Biomarkers for cognitive impairment in alpha-synucleinopathies: an overview of systematic reviews and meta-analyses by Elisa Mantovani, Alice Martini, Alessandro Dinoto, Chiara Zucchella, Sergio Ferrari, Sara Mariotto, Michele Tinazzi, Stefano Tamburin

“…Future studies should include large consortia, biobanks, multi-omics approach, artificial intelligence, and machine learning to better reflect the complexity of CI in α-synucleinopathies.…”
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Prolonged Systemic Inflammation Alters Muscarinic Long-Term Potentiation (mLTP) in the Hippocampus by Efrat Shavit-Stein, Amir Dori, Marina Ben Shimon, Shany Guly Gofrit, Nicola Maggio

“…The cholinergic system plays a fundamental role in learning and memory. Pharmacological activation of the muscarinic receptor M1R potentiates NMDA receptor activity and induces short-term potentiation at the synapses called muscarinic LTP, mLTP. …”
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Review of Acoustic Emission Detection Technology for Valve Internal Leakage: Mechanisms, Methods, Challenges, and Application Prospects by Dongjie Zheng, Xing Wang, Lingling Yang, Yunqi Li, Hui Xia, Haochuan Zhang, Xiaomei Xiang

“…Acoustic emission (AE) technology, functioning as an efficient non-destructive testing approach, is capable of capturing the transient stress waves induced by leakage, thereby furnishing an effective means for the real-time monitoring and quantitative assessment of internal leakage within the valve body. …”
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Improving working memory performance in healthy older adults: Investigating the training effects on central executive through a quasi-experimental approach by Abdelfattah Fassima, Driss Ait Ali, Hicham Khabbache

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Effectiveness of Partition and Graph Theoretic Clustering Algorithms for Multiple Source Partial Discharge Pattern Classification Using Probabilistic Neural Network and Its Adaptiv... by S. Venkatesh, S. Gopal, K. Kannan

“…Studies have indicated that classification of multi-source PD becomes difficult with the degree of overlap and that several techniques such as mixed Weibull functions, neural networks, and wavelet transformation have been attempted with limited success. …”
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Convergence-Driven Adaptive Many-Objective Particle Swarm Optimization by Yunfei Yi, ZhiYong Wang, Yunying Shi, Zhengzhuo Song, Binbin Zhao

“…Based on this metric, Convergence-Aware Learning Factor Adjustment (CALFA), Convergence-Oriented Dimension Variation Strategy (CODVS), and Convergence-Driven Archive Maintenance (CDAM) operations are proposed. …”
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Determinants of employee engagement and job satisfaction in a local municipality by Nkosinathi G. Masuku, Elriza Esterhuyzen, Mpolokeng G. Ramajoe

“…Motivation for the study: Administrative employees are critical for the effective functioning of local municipalities. However, limited research has explored the factors that influence engagement and satisfaction within the eMalahleni local municipality. …”
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Impact of Sublethal Insecticides Exposure on <i>Vespa magnifica</i>: Insights from Physiological and Transcriptomic Analyses by Qingmei Hu, Sijia Fan, Kaiqing Liu, Feng Shi, Xueting Cao, Yiquan Lin, Renyuan Meng, Zichao Liu

“…Transcriptomic analysis revealed increased adenosine triphosphate-related processes and mitochondrial electron transport activity, suggesting elevated energy expenditure to counter insecticide exposure, potentially impairing essential functions like flight, hunting, and immune response. …”
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A New Quantum Circuits of Quantum Convolutional Neural Network for X-Ray Images Classification by Mohammed Yousif, Belal Al-Khateeb, Begonya Garcia-Zapirain

“…In order to address a problem using CNN utilizing quantum computing, Quantum Convolutional Neural Network (QCNN) proposes a novel quantum solution or enhances the functionality of an existing learning model in terms of processing time during training. …”
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Synthetic Data Generation Using Large Language Models: Advances in Text and Code by Mihai Nadas, Laura Diosan, Andreea Tomescu

