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The production management of lactating sows is a crucial aspect of pig farm operations, as their health directly impacts the farm’s production efficiency. The feeding behavior of lactating sows can reflect their health and welfare status, and monitoring this behavior is essential for precise feeding and management. To address the issues of time-consuming and labor-intensive manual inspection of lactating sows’ feeding behavior and the reliance on breeders’ experience, we propose a method based on the improved YOLO (You Only Look Once) v5s algorithm and image segmentation for detecting the feeding behavior of lactating sows. Based on the YOLOv5s algorithm, the SE (Squeeze-and-Excitation) attention module was added to enhance the algorithm’s performance and reduce the probability of incorrect detection. Additionally, the loss function was replaced by WIoU (Weighted Intersection over Union) to accelerate the model’s convergence speed and improve detection accuracy. The improved YOLOv5s-C3SE-WIoU model is designed to recognize pre-feeding postures and feed trough conditions by detecting images of lactating sows. Compared to the original YOLOv5s, the improved model achieves an 8.9% increase in [email protected] and a 4.7% increase in [email protected] to 0.95. This improvement satisfies the requirements for excellent detection performance, making it suitable for deployment in large-scale pig farms. From the model detection results, the trough remnant image within the detection rectangle was extracted. This image was further processed using image processing techniques to achieve trough remnant image segmentation and infer the remnant amount. Based on the detection model and residue inference method, video data of lactating sows’ feeding behavior were processed to derive the relationship between feeding behavior, standing time, and residue amount. Using a standing duration of 2 s and a leftover-feed proportion threshold of 2% achieves the highest accuracy, enabling the identification of abnormal feeding behavior. We analyzed the pre-feeding postures and residual feed amounts of abnormal and normal groups of lactating sows. Our findings indicated that standing time was significantly lower and residual feed amount was higher in the abnormal groups compared to the normal groups. By combining standing time and residual feed amount information, accurate detection of the feeding status of lactating sows can be realized. This approach facilitates the accurate detection of abnormal feeding behaviors of lactating sows in large-scale pig farm environments. Full article

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic resulted in widespread morbidity and mortality, but generally, the diagnosis of other respiratory viruses was limited. This study aimed to assess the prevalence of other respiratory viruses during the 2020/21 pandemic among patients of all ages who accessed care at public healthcare facilities in Gauteng Province, South Africa. Laboratory diagnosis for respiratory viruses, with or without SARS-CoV-2, was conducted via multiplex real-time polymerase chain reactions using respiratory specimens. A total of 1776 patients were included from 1 April 2020 to 31 March 2021, of which 766 (43.1%) were positive for respiratory viruses other than SARS-CoV-2. RV (368/1776; 20.7%) was the most prevalent, followed by RSV (304/1776; 17.1%), AdV (112/1776; 6.3%) and EV (105/1776; 5.9%). hCoV-OC43 (39/1776; 2.2%) was the most prevalent common coronavirus. SARS-CoV-2 co-infections were detected in 4.8% (24/500) of patients. Only 27.1% (482/1776) of patients were admitted to high-care or intensive care units. A decrease in respiratory virus detections was observed, except for RSV, EV and hCoV-OC43. RSV prevalence increased in 2021, while influenza A/B viruses remained undetected. Full article

