations from Navarino Environmental Observatory (NEO), a new station located at the south west tip of Pelo-ponnese, Greece. The two sites at NEO, were evaluated to show the influence of the local meteorology but also to assess the general background aerosol possible. It was found that the background aerosol was originated from aged European aerosols and was strongly influenced by biomass burning, fossil fuel combustion, and industry. When subsiding into the boundary layer, local sources contributed in the air masses moving south. Mesoscale meteorology determined the diurnal variation of aerosol properties such as mass and number by means of typical sea breeze circulation, giving rise to pronounced morning and evening peaks in pollutant levels. While synoptic scale meteorology, mainly large-scale air mass transport and precipitation, strongly influenced the season-ality of the aerosol properties.

It is widely, but not universally, believed that the lipids of the plasma membrane are not uniformly distributed, but that "rafts'' of sphingolipids and cholesterol float in a "sea'' of unsaturated lipids. The physical origin of such heterogeneities is often attributed to a phase coexistence between the two different domains. We argue that this explanation is untenable for several reasons. Further we note that the results of recent experiments are inconsistent with this picture. However they are quite consistent with an alternate explanation, namely that the plasma membrane is an emulsion of the two kinds of regions. To show this, we briefly review a simplified version of this theory and its phase diagram. We also explicate the dependence of the predicted domain size on four physical parameters. Among them are the spontaneous curvature of the membrane and its bending modulus and surface tension. Taking values of the latter two from experiment, we obtain domain sizes for several different cell types that vary from 58 to 88 nm.

Pedigree data of the Border Collie dog breed was constructed in Hungary, to examine genetic diversity within the breed and between its different lines. The database based on available herd books from the development of the breed (the late 1800s) until now. The constructed pedigree file consisted of 13 339 individuals from which 1567 dogs (born between 2010 and 2016) composed the reference population that are still alive and active from breeding aspect. Since the breed is subdivided by phenotype, the reference population was dissected according to the existing lines. The number of founders was 894 but only 8 individuals were responsible for contributing 50% of the genetic variability. The reference population had a pedigree completeness 99.6% until 15 generations and inbreeding coefficient of 9.86%, respectively. Due to the changing breed standards and the requirements of the potential buyers the effective population size substantially decreased between 2010 and 2016. Generation intervals varied between 4.09 and 4.71 years where the sire paths were longer due to the later ages when males begin their breeding carrier compared to females. Genetic differences among the existing lines calculated by fixation indices are not significant, nonetheless ancestral inbreeding coefficients are able to show the contrasts.

Magnesium hydroxide continuous coagulation process was used for treating simulated reactive orange wastewater in this study. Effects of mixing conditions and retention time on the coagulation performance and floc properties of magnesium hydroxide were based on the floc size distribution (FSD), zeta potential and floc morphology analysis. Floc formation and growth in different reactors were also discussed.The results showed that increasing rapid mixing speed led to a decrease in the final floc size. Floc formation process was mainly carried out in rapid mixer, rapid mixing speed of 300rpm was chosen according to zeta potential and removal efficiency. Reducing retention time caused relatively small floc size in all reactors. When influent flow is 30 L/h (retention time of 2min in rapid mixer), the average floc size reached 8.06μm in rapid mixer, through breakage and re-growth, the floc size remained stable in flocculation basin. After growth, the final floc size reached to 11.21μm in sedimentation tank. The removal efficiency of reactive orange is 89% in magnesium hydroxide coagulation process.

Overexpression of a constitutively active truncated form of OsCDPK1 (OEtr) in rice produced smaller seeds, but a double-stranded RNA gene-silenced form of OsCDPK1 (Ri) yielded large seeds, suggesting that OsCDPK1 plays a functional role in rice seed development. In the study presented here, we propose a model in which OsCDPK1 plays key roles in negatively controlling the grain size, amylose content, and endosperm appearance, and also affects the physicochemical properties of the starch. The dehulled transgenic OEtr grains were smaller than the dehulled wild-type grains, and the OEtr endosperm was opaque and had a low amylose content and numerous small loosely packed polyhedral starch granules. However, the OEtr grain sizes and endosperm appearances were not affected by the temperature being either optimal (25 °C ) or low (22 °C) or high (31 °C) during the grain-filling phase. In contrast, the transgenic Ri grains were larger, had higher amylose contents, and had more transparent endosperms filled with tightly packed polyhedral starch granules. This demonstrates that OsCDPK1 plays a novel functional role in starch biosynthesis during seed development and affects the transparent appearance of the endosperm. These results improve our understanding of the molecular mechanisms through which the grain filling process occurs in rice.

