Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms by Roberta Puglisi, Caterina Testa, Sara Scuderi, Valentina Greco, Giuseppe Trusso Sfrazzetto, Manuel Petroselli, Andrea Pappalardo

“…Fluorescence titrations and density functional theory (DFT) calculations reveal and explain the high binding affinity of this receptor toward selected amines, demonstrating its potential as an effective tool for amine detection.…”
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Uncovering functional deterioration in the rhizosphere microbiome associated with post-green revolution wheat cultivars by Monique E. Smith, Vanessa N. Kavamura, David Hughes, Rodrigo Mendes, George Lund, Ian Clark, Tim H. Mauchline

“…Of the 113 functional genes that were differentially abundant between heritage and modern cultivars, 95% were depleted in modern cultivars and 65% of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). …”
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Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

“…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8. by Qian Shen, Yi Li, YuXiang Zhang, Lei Zhang, ShiHao Liu, Jinhua Wu

“…The model achieves precision on par with existing mainstream algorithms, while being simpler, significantly reducing computational requirements, and being more suitable for small target detection tasks. The source code and test results of the models used in this study are available at https://github.com/lyzzzzyy/CSW-YOLO.git.…”
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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Accurate detection of vulnerable road users (VRUs) is critical for enhancing traffic safety and advancing autonomous driving systems. …”
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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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Effect of Cs atoms adsorption on the work function of the LaB6 (100) surface by Huaqing Zheng, Xin Zhang, Jun Hu, Yuhong Xu, Guangjiu Lei, Sanqiu Liu, Heng Li, Zilin Cui, Yiqin Zhu, Xiaolong Li, Xiaoqiao Liu, Shaofei Geng, Xiaochang Chen, Haifeng Liu, Xianqu Wang, Hai Liu, Jun Cheng, Changjian Tang

“…These results provide some reference for the selection of fusion plasma gird materials and the production of hydrogen negative ion sources for neutral beam injection.…”
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Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

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Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

“…Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. …”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Samar Hussni Anbarkhan, Laith Abualigah

“…The objective function of the optimization problem is defined as the sum of squared errors of the actual and predicted voltage data. …”
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Investigating the utilization of biomaterials and bioengineering methods in developing functional cardiac tissue for heart repair by Omar Elsaka

“…The primary purpose of the present research is to examine the use of biomaterials and bioengineering methods to create functioning cardiac tissue. Techniques for tissue maturation, scaffold design, cell sources, and biomaterial selection are important subjects. …”
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Whole-Genome Resequencing Analysis of Copy Number Variations Associated with Athletic Performance in Grassland-Thoroughbred by Wenqi Ding, Wendian Gong, Tugeqin Bou, Lin Shi, Yanan Lin, Xiaoyuan Shi, Zheng Li, Huize Wu, Manglai Dugarjaviin, Dongyi Bai

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Statistically Optimized Near-Field Acoustic Holography Using Prolate Spheroidal Wave Functions by Xuxin Zhang, Jingjun Lou, Jinfang Lu, Ronghua Li, Shijian Zhu

“…Near-field acoustic holography (NAH) is an effective tool for realizing accurate sound field reconstruction in three-dimensional space on the prerequisite that appropriate elementary wave functions are selected or constructed to match the characteristics of the sound sources. …”
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A METHOD FOR INVESTIGATING MACHINE LEARNING ATTACKS ON ARBITER-TYPE PHYSICALLY UNCLONABLE FUNCTIONS by Yuri A. Korotaev

“…This approach allows for a preliminary evaluation of the effectiveness of different algorithms for attacking APUFs without access to challenge-response datasets from real instances of physically unclonable functions. Attacks were conducted on models of basic and modified variants of APUFs from the open-source library "pypuf", using classical logistic regression and artificial neural networks (ANNs). …”
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A fuzzy method for improving the functionality of search engines based on user's web interactions by Farzaneh Kabirbeyk, Ali Harounabadi, Mostafa Sabzekar

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Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data. by Qihai Liu, Kevin H Lee, Hyun Bin Kang

“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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Asynchronous bearing only tracking management approach in distributed multi-function integrated sensors by ZHANG Wei, YANG Qiu, LI Hao

“…The distributed multi-function system requires only one integrated sensor to switch to electronic support measure (ESM) mode within each tracking cycle to update the angle measurement information of target radiation source, while the other integrated sensors still work in the original planned mode and task. …”
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Forecasting springtime rainfall in southeastern Australia using empirical orthogonal functions and neural networks by S. Marčelja

“…In addition to standard ocean climate indicators such as El Niño or the Indian Ocean Dipole, other typical patterns of variation are captured in terms of the temperatures of selected ocean areas. When characteristic patterns of correlation are discovered, they are included in the predictor selection in the form of expansion in terms of the empirical orthogonal functions (EOFs). …”
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