Search Results (1,435)

The first step in comprehending the properties of Au₁₀ clusters is understanding the lowest energy structure at low and high temperatures. Functional materials operate at finite temperatures; however, energy computations employing density functional theory (DFT) methodology are typically carried out at zero temperature, leaving many properties unexplored. This study explored the potential and free energy surface of the neutral Au₁₀ nanocluster at a finite temperature, employing a genetic algorithm coupled with DFT and nanothermodynamics. Furthermore, we computed the thermal population and infrared Boltzmann spectrum at a finite temperature and compared it with the validated experimental data. Moreover, we performed the chemical bonding analysis using the quantum theory of atoms in molecules (QTAIM) approach and the adaptive natural density partitioning method (AdNDP) to shed light on the bonding of Au atoms in the low-energy structures. In the calculations, we take into consideration the relativistic effects through the zero-order regular approximation (ZORA), the dispersion through Grimme’s dispersion with Becke–Johnson damping (D3BJ), and we employed nanothermodynamics to consider temperature contributions. Small Au clusters prefer the planar shape, and the transition from 2D to 3D could take place at atomic clusters consisting of ten atoms, which could be affected by temperature, relativistic effects, and dispersion. We analyzed the energetic ordering of structures calculated using DFT with ZORA and single-point energy calculation employing the DLPNO-CCSD(T) methodology. Our findings indicate that the planar lowest energy structure computed with DFT is not the lowest energy structure computed at the DLPN0-CCSD(T) level of theory. The computed thermal population indicates that the 2D elongated hexagon configuration strongly dominates at a temperature range of 50–800 K. Based on the thermal population, at a temperature of 100 K, the computed IR Boltzmann spectrum agrees with the experimental IR spectrum. The chemical bonding analysis on the lowest energy structure indicates that the cluster bond is due only to the electrons of the 6 s orbital, and the Au d orbitals do not participate in the bonding of this system. Full article

Those responsible for elite and youth athletes are increasingly aware of the need to balance the quest for superior performance with the need to protect the physical and psychological wellbeing of athletes. As a result, regular assessment of risks to mental health is a common feature in sports organisations. In the present study, the Brazil Mood Scale (BRAMS) was administered to 898 athletes (387 female, 511 male, age range: 12–44 years) at a leading sports club in Rio de Janeiro using either “past week” or “right now” response timeframes. Using seeded k-means cluster analysis, six distinct mood profile clusters were identified, referred to as the iceberg, surface, submerged, shark fin, inverse iceberg, and inverse Everest profiles. The latter three profiles, which are associated with varying degrees of increased risk to mental health, were reported by 238 athletes (26.5%). The prevalence of these three mood clusters varied according to the response timeframe (past week > right now) and the sex of the athletes (female > male). The prevalence of the iceberg profile varied by athlete sex (male > female), and age (12–17 years > 18+ years). Findings supported use of the BRAMS as a screening tool for the risk of psychological issues among athletes in Brazilian sports organisations. Full article

This study introduces a novel satellite image digital surface model (DSM) reconstruction framework grounded in deep learning methodology. The proposed framework effectively utilizes a rational polynomial camera (RPC) model to establish the mapping relationship between image coordinates and geographic coordinates. Given the expansive coverage and abundant ground object data inherent in satellite images, we designed a lightweight deep network model. This model facilitates both coarse and fine estimation of a height map through two distinct stages. Our approach harnesses shallow and deep image information via a feature extraction module, subsequently employing RPC Warping to construct feature volumes for various angles. We employ variance as a similarity metric to achieve image matching and derive the fused cost volume. Following this, we aggregate cost information across different scales and height directions using a regularization module. This process yields the confidence level of the current height plane, which is then regressed to predict the height map. Once the height map from stage 1 is obtained, we gauge the prediction’s uncertainty based on the variance in the probability distribution in the height direction. This allows us to adjust the height estimation range according to this uncertainty, thereby enabling precise height value prediction in stage 2. After conducting geometric consistency detection filtering of fine height maps from diverse viewpoints, we generate 3D point clouds through the inverse projection of RPC models. Finally, we resample these 3D point clouds to produce high-precision DSM products. By analyzing the results of our method’s height map predictions and comparing them with existing deep learning-based reconstruction methods, we assess the DSM reconstruction performance of our proposed framework. The experimental findings underscore the robustness of our method against discontinuous regions, occlusions, uneven illumination areas in satellite imagery, and weak texture regions during height map generation. Furthermore, the reconstructed digital surface model (DSM) surpasses existing solutions in terms of completeness and root mean square error metrics while concurrently reducing the model parameters by 42.93%. This optimization markedly diminishes memory usage, thereby conserving both software and hardware resources as well as system overhead. Such savings pave the way for a more efficient system design and development process. Full article

