Untargeted pixel-by-pixel metabolite ratio imaging as a novel tool for biomedical discovery in mass spectrometry imaging by Huiyong Cheng, Dawson Miller, Nneka Southwell, Paola Porcari, Joshua L Fischer, Isobel Taylor, J Michael Salbaum, Claudia Kappen, Fenghua Hu, Cha Yang, Kayvan R Keshari, Steven S Gross, Marilena D'Aurelio, Qiuying Chen

“…Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. …”
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Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…Although performance of our model was not sufficient to be clinically implemented in our laboratory, our study provides a framework for AI-based AFB detection and a publicly available data set to support future advancements in automated detection of AFB.IMPORTANCEWe present the development of an artificial intelligence model to detect acid-fast bacilli (AFB) directly from stained clinical smears. While the model’s current performance requires further improvement to be clinically useful in our lab, we detail our approach and share our expertly annotated data set to support future advancements in this area. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…For FL, the Federated Adaptive (FedAdp) algorithm reduces communication rounds by 62% compared to Federated Averaging (FedAvg), maintaining near-centralized accuracy while preserving data locality. …”
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FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…However, the existing RT-DETR algorithm is limited by single-path feature extraction, a simplified fusion mechanism, and high-frequency information loss, which makes it difficult to balance detection accuracy and computational efficiency. …”
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Hydropower system in the Yarlung-Tsangpo Grand Canyon can mitigate flood disasters caused by climate change by Fengbo Zhang, Qin Yang, Jianhua Wang, Huan Liu, Qinghui Zeng, Long Yan, Baolong Zhao, Jiaxuan Tang, Kang Zhao, Yining Zang, Wei Liu, Peng Hu

“…Hydropower development stabilizes runoff regimes, enhances flood control capacity under climate scenarios (e.g., 29.2% peak reduction under Shared Socioeconomic Pathway 126), and mitigates downstream flood risks while supporting dry-season irrigation and navigation. …”
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Elevating E-Service Standards in Bangladesh: Merging FAHP and TOPSIS for Strategic Online Business Solutions by Farzana Tasnim, Tanjim Mahmud, Shefayatuj Johara Chowdhury, Tasnia Fahrin Choity, Aisha Ahmed, Mohammad Saeed Hasan Chowdhury, Mohammad Shahadat Hossain, Karl Andersson

“…To ensure a data-driven analysis, the Random Forest algorithm is utilized for feature importance extraction, followed by pairwise comparisons through fuzzy triangular matrices. …”
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Pork-YOLO: Automated collection of pork quality traits by Jiacheng Wei, Xi Tang, Jinxiu Liu, Ting Luo, Yan Wu, Junhui Duan, Shijun Xiao, Zhiyan Zhang

“…This study proposes an automated system utilizing high-resolution cameras to rapidly and efficiently measure eye muscle area and marbling scores on a large scale. A novel algorithm called ''Pork-YOLO'' was developed. First, a lightweight segmentation head network, Pork-Seg, was introduced, which utilizes shared convolution and group normalization to minimize parameters and enhance generalization, with prototype learning incorporated to reduce complexity. …”
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Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds by Pengwei Ren, Yongdong Peng, Liu Yang, Muhammad Zahoor Khan, Yadi Jing, Chao Qi, Zhansheng Liu, Shuer Zhang, Nenzhu Zheng, Meixia Zhang, Xiang Liu, Zhiming Zhu, Mingxia Zhu

“…Additionally, the WS and MT breeds were found to be closely related, possibly sharing a common ancestral group, while both breeds were genetically distinct from the WD breed. …”
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Exploring the host response in infected lung organoids using NanoString technology: A statistical analysis of gene expression data. by Mostafa Rezapour, Stephen J Walker, David A Ornelles, Muhammad Khalid Khan Niazi, Patrick M McNutt, Anthony Atala, Metin Nafi Gurcan

“…Additionally, the identification of shared and unique genes unveiled host-specific responses to specific pathogens. …”
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Enhancing Cross-Domain Remote Sensing Scene Classification by Multi-Source Subdomain Distribution Alignment Network by Yong Wang, Zhehao Shu, Yinzhi Feng, Rui Liu, Qiusheng Cao, Danping Li, Lei Wang

