Frustration and its impact on search and rescue canines by Sally Dickinson, Erica N. Feuerbacher

“…However, SAR operations can be both physically and psychologically demanding, requiring sustained focus, endurance, and consistent performance under stressful conditions. Frustration, a form of psychological stress, arises when a dog encounters blocked access to a goal or when an expectation is violated, triggering physiological and behavioral changes that may impact performance. …”
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Millimeter Wave SAR Imaging Denoising and Classification by Combining Image-to-Image Translation With ResNet by Pham The Hien, Ic-Pyo Hong

“…Unlike conventional cGAN, we employ a ResNet-based discriminator (RbD) to effectively improve the SAR image denoising ability of the model. …”
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Prediction Models for Mortality in Patients With Moderate to Severe ARDS Treated in the ICUTake-Home Points by Katrijn Daenen, MD, Sara C.M. Stoof, MD, PhD, Hugo van Willigen, MD, Anders Boyd, PhD, Virgil A.S.H. Dalm, MD, PhD, Diederik A.M.P.J. Gommers, MD, PhD, Eric C.M. van Gorp, MD, PhD, Abraham J. Valkenburg, MD, PhD, Henrik Endeman, MD, PhD, Jilske A. Huijben, MD, PhD

“…Interpretation: Substantial variability in discrimination exists across the included models, with calibration frequently unreported. …”
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Deep and Shallow Feature Fusion in Feature Score Level for Palmprint Recognition by Yihang Wu, Junlin Hu

“…Contactless palmprint recognition offers friendly customer experience due to its ability to operate without touching the recognition device under rigid constrained conditions. Recent palmprint recognition methods have shown promising accuracy; however, there still exist some issues that need to be further studied such as the limited discrimination of the single feature and how to effectively fuse deep features and shallow features. …”
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Photovoltaic Array Fault Detection Using Ensemble Learning-Based Technique by Anshul Shekhar, M. Senthil Kumar

“…It is observed that photovoltaic array measurements such as voltage, current, power, rate of change of voltage and current over time (dV/dt and dI/dt), and change in power to voltage and current (dP/dV and dP/dI) exhibit distinct fault characteristics, making them valuable for accurate fault discrimination. The proposed model is trained using the selected photovoltaic array measurements, and its effectiveness is validated through a testing dataset, with performance indices derived from the confusion matrix. …”
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Causal Inference-Based Self-Supervised Cross-Domain Fundus Image Segmentation by Qiang Li, Qiyi Zhang, Zheqi Zhang, Hengxin Liu, Weizhi Nie

“…However, despite the development of numerous automatic segmentation models, the lack of annotations in the target domain and domain shift among datasets continue to limit their segmentation performance. To address these issues, we propose a Causal Self-Supervised Network (CSSN) that leverages self-supervised learning to enhance model performance. …”
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Quality assurance and validity of AI-generated single best answer questions by Ayla Ahmed, Ellen Kerr, Andrew O’Malley

“…Students completed the online, closed-book exams on personal devices under exam conditions that reflected summative examinations. The performance of both AI-generated and human-authored questions was evaluated, focusing on facility and discrimination index as key metrics. …”
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Semi-Supervised Learning of Statistical Models for Natural Language Understanding by Deyu Zhou, Yulan He

“…In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.…”
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Inferring pathway activity toward precise disease classification. by Eunjung Lee, Han-Yu Chuang, Jong-Won Kim, Trey Ideker, Doheon Lee

“…For each pathway, an activity level is summarized from the gene expression levels of its condition-responsive genes (CORGs), defined as the subset of genes in the pathway whose combined expression delivers optimal discriminative power for the disease phenotype. …”
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Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features by Jingna Tao, Zhongmian Zhang, Linghan Meng, Liju Zhang, Jiaqi Wang, Zhihong Li

“…Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.ResultsAll three models demonstrated excellent diagnostic performance, with random forest and XGBoost models showing marginally superior accuracy, AUC values, and sensitivity compared with the Bayesian stepwise discrimination model. …”
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Adrenergic Modulation of Cortical Gain and Sensory Processing in the Mouse Visual Cortex by Ricardo Medina-Coss y León, Elí Lezama, Inmaculada Márquez, Mario Treviño