The possibility of releasing gold nanoparticles (GNP) into the environment has been rapidly increasing with the wide spread and flourishing application of gold nanoparticles (GNPs) in a wide range of areas. Consequently, environmental effects of GNP, especially toxicities to living organisms have drawn great attention. However, their toxicological characteristics still remain unclear. Fungi, as the decomposers of the ecosystem, interact directly with the environment and critically control the overall health of the biosphere. Thus, their sensitivity to GNP toxicity is particularly important. The aim of this study was to evaluate the role of shape and size of GNPs on their toxicities to fungi, which could help reveal the ecotoxicity of GNPs. Aspergillus niger, Mucor hiemalis and Penicillium chrysogenum were chosen for toxicity assessment, and spherical and star/flower-shaped GNPs sized from 0.7 nm to large aggregates of 400 nm have been synthesised. After exposure to GNPs and their corresponding reaction agents and incubation for 48 hours, the survival rates of each kind of fungus was calculated and compared. The results indicated that fungal species was the major determinant of the variation of survival rates, whereby A. niger was most sensitive and M. himalis was least sensitive to GNP exposure. Additionally, larger and non-spherical GNPs had relatively stronger toxicities.

Formaldehyde (HCHO), an indoor volatile organic compound, is seriously harmful to human health. Therefore, green and effective decomposition of HCHO is essential. TiO2 has been employed for the degradation of HCHO via photocatalytic generation of reactive oxygen species (ROS) (O2-, ·OH), yet the low specific surface area of crystalline TiO2 depressed the catalytic performance. Herein, we prepared TiO2 aerogels with high specific surface area and high porosity by sol-gel method, and added PVA to introduce flexible molecular chains for pore size regulation. The photocatalytic performance test verifies that the pore size of TiO2 aerogel is one of the important factors for HCHO decomposition. Notably, through the establishment of theoretical model and calculation, we validated that the efficiency of HCHO decomposition is related to the oxygen pressure in the pores of TiO2 aerogel, and the oxygen pressure is inversely proportional to the pore size. Accordingly, the optimal pore size of TiO2 aerogel for the photocatalytic HCHO decomposition is 2 nm-10 nm. This study provides a theoretical idea for TiO2 aerogels in the decomposition reaction of HCHO, which is expected to inspire more breakthroughs in the study of TiO2 aerogels for green chemistry.

Throughout the evolution of machine learning, the size of models has steadily increased as researchers strive for higher accuracy by adding more layers. This escalation in model complexity necessitates enhanced hardware capabilities. Today, state-of-the-art machine learning models have become so large that effectively training them requires substantial hardware resources, which may be readily available to large companies but not to students or independent researchers. To make the research on machine learning models more accessible, this study introduces a size reduction technique that leverages stages in Pyramid Training and Similarity Comparison. Our results demonstrate that pyramid training can reduce model complexity while maintaining accuracy of conventional full-sized models, offering a scalable and resource-efficient solution for researchers and practitioners in hardware-constrained environments.

This study investigates the impact of specimen size on the mechanical properties of wood, specifically focusing on compression strength, elastic modulus, and Poisson's ratio. Compression tests were conducted using three different specimen sizes (20mm×20mm×30mm, 40mm×40mm×60mm, 60mm×90mm×90mm) in the longitudinal, radial, and tangential directions. Mechanical parameters, failure mechanisms, load-displacement curves, and stress-strain relationships were systematically analyzed for each size. The study also evaluated the influence of specimen size on the accuracy of finite element numerical simulations by utilizing the obtained mechanical parameters. The results reveal a significant correlation between compressive strength and specimen size, indicating a decrease in compressive strength with increasing specimen size. Conversely, elastic modulus and Poisson's ratio exhibit less sensitivity to variations in specimen size. Notably, parameters derived from small-sized specimens (20mm×20mm×30mm) exhibited substantial errors, while those obtained from medium-sized (40mm×40mm×60mm) and large-sized specimens (60mm×90mm×90mm) demonstrated greater reliability, providing precise results in finite element numerical simulations.

River bed materials serve multiple environmental functions as a habitat for aquatic invertebrates and fishes. At the same time, the particle size of the bed material reflects the tractive force of the flow regime in a flood and provides useful information for flood control. The traditional river bed particle size surveys, such as sieving, require time and labor to investigate river bed materials. The authors proposed a method to classify aerial images taken by unmanned aerial vehicle (UAV) using convolutional neural networks (CNN), our previous study showed that terrestrial riverbed material could be classified with high accuracy. In this study, we attempted to classify riverbed materials distributed in shallow waters where the bottom can be seen from UAVs. After training the CNN to classify the images with the same grain size as being in the same class even if the surface flow types taken overlapping the riverbed material were different, the total accuracy reached 90.3%. Moreover, the proposed method was applied to the wide-ranging area to determine the distribution of the particle size. In parallel, the microtopography was surveyed using Lidar-UAV, and the relationship between the microtopography and particle size distribution was discussed. In the steep section, coarse particles were distributed and formed a rapid. Fine particles were deposited on the upstream side of those rapids, where the slope had become gentler due to the damming. There was good agreement between the microtopographical trends and the grain size distribution.

