Acute administration of lovastatin had no pronounced effect on motor abilities, motor coordination, gait nor simple cognition in a mouse model of Angelman syndrome by Timothy A. Fenton, Stela P. Petkova, Anna Adhikari, Jill L. Silverman

“…Metrics of gait, as well as motor coordination and motor learning in rotarod, previously observed to be impaired in AS mice, were not improved by lovastatin treatment. …”
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Deep sea spy: An online citizen science annotation platform for science and ocean literacy by Marjolaine Matabos, Pierre Cottais, Riwan Leroux, Yannick Cenatiempo, Charlotte Gasne-Destaville, Nicolas Roullet, Jozée Sarrazin, Julie Tourolle, Catherine Borremans

“…An agreement rate of 0.4 (i.e., 4 out of 10 participants detecting one given individual) was established as an efficient threshold to reach counts similar to that obtained from an expert. …”
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The ethics of data mining in healthcare: challenges, frameworks, and future directions by Mohamed Mustaf Ahmed, Olalekan John Okesanya, Majd Oweidat, Zhinya Kawa Othman, Shuaibu Saidu Musa, Don Eliseo Lucero-Prisno III

“…Technical safeguards must blend differential privacy (with empirically validated noise budgets), homomorphic encryption for high-value queries, and federated learning to maintain the locality of raw data. Governance frameworks must also mandate routine bias and robust audits and harmonized penalties for non-compliance. …”
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A radiomics-based interpretable model integrating delayed-phase CT and clinical features for predicting the pathological grade of appendiceal pseudomyxoma peritonei by Dong Bai, Guanjun Shi, Yuanzi Liang, Fang Li, Zhuozhao Zheng, Zhiqun Wang

“…DCA confirmed greater clinical utility across most threshold probabilities, with favorable Brier scores (training:0.124; testing:0.142) indicating excellent calibration. …”
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Abnormal Operation Detection of Automated Orchard Irrigation System Actuators by Power Consumption Level by Shahriar Ahmed, Md Nasim Reza, Md Rejaul Karim, Hongbin Jin, Heetae Kim, Sun-Ok Chung

“…Commercial current sensors measured actuator power consumption, enabling the identification of normal and abnormal operations by applying threshold values to distinguish activation and deactivation states. …”
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Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

“…Fusion of low- and high-level features facilitates final class distinction, with soft thresholding mitigating misclassification issues. A region-based similarity measurement enhances matching percentages. …”
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Methods for Extracting Fractional Vegetation Cover from Differentiated Scenarios Based on Unmanned Aerial Vehicle Imagery by Changning Sun, Yonggang Ma, Heng Pan, Qingxue Wang, Jiali Guo, Na Li, Hong Ran

“…In this paper, based on 12 UAV visible light images in differentiated scenarios in the Ebinur Lake basin, Xinjiang, China, various methods are used for high-precision FVC estimation: Otsu’s thresholding method combined with 12 Visible Vegetation Indices (abbreviated as Otsu-VVIs) (excess green index, excess red index, excess red minus green index, normalized green–red difference index, normalized green–blue difference index, red–green ratio index, color index of vegetation extraction, visible-band-modified soil-adjusted vegetation index, excess green minus red index, modified green–red vegetation index, red–green–blue vegetation index, visible-band difference vegetation index), color space method (red, green, blue, hue, saturation, value, lightness, ‘a’ (Green–Red component), and ‘b’ (Blue–Yellow component)), linear mixing model (LMM), and two machine learning algorithms (a support vector machine and a neural network). …”
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Spatial features of tumor-infiltrating lymphocytes in primary lesions of lung adenocarcinoma predict lymph node metastasis by Huibo Zhang, Ming Luo, Junwei Feng, Juan Tan, Yan Jiang, Dmitrij Frishman, Yang Liu

“…Hot spot analysis and deep learning-based feature extraction followed by K-means clustering were applied to identify and characterize spatial TIL clusters (sTILCs) from the global TIL maps. …”
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Urban Land Use Classification Model Fusing Multimodal Deep Features by Yougui Ren, Zhiwei Xie, Shuaizhi Zhai

“…The adaptive KNN graph construction method achieves accuracy comparable to that of the empirical threshold method. This study enables accurate large-scale urban land use classification with reduced manual intervention, improving urban planning efficiency. …”
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Synthesis and characterization of hematite nanomaterials imprinted with acetone, ethanol and methanol for AI-Based IoT gas sensor arrays by Rana M. Abdelghani, Abd El-Hady B. Kashyout, Iman Morsi, Taha Elsayed Taha, Naglaa F. Soliman, Walid El-Shafai

