A Novel Approach to Cognitive Load Measurement in N-Back Tasks Using Wearable Sensors, Empirical Mode Decomposition With Machine Learning, and Explainable AI for Feature Importance by Aakanksha Dayal, Ziaullah Khan, Kiramat Ullah, Hee-Cheol Kim

“…These results highlight the potential of combining physiological signals and EMD with machine learning for detecting mental workload and stress.…”
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The indirect spaced repetition concept by Louis Lafleur

“…Most importantly, it is based on Nation’s (2001) recommendation to consider all three tiers of word knowledge (meaning, form, and function/use) and subsequent 18 aspects of word knowledge for a more balanced approach in teaching and learning vocabulary. …”
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Exploring the relationship between graft dysfunction with serum metabolites and inflammatory proteins: integrating Mendelian randomization, single-cell analysis, machine learning,... by Jiyuan Li, Kankan Shui, Longkai Peng, Helong Dai, Fenghua Peng

“…In transplanted kidneys, IL-2RB is predominantly expressed elevated in T cells from rejection samples and is associated with decreased renal function. 10 hub genes were identified based on T cells with high and low expression of IL-2RB, of which NGboost reached AUC 0.77. …”
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NCoder—a quantum field theory approach to encoding data by D S Berman, M S Klinger, A G Stapleton

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Association between the (neutrophil + monocyte)/albumin ratio and all-cause mortality in sepsis patients: a retrospective cohort study and predictive model establishment according... by Lulu Liu, Qian Ma, Guangzan Yu, Xuhou Ji, Hua He

“…Predictive models using Cox regression and Random Forest algorithms showed strong performance, indicating that the NMa ratio could function as a predictor of negative prognosis in patients with sepsis.…”
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Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale E... by Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang

“…Conclusion: Our findings suggest that CMSE-derived circadian HRV features from Holter ECG could serve as a non-invasive, cost-effective, and interpretable solution for LVEF assessment in community settings. From a machine learning interpretable perspective, the proposed method emphasized CMSE’s clinical potential in capturing autonomic dynamics and cardiac function fluctuations.…”
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Deep neural network modeling attacks on arbiter-PUF-based designs by Huanwei Wang, Weining Hao, Yonghe Tang, Bing Zhu, Weiyu Dong, Wei Liu

“…Strong PUFs are susceptible to classical machine learning attacks, however, machine learning’s effectiveness in attacking complex structured strong PUFs is limited, and its efficiency is relatively low. …”
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SLiTRANet: An EEG-Based Automated Diagnosis Framework for Major Depressive Disorder Monitoring Using a Novel LGCN and Transformer-Based Hybrid Deep Learning Approach by Sagnik de, Anurag Singh, Vivek Tiwari, Harshita Patel, G. N. Vivekananda, Dharmendra Singh Rajput

“…We have utilized the Weighted Focal Binary Hinge Loss function, specifically designed for customized Linear Graph Convolution Network, to improve learning and handle unbalanced input. …”
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Associations between all-cause and ischemic heart disease mortality and long-term ambient ultrafine particles exposure: a comparison of statistical and machine learning exposure mo... by Julien Vachon, Audrey Smargiassi, Keith Van Ryswyk, Éric Lavigne, Elhadji Anassour Laouan Sidi, Claudia Blais, Stéphane Buteau

“…The estimated response function varied depending on the exposure assessment method.…”
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Enhanced Multigrained Scanning-Based Deep Stacking Network for Intrusion Detection in IoMT Networks by Pakarat Musikawan, Yanika Kongsorot, Phet Aimtongkham, Chakchai So-In

“…Drawing inspiration from the accomplishments of deep learning in cyber threat detection, we propose a multigrained scanning-based deep stacking network (MGDSN) to defend against sophisticated cyberattacks on Internet of Medical Things (IoMT) networks. …”
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A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…Performance comparison charts and loss function graphs emphasize AADMA’s superiority in addressing the complexities of real-time coordination and adaptability. …”
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Sesotho Language Acquisition by Faculty of Education Students in South Africa: A Systematic Review by Nthabiseng B. Khoalenyane, Patrick Alpheous Nyathi, Precious Moyo