Inland capture fisheries play a critical role in supporting food security and livelihoods in West Africa. Therefore, it is important to evaluate genetic health of exploited fish populations. The African bonytongue, Heterotis niloticus, supports important commercial and subsistence fisheries in West Africa. Sharp declines of stocks have been reported, however. Herein, we estimate contemporary effective population sizes (Ne) of four Heterotis populations in Nigeria, three in Benin, and five in Cameroon using the Linkage Disequilibrium method with correction for age structure. Ne estimates were used to assess genetic short-term (i.e., inbreeding depression) and long-term (i.e., loss of evolutionary potential) risks. Analyses failed to obtain Ne point estimates for two populations. For the remaining ten populations, corrected Ne point estimates fell well below 500, the minimum recommended for populations to retain evolutionary potential; with eight populations below 100 (range 2.8–83.5), the minimum recommended to avoid inbreeding depression, one borderline (100–125), and one above this threshold (312–392). The lower 95% confidence interval bound of Ne for eleven populations was very small (0.7–14.6), and for the remaining population it was 44.2. Accordingly, all populations examined can be considered potentially at risk of inbreeding depression.

The interactions of metal ions with fulvic acids resulted in changes in the particle size and charge. Particle size distribution was trimodal for fulvic acids, bimodal for fulvic complexes with calcium and magnesium, and copper-fulvic complexes had only one size fraction. The compensation of negative charge of carboxylic and phenolic functional groups by positive charged metal ions resulted in the increase in zeta potential which was getting closer to zero in the case of copper-fulvic complexes. However, all metal humic complexes behaved as colloidally unstable which resulted in visually observable sedimentation. Calorimetric measurements provided positive values of changes in enthalpy which indicated endothermic processes. In contrast quantum chemical calculations as well as experiments with model compounds provided negative values indicated exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive which meant spontaneous processes.

Crossbreeding in dairy cattle with exotic breeds continues to be an appealing practice to the dairy farmers of Bangladesh. However, there is limited knowledge regarding the impact of crossbreeding on both the physical attributes and milk quality traits of crossbred cattle in Bangladesh. Therefore, the primary objective of this study was to evaluate the impact of crossbreeding Bangladeshi local cattle with the exotic Holstein breed on their body characteristics and milk quality. To achieve the goal, data pertaining to body traits and milk samples were gathered from a total of 981 cows from 19 dairy farms located in the northwestern region of Bangladesh. A trained evaluator measured body condition score (BCS), udder score, locomotion score, and body conformation traits. Milk yield information was acquired from official records, while milk composition details were determined through milk analysis. The average measurements for body traits were as follows: wither height (WH) at 138 cm, body length (BL) at 155 cm, and heart girth (HG) at 203 cm. Notably, crossbred cows (Holstein x Local cattle) exhibited greater values for WH, BL, HG, BCS, and udder score than their Bangladeshi local counterparts. Furthermore, the average daily milk yield of sampled cows was recorded at 8.7 kg, with fat and protein contents of 3.78% and 3.67%, respectively. It is worth noting that crossbred cows produced a higher volume of milk compared to Bangladeshi local cattle. However, milk from crossbred cows displayed lower fat and protein content, although their somatic cell score (SCS) remained similar. Additionally, milk from crossbred cows exhibited a longer coagulation time when compared to that of Bangladeshi local cattle. A more comprehensive assessment of the crossbreeding scheme, particularly in comparison to Holstein, would necessitate further research, including an examination of its impact on cheese yield traits, health, fertility, and longevity.

This study describes a comparative in vitro study of the toxicity behavior of zinc oxide (ZnO) nanoparticles and micro-sized particles. The study aimed to understand the impact of particle size on ZnO toxicity by characterizing the particles in different media, including cell culture media, human plasma, and protein solutions (bovine serum albumin and fibrinogen). The study used various techniques such as atomic force microscopy (AFM), transmission electron microscopy (TEM), and dynamic light scattering (DLS) to characterize the particles and their interactions with proteins. Hemolytic activity, coagulation time, and cell viability assays were used to assess ZnO toxicity. The results highlight the complex interactions between ZnO NPs and biological systems, including their aggregation behavior, hemolytic activity, protein corona formation, coagulation effects, and cytotoxicity. Moreover, the study indicates that ZnO nanoparticles are not more toxic than micro-sized particles, and the 50 nm particles resulted in general the least toxic. Furthermore, the study found that at low concentrations, no acute toxicity was observed. Overall, this study provides important insights into the toxicity behavior of ZnO particles and highlights that no direct relationship between nanometer size and toxicity can be directly attributed.

Micro-nano-plastics (MNPs) are an important constituent of atmospheric aerosol. However, there is still no standard procedure for their sampling and size fractionation, which is an obstacle to the aggregation and critical analysis of results obtained by different research groups. This review focuses on the sampling and fractionation methodologies used for MNPs. Moreover, a straightforward optimized methodology for the sampling and fractionation is proposed.

