Short-term urban traffic forecasting in smart cities: a dynamic diffusion spatial-temporal graph convolutional network by Xiang Yin, Junyang Yu, Xiaoyu Duan, Lei Chen, Xiaoli Liang

“…Abstract Short-term traffic forecasting is an important part of intelligent transportation systems. Accurately predicting short-term traffic trends can avoid traffic congestion and plan travel routes, which is of great significance to urban management and traffic scheduling. …”
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Social media and capital markets: an interdisciplinary bibliometric analysis by Wen Long, Man Guo

“…These sample papers mainly include seven hot topics, including sentiment analysis and financial market prediction. Articles in business and finance focus more on social media’s impact on capital markets. …”
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Managing the human factor in agriculture: Motivation and control by Lapčević Goran, Nikitović Zorana

“…For agricultural systems where the human factor is not under sufficient control, that is, they have insufficiently developed organizational structure or in which it is completely lacking, self-determination theory, which is an upgrade of the Planned Behavior Theory, which provides an explanation of prediction of human behavior.…”
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Design and Construction of an Anemometer. by Mukhangu, Paul

“…Findings are expected to enhance weather prediction models, optimize wind energy systems, and facilitate a better understanding of wind patterns and their environmental impact. …”
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Research on Wood Defects Feature Imbalance Optimization and Recognition by Xiao Wang

“…Var Loss tends to decrease the fluctuation of prediction confidences, making model more robust in practical use. …”
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Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study by Daniel Tawfik, Tait D Shanafelt, Mohsen Bayati, Jochen Profit

“…We quantified EHR use using vendor-derived and investigator-derived measures, quantified burnout symptoms using emotional exhaustion and interpersonal disengagement subscales of the Stanford Professional Fulfillment Index, and used an ensemble of response propensity-weighted penalized linear regressions to develop a burnout symptom prediction model. ResultsAmong 697 surveys from 477 physicians with a response rate of 80.5% (697/866), always responders were similar to nonresponders in gender (204/340, 60% vs 38/66, 58% women; PPPPP ConclusionsEHR use measures showed limited utility for predicting burnout symptoms but allowed discrimination between responders and nonresponders. …”
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Soil Carbon Characteristics of a Fluvisol Affected by Aggregates from Two Tillage and Crop Regimes by Emmanuel Onweremadu, Frank Akamigbo, Chigozie Asiabaka

“…Aggregate size distribution was significantly (P < 0.05) influenced by tillage and crop type at 0 – 10 cm depth and soil carbon varied significantly (P < 0.05) with aggregate–size forms, tillage technique and crop species. Prediction of carbon behaviour in floodplain soils should take into consideration variability in ped forms, tillage method and crop types. …”
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Experimental investigation on flow pattern and void fraction for two-phase gas-liquid upflow in a vertical helically coiled micro-channel by Sira Saisorn, Phakkhanan Benjawun, Adirek Suriyawong, Somchai Wongwises

“…The slip ratio data explicitly showed that the annular flow tended to be highly affected by the secondary flow when compared to the throat-annular flow. The prediction based on different approaches indicated that the data aligned well with drift flux model incorporating inertia and channel orientation effects.…”
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Dynamic multiday seizure cycles and evolving rhythms in a tetanus toxin rat model of epilepsy by Parvin Zarei Eskikand, Mark J. Cook, Anthony N. Burkitt, David B. Grayden

“…One emerging area of interest is the identification of seizure cycles, including multiday patterns, which may offer insights into seizure prediction and treatment optimization. This study investigated multiday seizure cycles in a Tetanus Toxin (TT) rat model of epilepsy. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Because of the privacy concerns about the transaction data, it is essential not to leak it when training prediction models for credit card fraud analysis. Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. …”
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Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments by Jacob Wekalao, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-zahrani