The Coulomb coupling between transition densities of the pigments in photosynthetic pigment-protein complexes, termed excitonic coupling, is a key factor for the description of optical spectra and energy transfer. A challenging question is the quantification of the screening of the excitonic coupling by the optical polarizability of the environment. We use the equivalence between the sophisticated quantum chemical polarizable continuum (PCM) model and the simple electrostatic Poisson-TrEsp approach to analyze the distance and orientation dependence of the dielectric screening between chlorophylls in photosystem I trimers. On the basis of these calculations we find that the vacuum couplings $V_{mn}^{\left(0\right)}$ and the couplings in the dielectric medium $V_{mn}=f_{mn}{V}_{mn}^{\left(0\right)}$ are related by the empirical screening factor $f_{mn}=0.60+39.6\theta \left(\right|{\kappa }_{mn}|-1.17)exp(-0.56R_{mn}/\AA )$, where ${\kappa }_{mn}$ is the usual orientational factor of the dipole-dipole coupling between the pigments, $R_{mn}$ is the center-to-center distance, and the Heaviside-function $\theta \left(\right|{\kappa }_{mn}|-1.17)$ ensures that the exponential distance dependence only contributes for in-line type dipole geometries. We are confident that the present expression can be applied also to other pigment-protein complexes with chlorophyll or related pigments of similar shape. The variance between the Poisson-TrEsp and the approximate coupling values is found to decrease by a factor of 8 and 3–4 using the present expression, instead of an exponential distance dependent or constant screening factor, respectively, assumed previously in the literature. Full article

Spinel-type InGaMgO₄ with a = 8.56615(3) Å was prepared by treating layered YbFe₂O₄-type InGaMgO₄ at 6 GPa and 1473 K. DFT calculation and Rietveld analysis of synchrotron X-ray powder diffraction data revealed the inverse spinel structure with In³⁺:Ga³⁺/Mg²⁺ = 0.726:0.274 in the tetrahedral site and 0.137:0.863 in the octahedral site. InGaMgO₄ spinel is an insulator with an experimental band gap of 2.80 eV, and the attempt at hole doping by post-annealing in a reducing atmosphere to introduce an oxygen defect was unsuccessful. This is the first report of the bulk synthesis of AB₂O₄ compounds with both YbFe₂O₄ and spinel polymorphs. Full article

This paper presents the design and optimization of a small-size electromagnetic induction heating control system powered by a 3.7 V–900 mAh lithium battery and featuring an LC series resonant full-bridge inverter circuit, which can be used for small metal material heating applications, such as micro medical devices. The effects of the resonant capacitance, inductor wire diameter, heating tube material, and wall thickness were studied to maximize the heating rate of the workpiece and simultaneously reduce the temperature rise of the NMOS transistor. The optimal circuit configuration meeting the design requirements was finally identified by comparing the operational parameters and NMOS transistor loss under different circuit conditions. Validation experiments were conducted on designed electromagnetic induction smoking devices. The results indicate that under an output current of 4.6 A, the heating tube can reach the temperature target of 250 °C within 11 s, and all NMOS transistors stay below 50 °C in a 5 min heating process. Full article

Diabetic foot ulcers (DFUs) represent a significant and serious challenge associated with diabetes. It is estimated that approximately one third of individuals with diabetes will develop DFUs at some point in their lives. This common complication can lead to serious health issues if not properly managed. The early diagnosis and treatment of DFUs are crucial to prevent severe complications, including lower limb amputation. DFUs can be categorized into two states: ischemia and infection. Accurate classification is required to avoid misdiagnosis due to the similarities between these two states. Several convolutional neural network (CNN) models have been used and pre-trained through transfer learning. These models underwent evaluation with hyperparameter tuning for the binary classification of different states of DFUs, such as ischemia and infection. This study aimed to develop an effective classification system for DFUs using CNN models and machine learning classifiers utilizing various CNN models, such as EfficientNetB0, DenseNet121, ResNet101, VGG16, InceptionV3, MobileNetV2, and InceptionResNetV2, due to their excellent performance in diverse computer vision tasks. Additionally, the head model functions as the ultimate component for making decisions in the model, utilizing data collected from preceding layers to make precise predictions or classifications. The results of the CNN models with the suggested head model have been used in different machine learning classifiers to determine which ones are most effective for enhancing the performance of each CNN model. The most optimal outcome in categorizing ischemia is a 97% accuracy rate. This was accomplished by integrating the suggested head model with the EfficientNetB0 model and inputting the outcomes into the logistic regression classifier. The EfficientNetB0 model, with the proposed modifications and by feeding the outcomes to the AdaBoost classifier, attains an accuracy of 93% in classifying infections. Full article

