AgriSenAI: Automating UAV thermal and multispectral image processing for precision agriculture by Boaz B. Tulu, Fitsum Teshome, Yiannis Ampatzidis, Niguss Solomon Hailegnaw, Haimanote K Bayabil

“…However, processing and extracting useful information from UAV images is often complex, time-consuming, and requires specialized software, which limits its broader adoption for practical field implementations. …”
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AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts by Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong

“…The optimized agents adapt effectively to dynamic environments, ensuring timely detection of critical health deviations. Comparative evaluations reveal superior performance in metrics related to decision-making accuracy and response efficiency, highlighting the robustness of the framework. …”
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SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions by De-yu Tang, Yi-jun Mao, Jie Zhao, Jin Yang, Shi-yin Li, Fu-xiang Ren, Junxi Zheng

“…Abstract Background Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. …”
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Using Digital Technology to Conduct COVID-19 Surveillance: A Systematic Review by Fitrisia Rahma, Fatmah Fatmah, Rachmadhi Purwana

“…Conclusion: Digital technology has demonstrated its pivotal role in strengthening public health surveillance during the pandemic, improving efficiency, accuracy, and capacity in pandemic response. …”
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Transfer-Learning Approach for Enhanced Brain Tumor Classification in MRI Imaging by Amarnath Amarnath, Ali Al Bataineh, Jeremy A. Hansen

“…Results: Our findings indicate that these models can improve the accuracy of MRI analysis for brain tumor classification, with the Xception model achieving the highest performance with a test F1 score of 0.9817, followed by EfficientNetV2-S with a test F1 score of 0.9629. Conclusions: Implementing pre-trained deep learning models can enhance MRI accuracy for detecting brain tumors.…”
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Investigation of Opto‐magnetic Memory Effects in Antiferromagnetic CuMnAs Using Ultrafast Heat Dynamics and Quench Switching by Jan Zubáč, Miloslav Surýnek, Kamil Olejník, Andrej Farkaš, Filip Krizek, Lukáš Nádvorník, Peter Kubaščík, Zdeněk Kašpar, František Trojánek, Richard P. Campion, Vít Novák, Petr Němec, Tomáš Jungwirth

“…Abstract Solving complex tasks in a modern information‐driven society requires novel materials and concepts for energy‐efficient hardware. …”
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Genomic and Functional Analysis of a Novel Yeast <i>Cyberlindnera fabianii</i> TBRC 4498 for High-Yield Xylitol Production by Pawarin Bonthong, Benjarat Bunterngsook, Wuttichai Mhuantong, Katesuda Aiewviriyasakul, Wipawee Sritusnee, Verawat Champreda, Hataikarn Lekakarn

“…The development of yeast cell factories for efficient xylose utilization and xylitol production is crucial for advancing sustainable biotechnological processes. …”
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IoT Based Meat Freshness Classification Using Deep Learning by Zarif Wasif Bhuiyan, Syed Ali Redwanul Haider, Adiba Haque, Mohammad Rejwan Uddin, Mahady Hasan

“…The custom CNN showed a clear advantage in handling the complex image data, particularly in distinguishing between beef and mutton species as well as their freshness levels. …”
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Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes. by Josine L Min, George Nicholson, Ingileif Halgrimsdottir, Kristian Almstrup, Andreas Petri, Amy Barrett, Mary Travers, Nigel W Rayner, Reedik Mägi, Fredrik H Pettersson, John Broxholme, Matt J Neville, Quin F Wills, Jane Cheeseman, GIANT Consortium, MolPAGE Consortium, Maxine Allen, Chris C Holmes, Tim D Spector, Jan Fleckner, Mark I McCarthy, Fredrik Karpe, Cecilia M Lindgren, Krina T Zondervan

“…Since many genes and their interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations.…”
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Anaerobic digestion of microalgae: microbial response and recovery after organic loading disturbances by Juline M. Walter, Silvia Greses, Live H. Hagen, Valerie C. Schiml, Phillip B. Pope, Cristina González-Fernández, Magnus Ø Arntzen

“…ABSTRACT Industrial anaerobic digestion (AD) represents a relevant energy source beyond today’s fossil fuels, wherein organic matter is recycled to methane gas via an intricate and complex microbial food web. Despite its potential, anaerobic reactors often undergo process instability over time, which is frequently caused by substrate composition perturbations, making the system unreliable for stable energy production. …”
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Establishing a universal IVRP method for quadrivalent HPV vaccines to replace in vivo potency tests by Jinpan Hu, Zijing Jia, Meng Wang, Lingling Nie, Wangjun Fu, Qingfeng Zhang, Haiyang Qin, Jianhui Nie, Xiaoyu Xu, Lingjie Xu, Fengze Wang, Yingping Chen, Bo Xing, Tao Li, Danfeng Li, Shaowei Li, Ningshao Xia, Xiangxi Wang, Weijin Huang

