A Constrained Algorithm Based NMFα for Image Representation by Chenxue Yang, Tao Li, Mao Ye, Zijian Liu, Jiao Bao

“…Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT) conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. …”
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Exploring the Current Applications and Future Implications of Artificial Intelligence in Public Health Dentistry: A Narrative Review by Tanushri Mahendra Dalvi, Rajeshri Kotwadekar, Shrivardhan R Kalghatgi, Priyanka Paul Madhu, Priyanka Methildeotare

“…AI technologies such as machine learning, deep learning, and natural language processing have been able to show an enormously huge scale capacity for improvement in oral health outcomes at the population level, particularly among disadvantaged groups. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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A novel integrated TDLAVOA-XGBoost model for tool wear prediction in lathe and milling operations by Zhongyuan Che, Chong Peng, Chi Wang, Jikun Wang

“…Tool wear in machining operations compromises tool lifespan and performance. Machine learning models, particularly eXtreme Gradient Boosting (XGBoost), demonstrate pattern recognition capabilities for such predictions. …”
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JAX‐CanVeg: A Differentiable Land Surface Model by Peishi Jiang, Patrick Kidger, Toshiyuki Bandai, Dennis Baldocchi, Heping Liu, Yi Xiao, Qianyu Zhang, Carlos Tianxin Wang, Carl Steefel, Xingyuan Chen

“…The new model builds on the legacy CanVeg by incorporating advanced functionalities through JAX in the graphic processing unit support, automatic differentiation, and integration with DNNs. …”
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Towards Explainable Anomaly Detection in Safety-critical Systems: Employing FRAM and SpecTRM in International Space Station Telemetry by Shota Iino, Hideki Nomoto, Takashi Fukui, Sayaka Ishizawa, Yohei Yagisawa, Takayuki Hirose, Yasutaka Michiura

“…The methodology is verified and validated through its application to the thermal control system within the ISS's Japanese Experimental Module (JEM), illustrating its capacity to augment diagnostic capabilities and assist flight controllers and specialists in preserving the ISS's functional integrity. The findings underscore the importance of explainability in the machine learning-based anomaly detection of safety-critical systems and suggest a promising avenue for future explorations aimed at bolstering space system health management through improved explainability and operational resilience.…”
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Description of survival data extended to the case of competing risks: a teaching approach based on frequency tables by Davide Paolo Bernasconi, Laura Antolini

“…In introductory courses students learn how to describe right-censored survival time data using the product-limit estimator of the survival function on a given <em>end-point </em>relying on a product of conditional survival probabilities. …”
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The Effect of Hearing Aid Amplification on Gait Parameters: A Pilot Study Using Ear-Worn Motion Sensors by Ann-Kristin Seifer, Arne Küderle, Kaja Strobel, Ronny Hannemann, Björn M. Eskofier

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Integrative analysis of semaphorins family genes in colorectal cancer: implications for prognosis and immunotherapy by Jiahao Zhu, Benjie Xu, Zhixing Wu, Zhixing Wu, Zhiwei Yu, Shengjun Ji, Jie Lian, Haibo Lu

“…However, the prognostic value of SEMA-related genes in colorectal cancer (CRC) remains unclear.MethodsWe applied a novel machine learning framework that incorporated 10 machine learning algorithms and their 101 combinations to construct a SEMAs-related score (SRS). …”
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A way of relating to life; myself and others - a thematic analysis of patients’ experience of having an eating disorder by Malin Bäck, Sanna Aila Gustafsson, Karin Jacobson, Theresia Ljung, Rolf Holmqvist, Gerhard Andersson

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Integrating Ambient In-Home Sensor Data and Electronic Health Record Data for the Prediction of Outcomes in Amyotrophic Lateral Sclerosis: Protocol for an Exploratory Feasibility S... by William E Janes, Noah Marchal, Xing Song, Mihail Popescu, Abu Saleh Mohammad Mosa, Juliana H Earwood, Vovanti Jones, Marjorie Skubic