“…First, it includes a pre-trained convolutional neural network (CNN) as a common feature extractor to fully exploit the shared invariant features across one target and multiple source domains. …”
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Identifying key genes involved in HBV-related hepatocellular carcinoma: diagnose, prognosis, interaction and immune analysis by Yan Li, Sa-Sa Liu, Hua-Rong Jing, Hong-Wei Qian, Rui-Cheng Li

“…Immune infiltration analysis were performed by CIBERSORT algorithm. Drug–Gene Interaction Database (DGIdb) was used to screen the potential drug that affect hub genes. …”
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MSS-YOLO: Multi-Scale Edge-Enhanced Lightweight Network for Personnel Detection and Location in Coal Mines by Wenjuan Yang, Yanqun Wang, Xuhui Zhang, Le Zhu, Tenghui Wang, Yunkai Chi, Jie Jiang

“…Finally, the lightweight Shared Convolutional Detection Head (SCDH) ensures real-time detection under limited computational resources. …”
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Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer by Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu

“…This study integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to construct a prognostic model based on genes shared between ferroptosis and fatty acid metabolism (FAM). …”
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Automated Detection of High Frequency Oscillations in Intracranial EEG Using the Combination of Short-Time Energy and Convolutional Neural Networks by Dakun Lai, Xinyue Zhang, Kefei Ma, Zichu Chen, Wenjing Chen, Heng Zhang, Han Yuan, Lei Ding

“…In conclusion, this automated detection of the HFOs combing the STE and the CNN could allow analyzing large amounts of data in a short time while assuring a relatively higher accuracy and, thus, would potentially serve to provide a clinically useful tool.…”
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Fatigue symptoms in relation to neuroticism, anxiety-depression, and musculoskeletal pain. A longitudinal twin study. by Olav Vassend, Espen Røysamb, Christopher Sivert Nielsen, Nikolai Olavi Czajkowski

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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…This study aims to make sentence corpus containing SARA elements obtained from twitter, then label sentences with labels containing elements of SARA and not, and conduct group sentiments. The algorithm used for the labeling process is k-means, while Support Vector Machine (SVM) is used for the classification process. …”
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Efficient scheduling of multiple software projects for work continuity and identical completion time by Abdulrahman Aldhubaiban, Ali AlMatouq

“…This study describes a model that enables the use of efficient continuous variable nonlinear solvers for finding the optimal schedule for possibly a large number of multiple software projects that make use of shared resources. The study validates the proposed solution using a random generator of multiple software project instances while interfacing to online optimization solvers to find a solution. …”
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RMVAD-YOLO: A Robust Multi-View Aircraft Detection Model for Imbalanced and Similar Classes by Keda Li, Xiangyue Zheng, Jingxin Bi, Gang Zhang, Yi Cui, Tao Lei

“…Second, we propose the Shared Convolutional Dynamic Alignment Detection Head (SCDADH), which enhances task interaction and collaboration by sharing convolutions between the classification and localization branches while simultaneously reducing the number of parameters, enhancing the model’s ability to deal with multi-scale targets. …”
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Population Structure of the Invasive Asian Tiger Mosquito, Aedes albopictus, in Europe by Margaret K. Corley, Luciano Veiga Cosme, Peter A. Armbruster, Nigel Beebe, Anna Bega, Sebastien Boyer, Beniamino Caputo, Chun‐Hong Chen, Jacob E. Crawford, Alessandra dellaTorre, Roger Eritja, Michael C. Fontaine, Richard J. Gill, Trang Huynh, Perparim Kadriaj, Kevin Maringer, Ademir Jesus Martins, Andrew Maynard, Shomen Mukherjee, Leonard E. Munstermann, Verena Pichler, Maria Sharakhova, Sinnathamby Noble Surendran, Sandra Urbanelli, Enkelejda Velo, Isra Wahid, Muhammet Mustafa Akiner, Georgios Balatsos, Gilles Besnard, Maria Louise Borg, Daniel Bravo‐Barriga, Rubén Bueno Marí, Francisco Collantes, Cintia Horvath, Mihaela Kavran, Raquel Medialdea‐Carrera, Tanya Melillo, Antonios Michaelakis, Ognyan Mikov, Arianna Puggioli, Elton Rogozi, Francis Schaffner, Kayleigh Hackett, Thomas Johnson, Tina Wu, João Pinto, Vera Valadas, Adalgisa Caccone

“…Interestingly, some populations in Eastern Europe did not share genetic ancestry with any populations from the native range or Americas, indicating that these populations originated from areas not sampled in this study. …”
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