In addition to technical issues related to the instruments used, differences between soil moisture (SM) measured using ground-based methods and microwave remote sensing (RS) can be related to the main features of the study areas, which are intricately connected to hydraulic–hydrological conditions and soil properties. When long-term analysis is performed, these discrepancies are mitigated by the contribution of SM seasonality and are only evident when high-frequency variations (i.e., signal anomalies) are investigated. This study sought to examine the responsiveness of SM to seasonal variations in terrestrial ecoregions located in areas covered by the in situ Romanian Soil Moisture Network (RSMN). To achieve this aim, several remote sensing-derived retrievals were considered: (i) NASA’s Soil Moisture Active and Passive (SMAP) L4 V5 model assimilated product data; (ii) the European Space Agency’s Soil Moisture and Ocean Salinity INRA–CESBIO (SMOS-IC) V2.0 data; (iii) time-series data extracted from the H115 and H116 SM products, which are derived from the analysis of Advanced Scatterometer (ASCAT) data acquired via MetOp satellites; (iv) Copernicus Global Land Service SSM 1 km data; and (v) the “combined” European Space Agency’s Climate Change Initiative for Soil Moisture (ESA CCI SM) product v06.1. An initial assessment of the performance of these products was conducted by checking the anomaly of long-term fluctuations, quantified using the Absolute Variation of Local Change of Environment (ALICE) index, within a time frame spanning 2015 to 2020. These correlations were then compared with those based on raw data and anomalies computed using a moving window of 35 days. Prominent correlations were observed with the SMAP L4 dataset and across all ecoregions, and the Balkan mixed forests (646) exhibited strong concordance regardless of the satellite source (with a correlation coefficient R_ALICE > 0.5). In contrast, neither the Central European mixed forests (No. 654) nor the Pontic steppe (No. 735) were adequately characterized by any satellite dataset (R_ALICE < 0.5). Subsequently, the phenological seasonality and dynamic behavior of SM were computed to investigate the effects of the wetting and drying processes. Notably, the Central European mixed forests (654) underwent an extended dry phase (with an extremely low p-value of 2.20 × 10⁻¹⁶) during both the growth and dormancy phases. This finding explains why the RSMN showcases divergent behavior and underscores why no satellite dataset can effectively capture the complexities of the ecoregions covered by this in situ SM network. Full article

In this work, physically crosslinked injectable hydrogels based on carrageenan, locust bean gum, and gelatin, and mechanically nano-reinforced with green graphene oxide (GO), were developed to address the challenge of finding materials with a good balance between injectability and mechanical properties. The effect of GO content on the rheological and mechanical properties, injectability, swelling behavior, and biocompatibility of the nanocomposite hydrogels was studied. The hydrogels’ morphology, assessed by FE-SEM, showed a homogeneous porous architecture separated by thin walls for all the GO loadings investigated. The rheology measurements evidence that G′ > G″ over the whole frequency range, indicating the dominant elastic nature of the hydrogels and the difference between G′ over G″ depends on the GO content. The GO incorporation into the biopolymer network enhanced the mechanical properties (ca. 20%) without appreciable change in the injectability of the nanocomposite hydrogels, demonstrating the success of the approach described in this work. In addition, the injectable hydrogels with GO loadings ≤0.05% w/v exhibit negligible toxicity for 3T3-L1 fibroblasts. However, it is noted that loadings over 0.25% w/v may affect the cell proliferation rate. Therefore, the nano-reinforced injectable hybrid hydrogels reported here, developed with a fully sustainable approach, have a promising future as potential materials for use in tissue repair. Full article

