Preventive role of CD163-positive macrophages in postoperative peritoneal adhesions by Lianbo Li, Hiroki Hirao, Masaki Honda, Ahmad Adawy, Cheng Pan, Yukio Fujiwara, Daiki Yoshii, Weijie Xue, Masahiro Tomita, Jie Su, Taizo Hibi, Yoshihiro Komohara

“…While macrophages contribute to this process, the specific subtypes and underlying mechanisms remain unclear. …”
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In Vivo Detection of Staphylococcus aureus Infections Using Radiolabeled Antibodies Specific for Bacterial Toxins by María Isabel González, Mario González-Arjona, Lorena Cussó, Miguel Ángel Morcillo, John Jairo Aguilera-Correa, Jaime Esteban, Martha Kestler, Daniel Calle, Carlos Cerón, Marta Cortes-Canteli, Patricia Muñoz, Emilio Bouza, Manuel Desco, Beatriz Salinas

“…The physicochemical characterization of the immunotracer was performed by high-performance liquid chromatography (HPLC), radio-thin layer chromatography (radio-TLC), and electrophoretic analysis. …”
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Application of improved graph convolutional network for cortical surface parcellation by Jia Tan, Xiaomei Ren, Yong Chen, Xianju Yuan, Feiba Chang, Rui Yang, Chengqun Ma, Xiaoyu Chen, Miao Tian, Wei Chen, Zihong Wang

“…ADGCN consists of a deep graph convolutional layer with a symmetrical U-shaped structure, which enables it to effectively transmit detailed information of the original brain map and learn the complex graph structure, help the network enhance feature extraction capability. …”
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Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite by Imane Khalil, Amina Daghouri, Mohammed Alae Chanoui, Zouhair Guennoun, Adnane Addaim

“…This work, conducted within the project of the UM5-EOSat nanosatellite mission, utilized captured images from the Gecko imager for model evaluation. The customized SegNet architecture, tailored with minimal kernels and layers, achieved an accuracy of 93.50%, effectively balancing performance and computational efficiency. …”
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Hybrid Deep Neural Network Optimization with Particle Swarm and Grey Wolf Algorithms for Sunburst Attack Detection by Mohammad Almseidin, Amjad Gawanmeh, Maen Alzubi, Jamil Al-Sawwa, Ashraf S. Mashaleh, Mouhammd Alkasassbeh

“…Deep Neural Networks (DNNs) have been widely used to solve complex problems in natural language processing, image classification, and autonomous systems. …”
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Developing Legal Communication Skills in the South Pacific Context by Carolyn Penfold

“…Recognising that clinical education learning and teaching is multi-layered, the Flinders Legal Advice Clinic was established in 2011, drawing on best practice models from other Australian student legal clinics. …”
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Thermal Phase Curves in Hot Gas Giant Exoplanets Exhibit a Complex Dependence on Planetary Properties by Mark R. Swain, Kyle A. Pearson, Thaddeus D. Komacek, Geoffrey Bryden, Emeline Fromont, Gautam Vasisht, Gael Roudier, Robert T. Zellem

“…We suggest that differences between the 3.6 μ m and 4.5 μ m phase curve properties are due to 3.6 μ m observations probing regions of the atmosphere which could include a cloud layer. Taken together, the observed phase curve behavior suggests that different physical processes are responsible for establishing the thermal phase curve at different pressures, which are probed by different wavelengths, and that further 3D Global Circulation Model modeling is required to investigate the reason for this complex dependence on planetary properties.…”
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Thermal canopy segmentation in tomato plants: A novel approach with integration of YOLOv8-C and FastSAM by Hemamalini P, Chandraprakash MK, Laxman RH, Rathinakumari C, Senthil Kumaran G, Suneetha K

“…This study introduces an innovative approach combining compact YOLOv8-C detection technology with the Fast Segment Anything Model (FastSAM). The compact YOLOv8-C model differs from the original YOLOv8l (large) model by simplifying the Neck architecture and reducing the number of convolutional and upsampling layers. …”
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MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network by Zhanwei Hou, Yijun Li, Haixia Zhai, Junwei Luo, Yulian Ding, Yi Pan

“…Abstract Background Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process. The key to accurate DTA prediction lies in selecting appropriate computational models to effectively extract features from drug molecular structures and target protein structures. …”
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A data-driven hybrid framework for voltage transformer ratio error prediction: Addressing challenges in complex power systems by Jiuxi Cui, Zhenhua Li, Heping Lu, Feng Zhou, Haoyu Chen, Zhenxing Li