GaN-based micro-size light-emitting diodes (µLEDs) have a number of appealing and distinctive benefits for display, visible-light communication (VLC), and other novel applications. The smaller size of LEDs affords them the benefits of enhanced current expansion, less self-heating effects, and higher current density bearing capacity. Low external quantum efficiency (EQE) resulting from non-radiative recombination and quantum confined stark effect (QCSE) is the serious barrier for applications of µLEDs. In this work, the reasons for the poor EQE of µLEDs are reviewed, as well as the optimization techniques for improving the EQE of µLEDs.

The effect of biotic (e.g., growth characteristics) and a-biotic (e.g., crown closure) factors on cone production, fertility variation and gene diversity was evaluated in two consecutive years in 130 year old natural populations of Taurus cedar also called cedar of Lebanon (Cedrus libani A. Rich.). The a-biotic factors viz., altitude, temperature, aspect and rainfall varied; while some of them can be managed by cultural operations like management of crown and stand density. Impact of crown closure on cone production, fertility variation and related parameters were observed in Taurus cedar’s natural populations sampled from southern Turkey. Maximum cone production of 29 and 40/tree was recorded with full crown closure in two consecutive years by large differences among individuals within crown closure class. For instance, cone productions were between 10 and 67 in full crown closure of first year. The sibling coefficient, which is a measure of the fertility variation in a stand, was the highest (1.16) for full crown closure in the first (meaning 86% fertile trees) and the second year (1.55, 65%), while it was the lowest for medium crown closure (1.09, 92%) in both years. Gene diversity decreased from a degraded patch (0.987) to that with full crown closure (0.984). Results of variance analysis showed significant (p≤0.05) difference between crown closure classes for cone production within second year, and between years. Significant positive (p0.05) correlations were noted between years for cone production (r=0.22), and between cone production and crown closure in first and second years (r=0.29). However, growth characteristics had no effective on cone productions in individual crown closure classes, while there were significant (p0.05) correlations between diameter at breast height and cone production for both years (r= 0.15 and 0.17) in pooled populations.

This review critically examines the various ways in which the mechanical properties of wood have been understood. Despite the immense global importance of wood in construction, most understanding of its elastic and inelastic properties is based on models developed for other materials. Such models neglect wood’s cellular and fibrous nature. This review thus questions how well models that were originally developed for homogeneous and effectively continuous materials can describe wood’s mechanical properties. For example, the elastic moduli of wood have been found by many authors to depend on the size of the test specimen. Such observations are incompatible with classical elasticity theory. There is also much uncertainty about how well elastic moduli can be defined for wood. An analysis of different models for size effects of various inelastic properties of wood shows that these models only approximate the observed behaviour, and do not predict or explain the scatter in the results. A more complete understanding of wood’s mechanical properties must take account of it being in some sense intermediate between a material and a structure.

In order to solve the labor-intensive and time-consuming problem in the process of measuring yak body ruler and weight in yak breeding industry in Qinghai Province, a non-contact method for measuring yak body ruler and weight was proposed in this experiment, and key technologies based on semantic segmentation, binocular ranging and neural network algorithm were studied to boost the development of yak breeding industry in Qinghai Province. Main conclusions: (1) Study yak foreground image extraction, and implement yak foreground image extraction model based on U-net algorithm; select 2263 yak images for experiment, and verify that the accuracy of the model in yak image extraction is over 97%. (2) Develop an algorithm for estimating yak body ruler based on binocular vision, and use the extraction algorithm of yak body ruler related measurement points combined with depth image to estimate yak body ruler. The final test shows that the average estimation error of body height and body oblique length is 2.6%, and the average estimation error of chest depth is 5.94%. (3) Study the yak weight prediction model; select the body height, body oblique length and chest depth obtained by binocular vision to estimate the yak weight; use two algorithms to establish the yak weight prediction model, and verify that the average estimation error of the model for yak weight is 10.7% and 13.01% respectively.

Asphaltenes constitute a heavy fraction of fossil fuels and their characterization is still a very difficult and challenging issue due to their complex and variable composition. Asphaltene components are highly condensed aromatic molecules having some heteroatom and aliphatic functionalities. Their molecular weights distribution span a wide range, from hundreds to millions of units, in dependence on the diagnostic used, leading to speculation about possible occurrence of self-aggregation. In the present work, mass spectrometry, with properly developed mathematical methods, size ex-clusion chromatography and X-ray diffraction analysis have been applied to asphaltenes for giving some further insight on their MW distribution and characteristics. The results here reported give further quantitative support to the experimental data interpretation already reported in previous works.