Two-dimensional (2D) ferromagnetic semiconductors (FM SCs) provide an ideal platform for the development of quantum information technology in nanoscale devices. However, many developed 2D FM materials present a very low Curie temperature (T_C), greatly limiting their application in spintronic devices. In this work, we predict two stable 2D transition metal chalcogenides, V₃Se₃X₂ (X = S, Te) monolayers, by using first-principles calculations. Our results show that the V₃Se₃Te₂ monolayer is a robust bipolar magnetic SC with a moderate bandgap of 0.53 eV, while V₃Se₃S₂ is a direct band-gap FM SC with a bandgap of 0.59 eV. Interestingly, the ferromagnetisms of both monolayers are robust due to the V–S/Se/Te–V superexchange interaction, and T_Cs are about 406 K and 301 K, respectively. Applying biaxial strains, the FM SC to antiferromagnetic (AFM) SC transition is revealed at 5% and 3% of biaxial tensile strain. In addition, their high mechanical, dynamical, and thermal stabilities are further verified by phonon dispersion calculations and ab initio molecular dynamics (AIMD) calculations. Their outstanding attributes render the V₃Se₃Y₂ (Y = S, Te) monolayers promising candidates as 2D FM SCs for a wide range of applications. Full article

A two-step hydrothermal method was used to first obtain a SrTiO₃/TiO₂ composite then to dope the composite with Bi, Ni and Bi/Ni. Morphology, crystalline structures, surface valances and optical features of SrTiO₃/TiO₂ and Bi-, Ni-, Bi/Ni-doped SrTiO₃/TiO₂ were assessed. XRD and XPS analysis showed that Bi and Ni were successfully doped and existed in Bi(3+) and Ni(2+) oxidation state. UV–vis analysis further revealed that the bandgap energies of TiO₂ and SrTiO₃/TiO₂ were calculated to be 3.14 eV and 3.04 eV. By comparison, Bi, Ni and Bi/Ni doping resulted in the narrowing of bandgaps to 2.82 eV, 2.96 eV and 2.69 eV, respectively. The removal ability of SrTiO₃/TiO₂ and doped SrTiO₃/TiO₂ were investigated with tetracycline as the representative pollutant. After 40 min of exposure to visible light, Bi/Ni co-doped SrTiO₃/TiO₂ photocatalyst was able to remove 90% of the tetracycline with a mineralization rate of about 70%. In addition, first-order removal rate constant was 0.0074 min⁻¹ for SrTiO₃/TiO₂ and increased to 0.0278 min⁻¹ after co-doping. The strengthened removal by co-doped photocatalyst was attributed mainly to the enhanced absorption of visible light as co-doping resulted in the decreases of bandgap energies. At the same time, the co-doped material was robust against changes in pH. Removal of tetracycline was stable as pH changed from 5 to 9. Tetracycline removal was inhibited to a certain degree by the presence of nitrate, phosphate and high concentration of humic acid. Moreover, the co-doped material exhibited strong structural stability and reusability. In addition, a photocatalysis mechanism with photogenerated holes and ·O₂⁻ radicals as main oxidative species was proposed based on entrapping experiments and EPR results. Full article

Transition metal oxides (TMOs) are important anode materials in sodium-ion batteries (SIBs) due to their high theoretical capacities, abundant resources, and cost-effectiveness. However, issues such as the low conductivity and large volume variation of TMO bulk materials during the cycling process result in poor electrochemical performance. Nanosizing and compositing with carbon materials are two effective strategies to overcome these issues. In this study, spherical MnFe₂O₄@xC nanocomposites composed of MnFe₂O₄ inner cores and tunable carbon shell thicknesses were successfully prepared and utilized as anode materials for SIBs. It was found that the property of the carbon shell plays a crucial role in tuning the electrochemical performance of MnFe₂O₄@xC nanocomposites and an appropriate carbon shell thickness (content) leads to the optimal battery performance. Thus, compared to MnFe₂O₄@1C and MnFe₂O₄@8C, MnFe₂O₄@4C nanocomposite exhibits optimal electrochemical performance by releasing a reversible specific capacity of around 308 mAh·g⁻¹ at 0.1 A·g⁻¹ with 93% capacity retention after 100 cycles, 250 mAh·g⁻¹ at 1.0 A g⁻¹ with 73% capacity retention after 300 cycles in a half cell, and around 111 mAh·g⁻¹ at 1.0 C when coupled with a Na₃V₂(PO₄)₃ (NVP) cathode in a full SIB cell. Full article