“…The integration of LWLR-based optimization protocols substantially enhances prediction accuracy while reducing computational time by ≥ 85% as well as cutting down the required resources. …”
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Field Observations During the Tenth Microwave Water and Energy Balance Experiment (MicroWEX-10): from March 1, 2011 through January 5, 2012 by Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Daniel Preston, Patrick Rush, Xueyang Duan, Guanbo Chen, Robert Terwilleger, Alejandro Monsivais-Huertero, Roger De Roo, Jasmeet Judge, Ruzbeh Akbar, Mary Morris, Olivia Williams, Lindsey Marks, Courtnay Cardozo, Mahta Moghaddam, Anthony England

“… For accurate weather prediction, accurate modeling of surface hydrological processes is very important. …”
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Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

“…However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors.The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers.This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. …”
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On the assessment and reliability of political and ideological education in colleges using deep learning methods by Yongsheng Ma, Xianhui Sun, Aiqun Ma

“…This study focuses on predicting assessment scores to evaluate student performance, identify areas of vulnerability, and implement targeted interventions. …”
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Incorporating Machine Learning in Capture-Recapture Estimation of Survey Measurement Error by Maaike Walraad, Jonas Klingwort, Joep Burger

“…In particular, we study differences in prediction quality, point estimates, variance estimates, and estimates of measurement error in five years. …”
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The Enlightenment of Domestic and International Legal and Policies Related to the Sea Level Rise Adaptation by ZHANG Zefei, REN Shutong, XIA Dongdong, SHEN Xiaoying

“…By conducting an in-depth analysis from the perspectives of socialist rule of law and local legislation, we suggest that coastal local governments should strive to balance the conflicts between coastal development and environment protection under the backdrop of climate change by: a) strengthening research on local relative sea level rise prediction and its impact, b) applying research outcomes to coastal development management, c) raising public awareness about sea level rise, and d) progressively initiating the local legislative process.…”
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FusOn-pLM: a fusion oncoprotein-specific language model via adjusted rate masking by Sophia Vincoff, Shrey Goel, Kseniia Kholina, Rishab Pulugurta, Pranay Vure, Pranam Chatterjee

“…Employing a unique cosine-scheduled masked language modeling strategy, FusOn-pLM dynamically adjusts masking rates (15%–40%) to optimize feature extraction and representation quality, surpassing baseline embeddings in fusion-specific tasks, including localization, puncta formation, and disorder prediction. FusOn-pLM uniquely predicts drug-resistant mutations, providing insights for therapeutic design that anticipates resistance mechanisms. …”
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Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer by Congcong Chen, Yang Li, Yayun Gu, Qiqi Zhai, Songwei Guo, Jun Xiang, Yuan Xie, Mingxing An, Chenmeijie Li, Na Qin, Yanan Shi, Liu Yang, Jun Zhou, Xianfeng Xu, Ziye Xu, Kai Wang, Meng Zhu, Yue Jiang, Yuanlin He, Jing Xu, Rong Yin, Liang Chen, Lin Xu, Juncheng Dai, Guangfu Jin, Zhibin Hu, Cheng Wang, Hongxia Ma, Hongbing Shen

“…We developed a modified polygenic risk score using the potential causal variants from Chinese populations, improving the performance of risk prediction in 450,821 Europeans from the UK Biobank. …”
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Coal mining-induced composite damage to geological bodies and geological guarantee against damage reduction by Shuangming WANG, Qiang SUN, Xin HU, Jishi GENG, Enke HOU, Shengquan WANG, Shutao ZHOU, Qingmin SHI, Shihao YUAN, Kai CHEN, Shijie SONG

“…The purpose is to achieve transparent geological structure conditions, effective evaluation models and methods, optimized coal development models, advanced prediction of risk dynamics, and scientific strategies for geological security. …”
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Sonographic Evaluation of the Obstetric Causes of Vaginal Bleeding During the First Trimester by Naveen Reddy Bandi, Ranjan Nayak Soumya, Jena Satyaswarup, Sahu Niranjan, Das Somadatta

“…This aids the obstetrician in selecting the best treatment planning and helps with prognosis prediction, establishing an accurate diagnosis in a few clinically misdiagnosed cases.…”
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