Spatiotemporal Analysis of B-Value at Mount Slamet (2014–2023) by Ika Maulita, Sugito Sugito, Lusia Silfia Pulo Boli

“…These spatial patterns align with geological features, highlighting zones of intense tectonic and magmatic interactions. …”
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DyGS-SLAM: Realistic Map Reconstruction in Dynamic Scenes Based on Double-Constrained Visual SLAM by Fan Zhu, Yifan Zhao, Ziyu Chen, Chunmao Jiang, Hui Zhu, Xiaoxi Hu

“…We introduce DyGS-SLAM, a Visual SLAM system that employs dual constraints to achieve high-fidelity static map reconstruction in dynamic environments. We extract ORB features within the scene, and use open-world semantic segmentation models and multi-view geometry to construct dual constraints, forming a zero-shot dynamic information elimination module while recovering backgrounds occluded by dynamic objects. …”
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Cavernous Hemangioma of the Orbit and Its Impact on Orbital Fat by O. Yu. Yatsenko

“…We studied 36 patients with cavernous hemangioma of the orbit. CT scans were performed according to standard procedures to give axial and frontal slices. …”
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Visuospatial sequence learning without seeing. by Clive R Rosenthal, Christopher Kennard, David Soto

“…More generally, the results pose a challenge to neural models of learning to account for a previously unknown capacity of the human visual system to support the detection, learning and recognition of higher-order sequential associations under conditions where observers are unable to see the target sequence or perform responses that coincide with structure of the target sequence.…”
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Effect of Urban Road Trees on Temperature Caused by Surface Materials by Elif Bozdoğan Sert

“…Urban roads play a significant role for analyzing the complex structure of the city. The climatic features of the city provide information about the comfort of the inhabitants. …”
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Opportunities for Public Participation Influence on the Russian Waste Management Reform: Statistical Analysis by D. K. Tinyakov

“…Data for 69 constituent entities of the Russian Federation for 2018–2019 were analyzed by statistical methods (models of ordinal and logistic regressions). The results of the analysis show that civic participation was a significant factor in reform outcomes in regions with less transparent bureaucracies and in regions less dependent on the center. …”
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A pathology-attention multi-instance learning framework for multimodal classification of colorectal lesions by Fanglei Fu, Xuemei Zhang, Zhaoxuan Wang, Luxi Xie, Mingxi Fu, Jing Peng, Jianfeng Wu, Zhe Wang, Tian Guan, Yonghong He, Jin-Shun Lin, Lianghui Zhu, Wenbin Dai

“…Although deep learning has shown promise in classifying whole slide images (WSIs) in digital pathology, existing weakly supervised methods struggle to fully model the multimodal diagnostic process, which involves both visual feature analysis and pathological knowledge. …”
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Row-Column Decoupled Loss: A Probability-Based Geometric Similarity Framework for Aerial Micro-Target Detection by Xiaohui Chen, Yunzhi Ling, Lingjun Chen, Li Liu, Xuechen Cui, Ziqiang Liu, Zhenyu Wang

“…Detectors equipped with Row-Column Decoupled Loss exhibit significant performance enhancements over baseline models, achieving a peak value of 60.5 in <inline-formula> <tex-math notation="LaTeX">$AP_{0.5} $ </tex-math></inline-formula> and delivering a maximum improvement margin of 16.2 in <inline-formula> <tex-math notation="LaTeX">$AP_{0.5} $ </tex-math></inline-formula> compared to baselines.…”
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network by Ge Gao, Xu Zhang, Xiang Chen, Zhang Chen

“…The SAEN model was trained with a variety of shifted-view and masked-view feature maps, which were simulated through feature transformation operated on the original feature maps. …”
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Body roundness index, visceral adiposity index, and metabolic score for visceral fat in predicting new-onset atrial fibrillation: a UK Biobank cohort study by Yi ZHENG, Lei LIU, Xinyu ZHENG, Tong LIU, Xiaoping LI

“…Three Cox regression models were employed to investigate the longitudinal associations of the BRI, VAI, and METS-VF changes with the risk of incident new-onset AF. …”
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How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences. by Michael Moutoussis, Raymond J Dolan, Peter Dayan

