Biomarker Investigation Using Multiple Brain Measures from MRI Through Explainable Artificial Intelligence in Alzheimer’s Disease Classification by Davide Coluzzi, Valentina Bordin, Massimo W. Rivolta, Igor Fortel, Liang Zhan, Alex Leow, Giuseppe Baselli

“…This work compares a novel DL model using structural connectivity (namely, BC-GCN-SE adapted from functional connectivity tasks) with an established model using structural magnetic resonance imaging (MRI) scans (namely, ResNet18). …”
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Dynamic Balance: A Thermodynamic Principle for the Emergence of the Golden Ratio in Open Non-Equilibrium Steady States by Alejandro Ruiz

“…Requiring any smooth, strictly convex Lyapunov functional to be invariant under both maps enforces a single non-equilibrium fixed point: the golden mean. …”
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Establishment of methods for identifying rapidly and precisely transgenic rice and soybean containing herbicide-resistant gene bar and EPSPS by MA Lin, ZHOU Lian, ZHOU Zheng-jian, TANG Gui-xiang, SHEN Zhi-cheng, SHOU Hui-xia

“…Genetic engineering is an important tool in plant functional genomics research and crop improvement applications. …”
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Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms by Anjan Kumar Pradhan, Prasad Gandham, Kanniah Rajasekaran, Niranjan Baisakh

“…The top-ranked genes predicted to be key players in multiple stress resistance in maize need to be functional validated to ascertain their roles and further utilization in developing stress-resistant maize varieties.…”
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Electrocardiographic, echocardiographic and lipid parameters in predicting obstructive coronary artery disease in patients with non-ST elevation acute coronary syndrome by M. M. Tsivanyuk, B. I. Geltser, K. I. Shakhgeldyan, E. D. Emtseva, G. S. Zavalin, O. I. Shekunova

“…Two groups were distinguished, the first of which consisted of 351 (67%) patients with oCAD (stenosis 50%), and the second — 174 (33%) without oCAD (<50%). Clinical and functional status of patients before CAG was assessed by 40 indicators. …”
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The Safety of Using Body-Transmit MRI in Patients with Implanted Deep Brain Stimulation Devices. by Joshua Kahan, Anastasia Papadaki, Mark White, Laura Mancini, Tarek Yousry, Ludvic Zrinzo, Patricia Limousin, Marwan Hariz, Tom Foltynie, John Thornton

“…Patients receiving chronic DBS provide a unique opportunity to explore the underlying mechanisms of DBS using functional MRI. It has been shown that the main safety concern with MRI in these patients is heating at the electrode tips - which can be minimised with strict adherence to a supervised acquisition protocol using a head-transmit/receive coil at 1.5T. …”
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Uncertainty Quantification of Herschel–Bulkley Fluids in Rectangular Ducts Due to Stochastic Parameters and Boundary Conditions by Osama Hussein Galal, Eman Alruwaili

“…This study presents an innovative approach to quantifying uncertainty in Herschel–Bulkley (H-B) fluid flow through rectangular ducts, analyzing four scenarios: uncertain apparent viscosity (Case I), uncertain pressure gradient (Case II), uncertain boundary conditions (Case III) and uncertain apparent viscosity and pressure gradient (Case IV). …”
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A theoretical model for ROP localisation by auxin in Arabidopsis root hair cells. by Robert J H Payne, Claire Suzanne Grierson

“…<h4>Background</h4>Local activation of Rho GTPases is important for many functions including cell polarity, morphology, movement, and growth. …”
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Variable Selection for Multivariate Failure Time Data via Regularized Sparse-Input Neural Network by Bin Luo, Susan Halabi

“…Both methods are optimized using a composite gradient descent algorithm combining standard gradient steps with proximal updates. …”
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The Expression of Innate Immunity Responsible Genes in Human Macrophages Encountering Mycobacterium Tuberculosis by Farhang Babamahmoodi, Hadiseh Saberi, Farzaneh Rabiae, Hossein Jalali, Mohammad Reza Mahdavi