Polymeric Intraocular lenses (IOLs) are vital for restoring vision following cataract surgery and for correcting refractive errors. Despite technological and medical advancements, challenges persist in achieving optimal vision and preventing complications. Surface modifications aim to mitigate the risk of posterior capsule opacification (PCO), while pre-operative measurements aid in selecting suitable IOLs. However, individualized solutions are lacking and there is a clear demand for the development of fully customized IOL surfaces. We employ laser micromachining technology for precise modifications via ablation on PMMA and acrylic IOLs, using femtosecond (fs), nanosecond (ns), and diode continuous wave (CW) lasers, at wavelengths ranging from near-ultraviolet to infrared. Characterization reveals controlled ablation patterning, achieving feature sizes from as small as 400 nm to several micrometers. Regular and confocal micro-Raman spectroscopy revealed alterations of the IOL materials’ structural integrity for some patterning cases, thus affecting the optical properties, while these can be minimized by the proper selection of micromachining conditions. The results suggest the feasibility of accurate IOL patterning, which could offer personalized vision correction solutions, based on relevant corneal wavefront data, thus surpassing standard lenses, marking a significant advancement in cataract surgery outcomes. Full article

This paper reports on the coating of heterostructured TiO₂ nanopores/nanotubes on Ti substrates by anodizing at high voltages to design surfaces for biomedical implants. As the anodized voltage from 50 V to 350 V was applied, the microstructure of the coating shifted from regular TiO₂ nanotubes to heterostructured TiO₂ nanopores/nanotubes. In addition, the dimension of the heterostructured TiO₂ nanopores/nanotubes was a function of voltage. The electrochemical characteristics of TiO₂ nanotubes and heterostructured TiO₂ nanopores/nanotubes were evaluated in simulated body fluid (SBF) solution. The creation of heterostructured TiO₂ nanopores/nanotubes on Ti substrates resulted in a significant increase in BHK cell attachment compared to that of the Ti substrates and the TiO₂ nanotubes. Full article

The uneven distribution of global navigation satellite system (GNSS) continuous stations in the Yellow River Basin, combined with the sparse distribution of GNSS continuous stations in some regions and the weak far-field load signals, poses challenges in using GNSS vertical displacement data to invert terrestrial water storage changes (TWSCs). To achieve the inversion of water reserves in the Yellow River Basin using unevenly distributed GNSS continuous station data, in this study, we employed the Tikhonov regularization method to invert the terrestrial water storage (TWS) in the Yellow River Basin using vertical displacement data from network engineering and the Crustal Movement Observation Network of China (CMONOC) GNSS continuous stations from 2011 to 2022. In addition, we applied an inverse distance weighting smoothing factor, which was designed to account for the GNSS station distribution density, to smooth the inversion results. Consequently, a gridded product of the TWS in the Yellow River Basin with a spatial resolution of 0.5 degrees on a daily scale was obtained. To validate the effectiveness of the proposed method, a correlation analysis was conducted between the inversion results and the daily TWS from the Global Land Data Assimilation System (GLDAS), yielding a correlation coefficient of 0.68, indicating a strong correlation, which verifies the effectiveness of the method proposed in this paper. Based on the inversion results, we analyzed the spatial–temporal distribution trends and patterns in the Yellow River Basin and found that the average TWS decreased at a rate of 0.027 mm/d from 2011 to 2017, and then increased at a rate of 0.010 mm/d from 2017 to 2022. The TWS decreased from the lower-middle to lower reaches, while it increased from the upper-middle to upper reaches. Furthermore, an attribution analysis of the terrestrial water storage changes in the Yellow River Basin was conducted, and the correlation coefficients between the monthly average water storage changes inverted from the results and the monthly average precipitation, evapotranspiration, and surface temperature (AvgSurfT) from the GLDAS were 0.63, −0.65, and −0.69, respectively. This indicates that precipitation, evapotranspiration, and surface temperature were significant factors affecting the TWSCs in the Yellow River Basin. Full article