“…We examine how these methods can enrich low-resource tasks (e.g. classification, question answering) and facilitate code-centric applications (e.g. instruction tuning, code translation, bug repair) through automated verification of functional correctness. Alongside potential benefits&#x2014;cost-effectiveness, broad coverage, and controllable diversity&#x2014;we discuss the accompanying challenges, including factual inaccuracies in generated text, insufficient stylistic or distributional realism, and risks of bias amplification. …”
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Utilizing an Enhanced YOLOv8 Model for Fishery Detection by Hanyu Jiang, Jiacheng Zhong, Fuyu Ma, Cheng Wang, Ruiwen Yi

“…Additionally, we introduced the Channel Aggregation Efficient Downsampling Block (CAEDB) for more efficient upsampling and to improve the network’s expressive power and information flow through channel aggregation functionality. We further optimized the detection head for more effective use of the top-layer network’s rich semantic information, and addressed the class imbalance that was present in the data. …”
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Exploring subthreshold processing for next-generation TinyAI by Farid Nakhle, Antoine H. Harfouche, Antoine H. Harfouche, Hani Karam, Vasileios Tserolas

“…The energy demands of modern AI systems have reached unprecedented levels, driven by the rapid scaling of deep learning models, including large language models, and the inefficiencies of current computational architectures. …”
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Beyond biomedical frontiers: Multidimensional applications of silk and its derived proteins in energy, environment, and agri-food systems by Huanyan Ma, Zhaoyang Wang, Meiliang Pan, Fengyang Hu, Guangdong Sun, Xiuling He

“…The review concludes by outlining synergistic research directions combining synthetic biology, machine learning, and green chemistry to advance silk’s role in sustainable manufacturing paradigms.…”
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An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…Based on 23 classical test functions, the influence of the distribution probability, the three improved mechanisms, and the exploration–exploitation ratio in IHHO‐ELSDF are analyzed. …”
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stClinic dissects clinically relevant niches by integrating spatial multi-slice multi-omics data in dynamic graphs by Chunman Zuo, Junjie Xia, Yupeng Xu, Ying Xu, Pingting Gao, Jing Zhang, Yan Wang, Luonan Chen

“…These findings are supported by independent functional and clinical data. Notably, stClinic excels in label annotation through zero-shot learning and facilitates multi-omics integration by relying on other tools for latent feature initialization.…”
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Upgoing and Downgoing Wavefield Separation in Vertical Seismic Profiling Guided by Signal Knowledge Representation by Cai Lu, Liyuan Qu, Jijun Liu, Jianbo Gao

“…Its distinct branches extracted up/down wave information, while the KRs, transformed into loss functions, enabled knowledge-driven unsupervised VSP wave separation. …”
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Research on Electric Vehicle Charging Load Prediction Methods Combining Signal Noise Reduction and Time Series Modeling by Liyun Liu, Xiaomei Xu, Jinsong Zhang, Dong Li

“…The proposed method begins with the application of CEEMDAN to decompose the data into intrinsic mode functions (IMFs) and residuals. Subsequently, it employs convolutional and pooling layers within the CNN to reduce the dimensionality of the data, thereby optimizing the input dimensions. …”
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Recent Advances in Flexible and Wearable Gas Sensors Harnessing the Potential of 2D Materials by Azmira Jannat, Md Mehdi Masud Talukder, Zhong Li, Jian Zhen Ou

“…It highlights how engineering approaches like defect creation, composite formation, and surface functionalization significantly enhance sensor sensitivity, selectivity, and response times. …”
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LO-MLPRNN: A Classification Algorithm for Multispectral Remote Sensing Images by Fusing Selective Convolution by Xiangsuo Fan, Yan Zhang, Yong Peng, Qi Li, Xianqiang Wei, Jiabin Wang, Fadong Zou

“…The extracted features are mapped to a high-dimensional space through a Gate Recurrent Unit (GRU) and fully connected layers, with nonlinear characteristics enhanced by activation functions, ultimately achieving pixel-level land cover classification. …”
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Unveiling the power of data in bidirectional charging: A qualitative stakeholder approach exploring the potential and challenges of V2G by Jan Lukas Demuth, Johannes Buberger, Annsophie Huber, Emma Behrens, Manuel Kuder, Thomas Weyh

“…Our analysis reveals evolving stakeholder roles, the potential for cost benefits and new revenue streams, and challenges related to costs, functionality, legal aspects, and market collaboration. …”
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