“…The IVRP results were correlated with potency data from mouse models, offering an efficient alternative to in vivo potency experiments.…”
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Rapid Determination of Trace Impurity Elements in Pure Molybdenum by Inductively Coupled Plasma-Mass Spectrometry Based on the Online-Standard-Addition Method by Yichuan TANG, Yuanyuan FENG, Tao ZHOU, Yanjie CUI, Jianying ZHANG

“…Matrix matching method, standard addition method and isotope dilution mass spectrometry (IDMS) based on isotope abundance ratio measurement can effectively compensate for the complex matrix effect, and accurate analytical results can be obtained, but the analysis processes are complicated, the efficiency is low, and the cost is high, making it difficult to meet the measurement requirements of high throughput.　　…”
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Reconstructed hyperspectral imaging for in-situ nutrient prediction in pine needles by Yuanhang Li, Yuanhang Li, Jun Du, Jun Du, Chuangjie Zeng, Chuangjie Zeng, Yongshan Wu, Yongshan Wu, Junxian Chen, Junxian Chen, Teng Long, Teng Long, Yongbing Long, Yongbing Long, Yubin Lan, Yubin Lan, Xiaoliang Che, Tianyi Liu, Jing Zhao, Jing Zhao

“…It facilitates efficient in situ nutrient detection and offers a promising tool for sustainable forestry development.…”
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Beyond N-Grams: Enhancing String Kernels With Transformer-Guided Semantic Insights by Nazar Zaki, Reem Alderei, Mahra Alketbi, Alia Alkaabi, Fatima Alneyadi, Nadeen Zaki

“…This work sets a new standard in AI-text detection methodologies, enhancing reliability, efficiency, and scalability for real-world applications.…”
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A Composite Vision-Based Method for Post-Assembly Dimensional Inspection of Engine Oil Seals by Yu Li, Jing Zhao, Xingyu Gao, Weiming Li, Rongtong Jin, Guohao Tang, Yang Huang, Shuibiao Chen

“…Compared with existing methods, the proposed approach not only enhances detection accuracy and efficiency but also provides a practical and reliable solution for real-time monitoring of engine oil seal assembly dimensions, highlighting its substantial industrial application potential.…”
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A multi-robot collaborative manipulation framework for dynamic and obstacle-dense environments: integration of deep learning for real-time task execution by Afnan Ahmed Adil, Saber Sakhrieh, Jinane Mounsef, Noel Maalouf

“…This multirobot architecture is adaptable, allowing configuration of team size for collaborative tasks based on load requirements and environmental complexity. By integrating computer vision and deep learning for visual processing, and YOLOv2 for object detection, the system efficiently identifies, picks, and transports objects to designated locations, demonstrating the scalability of multi-robot framework for future applications in logistics automation, collaborative manufacturing, and dynamic human-robot interaction scenarios.…”
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Attention-based integrated deep neural network architecture for predicting the effectiveness of data center power usage by Yang-Cheng Shih, Sathesh Tamilarasan, Chin-Sheng Chen, Omid Ali Zargar, Yean-Der Kuan

“…The integration of convolutional layers processes hourly data inputs efficiently, reducing complexity and improving pattern detection. …”
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Deep sequencing of yeast and mouse tRNAs and tRNA fragments using OTTR by Hans Tobias Gustafsson, Lucas Ferguson, Carolina Galan, Tianxiong Yu, Heather Upton, Ebru Kaymak, Zhiping Weng, Kathleen Collins, Oliver J Rando

“…Applying this protocol to mature mouse spermatozoa, our data dramatically alter our understanding of the small RNA cargo of mature mammalian sperm, revealing a far more complex population of tRNA fragments – including both 5′ and 3′ tRNA halves derived from the majority of tRNAs – than previously appreciated. …”
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Genomic signal selection analysis reveals genes related to the lambing trait of Hotan sheep by XinKun Wang, Wei Li, QiaoYan Huang, HuiPing Sun, LeXiao Zhu, RuoHuai Gu, Feng Xing

“…Objective Lambing in ewes is a complex and crucial aspect of sheep production that directly influences economic viability and production efficiency. …”
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Evaluation of long-read sequencing for Ostreid herpesvirus type 1 genome characterization from Magallana gigas infected tissues by Aurélie Dotto-Maurel, Camille Pelletier, Lionel Degremont, Serge Heurtebise, Isabelle Arzul, Benjamin Morga, Germain Chevignon

“…ABSTRACT Since the 1990s, the Pacific oyster Magallana gigas has faced significant mortality, which has been associated with the detection of the Ostreid Herpesvirus type 1 (OsHV-1). …”
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