“…To enhance the accuracy and reliability of gas detection, artificial intelligence (AI) algorithms were employed to analyze sensor data, enabling precise gas concentration monitoring and issuing alerts when predefined threshold levels are exceeded. The dataset, obtained from sensor responses to different concentrations of acetone, ethanol, and methanol, was analyzed using multiple hybrid machine learning models, including CNN-LSTM, PCA-CNN-LSTM, PCA-XGBoost, Random Forest (RF), RF-GB, RF-GB-NN, and KNN. …”
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Fracture identification and 3D reconstruction of coal-rock combinations based on VRA-UNet network by Dengke WANG, Longhang WANG, Yaguang QIN, Le WEI, Tanggen CAO, Wenrui LI, Lu LI, Xu CHEN, Yuling XIA

“…In the 3D reconstruction of coal-rock combinations fractures, in response to the problem that traditional threshold segmentation methods cannot accurately determine the threshold size between coal and rock, resulting in poor fracture segmentation performance, a new VRA-UNet coal-rock combinations fracture identification model based on deep learning theory is proposed, providing an optimized solution for accurate identification of coal-rock combinations fractures. …”
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Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest by Qiang Wu, Qiang Wu, Fang Zhang, Yuchang Fei, Zhenfen Sima, Shanshan Gong, Qifeng Tong, Qingchuan Jiao, Hao Wu, Jianqiu Gong, Jianqiu Gong

“…ObjectiveIn this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP.MethodsData of 332 stroke patients admitted to a tertiary hospital in Zhejiang Province from January 2022 to January 2023 were collected. …”
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Deconvolution of cell types and states in spatial multiomics utilizing TACIT by Khoa L. A. Huynh, Katarzyna M. Tyc, Bruno F. Matuck, Quinn T. Easter, Aditya Pratapa, Nikhil V. Kumar, Paola Pérez, Rachel J. Kulchar, Thomas J. F. Pranzatelli, Deiziane de Souza, Theresa M. Weaver, Xufeng Qu, Luiz Alberto Valente Soares Junior, Marisa Dolhnokoff, David E. Kleiner, Stephen M. Hewitt, Luiz Fernando Ferraz da Silva, Vanderson Geraldo Rocha, Blake M. Warner, Kevin M. Byrd, Jinze Liu

“…TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. …”
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Loss aversion and evidence accumulation in short-video addiction: A behavioral and neuroimaging investigation by Chang Liu, Jinlian Wang, Hanbing Li, Qianyi Shangguan, Weipeng Jin, Wenwei Zhu, Pinchun Wang, Xuyi Chen, Qiang Wang

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Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson’s Disease by Guangying Pei, Mengxuan Hu, Jian Ouyang, Zhaohui Jin, Kexin Wang, Detao Meng, Yixuan Wang, Keke Chen, Li Wang, Li-Zhi Cao, Shintaro Funahashi, Tianyi Yan, Boyan Fang

“…The identified brain spatiotemporal neural markers were validated using machine learning models to assess the efficacy of MIRT in motor rehabilitation for PD patients, achieving an average accuracy rate of 86%. …”
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Development of a single-center predictive model for conventional in vitro fertilization outcomes excluding total fertilization failure: implications for protocol selection by Hai Wang, Haojie Pan, Zitong Xu, Xianjue Zheng, Shuqi Xia, Jiayong Zheng

“…Decision curve analysis confirmed clinical utility at threshold probabilities between 0.05 and 0.60. Conclusions The logistic regression-based prediction model exhibits robust performance in assessing c-IVF fertilization failure risk. …”
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Association between long-term exposure to PM2.5 and thyroid nodules in school-aged children and adolescents: a cross-sectional study in Eastern China by Mao Liu, Pei-hua Wang, Yun-jie Ye, Li Shang, Yu-ting Xia, Yang Wang, Zhen Ding, Yan Xu

“…Annual PM2.5 concentrations were estimated by a satellite based space-time model based on machine learning. Individual exposure concentrations were assigned according to the school addresses of the participants. …”
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SAR Small Ship Detection Based on Enhanced YOLO Network by Tianyue Guan, Sheng Chang, Chunle Wang, Xiaoxue Jia

“…Since the rise of deep learning, ship detection in synthetic aperture radar (SAR) images has achieved significant progress. …”
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Predicting cutoff L-shells of solar protons using the GPPSn particle dataset by Yue Chen, Steven K. Morley, Matthew R. Carver, Andrew S. Hoover, Cordell J. Delzer, Katherine E. Gattiker, Elizabeth C. Auden

“…Therefore, the L-profiles of ∼10s–100 MeV solar protons and their associated cutoff L-shells can be determined from the GPPSn dataset, using predefined threshold proton flux values rather than traditional flux ratios. …”
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Postpartum depression in Northeastern China: a cross-sectional study 6 weeks after giving birth by XuDong Huang, LiFeng Zhang, ChenYang Zhang, Jing Li, ChenYang Li

“…Key risk factors were identified through machine learning techniques, including LASSO regression and the Boruta algorithm, and their associations were evaluated using logistic regression. …”
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