Story reading with incidental comprehension and memory: left hemisphere dominance by Nora Silvana Vigliecca

“…There is a need for validation of cerebral laterality in this type of verbal recall, which includes spontaneous performance (free or uncued condition (UC)), and induced-through-question performance regarding the forgotten units (cued condition (CC)). …”
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THERMAL IMAGING AND GYMNASTICS INJURIES: A MEANS OF SCREENING AND INJURY IDENTIFICATION by William A. Sands, Jeni R. McNeal, Michael H. Stone

“…Thermal images show bilateral and tissue area thermal differentials by differences in gray scale. This information discriminates injuries, inflammation, and other conditions without invasive procedures. …”
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Superpixel guided spectral-spatial feature extraction and weighted feature fusion for hyperspectral image classification with limited training samples by Yao Li, Liyi Zhang, Lei Chen, Yunpeng Ma

“…In addition, under the condition of only five training samples for each class, we conducted comparative experiments with several of the state-of-the-art classification methods and verified the excellent performance of our method on three widely used data sets.…”
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Semi-Supervised Burn Depth Segmentation Network with Contrast Learning and Uncertainty Correction by Dongxue Zhang, Jingmeng Xie

“…Burn injuries are a common traumatic condition, and the early diagnosis of burn depth is crucial for reducing treatment costs and improving survival rates. …”
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Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study by Zhengping Pu, Hongna Huang, Man Li, Hongyan Li, Xiaoyan Shen, Lizhao Du, Qingfeng Wu, Xiaomei Fang, Xiang Meng, Qin Ni, Guorong Li, Donghong Cui

“…Prediction models were built by combining features of prefrontal FC and cognitive scale performance and applying machine learning models, The models showed generally satisfactory abilities to differentiate among the three groups, especially those employing linear discriminant analysis, logistic regression, and support vector machine. …”
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WIVIDOSA-Net: Wigner–Ville distribution based obstructive sleep apnea detection using single lead ECG signal by Amit Bhongade, Tapan Kumar Gandhi

“…The proposed model extracts high-resolution spatial and temporal information, making the pipeline very effective in discriminating OSA episodes from normal. Therefore, it exhibits superior performance in comparison to all current state-of-the-art approaches, with a reduced computation burden due to its limited number of learnable parameters.…”
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Pharmacological Enhancement of Adult Hippocampal Neurogenesis Improves Behavioral Pattern Separation in Young and Aged Male Mice by Wei-li Chang, Karly Tegang, Benjamin A. Samuels, Michael Saxe, Juergen Wichmann, Denis J. David, Indira Mendez David, Angélique Augustin, Holger Fischer, Sabrina Golling, Jens Lamerz, Doris Roth, Martin Graf, Sannah Zoffmann, Luca Santarelli, Ravi Jagasia, René Hen

“…Background: Impairments in behavioral pattern separation (BPS)—the ability to distinguish between similar contexts or experiences—contribute to memory interference and overgeneralization seen in many neuropsychiatric conditions, including depression, anxiety, posttraumatic stress disorder, dementia, and age-related cognitive decline. …”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

“…Background Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associated with an unfavourable prognosis. …”
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Multi-environment evaluation and identification of Tartary buckwheat (Fagopyrum tataricum Gaertn.) genotypes for superior agronomic and nutritional potential in the North-Western H... by Vivek Singh, Amit Rana, Shorya Kapoor, Rhitisha Sood, Shabnam Kumari, Shailja Sharma, Nimit Kumar, Indra Pratap Singh, Gopal Katna

“…These findings provide critical insights into the adaptability and performance of buckwheat genotypes under diverse agro-climatic conditions. …”
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Enhancing Fault Diagnosis: A Hybrid Framework Integrating Improved SABO with VMD and Transformer–TELM by Jingzong Yang, Xuefeng Li, Min Mao

“…However, continuous operation under complex working conditions can easily lead to gradual performance degradation and sudden faults, which not only result in equipment failure but may also trigger a cascading failure effect, significantly amplifying downtime losses. …”
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Generative adversarial networks (GANS) for generating face images by Dolly Indra, Muh Wahyu Hidayat, Fitriyani Umar

