CLINICAL AND ELECTROENCEPHALOGRAPHIC CHARACTERISTICS OF IDIOPATHIC CHILDHOOD FOCAL EPILEPSY WITH CENTROTEMPORAL SPIKES by K. Yu. Mukhin

“…Sulthiame (ospolot) as monotherapy is used in Germany.Based on their findings and the data available in the literature, the authors consider the etiology, pathogenesis, clinical manifestations of RE and its diagnosis, treatment principles, and prognosis. The specific features of the electroencephalographic pattern in this disease are detailed.…”
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Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification. by Daniel R Ripoll, Sidhartha Chaudhury, Anders Wallqvist

“…We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that can serve as a "fingerprint" to recognize uncharacterized Abs. …”
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Windows Malware Detection via Enhanced Graph Representations with Node2Vec and Graph Attention Network by Nisa Vuran Sarı, Mehmet Acı, Çiğdem İnan Acı

“…Finally, the enhanced embeddings are classified using Convolutional Neural Network (CNN) and Gated Recurrent Units (GRU)s, a custom hybrid CNN-GRU-3 deep learning-based model capable of effectively modeling sequential patterns. The dual role of GAT as a classifier and feature extractor is also analyzed to evaluate its impact on embedding quality and classification accuracy. …”
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Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals by Mesfer Al Duhayyim

“…Furthermore, the ResNet50 model is employed for feature extraction to capture complex spatial patterns in visual data. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Deep learning (DL) focused cyberthreat detection has developed as a powerful and effective approach to identifying abnormal patterns or behaviours in the data field. …”
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Exploring the potential of deep learning models integrating transformer and LSTM in predicting blood glucose levels for T1D patients by Xin Xiong, XinLiang Yang, Yunying Cai, Yuxin Xue, JianFeng He, Heng Su

“…The Transformer Encoder captures long-range dependencies, while the LSTM models short-term patterns. To improve feature extraction, we integrate Bidirectional LSTM and Transformer Encoder layers at multiple stages. …”
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Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews by Miehleketo Mathebula, Abiodun Modupe, Vukosi Marivate

“…Additionally, the pre-training of a larger language model (PTLM) struggles to capture bidirectional contextual knowledge learnt through word dependency because the sentence-level representation fails to take broad features into account. We develop a novel structure called language feature extraction and adaptation for reviews (LFEAR), an advanced natural language model that amalgamates retrieval-augmented generation (RAG) with a conversation format for an auto-regressive fine-tuning model (ARFT). …”
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How are cantonese sentence-final particles phonologically and semantically processed in the mind? by Lu Aitao, Wang Xuebin, Zhang Ye, Liu Siyi, Huang Xin, Jiang Lilan

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The precipitous decline of a gray fox population by Max R. Larreur, Clayton K. Nielsen, Damon B. Lesmeister, Guillaume Bastille-Rousseau

“…We then developed three predictive occupancy models that allowed comparison of gray fox spatial patterns and occupancy estimates over time. …”
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Spatial heterogeneity of cultural ecosystem services in grand canal rural heritage sites: A community gradient framework using participatory mapping by Xin Jiang, Xi Chen, Qinghai Zhang, Yutao Li, Mingrui Wang, Yongjun Li, Xing Xiong, Xiaoning Wu, Xin Li, Yujia Zhong, Yong Lu

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Detection and Localization of Stationary Waves on Venus Using a Self‐Supervised Anomaly Detection Model by Husnu Baris Baydargil, Jose Eduardo Oliveira Silva, Yeon Joo Lee, Meeyoung Cha