Introduction: Body size is correlated with many aspects of an animal species' natural history, such as life span, abundance, dispersal capacity and diet breadth. However, contrasting trends have been reported for the relationship between body size and these ecological traits. Methods: Butterfly species from fruit-feeding guilds were used to investigate whether body size correlates with species abundances, dispersal, permanence, and diet breadth in a Neotropical savanna in Brazil (Cerrado). We used Blomberg’s K and Phylogenetic Generalized Least Squares models (PGLS) to measure phylogenetic signal strength in species traits, and to estimate size-dispersal-diet breadth associations while taking shared ancestry into account. Results: 539 individuals from 27 species were captured, and 190 individuals were recaptured, representing a 35% recapture rate. We found that body size negatively influenced butterfly abundance. In contrast, body size was positively associated with dispersal levels, distance traveled, number of traps visited, individual permanence, and diet breadth. These results indicate that larger butterflies have a greater proportion of dispersing individuals over longer distances, as they permanence were detected over longer periods than their smaller relatives. Moreover, larger butterflies are more generalized, based on the number of host plant families and genera they consume. Smaller butterflies demand fewer resources, which is reflected in their higher survival in small patches, and may explain their lower dispersal ability, and higher diet specialization. Nevertheless, lower dispersal ability, if not compensated by large population sizes, may threaten small-bodied species inhabiting environments with intense deforestation rates, such as the Cerrado. Conclusions: Body size positively influences dispersal and diet breadth in the fruit-feeding butterflies collected in this study.

Despite a significant number of investigations in the field of phosphazene chemistry, the mechanism of this class cyclic compounds formation is still poorly studied. At the same time, a thorough understanding of this process is necessary both for the direct production of phosphazene rings with a given size, and for the controlled cyclization reaction when it is secondary and undesirable. Here we have synthesized a series of short linear phosphazene oligomers with the general formula Cl[PCl2=N]n–PCl3+PCl6– and studied their tendency to form cyclic structures under the influence of elevated temperature or in the presence of nitrogen-containing agents, such as hexamethyldisilazane (HMDS) or ammonium chloride. It was established that linear oligophosphazenes are inert when heated in the absence of the mentioned cyclization agents, and the formation of cyclic products occurs only when these agents are involved in the process. It is for the first time shown the ability to obtain the desired size phosphazene cycle from corresponding linear chain. Known obstacles like side interaction with the PCl6– counterion and a tendency of longer chains to undergo crosslinking elongation instead of cyclization are still relevant and ways to overcome them are being discussed.

The increasing demand for higher inclusion cleanliness levels motivates the control over the formation and evolution of inclusions in the steel production process. In this work, the evolution of the chemical composition and size distribution of inclusions throughout a slab production process of Al-killed steel, including ladle furnace (LF) treatment and continuous casting (CC), was followed. The initial solid Al2O3 and Al2O3-MgO inclusions were modified to liquid Al2O3-CaO-MgO inclusions during LF treatment. The evolution of the size distributions during LF treatment was associated with the growth and removal of inclusions, as new inclusions were not created after the deoxidation process, according to a population density function (PDF) analysis. Additionally, the size distributions tended to be similar as the LF treatment progressed regardless of their initial features, whereas they differed during CC. Analysis of the upper tails of the distributions through generalized extreme values theory showed that inclusion distributions shifted from larger to smaller sizes as the process progressed. There were great changes in the distributions of large inclusions throughout the LF treatment and between the end of the LF treatment and the start of the CC process. Additionally, distributions of large inclusions differed at the end of the LF treatment, whereas such differences decreased as CC progressed.

In this work, anchoring of cinchona derivatives to trifunctional cores (hub approach) was demonstrated to obtain size-enlarged organocatalysts. By modifying the cinchona skeleton in different positions, we prepared four C3-symmetric size-enlarged cinchona derivatives (hub-cinchonas), which were tested as organocatalysts and their catalytic activities were compared with the parent cinchona (hydroquinine) catalyst. We showed that in the hydroxyalkylation reaction of indole, hydroquinine provides good enantioselectivities (up to 73% ee), while the four new size-enlarged derivatives gave significantly lower values (up to 29% ee) in this reaction. Anchoring cinchonas to trifunctional cores was found to facilitate nanofiltration-supported catalyst recovery using PolarClean alternative solvent. The C3-symmetric size-enlarged organocatalysts were completely rejected by all the applied membranes, whereas the separation of hydroquinine was found to be insufficient using organic solvent nanofiltration. Furthermore, the asymmetric catalysis was successfully demonstrated in the case of Michael reaction of 1,3-diketones and trans-β-nitrostyrene using Hub3-cinchona (up to 96% ee) as a result of the positive effect of the C3-symmetric structure using a bulkier substrate. This means an increased selectivity of the catalyst in comparison to hydroquinine in the latter Michael reaction.

In this study, a simple and direct numerical scheme is proposed for the similarity solution of Smoluchowski coagulation equation based on Taylor series expansion method of moment. The results show that the present method is convergence with high accuracy by comparison with previous work in the literatures.

