Expanding Multilingual Co-Speech Interaction: The Impact of Enhanced Gesture Units in Text-to-Gesture Synthesis for Digital Humans by Ghazanfar Ali, Woojoo Kim, Muhammad Shahid Anwar, Jae-In Hwang, Ahyoung Choi

“…Incorporating a cutting-edge gesture-pose matching model with deep contrastive learning, we retrieved gestures from a comprehensive rule base containing 210,000 rules. …”
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Exploring potential methylation markers for ovarian cancer from cervical scraping samples by Ju-Yin Lien, Lu Ann Hii, Po-Hsuan Su, Lin-Yu Chen, Kuo-Chang Wen, Hung-Cheng Lai, Yu-Chao Wang

“…Therefore, this study aimed to develop a methylation-based machine-learning model to stratify patients with ovarian cancer from the cervical scraping samples collected via Pap test. …”
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Decoding per- and polyfluoroalkyl substances (PFAS) in hepatocellular carcinoma: a multi-omics and computational toxicology approach by Yanggang Hong, Deqi Wang, Zeyu Liu, Yuxin Chen, Yi Wang, Jiajun Li

“…Through integrated machine learning and PPI network analysis, we identified six genes, APOA1, ESR1, IGF1, PPARGC1A, SERPINE1, and PON1, that serve as core targets of PFAS in both HCC progression and prognosis. …”
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Extraction of <i>Suaeda salsa</i> from UAV Imagery Assisted by Adaptive Capture of Contextual Information by Ning Gao, Xinyuan Du, Min Yang, Xingtao Zhao, Erding Gao, Yixin Yang

“…In this paper, for <i>Suaeda salsa</i>, which is a weak target with a sparse distribution and inconspicuous features, relying on the high-resolution and spatial information-rich features of UAV imagery, we establish an adaptive contextual information extraction deep learning semantic segment model (ACI-Unet), which can solve the problem of recognizing <i>Suaeda salsa</i> from high-precision UAV imagery. …”
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The need for advancing algal bloom forecasting using remote sensing and modeling: Progress and future directions by Cassia B. Caballero, Vitor S. Martins, Rejane S. Paulino, Elliott Butler, Eric Sparks, Thainara M. Lima, Evlyn M.L.M. Novo

“…Remote sensing, particularly ocean-color products, has emerged as a foundation for algal bloom monitoring and forecasting, providing critical spatial–temporal data to address the limitations of in situ measurements. Machine learning and deep learning models dominate recent developments, demonstrating their capabilities in capturing non-linear and complex dynamics and enhancing accuracy in forecasting. …”
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BASE: a web service for providing compound-protein binding affinity prediction datasets with reduced similarity bias by Hyojin Son, Sechan Lee, Jaeuk Kim, Haangik Park, Myeong-Ha Hwang, Gwan-Su Yi

“…Abstract Background Deep learning-based drug-target affinity (DTA) prediction methods have shown impressive performance, despite a high number of training parameters relative to the available data. …”
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Causal estimation of the relationship between reproductive performance and the fecal bacteriome in cattle by Yutaka Taguchi, Haruki Yamano, Yudai Inabu, Hirokuni Miyamoto, Koki Hayasaki, Noriyuki Maeda, Yoshiro Kanmera, Seiji Yamasaki, Noboru Ota, Kenji Mukawa, Atsushi Kurotani, Shigeharu Moriya, Teruno Nakaguma, Chitose Ishii, Makiko Matsuura, Tetsuji Etoh, Yuji Shiotsuka, Ryoichi Fujino, Motoaki Udagawa, Satoshi Wada, Jun Kikuchi, Hiroshi Ohno, Hideyuki Takahashi

“…Abstract Background The gut bacteriome influences host metabolic and physiological functions. However, its relationship with reproductive performance remains unclear. …”
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Large language models meet user interfaces: The case of provisioning feedback by Stanislav Pozdniakov, Jonathan Brazil, Solmaz Abdi, Aneesha Bakharia, Shazia Sadiq, Dragan Gašević, Paul Denny, Hassan Khosravi