Bovine adenovirus (BAdV)-3 genome encodes a 26 kDa core protein designated as protein VII, which localizes to the nucleus/nucleolus. The requirement of a protein VII-complementing cell line for the replication of VII-deleted BAdV-3 suggests that protein VII is required for the production of infectious progeny virions. An analysis of the BAV.VIId⁺ virus (only phenotypically positive for protein VII) detected no noticeable differences in the expression and incorporation of viral proteins in the virions. Moreover, protein VII does not appear to be essential for the formation of mature BAV.VIId⁺. However, protein VII appeared to be required for the efficient assembly of mature BAV.VIId^- virions. An analysis of the BAV.VIId^- virus (genotypically and phenotypically negative for protein VII) in non-complementing cells detected the inefficient release of virions from endosomes, which affected the expression of viral proteins or DNA replication. Moreover, the absence of protein VII altered the proteolytic cleavage of protein VI of BAV.VIId^-. Our results suggest that BAdV-3 protein VII appears to be required for efficient production of mature virions. Moreover, the absence of protein VII produces non-infectious BAdV-3 by altering the release of BAdV-3 from endosomes/vesicles. Full article

Electrical devices are integral to daily life, but limited battery life remains a significant issue. A proposed solution is to convert dissipated energy from human motion into electricity using piezoelectric materials. This study investigates lead–zirconate–titanate (PZT) piezoelectric materials in bimorph configuration, conducts performance tests to understand their characteristics and determine the optimal load resistance, and develops an energy-harvesting prototype. Performance tests adjusted input parameters and varied load resistance and input magnitude to optimize power gained from the PZT bimorph. A suitable human movement for the application of the bimorph is a mouse-clicking motion by fingers. A prototype was created by integrating the bimorph into a computer mouse to capture energy from clicks. The results showed that the deformation rate of the PZTs, input magnitude, and resistance load were key factors in optimization. The bimorph configuration produced 0.34 mW of power and 5.5 V at an optimum load of 5072 Ω, requiring less effort to generate electricity. For the computer mouse energy harvester case, it yielded a total average power of approximately 38.4 μW per click with a click frequency of 4 Hz. This power could be used to support IoT devices such as human sensors (e.g., CO₂, temperature, and pulse sensors) and smart home sensors, enabling comprehensive health and environmental monitoring. In conclusion, input specifications, magnitude, and load resistance are essential for optimizing piezoelectric energy harvesters. Full article

Accurate prediction of the friction factor is fundamental for designing and calibrating fluid transport systems. While the Colebrook–White equation is the benchmark for precision due to its physical basis, its implicit nature hinders practical applications. Explicit correlations like Churchill’s equation are commonly used but often sacrifice accuracy. This study introduces two novel modifications to Churchill’s equation to enhance predictive capabilities. Developed through a rigorous analysis of 240 test cases and validated against a dataset of 21,000 experiments, the proposed Churchill B(Re) and Churchill B(V,ε) models demonstrate significantly improved accuracy compared to the original Churchill equation. The development of these functions was achieved through generalized reduced gradient (GRG) nonlinear optimization. This optimized equation offers a practical and precise alternative to the Colebrook–White equation. The mean relative errors (MRE) for the modified models, Churchill B(Re) and Churchill B(V,ε), are 0.025% and 0.807%, respectively, indicating a significant improvement over the original equation introduced by Churchill in 1973, which exhibits an MRE of 0.580%. Similarly, the mean absolute errors (MAE) are 0.0008% and 0.0154%, respectively, compared to 0.0291% for the original equation. Beyond practical applications, this research contributes to a deeper understanding of friction factor phenomena and establishes a framework for refining other empirical correlations in the field. Full article