Hyperglycemia has been associated with increased inflammatory indexes and larger infarct sizes in patients with obstructive acute myocardial infarction (obs-AMI). In contrast, no studies have explored these correlations in non-obstructive acute myocardial infarction (MINOCA). We investigated the relationship between hyperglycemia, inflammation and infarct size in a cohort of AMI patients that included MINOCA. Patients with AMI undergoing coronary angiography between 2016 and 2020 were enrolled. The following inflammatory markers were evaluated: C-reactive protein, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and neutrophil-to-platelet ratio (NPR). Myocardial infarct size was measured by peak high sensitivity troponin I (Hs-TnI) levels, left-ventricular-end-diastolic-volume (LVEDV) and left ventricular ejection fraction (LVEF). The final study population consisted of 2450 patients with obs-AMI and 239 with MINOCA. Hyperglycemia was more prevalent among obs-AMI cases. In all hyperglycemic patients - obs-AMI and MINOCA - NLR, NPR, and LPR were markedly altered. Hyperglycemic obs-AMI subjects exhibited a higher Hs-TnI, a larger LVEDV and a lower LVEF compared to normoglycemic ones. Conversely, MINOCA patients showed similar myocardial damage, irrespective of glycemia. Our data confirm the association of hyperglycemic obs-AMI with elevated inflammatory markers and larger infarct sizes. MINOCA patients exhibited modest myocardial damage, regardless of admission glucose levels.

The environmental policy is compelling industries to treat their wastewater to a level that can be released into the domestic sewer system or even for reuse. However, many industrial branches are lacking space for traditional wastewater plant. Hence, electrokinetics wastewater treatment is a viable alternative as it is fast and does not require large space. However, the electrokinetics wastewater treatment is still mostly tested in the laboratory. In the current study, a prototype of electrokinetics wastewater treatment industrial-size device has been designed, constructed and tested under real conditions. In this paper the device is described and the results obtained from the operation of the device are presented and discussed.

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximise the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

Photodynamic therapy (PDT) with a suitable photosensitizer molecule is a promising anticancer treatment. We evaluated two chlorin molecules as potential photosensitizers, methyl pyropheophorbide a (MPPa) and N-methoxyl purpurinimide (NMPi), against A549 human lung adenocarcinoma cells in vitro as well as in A549 tumor-bearing mice in vivo. Cell viability, microscopy, and FACS analyses were performed for the in vitro studies. MPPa and NMPi showed high phototoxicity in vitro, which was dependent on the concentration of the photosensitizers as well as the light irradiation time. In the animal study, tumor volume change, tumor surface alterations, and H&E and TUNEL staining analyses were performed and compared between small (tumor volume of <50 mm³) and large (tumor volume of >50 mm³) size of initial tumors. MPPa and NMPi showed high anticancer efficacy against small-size tumors, indicating that early treatment with PDT is effective. Especially, repeated two times PDT with NMPi allowed almost complete eradication against small-size tumors. However, MPPa and NMPi were not effective against large-size tumors. In conclusion, the two chlorin derivatives, MPPa and NMPi, show good anticancer efficacy as promising photosensitizers for PDT in vitro and in vivo. Moreover, their activity in vivo was significantly dependent on the initial tumor size in mice, which confirms the importance of early cancer treatment.

In order to investigate the size distributions and seasonal variations of carbonaceous aerosols (OC and EC), the carbonaceous species were collected and then analyzed by using a 9-stage Anderson-type aerosol sampler and DRI Model 2001A Thermal/Optical Carbon Analyzer on the typical industrial city Nanjing in Yangtze River Delta, China in the summer, autumn and winter of 2013 and spring of 2014. OC, EC, SOC and POC exhibited obvious seasonal variations, with the highest level in winter (39.1±14.0, 5.7±2.1, 23.6±11.7 and 14.1±5.7 μg•m^-3) and the lowest level in summer (20.6±6.7, 3.3±2.0, 12.2±3.8 and 8.4±4.1 μg•m^-3), and were mainly centralized in PM_1.1 in four seasons. The concentrations of OC in PM_1.1 varied in the order of winter > autumn > spring > summer, while EC ranked in the order of autumn > winter > summer > spring. In the PM_1.1-2.1 and PM_2.1-10, the concentrations of OC and EC decreased in the sequence of winter > spring > autumn > summer. The size spectra of OC, EC and SOC had bimodal distributions in four seasons, except for EC with four peaks in summer. The size spectra of POC varied greatly with seasons, exhibiting bimodal distribution in winter, trimodal distribution in spring and summer, and four peaks in autumn. The OC/EC ratios were 7.0, 6.3, 7.6 and 6.9 in spring, summer, autumn and winter, respectively, which demonstrated the abundance of secondary organic aerosols in Nanjing. The sources of carbonaceous aerosol varied significantly with seasons, and were dominated by vehicle exhaust, coal and biomass burning in PM_2.1, and dominant by dust, coal and biomass burning in PM_2.1-10.