“…Results indicate that training from scratch with the public dataset (FFHQ) using a batch size of 16 and a learning rate of 0.0025 achieves an FID score of 85.67 and performance of 86.46% at Tick 100, whereas the private dataset, under the same conditions, results in an FID score of 98.59 with a performance of 18.54%.. …”
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Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox by Samuel M. Gbashi, Paul A. Adedeji, Obafemi O. Olatunji, Nkosinathi Madushele

“…To address this problem, this study advanced a framework for choosing the best features for a k-NN fault diagnostic model while also leveraging the benefits of “weighting” to further improve its performance. The framework was validated using vibration signals from a wind turbine gearbox under four different fault conditions. …”
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A stacked learning framework for accurate classification of polycystic ovary syndrome with advanced data balancing and feature selection techniques by Heba M. Emara, Walid El-Shafai, Naglaa F. Soliman, Abeer D. Algarni, Reem Alkanhel, Fathi E. Abd El-Samie

“…These results underscore the proficiency of the proposed framework in discriminating PCOS cases with a high degree of precision. …”
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Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…Traditional pest recognition methods, which rely heavily on manual feature extraction, are not only time consuming and labor intensive but also lack robustness in diverse conditions. While deep learning (DL) models have improved performance over conventional approaches, they typically suffer from high computational demands and large model sizes, limiting their real-world applicability. …”
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A Coherent Approach-Based Fine-Tuning of Segment Anything Model Plus Watershed Algorithm for Instance Segmentation of Mitochondria in Electron Microscopy Images by Zahra Faska, Lahbib Khrissi, Imadeddine Mountasser, Khalid Haddouch, Nabil El Akkad, Samah Alshathri, Walid El-Shafai

“…This model would be able to perform precise segmentation for a diverse array of targets across different imaging conditions at the level of performance of specialized U-Net models, or even better. …”
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Shape-Aware Adversarial Learning for Scribble-Supervised Medical Image Segmentation with a MaskMix Siamese Network: A Case Study of Cardiac MRI Segmentation by Chen Li, Zhong Zheng, Di Wu

“…MaskMixAdv works under constrained annotation conditions as a label-efficient learning approach for medical image segmentation. …”
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GLLR-HAD: Global-local low-rank integration for hyperspectral image anomaly detection by Yu Bai, Yanling Zhang, Lili Zhang, Tan Zhao

“…Through the collaborative optimization of global and local components, the proposed method achieves robust detection performance across diverse scenarios and demonstrates strong adaptability to complex and variable spectral conditions. …”
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Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease by Tong Feng, PeiPei Li, Ran Duan, Zhi Jin

“…The Support Vector Machine (SVM) model achieved the highest performance, with an AUC of 0.890 in the validation set and 0.887 in the test set, demonstrating robust discriminative ability and clinical applicability. …”
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Multi-Step Prediction of TBM Tunneling Speed Based on Advanced Hybrid Model by Defu Liu, Yaohong Yang, Shuwen Yang, Zhixiao Zhang, Xiaohu Sun

“…Firstly, four datasets were selected under different geological conditions, and the original data were preprocessed using the binary discriminant function and the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mi>σ</mi></mrow></semantics></math></inline-formula> principle; secondly, the preprocessed data were decomposed using the empirical wavelet variation (EWT) to obtain several subseries and residual series; then, Intrinsic Computing Expressive Empirical Mode Decomposition With Adaptive Noise (ICEEMDAN) was used to perform further decomposition on residual sequences. …”
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Heat stress has divergent effects on the milk microbiota of Holstein and Brown Swiss cows by F. Ceciliani, A. Maggiolino, F. Biscarini, Y. Dadi, L. De Matos, P. Cremonesi, V. Landi, P. De Palo, C. Lecchi

“…Under the same thermal comfort condition, milk microbiota did not discriminate between Brown Swiss and Holstein. …”
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