“…This analysis seeks to provide a more comprehensive understanding of the mechanisms underlying innate immune function. Materials and methods: Peripheral blood mononuclear cells (PBMCs) were isolated from 40 cc of peripheral blood drawn from five healthy individuals with negative PPD test results, using Ficoll density gradient centrifugation. …”
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Testing a Hump-Shaped Pattern with Increasing Elevation for Ant Species Richness in Daliang Mountain, Sichuan, China by Shi-Jia You, Zheng-Hui Xu, Xin-Min Zhang

“…Understanding the patterns of ant species richness along elevational gradients is crucial for elucidating their ecological functions within ecosystems. …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. …”
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Identification and Analysis of the Plasma Membrane H⁺-ATPase Gene Family in Cotton and Its Roles in Response to Salt Stress by Cong Cheng, Fengyuan Zhang, Li Li, Zhiyong Ni

“…Plant plasma membrane (PM) H⁺-ATPase functions as a proton-motive force by exporting cellular protons to establish a transmembrane chemical gradient of H⁺ ions and an accompanying electrical gradient. …”
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Security monitoring via sound analysis and voice identification with artificial intelligence by Balabanova Ivelina, Sidorova Kristina, Georgiev Georgi

“…The neural architectures were trained with Scaled Gradient Descent (SCG) and Levenberg Marquardt (LM) algorithms, using different transfer functions in the output structural layers. …”
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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…Training LSTM models, however, is an NP-hard problem, with gradient-based methods facing limitations such as getting trapped in local minima, high computational costs, and the need for continuous objective functions. …”
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Integrated multi-omics and machine learning reveals immune-metabolic signatures in osteoarthritis: from bulk RNA-seq to single-cell resolution by Hui He, Xiumei Zhao, Bo Zhang, Shijian Zhao, Yinteng Wu

“…Subsequently, Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules associated with OA and immune-metabolism scores, followed by enrichment analysis to reveal the functional characteristics of these modules. To identify immune-metabolism related differentially expressed genes (DEGs), we utilized seven machine learning methods, including lasso regression, random forest, bagging, gradient boosting machines (GBM), Xgboost-xgbLinear, Xgboost-xgbtree, and decision trees, to construct predictive models and validate their reliability. …”
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Rice Leaf Disease Image Enhancement Based on Improved CycleGAN by YAN Congkuan, ZHU Dequan, MENG Fankai, YANG Yuqing, TANG Qixing, ZHANG Aifang, LIAO Juan

“…Furthermore, a perception similarity loss function, designed to align with the human visual system, was incorporated into the overall loss function. …”
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Grazing-induced abiotic and resource changes drive distinct responses of soil bacterial and fungal community in temperate meadow steppe: Implications for carbon dynamics by Cuixia Jiang, Xiaoping Xin, Kai Xue, Zhigang Zhao, Weixing Liu, Haonan Guo, Feng Liu, Hui Li, Zihao Li, Yufan Si, Ruirui Yan

“…Soil microbial communities play a crucial role in maintaining grassland ecosystem functions and are strongly influenced by livestock grazing. …”
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Machine learning-driven integration of time-series InSAR and multiple surface factors for landslide identification and susceptibility assessment by Qianyu Wang, Wen Zhang, Jinglin Li, Ziyang Li, Zhi Luo, Qiang Zhao, Jianbo Jian, Fang Shangguan, Yuanxing Yang, Yangyang Ma, Zhen Zhang, Shuangming Zhao, Linyi Li, Lingkui Meng

“…Based on the delineated landslide areas, we enhanced the information value model using the inverse tangent function, which was then integrated with Random Forest and Extreme Gradient Boosting methods for landslide susceptibility assessment. …”
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ROS‐Activated Nanohydrogel Scaffolds with Multi‐Factors Controlled Release for Targeted Dual‐Lineage Repair of Osteochondral Defects by Xiuhui Wang, Shunli Wu, Ruiyang Li, Huijian Yang, Yue Sun, Zijie Cao, Xiao Chen, Yan Hu, Hao Zhang, Zhen Geng, Long Bai, Zhongmin Shi, Ke Xu, Hongbo Tan, Jiacan Su

“…These findings suggest that ROS‐activated nanohydrogel scaffolds with such specific soft‐hard bilayer structure and sequential delivery of functional factors, provides a promising strategy in dual‐lineage regeneration of osteochondral defects.…”
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