“…People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person's choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person's choice variability. …”
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Artificial intelligence–enhanced mapping of the international classification of functioning, disability and health via a mobile app: a randomized controlled trial by Zhandos Kurban, Didar Khassenov, Didar Khassenov, Zhandos Burkitbaev, Sholpan Bulekbayeva, Azat Chinaliyev, Serik Bakhtiyar, Samat Saparbayev, Tokan Sultanaliyev, Ulzhalgas Zhunissova, Natalia Slivkina, Elena Titskaya, Luis Arias, Dana Aldakuatova, Gulfairus Yessenbayeva, Zhanerke Ermakhan

“…The AI demonstrated high sensitivity and specificity for common functional domains (e.g., codes 1–2), though performance decreased for rare qualifiers. The micro-averaged sensitivity and specificity were 0.806 and 0.952, respectively. …”
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The impact of technological mega trends on the development of universities in Iran; A case study of the effects of technological developments on the financing of public universitie... by Reza Naghizadeh

“…One of the main steps of research is research validation. Four features including construct validity, internal validity, external validity and reliability were validated in single case study in this research. …”
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Project quality, regulation quality by Elena Mussinelli

“…There is a conceptual and operational reversal with respect to creative, responsibly inductive design action, which experiments and innovates, putting the principles of adequate performance and compliance with needs over the criteria of formal conformity. …”
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Joint analysis of single-cell RNA sequencing and bulk transcriptome reveals the heterogeneity of the urea cycle of astrocytes in glioblastoma by Minfeng Tong, Qi Tu, Lude Wang, Huahui Chen, Xing Wan, Zhijian Xu

“…A prognostic model based on 5 feature genes (RGS4, CTSB, SERPINE2, ID1, and CALD1) was established through multivariate Cox analysis. …”
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Analysis of product range of microcontrollers for creation of elements of home automation by Oleksandr Vdovichenko, Artem Perepelitsyn

“…The tasks: to analyze a significant parameters of microcontroller for practical use; to analyze the product range and a modern manufacturers list of the most widely used microcontrollers; to analyze the main features of AVR microcontrollers; to perform an analysis of the advantages of STM32 microcontrollers; to analyze the capabilities of ESP32 microcontrollers; to perform the comparison of hardware resources of these three groups of microcontrollers. …”
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Machine Learning Reveals Aneuploidy Characteristics in Cancers: The Impact of BEX4 by Aizhong Xu, Jianjun Liu, Li Tong, Tingting Shen, Songlin Xing, Yujie Xia, Bosen Zhang, Zihao Wu, Wenkang Yuan, Anhai Yu, Zijie Kan, Wenqi Yang, Chao Zhang, Chong Zhang

“…Residual analysis indicates superior screening performance by random forest (RF). An aneuploid feature gene set with BEX4 as the core was screened to construct a Nomogram model. …”
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A detection algorithm for small surface floating objects based on improved YOLOv5s by Xusheng YUE, Jun LI, Yaohong WANG, Penghao ZHU, Zhexing WANG, Xuanhao XU

“…Method First, data augmentation was performed on the Flow-Img dataset to expand the data and avoid model overfitting. …”
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Topological Sequences Connected With Inverse Graphs of Finite Flexible Weak Inverse Property Quasigroups: An Approach From Polynomials to Machine Learning by Faizah D. Alanazi

“…Moreover, they empower models to extrapolate complex real-world data, facilitating tasks like regression, classification, optimized performance, and feature adaptation. …”
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Machine Learning Based Early Diagnosis of ADHD with SHAP Value Interpretation: A Retrospective Observational Study by Zhang X, Xiao X, Luo Y, Xiao W, Cao Y, Chang Y, Wu D, Xu H, Zhao J, Deng X, Jiang Y, Xie R, Liu Y

“…Clinical data, including complete blood count, liver and kidney function tests, blood glucose levels, serum electrolyte tests, and serum 25-dihydroxyvitamin D3 levels, were collected. Feature selection and model construction were performed using various machine learning algorithms.Results: Our results indicated that the Gradient Boosting Machine algorithm is the optimal model.Conclusion: Our machine learning analyses suggest that the Gradient Boosting Machine (GBM) model may be the optimal choice, highlighting blood beta-2 microglobulin levels, red blood cell distribution width, 25-dihydroxyvitamin D3, and the percentage of eosinophils as key predictors of ADHD risk, thereby aiding early diagnosis. …”
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