Predicting the thermophysical properties of designed materials at the nanoscale is crucial. However, this remains a significant challenge despite numerous efforts by researchers and scientists. This paper presents a unified thermodynamic model to study the size and shape-dependent cohesive energy, as well as the melting temperature of semiconductor nanosolids, including InSb, ZnSe, CdS, and CdSe. The model provides insight into the thermal stability of nanosolid materials by considering the combined impact of size, shape, and packing density. The finding indicates that smaller nanoparticles exhibit a lower cohesive energy compared to larger ones. Our unified thermodynamic model yields results consistent with experimental values and demonstrates a closer agreement than those from the universal liquid drop model of size-dependent cohesive energy, which includes a shape factor of α = 2/3 for nanowires. According to the results, the melting temperature of nanoparticles drops as their size decreases. Below a diameter of 5 nm, this trend becomes more noticeable. In the nano-scale domain, the nanoparticle's shape also matters greatly. In particular, compared to tetrahedral nanoparticles, nanowires show a lesser reduction in melting temperature. Also, up to a diameter of roughly 10 nm, the melting temperatures of these nanoparticles rise with particle size. The search results show that, especially in the < 5 nm size range, the size and shape of nanoparticles significantly affect their melting point. The models accurately predict the relationship between particle size and melting point for various semiconductor nanomaterials, aligning with experimental findings. Interestingly, the information points to a potential preference for these nanomaterials to form nanowire structures in the < 5 nm size range. Our research offers helpful insights into the thermophysical properties of these semiconducting materials, which may have significant implications for their use in a diversity of technological applications.

Cotton seeds as the main by-product of cotton are not only an important raw material for edible oil and feed but also a source of biofuel. The quality of cotton seeds directly affects cotton planting and is closely related to the yield and fiber quality. However, the molecular mechanism governing cotton seed size remains largely unexplored. This study investigates the regulatory mechanisms of cotton seed size by focusing on two cotton genotypes, N10 and N12, which exhibit notable phenotypic variations across multiple environments. Developing seeds were sampled at various stages (5, 20, 30, and 35 DAP) and subjected to RNA-seq. The temporal pattern clustering and WGCNA on differentially expressed genes identified 413 candidate genes, including these related to sugar metabolism that were significantly enriched in transcriptional regulation. A genetic transformation experiment indicated that the overexpression of the GhUXS5 gene encoding UDP-glucuronate decarboxylase 5 significantly increased seed size, suggesting an important role of GhUXS5 in regulating cotton seed size. This discovery provides crucial insights into the molecular mechanisms controlling cotton seed size, helping to unravel the complex regulatory network and offering new strategies and targets for cotton breeding to enhance the economic value of cotton seeds and overall cotton yield.

The present paper investigates flaw strength distributions established using various flexural tests on batches of SiC bar test specimens: 4-point bending as well as 3-point bending with different span lengths. Flaw strength is given by the elemental stress operating on the critical flaw at fracture of a test specimen. Fracture inducing flaws and their locations are identified by fractography. A single population of pores was found to dominate fracture. The construction of diagrams of p-quantile vs elemental strengths was aimed at assessing the Gaussian nature of flaw strengths. Then, empirical cumulative distributions of strengths were constructed using the normal distribution function. Weibull cumulative probability distributions were derived from the mean and the standard deviation using the first moment equation. Agreement was obtained between both Weibull and normal flaw strengths distributions. The cumulative distributions for the different bending tests were predicted satisfactorily from the flaw strength density function using the elemental strength model. Flaw strength distributions that include potential weaker flaws encountered in larger test pieces are extrapolated using the p-quantile diagrams. Implications are discussed about the pertinence of an intrinsically representative flaw strength distribution, about failure predictions, about size effects, and about the significance of flaw spatial distributions.

Quantitative determination of the critical size of inclined coal pillar in old goaf water affected area is of great significance for water damage prevention and safe mining. The critical size of inclined waterproof coal pillar is derived by using theoretical analysis, numerical calculation and field engineering practice for the stability of the waterproof coal pillar in old goaf water affected area of 1303 working face of Dananhu I mine in Xinjiang region. Firstly, a force model of inclined waterproof coal pillar was established to reveal the law that the critical size of the coal pillar increases with the increase of coal seam inclination under the action of asymmetric load. Then, numerical simulation was applied to reveal the dynamic evolution process of plastic deformation-destabilization-destruction of section coal pillar under the influence of mining and single-side water pressure, and the critical size of waterproof coal pillar in study area was determined to be 19.09m. Finally, measures such as pumping and pressure relief and slurry reinforcement were adopted to reduce the deformation rate of the roadway on side of waterproof coal pillar, which ensured the stability of the coal pillar and roadway and the safe recovery of the working face.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions. This IRB approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. We used a General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) to acquire two DTI sequences of the left knee on each child at 3T: an in-plane 2.0 x 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel, neither had an inter-section gap. We used a multi-band DTI acquisi-tion with fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 sec/mm2). The MR vendor-provided a commercially available DL model applied with 75% noise reduction settings to same subject DTI sequences at different spatial res-olutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for femur and tibia, at each spatial resolution. Differences were evaluated using Wilcox-on-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffu-sion metrics in femur and tibia using the 2 mm x 2mm x 3 mm voxel dimension there were no significant differences between tract count (p = 0.1, p =0.14) tract volume (p = 0.14, p = 0.29), or tibial tract length (p=0.16); femur tract length exhibited a significant difference (p

