Training University Psychology Students to Teach Multiple Skills to Children with Autism Spectrum Disorder by Daniel Carvalho de Matos, Ryan Matos e Silva Moura de Brito, Fabrício Brito Silva, Juliana Ribeiro Rabelo Costa, Leila Bagaiolo, Claudia Romano Pacífico, Pollianna Galvão Soares

“…A recommended training package is called behavioral skills training (BST), which involves four components (didactic instruction, modeling, role-play, and performance feedback). Background/Objectives: The purpose was to assess the effects of BST on the accurate teaching of multiple skills via DTT by six psychology university students to a confederate and six children diagnosed with ASD. …”
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Primordial black holes from effective field theory of stochastic single field inflation at NNNLO by Sayantan Choudhury, Ahaskar Karde, Pankaj Padiyar, M. Sami

“…Abstract We present a study of the Effective Field Theory (EFT) generalization of stochastic inflation in a model-independent single-field framework and its impact on primordial black hole (PBH) formation. …”
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Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies by Longfei He, Zhaoguang Xu, Zhanwen Niu

“…Furthermore, numerical studies by featuring exponentially distributed demand compare systemwide performances in various scenarios. …”
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TRI-POSE-Net: Adaptive 3D human pose estimation through selective kernel networks and self-supervision with trifocal tensors. by Nabeel Ahmed Khan, Aisha Ahmed Alarfaj, Ebtisam Abdullah Alabdulqader, Nuha Zamzami, Muhammad Umer, Nisreen Innab, Tai-Hoon Kim

“…In order to tackle the problem of precise 3D pose estimation, this work introduces TRI-POSE-Net, a model intended for scenarios with limited supervision. …”
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Survey on vertical federated learning: algorithm, privacy and security by Jinyin CHEN, Rongchang LI, Guohan HUANG, Tao LIU, Haibin ZHENG, Yao CHENG

“…Federated learning （FL） is a distributed machine learning technology that enables joint construction of machine learning models by transmitting intermediate results （e.g., model parameters, parameter gradients, embedding representation, etc.） applied to data distributed across various institutions.FL reduces the risk of privacy leakage, since raw data is not allowed to leave the institution.According to the difference in data distribution between institutions, FL is usually divided into horizontal federated learning （HFL）, vertical federated learning （VFL）, and federal transfer learning （TFL）.VFL is suitable for scenarios where institutions have the same sample space but different feature spaces and is widely used in fields such as medical diagnosis, financial and security of VFL.Although VFL performs well in real-world applications, it still faces many privacy and security challenges.To the best of our knowledge, no comprehensive survey has been conducted on privacy and security methods.The existing VFL was analyzed from four perspectives: the basic framework, communication mechanism, alignment mechanism, and label processing mechanism.Then the privacy and security risks faced by VFL and the related defense methods were introduced and analyzed.Additionally, the common data sets and indicators suitable for VFL and platform framework were presented.Considering the existing challenges and problems, the future direction and development trend of VFL were outlined, to provide a reference for the theoretical research of building an efficient, robust and safe VFL.…”
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Decentralized EEG-based detection of major depressive disorder via transformer architectures and split learning by Muhammad Umair, Jawad Ahmad, Nada Alasbali, Oumaima Saidani, Muhammad Hanif, Aizaz Ahmad Khattak, Muhammad Shahbaz Khan

“…State of the art machine learning models i.e., Random Forest, Support Vector Machine, and Gradient Boosting are utilized, while deep learning models such as Transformers and Autoencoders are selected for their robust feature-extraction capabilities. …”
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Exome sequencing of patients with syndromic tall stature reveals four novel candidate genes by Gabriela Jeesoo Kim, Edoarda Vasco de Albuquerque Albuquerque, Raissa C Rezende, Laurana De Polli Cellin, Ana Maria Santillan Vasconez, Ana C V Krepischi, Lucas Santana, Antônio Marcondes Lerario, Vinicius de Souza, Renata Scalco, Alexander A L Jorge

“…For patients in whom diagnosis of a known tall stature disorder could not be achieved, we performed analysis for candidate genes. The search considered deleterious variants in constrained genes that were linked with height in association studies, animal models consistent with the proposed phenotype, and/or variants recurrent in the literature or our cohort. …”
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Detection of a Highly Ionized Outflow in the Quasiperiodically Erupting Source GSN 069 by P. Kosec, E. Kara, L. Brenneman, J. Chakraborty, M. Giustini, G. Miniutti, C. Pinto, D. Rogantini, R. Arcodia, M. Middleton, A. Sacchi