“…Incorporating Generative Artificial Intelligence (GenAI), especially Large Language Models (LLMs), into educational settings presents valuable opportunities to boost the efficiency of educators and enrich the learning experiences of students. A significant portion of the current use of LLMs by educators has involved using conversational user interfaces (CUIs), such as chat windows, for functions like generating educational materials or offering feedback to learners. …”
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Evaluating the role of training data origin for country-scale cropland mapping in data-scarce regions: A case study of Nigeria by Joaquin Gajardo, Michele Volpi, Daniel Onwude, Thijs Defraeye

“…Handling class imbalance was also critical, with weighted loss functions improving accuracy by up to 0.071 for the single-headed LSTM. …”
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Exploring the complex interplay between oral Fusobacterium nucleatum infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs by Syam Jeepipalli, Aravindraja C, William Duncan, V. M. Krishna, Bikash Sahay, Edward K. L. Chan, L. Kesavalu

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Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers by Wentong Li, Yiyi Zhang, Chuanhong Li, Mingyang Jiang, Dong Wang, Luomeng Chao, Luomeng Chao, Luomeng Chao, Yuxia Yang

“…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality &gt;20). Machine learning validation demonstrated their combined exceptional diagnostic efficacy (AUC=0.963, F1 = 0.88). …”
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Promoting the Integration of Public Perspective into Urban Design Decision-Making Based on Crowdsourced Visual Perception Method by Lu HUANG, Takuya (JPN) OKI

“…Thus, understanding and integrating public urban perception not only enhances design responsiveness to user needs but also fosters a harmonious balance of functional efficiency and humanistic care. Crowdsourced visual perception data and analysis methods, with their advantages of efficiency, broad representativeness, and low cost, have become key methodological tools in urban built environment research. …”
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Predicting Mental and Neurological Illnesses Based on Cerebellar Normative Features by Milin Kim, Nitin Sharma, Esten H. Leonardsen, Saige Rutherford, Geir Selbæk, Karin Persson, Nils Eiel Steen, Olav B. Smeland, Torill Ueland, Geneviève Richard, Aikaterina Manoli, Sofie L. Valk, Dag Alnæs, Christian F. Beckman, Andre F. Marquand, Ole A. Andreassen, Lars T. Westlye, Thomas Wolfers, Torgeir Moberget

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Connectogram-COH: A Coherence-Based Time-Graph Representation for EEG-Based Alzheimer’s Disease Detection by Ehssan Aljanabi, İlker Türker

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A SMARTTR workflow for multi-ensemble atlas mapping and brain-wide network analysis by Michelle Jin, Simon O Ogundare, Marcos Lanio, Sophia Sorid, Alicia Ruth Whye, Sofia Leal Santos, Alessandra Franceschini, Christine Ann Denny

“…During LH expression, the substantia nigra emerges as a highly influential region that shows a functional reversal following IS, indicating a possible regulatory function of motor activity during helplessness. …”
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CSI feedback algorithm based on deep unfolding for massive MIMO systems by Yong LIAO, Gang CHENG, Yujie LI

“…In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning.…”
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La enseñanza del español a hablantes de herencia en inmersión parcial y total: factores eficaces del aprendizaje en aulas heterogéneas / The teaching of Spanish to heritage speaker... by María Pilar López-García

“…Considering the specificities of these students in partial immersion and in total immersion programmes has led us to examine the functioning of heterogeneous classrooms and the needs of these students. …”
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Una experiencia de aprendizaje-servicio en la asignatura «Bases anatómicas y fisiológicas del movimiento» del Área de Didáctica de la Expresión Corporal (A service-learning experie... by Jesús Gil Gómez, Óscar Chiva Bartoll

“…Key words: Service-Learning, Physical Education Teaching, Methodological Innovation, Functional Diversity, Higher Education. …”
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AI-based tool wear prediction with feature selection from sound signal analysis by Viet Q. Vu, Tien-Ninh Bui, Minh-Quang Tran

“…First, the measured sound signals in the milling process are extracted into a series of intrinsic mode functions (IMFs) using the ensemble empirical mode decomposition (EEMD). …”
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Progressive multi-scale attention neural network for pneumonia classification in chest X-rays by Mohammad Reza Mahdiani

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