A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

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Fermented Buffalo Milk with Conjugated Linoleic Acid-Producing Bacteria: Strain Selection and Functional Applications by Bruna Samara dos Santos Rekowsky, Lorena Brandão Rocha Martinez Fernandez, Katherine Gutierrez Alzate, Carini Aparecida Lelis, Marcelo Resende de Souza, Carolina Oliveira de Souza, Bruno Dutra da Silva, Carlos Adam Conte-Júnior, Carla Paulo Vieira, José Givanildo da Silva, Marion Pereira da Costa

“…Buffalo milk is a rich source of precursor fatty acids for bioactive compounds and provides an optimal environment for bacterial growth. …”
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Enhancing Shiga toxin detection using surface plasmon resonance a study of antibody immobilization strategies by Zahra Karbalaee, Ali Hossein Rezayan, Ramezan Ali Taheri, Seyed Ali Mirhosseini, Mohammad Barshan-Tashnizi

“…The approach demonstrates particular promise for rapid, label-free detection of bacterial toxins in resource-limited settings.…”
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The structural and functional brain alternations in tobacco use disorder: a systematic review and meta-analysis by Longyao Ma, Longyao Ma, Qiuying Tao, Qiuying Tao, Jinghan Dang, Jinghan Dang, Jieping Sun, Jieping Sun, Xiaoyu Niu, Xiaoyu Niu, Mengzhe Zhang, Mengzhe Zhang, Yimeng Kang, Yimeng Kang, Weijian Wang, Weijian Wang, Jingliang Cheng, Jingliang Cheng, Yong Zhang, Yong Zhang

“…BackgroundWhile numerous previous studies have indicated that nicotine intake results in gray matter and functional brain abnormalities in tobacco use disorder (TUD), the majority of results could not be replicated or even reversed. …”
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Functional kombucha production from fusions of black tea and Indian gooseberry (Phyllanthus emblica L.) by Haruthairat Kitwetcharoen, Yupaporn Phannarangsee, Preekamol Klanrit, Sudarat Thanonkeo, Patcharaporn Tippayawat, Poramaporn Klanrit, Poramate Klanrit, Mamoru Yamada, Pornthap Thanonkeo

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Fluorescent carbon quantum dots from Syzygium aromaticum as a selective sensor for Fe3+ and Cd2+ detection in aqueous solution by Said Ali Akbar, Muhammad Hasan, Muhammad Nazar, Ilham Zulfahmi, Edy Miswar, Muhammad Iqhrammullah, Zulkarnain Jalil

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Deep Defense Against Mal-Doc: Utilizing Transformer and SeqGAN for Detecting and Classifying Document Type Malware by Gati Lother Martin, Sang-Min Lee, Jong-Hyun Kim, Young-Seob Jeong, Ah Reum Kang, Jiyoung Woo

“…The proposed model will solve this gap by detecting and classifying document-type malware families using script codes, including tags, to write documents and script languages to execute malicious functions. …”
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A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…Then, structural pruning was applied to refine the model and enhance its capability in detecting small objects. Moreover, to conserve computational resources, a lightweight CED module was introduced to reduce parameters and conserve the computing resources of the UAV. …”
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Edge enhancement of potential field data using the enhanced gradient (EG) filter by Ahmad Alvandi, Korimilli N Durga Prasad, Hazel Deniz Toktay

“…The EG is tested on two dimensional (2D) and three dimensional (3D) synthetic magnetic models with sources buried at different depths and variable properties. …”
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Cholinergic Mechanisms of Target Oddball Stimuli Detection: The Late “P300-Like” Event-Related Potential in Rats by A. Ahnaou, R. Biermans, W. H. I. M. Drinkenburg

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Waterbody Detection and Reservoir Water Level Prediction Using Bayesian Mixture Models with Sentinel-1 GRD Data by DongHyeon Yoon, Ha-Eun Yu, Euiho Hwang, Ki-mook Kang, Gibeom Nam, Jin-Gyeom Kim

“…For future research, higher-resolution data or complementary algorithms may further enhance detection accuracy for smaller and more complex water features, contributing to more refined water resource management strategies.…”
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A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

“…While industrial ceiling fans play a vital role in maintaining efficient airflow and system stability within factory settings, surface defects on their blades that arise over time can disrupt their functionality and create safety hazards. Detecting these surface defects is crucial; however, accurate and rapid detection typically involves complex machine vision algorithms, such as You Only Look Once (YOLO) networks, that require considerable computing resources, which contradicts the industry’s preference for simpler algorithms that can be deployed using low-cost computing power. …”
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Complex-amplitude-modulated meta-device for optical image processing by Xinchen Jiang, Peicheng Lin, Yeang Zhang, Tao Tao, Yuan Du, Xuecou Tu, Ting Xu, Yan-qing Lu, Jun-long Kou

“…However, considering that electronic convolutional operation always contains million-level parameters and complex calculation process, it consumes a large number of computing resources and time. To overcome these limitations, we proposed a design of complex-amplitude-modulated meta-device which could perform various functions of image processing. …”
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LI-YOLOv8: Lightweight small target detection algorithm for remote sensing images that combines GSConv and PConv. by Pingping Yan, Xiangming Qi, Liang Jiang

“…In the domain of remote sensing image small target detection, challenges such as difficulties in extracting features of small targets, complex backgrounds that easily lead to confusion with targets, and high computational complexity with significant resource consumption are prevalent. …”
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Patient-derived esophageal adenocarcinoma organ chip: a physiologically relevant platform for functional precision oncology by Sanjima Pal, Elee Shimshoni, Salvador Flores Torres, Mingyang Kong, Kulsum Tai, Veena Sangwan, Nicholas Bertos, Swneke Donovan Bailey, Julie Bérubé, Donald E. Ingber, Lorenzo Ferri

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A novel rhodamine 6G-based chemosensor for Fe3+ detection in water samples and cellular imaging by Bao-Long Hou, Wenyu Li, Ruirui Feng, Xiumei Yang, Jianli Liu, Cuiling Wang

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Bearing-Only Multi-Target Localization Incorporating Waveguide Characteristics for Low Detection Rate Scenarios in Shallow Water by Xiaohan Mei, Bo Zhang, Duo Zhai, Zhaohui Peng

“…A <i>β</i>-S-dimensional assignment (<i>β</i>-SDA) method incorporating waveguide characteristics is proposed to address the BOMTL problem in shallow water with low detection rates. The estimated distance for the warping transformation is derived from the intersection points of the bearing lines, then the autocorrelation function of the broadband beamforming output is transformed using a warping operator to obtain the corresponding characteristic spectrum. …”
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Correlation between D-dimer and size of middle cerebral artery infarction and its relation to functional outcome by Ramy Taha Alloush, Mohamed Hamdy Ibrahim, Shahinaz Mohamed Helmy, Aya Ebrahim Marwan, Mona Ali Eissa, Adel T. Alloush, Mohamed Khaled Elewa

“…Furthermore, data from neuroimaging, clinical, laboratory, and demographic sources were examined. Additionally, the modified Rankin Scale (mRS) score was used to evaluate the predictive usefulness of plasma D-dimer on a patient's functional outcome after three months. …”
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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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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…To address these issues, this study proposes the Supervised Dynamic Kernel U-Net (SDKU-Net), a novel architecture designed to enhance shadow detection in complex remote sensing scenarios. SDKU-Net integrates dynamic kernel adjustment, a combined loss function incorporating Focal and Tversky Loss, and optimizer switching to effectively tackle class imbalance and improve segmentation quality. …”
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