“…We apply photoionization spectral models and identify the absorption lines as an outflow blueshifted by 1700−2900 km s ^−1 , with a column density of about 10 ^22 cm ^−2 and an ionization parameter $\mathrm{log}(\xi $ /erg cm s ^−1 ) of 3.9−4.6. …”
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CTSeg: CNN and ViT collaborated segmentation framework for efficient land-use/land-cover mapping with high-resolution remote sensing images by Jifa Chen, Gang Chen, Pin Zhou, Yufeng He, Lianzhe Yue, Mingjun Ding, Hui Lin

“…Semantic segmentation models present significant work in land-use/land-cover (LULC) mapping. …”
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A Review of Advanced Deep Learning Methods of Multi-Target Segmentation for Breast Cancer WSIs by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

“…However, manually reviewing whole slide images (WSIs) for tissue segmentation is time-consuming and prone to errors, highlighting the need for multi-target deep learning models to automate the segmentation of these complex structures. …”
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ThermalGS: Dynamic 3D Thermal Reconstruction with Gaussian Splatting by Yuxiang Liu, Xi Chen, Shen Yan, Zeyu Cui, Huaxin Xiao, Yu Liu, Maojun Zhang

“…Thermal infrared (TIR) images capture temperature in a non-invasive manner, making them valuable for generating 3D models that reflect the spatial distribution of thermal properties within a scene. …”
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Vision-Based Fall Risk Assessment Through Attention Augmented Neural Encoding and Data Augmentation by Chunhua Pan, Rui Miao, Qing Zhang, Boting Qu, Xin Wang

“…These sequences are then fed into GTrans, an attention-augmented encoder combining message passing aggregation mechanism with Transformer-based spatial-temporal modeling for nuanced feature extraction. To overcome limited data availability, six skeleton-oriented data augmentation strategies are applied, which significantly enhance the diversity and robustness of training samples. …”
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A Brief Review on the Development Progress of High-Efficiency Klystrons by Soumaya Mandal, Ayan Kumar Bandyopadhyay, Chaitali Koley, Debasish Pal, Taha Selim Ustun, Ahmet Onen

“…The linear beam ‘O’ type klystrons that feature very high output power (greater than several MW) with an efficiency level of 90% are considered in this study. …”
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ALG3 as a prognostic biomarker and mediator of PD-1 blockade resistance in hepatocellular carcinoma by Pengju Tang, Zhenwei Han, Yiming Zhao, Tianxin Xu, Yu Zhang, Lirong Zhu, Fei Song, Cheng Gao, Jinbo Gong, Ji Cheng, Chenggui Wang, Tianlun Wang, Jie Xu, Yu Wang, Zhong Chen

“…First, bioinformatics analysis of HCC-related data from the TCGA database was performed to investigate ALG3 expression patterns in tumor tissues and its correlation with clinical features. …”
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Toward Real-Time Recognition of Continuous Indian Sign Language: A Multi-Modal Approach Using RGB and Pose by M. Geetha, Neena Aloysius, Darshik A. Somasundaran, Amritha Raghunath, Prema Nedungadi

“…Additionally, it shows competitive performance on the German Phoenix 2014 and Phoenix 2014T datasets.…”
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PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation. by George Crowley, James Kim, Sophia Kwon, Rachel Lam, David J Prezant, Mengling Liu, Anna Nolan

“…Cases and controls (n = 15/group) underwent untargeted metabolomics, then feature selection performed on metabolites, cytokines, chemokines, and clinical data. …”
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Software lifecycle management based on the OMG Essence standard by Andrii Zelenkov, Ludmila Mandrikova, Yevhen Borovkov

“…Research Methods: the study employs scientific and technical documentation analysis, system analysis, and the planning and modeling of the software development process. Results. …”
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Enhancing electric vehicle charging infrastructure: A framework for efficient charging point management by Prajeesh C B, Krishna Priya R, Anju S Pillai, Ahmed S Khwaja, Alagan Anpalagan

“…Our findings demonstrate that K-Means outperforms other clustering algorithms, including DBSCAN, K-Medoids, Agglomerative clustering, and Gaussian mixture models (GMM), with a CH score of 1200, a Silhouette score of 0.45, and a DB score of 0.74. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Additional prospective studies are needed to validate clinical utility of predictive models that target derived pediatric sepsis phenotypes in emergency department settings.…”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

“…However, machine learning (ML) models to predict COVID-19 hospitalization in Asian children are lacking. …”
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