“…To address this, we propose a self‐supervised anomaly detection model based on a vector‐quantized generative adversarial network to identify and localize stationary atmospheric waves in spacecraft images of Venus. Our model is developed over Akatsuki images of Venus and is trained on smaller cropped images containing features other than stationary waves, allowing it to learn the underlying patterns of normal cloud features. …”
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Frequency and Determinants of Flare and Persistently Active Disease in a Large Multinational Prospective Lupus Cohort by Yanjie Hao, Dylan Hansen, Worawit Louthrenoo, Yi‐Hsing Chen, Jiacai Cho, Aisha Lateef, Laniyati Hamijoyo, Shue Fen Luo, Yeong‐Jian Wu, Sandra Navarra, Leonid Zamora, Zhanguo Li, Sargunan Sockalingam, Yasuhiro Katsumata, Masayoshi Harigai, Lanlan Ji, Zhuoli Zhang, Madelynn Chan, Jun Kikuchi, Tsutomu Takeuchi, Sang‐Cheol Bae, Fiona Goldblatt, Sean O'Neill, Kristine (Pek Ling) Ng, B. M. D. B. Basnayake, Nicola Tugnet, Naoaki Ohkubo, Yoshiya Tanaka, Cherica Tee, Michael Tee, C. S. Lau, Ning Li, Vera Golder, Alberta Hoi, Rangi Kandane‐Rathnayake, Eric Morand, Shereen Oon, Mandana Nikpour, for the Asia Pacific Lupus Collaboration

“…Conclusion Both flare and PAD are common disease activity patterns in SLE; both predict organ damage accrual but differ in disease features and predictive factors. …”
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A Comprehensive Framework for Adaptive Electric Vehicle Charging Station Siting and Sizing Based on Transferable Spatio-Temporal Demand Prediction by Yutong Peng, Liqi Ye, Wenrui Ouyang, Qi Xi, Jing Wang, Xiaolin Wang

“…The derived best-performing ConvLSTM model, trained on basic features and calculated charging demand, can be applied to cross-city demand prediction by inputting identical basic features. …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Dynamic environmental factors, such as crop growth, changing weather patterns, and livestock movement, increase system uncertainty. …”
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Geografia dell’automazione industriale. L’impatto dell’uso dei robot sulle localizzazioni manifatturiere by Lucia Simonetti

“…Robotics seems to be able to slow down (at least in some industrial sectors) the pace of offshoring, but it does not seem to be able to lead to the reshoring of activities to developed economies. And while labour-cost differentials still remain a key feature in firms’ decisions of where to locate manufactures, especially of goods with a high labour content, demand factors, such as the size and growth of local markets, are progressively becoming major determinants.…”
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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…The MCNN architecture effectively captures local patterns in text using multiple filter sizes, enabling comprehensive feature extraction with low computational overhead. …”
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Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow by Álvaro Ospina, Ever Herrera Ríos, Jaime Jaramillo, Camilo A. Franco, Esteban A. Taborda, Farid B. Cortes

“…The synergy lies in DA’s ability to reduce dimensionality and identify meaningful features, which enhances the ML models’ interpretability, while ML leverages these features to model non-linear and time-dependent patterns that DA alone cannot address. …”
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Quantitative analysis of communication dynamics in agile software teams through multimodal analytics by Diego Miranda, Rene Noel, Jaime Godoy, Carlos Escobedo, Cristian Cechinel, Roberto Munoz

“…Abstract Effective collaboration in agile software development depends on communication, cooperation, and coordination. …”
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Conceptualizing resilience in public health: a philosophical approach by Jishnu Pawan K., Mala Ramanathan

“…Abstract Background The initial inquiry into the concept revealed its usage as a boundary object and how this facilitated its interdisciplinary utilization. The same feature enabled the shift to literature within other disciplines and then identify its conceptualization in them. …”
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Geographically Aware Air Quality Prediction Through CNN-LSTM-KAN Hybrid Modeling with Climatic and Topographic Differentiation by Yue Hu, Yitong Ding, Wenjing Jiang

“…Air pollution poses a pressing global challenge, particularly in rapidly industrializing nations like China where deteriorating air quality critically endangers public health and sustainable development. To address the heterogeneous patterns of air pollution across diverse geographical and climatic regions, this study proposes a novel CNN-LSTM-KAN hybrid deep learning framework for high-precision Air Quality Index (AQI) time-series prediction. …”
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