“… BackgroundAmyotrophic lateral sclerosis (ALS) leads to rapid physiological and functional decline before causing untimely death. Current best-practice approaches to interdisciplinary care are unable to provide adequate monitoring of patients’ health. …”
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Robotic-Assisted Total Knee Arthroplasty Improves Accuracy and Reproducibility of the Polyethylene Insert Thickness Compared to Manual Instrumentation or Navigation: A Retrospectiv... by Yoan Bourgeault-Gagnon, FRCSC, Lucy J. Salmon, BAppSci (Physio), PhD, Matthew C. Lyons, MBBS, FRACS

“…Background: Increased accuracy and lower rates of component positioning outliers have been associated with better long-term survival and functional outcomes of total knee arthroplasty (TKA). …”
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Examining AI-Powered ADHD Diagnosis: Current Trends, Key Challenges, and Future Directions in the Field by Qurat Ul Ain, Soyiba Jawed, Ahmad Rauf Subhani, Wasi Haider Butt, Muhammad Usman Akram

“…Consequently, in this article we systematically investigate various Machine Learning (ML) and Deep Learning (DL) approaches as well as different diagnostic tools or modalities employed for the identification of ADHD. …”
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Explainable Self-Supervised Dynamic Neuroimaging Using Time Reversal by Zafar Iqbal, Md. Mahfuzur Rahman, Usman Mahmood, Qasim Zia, Zening Fu, Vince D. Calhoun, Sergey Plis

“…Objective: Functional magnetic resonance imaging data pose significant challenges due to their inherently noisy and complex nature, making traditional statistical models less effective in capturing predictive features. …”
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Prioritising and including children in intersectoral policymaking: uncovering Immunity to Change in Ghana by Sarah L Dalglish, Aku Kwamie, Isabella Sagoe-Moses, Leonie Akofio-Sowah, Maria Lisa Soraghan, Srivatsan Rajagopalan, Kwame S Sakyi, Bethany Jennings, Florence Ayisi Quartey, Prince Owusu

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Crocin nano-chitosan-coated compound mitigates hippocampal blood-brain barrier disruption, anxiety, and cognitive deficits in chronic immobilization stress-induced rats by Mohsen Khodadadi, Gila Pirzad Jahromi, Gholam Hossein Meftahi, Hossein Khodadadi, Mohammadmehdi Hadipour, Masoud Ezami

“…Stressful conditions can disrupt the central nervous system's normal homeostasis and physiological functions, resulting in blood-brain barrier malfunction, memory and learning impairment, anxiety, etc. …”
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Differential MR/GR Activation in Mice Results in Emotional States Beneficial or Impairing for Cognition by Vera Brinks, Maaike H. van der Mark, E. Ron de Kloet, Melly S. Oitzl

“…Corticosteroids regulate stress response and influence emotion, learning, and memory via two receptors in the brain, the high‐affinity mineralocorticoid (MR) and low‐affinity glucocorticoid receptor (GR). …”
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Statistical Software Usability for Novice Research Students in the Social Sciences: An Eye-Tracking Study by Sedigheh Abbasnasab Sardareh, Gavin T. L. Brown, Paul Denny

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Research on load labeling method for big data in novel power system by ZHANG Ximing, XU Huan, YANG Qiuyong

“…By proposing a flexible framework to mark load patterns and usage habits in a non-intrusive way, the composite data tag file is used for smart grid functions such as demand response, energy management and load monitoring. …”
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Towards Therapeutic Applications of Arthropod Venom K+-Channel Blockers in CNS Neurologic Diseases Involving Memory Acquisition and Storage by Christiano D. C. Gati, Márcia R. Mortari, Elisabeth F. Schwartz

“…Potassium channels are the most heterogeneous and widely distributed group of ion channels and play important functions in all cells, in both normal and pathological mechanisms, including learning and memory processes. …”
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