This article explores the use of citrus residues as a source of different pectic materials for packaging film production: a water-soluble orange residue extract (WSE) (~5% pectin), semi-pure pectins extracted in citric acid (SP) (~50% pectin), and commercial pure citrus pectins (CP). First, these materials were characterized in terms of chemical composition. Then, films were produced using them pure or mixed with chitosan or glycerol through solvent-casting. Finally, antioxidant activity, functional properties (e.g., mechanical and gas barrier properties), and visual appearance of the films were assessed. WSE films showed the highest antioxidant activity but the lowest mechanical strength with the highest elongation at break (EB) (54%); incorporating chitosan increased the films’ strength (Young’s modulus 35.5 times higher). SP films showed intermediate mechanical properties, reinforced by chitosan addition (Young’s modulus 4.7 times higher); they showed an outstanding dry O₂ barrier. CP films showed a similar O₂ barrier to SP films and had the highest Young’s modulus (~29 MPa), but their brittleness required glycerol for improved pliability, and chitosan addition compromised their surface regularity. Overall, the type of pectic material determined the film’s properties, with less-refined pectins offering just as many benefits as pure commercial ones. Full article

Considering the role of phytoplankton in the functioning and health of marine systems, it is important to characterize its responses to a changing environment. The central Adriatic Sea, as a generally oligotrophic area, is a suitable environment to distinguish between regular fluctuations in phytoplankton and those caused by anthropogenic or climatic influences. This study provides a long-term perspective of phytoplankton assemblage in the central eastern Adriatic Sea, with 14 years of continuous time series data collected at two coastal and two offshore stations. The predominant phytoplankton groups were diatoms and phytoflagellates, but their proportion varied depending on the vicinity of the coast, as evidenced also by the distribution of chlorophyll a. In the coastal environment, the phytoplankton biomass was substantially higher, with a higher proportion of microphytoplankton, while small phytoplankton accounted for the majority of biomass in the offshore area. In addition, a decreasing trend in diatom abundance was observed in the coastal waters, while such trend was not so evident in the offshore area. Using a neural gas algorithm, five clusters were defined based on the contribution of the major groups. The observed increase in diversity, especially in dinoflagellates, which outnumber diatom taxa, could be a possible adaptation of dinoflagellates to the increased natural solar radiation in summer and the increased sea surface temperature. Full article

High-strength steel is a candidate material for offshore structures, which are currently being constructed with regular-strength steel. These structures are constantly exposed to harsh environmental conditions and experience cyclic loadings, which can lead to premature failure due to the synergistic effects of corrosion and fatigue. In this regard, the current study aims to investigate the effects of corrosion and High-Frequency Mechanical Impact (HFMI) treatment on the fatigue behavior of welded joints made of S700MC steel. Multipass butt-welded joints were fabricated via the Robot GMAW method at an optimally selected heat input of 0.7405 kJ/mm. The microstructure of the weldments was studied using light optical microscopy. Tensile and Vickers microhardness tests were performed to evaluate the mechanical properties of the welded joints. To simulate marine environment corrosion in the laboratory, the as-welded samples were exposed to salt fog spray for 720 h. Subsequently, specimens were subjected to cyclic loading to evaluate their fatigue strength, while SEM and stereomicroscopy were used to analyze the fractured surfaces, providing a comprehensive understanding of the fracture mode. The findings suggest that although corrosion led to increased surface roughness and the formation of corrosion pits, its influence on the fatigue behavior of the weldments might be less significant compared to other geometrical factors, at least for the exposure time employed in the study. Full article