“…Behaviorally, clonidine impaired accuracy at moderate noise levels, while atomoxetine reduced discrimination performance and increased response variability. …”
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Psychosocial factors in young patients with type 1 diabetes mellitus ? a practical approach by Evgenia Michailovna Patrakeeva, Natalya Sergeevna Novoselova, Alsu Gafurovna Zalevskaya, Irina Georgievna Rybkina

“…Psychosocial factors play a significant role in the management of young type 1 diabetes mellitus (T1DM) patients who may have difficulties in coping with their condition. DM can lead to discrimination and changes in social relationships. …”
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Fault Diagnosis Method of Planetary Gearboxes Based on LMD Permutation Entropy and BP Neural Network by Gao Sujie, Wu Shijing, Zhou Jianhua, Zheng Pan, Chen Ben, Xu Jiacai

“…Moreover, this method shows better comprehensive performance when the number of training groups changes.…”
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Spatiotemporal Interactive Learning for Cloud Removal Based on Multi-Temporal SAR–Optical Images by Chenrui Xu, Zhenfei Wang, Liang Chen, Xiangchao Meng

“…To address these challenges, a spatiotemporal feature interaction-based cloud removal method is proposed to effectively fuse SAR and optical images. Built upon a conditional generative adversarial network framework, the method incorporates three key modules: a multi-temporal spatiotemporal feature joint extraction module, a spatiotemporal information interaction module, and a spatiotemporal discriminator module. …”
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Acculturation and English writing anxiety among indigenous students of Kerala by Reshma Das M, Binu Zachariah

“…The psychological changes, the cultural shifts and the caste/class discrimination that happen in an academic environment have to be identified using proper measuring tools. …”
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Combination of the gut microbiota and clinical indicators as a potential index for differentiating idiopathic membranous nephropathy and minimal change disease by Yumin Jiang, Ting Wang, Wei Yu, Feng Wu, Ruixue Guo, Huangmin Li, Yiding Zhang, Ge Yan, Li Wang, Zhanzheng Zhao

“…We constructed a noninvasive classifier with a discrimination efficacy of 0.939 that combined the clinical data and gut microbiota information to identify IMN and MCD.Conclusions The classifier of the gut microbiota combined with clinical indicators has achieved good performance in identifying IMN and MCD, which provides a new approach for the noninvasive discrimination of different pathological types of kidney disease.…”
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Degradation Type-Aware Image Restoration for Effective Object Detection in Adverse Weather by Xiaochen Huang, Xiaofeng Wang, Qizhi Teng, Xiaohai He, Honggang Chen

“…Mainstream algorithms for adverse weather object detection enhance detection performance through image restoration methods. Nevertheless, the majority of these approaches are designed for a specific degradation scenario, making it difficult to adapt to diverse weather conditions. …”
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A hybrid approach combining Bayesian networks and logistic regression for enhancing risk assessment by Xueyuan Wei, Yingdong Dong

“…Second, these posterior probabilities serve as input features for an LR classifier, combining the BN’s dependency structure with LR’s discriminative power to predict vulnerability risk levels. …”
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Brief memory reactivations enable generalization of offline visual perceptual learning mechanisms by Taly Kondat, Yuka Sasaki, Takeo Watanabe, Nitzan Censor

“…Human participants encoded a visual discrimination task with the target stimulus at retinotopic location A. …”
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Mapping Burned Forest Areas in Western Yunnan, China, Using Multi-Source Optical Imagery Integrated with Simple Non-Iterative Clustering Segmentation and Random Forest Algorithms i... by Yue Chen, Weili Kou, Wenna Miao, Xiong Yin, Jiayue Gao, Weiyu Zhuang

“…A machine learning workflow was developed on Google Earth Engine by combining Dynamic World land cover data with official fire records, utilizing a logistic regression-based feature selection strategy and an enhanced SNIC segmentation GEOBIA framework. The performance of four classifiers (RF, SVM, KNN, CART) in burn detection was evaluated through a comparative analysis of their spectral–spatial discrimination capabilities. …”
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