Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

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Saponins from <i>Solanum nigrum</i> L. Fruit: Extraction Optimization, Structural Characterization, and Dual-Functional Efficacy by Shuyuan Chen, Weiyun Guo, Tonghe Zhang, Jianfang Chen, Li Huang, Jihong Huang, Ruqiang Huang

“…., a widely consumed Asian medicinal edible plant, is a promising source of bioactive saponins for functional food applications. …”
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Adaptive integrated weight unsupervised multi-source domain adaptation without source data by Zhirui Wang, Liu Yang, Yahong Han

“…Because target samples with low entropy measured from the pre-trained source model achieve high accuracy, the trust center samples are selected first using the entropy function. …”
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Physiological and biochemical aspects of using black lion fly larvae as a source of biologically active and nutrient substances by M. S. Talan, I. S. Dokuchaeva, M. A. Mukhamed'yarov

“…Introduction. Functional foods are products that, in addition to taste and nutritional value, have a physiological effect on the human body. ω-6 and ω-3 fatty acids, when consumed in the form of triglycerides from various food sources, undergo digestion in the small intestine, allowing absorption and transport into the blood and subsequent assimilation into the body, including the brain, retina, heart and other tissues. …”
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Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content by J. LIU, Y. WANG, X.M. LIN, Z.C. XUE, F.R. ZENG

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LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach by Mingxin Liu, Mingxin Liu, Yujie Wu, Ruixin Li, Cong Lin, Cong Lin

“…Underwater object detection plays a significant role in fisheries resource assessment and ecological environment protection. …”
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KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection by Saeed Ullah, Junsheng Wu, Mian Muhammad Kamal, Abdul Khader Jilani Saudagar

“…Abstract The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stringent resource constraints of IoT devices. …”
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Regional Frequency Analysis Using L-Moments for Determining Daily Rainfall Probability Distribution Function and Estimating the Annual Wastewater Discharges by Pau Estrany-Planas, Pablo Blanco-Gómez, Juan I. Ortiz-Vallespí, Javier Orihuela-Martínez, Víctor Vilarrasa

“…The Generalized Pareto gave the best probability distribution function for the selected region, and it was used to simulate daily rainfall and system discharges over annual periods using Monte Carlo techniques. …”
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An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation by Xianliang Chen, Zhicheng Xie, Jiashu Wu, Xiaofeng Wu

“…To solve this problem, a Fault Detection, Isolation, and Recovery (FDIR) was proposed, which integrates an adaptive unscented Kalman filter (AUKF), a radial basis function (RBF) neural network for fault detection, and a QUEST-based estimator. …”
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MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

“…This paper proposes two effective edge detection tools: one combining the balanced total horizontal gradient (BHG), and the hyperbolic tangent function, abbreviated as “MTBHG”; and the other combining the tilt angle of the total horizontal gradient (TAHG) and the hyperbolic tangent function, abbreviated as “MTAHG.” …”
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SDDGRNets: Level–Level Semantically Decomposed Dynamic Graph Reasoning Network for Remote Sensing Semantic Change Detection by Zhuli Xie, Gang Wan, Yunxia Yin, Guangde Sun, Dongdong Bu

“…Semantic change detection technology based on remote sensing data holds significant importance for urban and rural planning decisions and the monitoring of ground objects. …”
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Broad-line AGNs at 3.5 < z < 6: The Black Hole Mass Function and a Connection with Little Red Dots by Anthony J. Taylor, Steven L. Finkelstein, Dale D. Kocevski, Junehyoung Jeon, Volker Bromm, Ricardo O. Amorín, Pablo Arrabal Haro, Bren E. Backhaus, Micaela B. Bagley, Eduardo Banados, Rachana Bhatawdekar, Madisyn Brooks, Antonello Calabrò, Óscar A. Chávez Ortiz, Yingjie Cheng, Nikko J. Cleri, Justin W. Cole, Kelcey Davis, Mark Dickinson, Callum Donnan, James S. Dunlop, Richard S. Ellis, Vital Fernández, Adriano Fontana, Seiji Fujimoto, Mauro Giavalisco, Andrea Grazian, Jingsong Guo, Nimish P. Hathi, Benne W. Holwerda, Michaela Hirschmann, Kohei Inayoshi, Jeyhan S. Kartaltepe, Yana Khusanova, Anton M. Koekemoer, Vasily Kokorev, Rebecca L. Larson, Gene C. K. Leung, Ray A. Lucas, Derek J. McLeod, Lorenzo Napolitano, Masafusa Onoue, Fabio Pacucci, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Rachel S. Somerville, Jonathan R. Trump, Stephen M. Wilkins, L. Y. Aaron Yung, Haowen Zhang

“…We select these sources directly from JWST/NIRSpec G395M/F290LP spectra. …”
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Integrating individual tracking data and spatial surveys to improve estimation of animal spatial distribution by Valentin Lauret, Nicolas Courbin, Olivier Scher, Aurélien Besnard

“…Simulations showed that the integrated model correctly estimated habitat selection coefficients and benefited from both data sources with better accuracy and precision than RSF and Poisson GLM alone, especially when data are limited. …”
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Western spotted skunk spatial ecology in the temperate rainforests of the Pacific Northwest by Marie I. Tosa, Damon B. Lesmeister, Taal Levi

“…Using these home ranges, we fitted a resource selection function using environmental covariates that we assigned to various hypotheses such as resources, predator avoidance, thermal tolerance, and disturbance. …”
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Assessing variability and detecting the effective traits on yield of chickpea (Cicer arietinum L.) promising lines under drought stress condition by Sayyed Saeed Moosavi, Mohammad Reza Abdollahi, Fatemeh Abdi, Homayoun Kanouni

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Antioxidant Peptides from the Fruit Source of the Oil Crop <i>Litsea cubeba</i> Ameliorate FFA-Induced Oxidative Stress Injury: Based on Nrf2/Keap1 Pathway and Molecular Dynamics S... by Li Li, Ying Hu, Yu-Mei Wang, Xiao-Xue Wu, Si-Tong Lin, Hang Li, Ji Zhang, Guo-Rong Fan, Zong-De Wang, Bin Wang, Shang-Xing Chen

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National occupational safety and health systems: Exploring the underlying networks for future sustainable development by Gaia Vitrano, Guido J.L. Micheli

“…As a result, a range of fundamental functions and recurring bodies, covering – to different extents – the previously identified functions, constitute the framework, which are the most transversal functions for the selected countries. …”
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ContDataQC: An R package and Shiny app for quality control of continuous water quality sensor data by Michael J. Pennino, Jen Stamp, Erik W. Leppo, David A. Gibbs, Britta G. Bierwagen

“…ContDataQC helps users speed up and standardize the QC process, minimize undetected data errors, and make full use of their sensor data. It has three main functions: generate QC reports to detect anomalies and erroneous data values, merge QC'd data files from different time periods, and generate time series plots and basic summary statistics. …”
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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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Novel Genomic Regions and Gene Models Controlling Copper and Cadmium Stress Tolerance in Wheat Seedlings by Amira M. I. Mourad, Sara Baghdady, Fatma Al-Zahraa M. Abdel-Aleem, Randa M. Jazeri, Andreas Börner

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