Co-based catalysts have shown great promise for propane dehydrogenation (PDH) reactions due to their merits of environmental friendliness and low cost. In this study, ordered mesoporous molecular sieve-supported CoO_x species (CoO_x/Al-SBA-15 catalyst) were prepared by one-step organometallic complexation. The catalysts show worm-like morphology with regular straight-through mesoporous pores and high external specific surface area. These typical features can substantially enhance the dispersion of CoO_x species and mass transfer of reactants and products. Compared with the conventional impregnation method, the 10CSOC (10 wt.% Co/Al-SBA-15 prepared by the organometallic complexation method) sample presents a smaller CoO_x size and higher Co²⁺/Co³⁺ ratio. When applied to PDH reaction, the 10CSOC delivers higher propane conversion and propylene selectivity. Under the optimal conditions (625 °C and 4500 h⁻¹), 10CSOC achieves high propane conversion (43%) and propylene selectivity (83%). This is attributed to the smaller and better dispersion of CoO_x nanoparticles, more suitable acid properties, and higher content of Co²⁺ species. This work paves the way for the rational design of high-performance catalysts for industrially important reactions. Full article

Oblique photography is a regional digital surface model generation technique that can be widely used for building 3D model construction. However, due to the lack of geometric and semantic information about the building, these models make it difficult to differentiate more detailed components in the building, such as roofs and balconies. This paper proposes a deep learning-based method (U-NET) for constructing 3D models of low-rise buildings that address the issues. The method ensures complete geometric and semantic information and conforms to the LOD2 level. First, digital orthophotos are used to perform building extraction based on U-NET, and then a contour optimization method based on the main direction of the building and the center of gravity of the contour is used to obtain the regular building contour. Second, the pure building point cloud model representing a single building is extracted from the whole point cloud scene based on the acquired building contour. Finally, the multi-decision RANSAC algorithm is used to segment the building detail point cloud and construct a triangular mesh of building components, followed by a triangular mesh fusion and splicing method to achieve monolithic building components. The paper presents experimental evidence that the building contour extraction algorithm can achieve a 90.3% success rate and that the resulting single building 3D model contains LOD2 building components, which contain detailed geometric and semantic information. Full article

Regular wave patterns were created by a 2 kV gallium ion on Si(111) monocrystals at incidence angles between 60° and 80° with respect to the surface normal. The characteristic wavelength and surface roughness of the structured surfaces were determined to be between 35–75 nm and 0.5–2.5 nm. The local slope distribution of the created periodic structures was also studied. These topography results were compared with the predictions of the Bradley–Harper model. The amorphised surface layers were investigated by a spectroscopic ellipsometer. According to the results, the amorphised thicknesses were changed in the range of 8 nm to 4 nm as a function of ion incidence angles. The reflectance of the structured surfaces was simulated using ellipsometric results and measured with a reflectometer. Based on the spectra, a controlled modification of reflectance within 45% and 50% can be achieved on Si(111) at 460 nm wavelength. According to the measured results, the characteristic sizes (periodicity and amplitude) and optical property of silicon can be fine-tuned by low-energy focused ion irradiation at the given interval of incidence angles. Full article