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Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning Reveals the Giant Exoplanet AF Lep b in High-contrast Imaging Data from 2011 by Markus J. Bonse, Timothy D. Gebhard, Felix A. Dannert, Olivier Absil, Faustine Cantalloube, Valentin Christiaens, Gabriele Cugno, Emily O. Garvin, Jean Hayoz, Markus Kasper, Elisabeth Matthews, Bernhard Schölkopf, Sascha P. Quanz

“…We find that PCA learns the shape of the telescope point-spread function for high numbers of PCA components. …”
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A Multiclassification Model for Skin Diseases Using Dermatoscopy Images with Inception-v2 by Shulong Zhi, Zhenwei Li, Xiaoli Yang, Kai Sun, Jiawen Wang

“…In this paper, a multiclassification model based on the Inception-v2 network and the focal loss function is proposed on the basis of deep learning, and the ISIC 2019 dataset is optimised using data augmentation and hair removal to achieve seven classifications of dermatological images and generate heat maps to visualise the predictions of the model. …”
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Implementation of a neural network model in the Statistica 12 for mudflow frequency forecasting by B. A. Ashabokov, A. A. Tashilova, L. A. Kesheva, N. V. Teunova

“…A multilayer perceptron (MLP) was chosen as a neural network method, and a hyperbolic tangent (tanh) was used as an activation function. Based on deep learning algorithms, a mathematical model MPL 2-50-1 was developed, which is capable of learning on the used data (precipitation, temperature, number of mudflows for the period 1953-2015) and forecasting the number of mudflows based on the meteorological parameters (precipitation, temperature) entered into the model. …”
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Effects and mechanisms of synchronous virtual reality action observation and electrical stimulation on upper extremity motor function and activities of daily living in patients wit... by Yao Cui, Yao Cui, Fang Cong, Fang Cong, Ming Zeng, Jun Wang

“…BackgroundExisting rehabilitation techniques are not satisfactory in improving motor function after stroke, resulting in heavy social burdens. …”
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The effects of treadmill exercise and diet control on cognitive function in HFD-induced ApoE-/- mice based on the SIRT1-NF-κB/PGC-1α-BDNF signaling pathways by Xu Ting, Deng Wenjuan, Li Shufeng, Liu Yi, Shi Zhitong, Zhang Xiaoyue, Wang Ningping

“…[Conclusion] Treadmill exercise and diet control can reduce the inflammatory response in the hippocampus of mice by mediating the SIRT1-NF-κB/PGC-1α-BDNF signaling pathway, thereby improving cognitive function in mice.…”
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Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated function enabl... by Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Justine Charon, Adrian Diaz, Kris De Jonghe, Sebastien Massart, Thierry Michon, Wim Vranken, Wim Vranken, Wim Vranken, Wim Vranken

“…The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are demonstrably modulated by native substrates of dynamic and interconvertible conformational ensembles. …”
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Inclusión y accesibilidad al deporte de estudiantes con diversidad funcional en el contexto educativo ecuatoriano (Inclusion and accessibility to sport for students with functional... by Olga Alicia Mayanza Paucar, Alexandra Marisol Barcia Maridueña, Sayonara Elizabeth Morejón Calixto, Efraín Enrique Vásquez Alvarado

“…The results indicated that there were no barriers to access to sports venues according to 77.8% of educators, 56.5% indicated that they do not usually consider the accessibility and adaptation needs of students with functional diversities, 48.4% explained that educational entities do not They show sensitivity to people with functional diversity and 81.5% expressed that there are no specialized teachers for the development of adapted sports practices. …”
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Host genetics maps to behaviour and brain structure in developmental mice by Sarah Asbury, Jonathan K. Y. Lai, Kelly C. Rilett, Zeeshan Haqqee, Benjamin C. Darwin, Jacob Ellegood, Jason P. Lerch, Jane A. Foster

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