“…Finally, 15 benchmark prediction models are constructed to validate the effectiveness of the proposed prediction framework. …”
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Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems by D. T. Yakupov, O. N. Rozhko

“…A sufficiently high verification in the application of ANN for difficult-to-forecast indicators of the transport process confirms the practical significance of the application of this method in the modeling of the logistics network.…”
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Design and Numerical Simulation of a Device for Film–Soil Vibrating Conveying and Separation Based on DEM–MBD Coupling by Shilong Shen, Jiaxi Zhang, Hu Zhang, Yongxin Jiang, Xin Zhou, Yichao Wang, Xuanfeng Liu, Haichun Zhang

“…This research provides a theoretical foundation and equipment support for addressing residual film pollution in the cultivated layer of Xinjiang region.…”
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Seismic Random Noise Attenuation Using DARE U-Net by Tara P. Banjade, Cong Zhou, Hui Chen, Hongxing Li, Juzhi Deng, Feng Zhou, Rajan Adhikari

“…Dense connections enhance the receptive field and ensure that information from different scales is considered during the denoising process. Our model implements local residual connections between layers within the encoder, which allows earlier layers to directly connect with deep layers. …”
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Integrated Identification and Efficient Use of Biodiversity in Mountainous Regions by Mehdiyeva A. M., Mahmudova Z. A., Rustamova D. F., Mansurova D., Juraeva G.

“…Based on the data from drilled exploratory oil wells, the conditions for the formation of thermal water layers in various hydrogeological structures will be determined; hydrochemical research methods will be aimed at assessing the macro- and microcomponent composition and radiation background of thermal waters at various intervals of migration routes by determining various indicators at different depths of their formation (based on the petrochemical structure of the geological part); isotopic studies of the gas composition of thermal waters will help to identify their genesis and use them as a marker when determining the points of formation; computer modeling of the underground hydrosphere of a representative object was carried out using mathematical programs.…”
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Estimating atmospheric precipitable water vapor in northern Morocco: A ground-based GNSS approach by Reda Drissi El Bouzaidi, Hajar El Talibi, Said El Moussaoui, Taoufik Mourabit

“…To validate the results, PWV values obtained from each station were compared with meteorological data collected from nearby meteorological stations during the same period, and compared to ERA5 reanalysis numerical weather model. The validation process revealed favorable results, evidenced by a reasonable spatial distribution of PWV. …”
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Lactobacillus Supplementation Modulates Rumen Microbiota and Metabolism in Yaks Under Fattening Feeding Conditions: A Comprehensive Multi-Omics Analysis by Jianlei Jia, Pengjia Bao, Ning Li, Siyuan Kong, Min Chu, Qian Chen, Ping Yan

“…Correlation phenotypic data and multi-omics analyses (rumen microbial sequencing and rumen epithelial metabolomics) were conducted to investigate the regulatory effects of Lactobacillus supplementation on rumen microbiota and metabolic processes in a concentrate-based rearing yak model. …”
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A new hybrid approach for solving partial differential equations: Combining Physics-Informed Neural Networks with Cat-and-Mouse based Optimization by Nursyiva Irsalinda, Maharani A. Bakar, Fatimah Noor Harun, Sugiyarto Surono, Danang A. Pratama

“…Extensive experiments were conducted under varying scenarios, including different numbers of hidden layers (3, 5, 7) and neurons per layer (10, 30, 50). …”
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Sustainable Material Cutting Optimization Using Deep Q-Networks: A Reinforcement Learning Approach for Resource Efficiency by Chen Linxuan

“…The GNN model is embedded with Graph Convolutional Networks (GCN) layers, while the DRL model is structured with Deep Q-network (DQN). …”
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Validation and uncertainty quantification of three state-of-the-art ammonia surface exchange schemes using NH₃ flux measurements in a dune ecosystem by T. Jongenelen, M. van Zanten, M. van Zanten, E. Dammers, E. Dammers, R. Wichink Kruit, A. Hensen, L. Geers, J. W. Erisman

“…Yet none of these schemes captured the emission events at Solleveld, pointing to considerable uncertainty in the compensation point parameterization and possibly in the modelling of <span class="inline-formula">NH₃</span> desorption processes from wet surface layers. …”
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Understanding the Magnetic Field and Plasma-β along Umbral Fan Loops Traced Using 3 Minute Slow Waves by Ananya Rawat, Girjesh Gupta, Tom Van Doorsselaere, S. Krishna Prasad, Robertus Erdélyi

“…Plasma- β is an important fundamental physical quantity in solar plasma physics, which determines the dominating process in the solar atmosphere, i.e., magnetic or thermodynamic processes. …”
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