Background: Nowadays, the prevalence of digital device usage has shifted the demands for multifocal intraocular lenses. To accurately capture outcomes, clinical practice must evaluate digital reading performance. We aimed to assess the digital reading performance using a digital device in patients with diffractive multifocal intraocular lenses. Methods: Patients with bilateral diffractive multifocal intraocular lens implantation were included in the study. Monocular and binocular uncorrected and corrected visual acuity was measured using the LogMAR chart and the MNREAD application. Binocular uncorrected defocus curves were obtained using the LogMAR chart at 4m. The reading acuity was measured using the MNREAD application with positive and negative display polarities. The mean digital critical print size (CPS) was recorded using the MNREAD application at 40cm. Results: Our study reported uncorrected distance, intermediate, and near visual acuity were -0.084 ± 0.079, -0.014 ± 0.078, and 0.040 ± 0.081, respectively. The mean reading acuity at three months postoperatively with positive display polarity at 60cm and 40cm was -0.115 ± 0.102 and -0.008 ± 0.083, respectively. The mean digital CPS at three months postoperatively was 0.238 ± 0.100 logMAR. Conclusions: Incorporating digital reading performance measurements provides additional advantages in assessing the effectiveness of bilateral diffractive multifocal intraocular lens implantation.

ABSTRACT: Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses among different growth stages. The effects of waterlogging at flowering stage on the grain yield and starch quality of waxy maize were studied using Suyunuo5 (SYN5) and Yunuo7 (YN7). The grain yield and starch concentration of both hybrids were reduced by waterlogging. The size of starch granules and proportion of small-molecule amylopectin increased in SYN5 and decreased in YN7 when plants suffered waterlogging at flowering, in contrast to the change trend of relative crystallinity. The pasting viscosities and gelatinization temperatures were reduced, whereas the gelatinization enthalpy was unaffected by waterlogging in both hybrids. Our study indicated that waterlogging at flowering reduced the grain yield, restricted starch deposition, and deteriorated the pasting property of waxy maize. Between the two hybrids, YN7 and high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for viscous and less retrograde food. Results provide information for utilization of waxy maize grain in food production.

Network neuroscience delves into comprehending the intricate arrangement and interactions within the neural networks of the brain. By merging insights from both neuroscience and network theory, it investigates the brain's structure and function through the lens of interconnected nodes (symbolizing brain regions) and edges (symbolizing the connections among these regions) forming a dynamic network. Graph metrics play a pivotal role in neuroscience by providing quantifiable insights into the intricate connectivity patterns within the brain's neural networks. Frequently, nodes are extracted from functional or structural atlases, which can lead to diverse shapes and sizes. Nevertheless, our understanding of how these differing node characteristics and definitions impact the computed graph metrics in neuroimaging data remains limited. This study adopts a data-driven methodology to delineate functional nodes, subsequently examining the influence of their sizes on resultant graph metrics. By employing the Neuromark framework, an entirely automated independent component analysis (ICA) is applied to resting state fMRI data. Through this, functional network connectivity (FNC) matrices are computed—capturing Pearson correlations between component-time courses—while employing a proportional threshold to streamline node connections based on these correlations. Subsequently, various global and local graph metrics are computed, offering insights into network characteristics. Global metrics provide an overarching summary of the network structure, while local measures delve into structural intricacies at the individual component level. Node sizes are computed based on voxel counts surpassing a designated threshold. Next, we calculated the Pearson correlation between the obtained node sizes and the graph metrics, which we term 'node-metric coupling' (NMC). Our findings revealed consistent and noteworthy correlations between the values of graph metrics and the dimensions of brain nodes. To delve deeper into the implications of this correlation, we examined the node-metric coupling within a dataset comprising Alzheimer's disease, mild cognitive impairment, and control subjects. The disparities observed in node-metric coupling among these groups underscore the necessity of accounting for this factor during analysis. The two principal outcomes of this study are as follows: Firstly, the substantial interplay between varying node sizes within a given atlas and the resultant graph metrics; and secondly, the potential utility of node-metric coupling as a viable biomarker for brain disorders. These discoveries hold significant ramifications. While comparing studies employing diverse atlases is already a challenge, our work highlights an additional, critical source of variability: accounting for node sizes. Consequently, the association between intra-atlas node size and graph metric should be thoughtfully acknowledged in future neuroimaging investigations.