The estimation of water quality properties through satellite remote sensing relies on (1) the optical characteristics of the water body, (2) the resolutions (spatial, spectral, radiometric and temporal) of the sensor and (3) algorithm(s) applied. More than 80% of global water bodies fall under Case I (open ocean) waters, dominated by scattering and absorption associated with phytoplankton in the water column. Globally, previous studies show significant correlations between satellite-based retrieval methods and field measurements of absorbing and scattering constituents, while limited research from Australian coastal water bodies appears. This study presents a methodology to extract chlorophyll a properties from surface waters from near-coastal environments, within 2 km of coastline, in Tasmania, south-eastern Australia. We use general purpose, global, long-time series, multi-spectral satellite data, as opposed to ocean colour-specific sensor data. This approach may offer globally applicable tools for combining global satellite image archives with in situ field sensors for water quality monitoring. To enable applications from local to global scales, a cloud-based geospatial analysis workflow was developed and tested on several sites. This work represents the initial stage in developing a semi-automated near-coastal water-quality workflow using easily accessed, fully corrected global multi-spectral datasets alongside large-scale computation and delivery capabilities. Our results indicated a strong correlation between the in situ chlorophyll concentration data and blue-green band ratios from the multi-spectral sensor. In line with published research, environment-specific empirical models exhibited the highest correlations between in situ and satellite measurements, underscoring the importance of tailoring models to specific coastal waters. Our findings may provide the basis for developing this workflow for other sites in Australia. We acknowledge the use of general purpose multi-spectral data such as the Sentinel-2 and Landsat Series, their corrections and algorithms may not be as accurate and precise as ocean colour satellites. The data we are using are more readily accessible and also have true global coverage with global historic archives and regular, global collection will continue at least 10 years in the future. Regardless of sensor specifications, the retrieval method relies on localised algorithm calibration and validation using in situ measurements, which demonstrates close-to-realistic outputs. We hope this approach enables future applications to also consider these globally accessible and regularly updated datasets that are suited to coastal environments. Full article

The sedimentation of a soft particle composed of an uncharged hard sphere core and a charged porous surface layer inside a concentric charged spherical cavity full of a symmetric electrolyte solution is analyzed in a quasi-steady state. By using a regular perturbation method with small fixed charge densities of the soft sphere and cavity wall, a set of linearized electrokinetic equations relevant to the fluid velocity field, electrical potential profile, and ionic electrochemical potential energy distributions are solved. A closed-form formula for the sedimentation velocity of the soft sphere is obtained as a function of the ratios of core-to-particle radii, particle-to-cavity radii, particle radius-to-Debye screening length, and particle radius-to-porous layer permeation length. The existence of the surface charge on the cavity wall increases the settling velocity of the charged soft sphere, principally because of the electroosmotic enhancement of fluid recirculation within the cavity induced by the sedimentation potential gradient. When the porous layer space charge and cavity wall surface charge have the same sign, the particle velocity is generally enhanced by the presence of the cavity. When these fixed charges have opposite signs, the particle velocity will be enhanced/reduced by the presence of the cavity if the wall surface charge density is sufficiently large/small relative to the porous layer space charge density in magnitude. The effect of the wall surface charge on the sedimentation of the soft sphere increases with decreases in the ratios of core-to-particle radii, particle-to-cavity radii, and particle radius-to-porous layer permeation length but is not a monotonic function of the ratio of particle radius-to-Debye length. Full article

The exploiting of hybrid beamforming (HBF) in massive multiple-input multiple-output (MIMO) systems can enhance the system’s sum rate while reducing power consumption and hardware costs. However, designing an effective hybrid beamformer is challenging, and interference between multiple users can negatively impact system performance. In this paper, we develop a scheme called Subset Optimization Algorithm-Hybrid Beamforming (SOA-HBF) that is based on the subset optimization algorithm (SOA), which effectively reduces inter-user interference by dividing the users set into subsets while optimizing the hybrid beamformer to maximize system capacity. To validate the proposed scheme, we constructed a system model that incorporates an intelligent reflecting surface (IRS) to address obstacles between the base station (BS) and the users set, enabling efficient wireless communication. Simulation results indicate that the proposed scheme outperforms the baseline by approximately 8.1% to 59.1% under identical system settings. Furthermore, the proposed scheme was applied to a classical BS–users set link without obstacles; the results show its effectiveness in both mmWave massive MIMO and IRS-assisted fully connected hybrid beamforming systems. Full article