Characteristics and favorable area optimization of ultra-deep high-pressure basement reservoirs: A case study of Kun 2 block in Kunteyi gas reservoir, Qaidam Basin by CAO Hui, ZHANG Guoqing, XU Li, LI Zhexiang, WANG Haicheng, ZHAO Changyang, FEI Ying

“…Overall, this demonstrated tight and low-permeability characteristics. (2) The development of dissolution pores was fault-controlled, primarily distributed along Kun 1, North Kun 2, and North Kun 101 faults. …”
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Optimisation of Integrated Heat Pump and Thermal Energy Storage Systems in Active Buildings for Community Heat Decarbonisation by Zaid Al-Atari, Rob Shipman, Mark Gillott

“…The model optimises heat pump operations in conjunction with thermal energy storage units to reduce peak demand on low-voltage networks by using real-time measured electricity demand data and modelled heat demand data for 76 houses. …”
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Effects of meteorological factors on outpatient visits for chronic rhinosinusitis in Wuhan, China (2018–2019): a time-series analysis by Xiaoli Guan, Wen Xiang, Ao Huang, Min Zhou, Ming Zeng

“…A generalized additive negative binomial regression model combined with a distributed lag non-linear model (DLNM) was employed to analyze the lag-exposure-response relationship between meteorological factors and the number of CRS outpatient visits. …”
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Climate change and topographic variations affect infestation by Xyleutes ceramica (Walker, 1865) (Lepidoptera: Cossidae) in teak plantations in Thailand by Thanapol Choochuen, Jiří Foit, Ponthep Meunpong, Warong Suksavate

“…The maximum entropy (MaxEnt) model was used to assess the effects of environmental factors and predict the occurrence probability of the species using current and projected (2050) climate data based on the Shared Socioeconomic Pathways SSP1-2.6 and SSP5-8.5 scenarios from multiple global climate models. …”
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Association between hydrometeorological conditions and hemorrhagic fever with renal syndrome in Shandong Province, China, from 2005 to 2019. by Qi Gao, Chuanlong Cheng, Hui Zuo, Rui Xi, Zhiqiang Wang, Xiujun Li

“…A spatiotemporal Bayesian hierarchical model combined with distributed lag non-linear model was applied to explore the association between climate indicators and HFRS risk over a 6-month lag. …”
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The role of extrapulmonary personalized factors in asthma control by L. V. Tribuntceva, A. V. Budnevsky, G. G. Prozorova, O. N. Choporov, S. A. Kozhevnikova, I. A. Olysheva

“…Asthma control was assessed by Asthma Control Questionnaire-5, physical activity – by the motor activity questionnaire (ODA23+), physical activity motivation – by data from the questionnaire. A linear regression model was built with the inclusion of sex, smoking, BMI, physical activity to predict the level of asthma control. …”
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Electro-mechanical coupled design of self-powered sensing systems and performances comparison through experiments by A. Somà, G. De Pasquale

“…Recent advances in low-power sensors and electronic components open to innovative strategies in structural monitoring and real-time data processing, in particular for industrial and vehicular fields. …”
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Lactylation Modification as a Promoter of Bladder Cancer: Insights from Multi-Omics Analysis by Yipeng He, Lingyan Xiang, Jingping Yuan, Honglin Yan

“…Functional enrichment analysis, tumor microenvironment analysis, and treatment response evaluation were performed on the high- and low-risk groups. Single-cell and spatial transcriptome data were used to analyze the distribution characteristics of model genes and their changes during epithelial carcinogenesis. …”
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A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Firstly, we propose a model to recognize a reduced dimensional clustering of different spectrums drawn from the imaging spectrum data sets, in order to judge whether a sample includes a feature indicating a defect or not in a low-dimensional space. …”
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Integration of Bulk and Single-Cell RNA Sequencing to Identify RNA Modifications-Related Prognostic Signature in Ovarian Cancer by Wang S, Zheng Q, Chen L

“…Prognostic genes were gained via machine learning techniques, particularly LASSO regression. A risk model was built to predict the prognosis. OC patients were divided into high-risk and low-risk groups according to risk score. …”
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A proposed basic paediatric surgical skills training course: a pilot, feasibility and outcome study towards standardisation of induction to paediatric surgery training by Mahmoud Marei Marei, Sherif Nabhan Mohamed Tawfik Kaddah, Moemen M. Farouk, Abeer Aboalazayem, Hadeer Mohamed Nasreldin, Fatima Khalid Ahmed Mohamed Ali, Hadeer Abdelwahab El-Ghareeb, Mohamed Mahmoud El-Seoudi, Mahmoud Tarek, Ahmed Ezzat Abdelnabi Arafat, Mahmoud Mohamed Assem Elfiky, Basma Magdy

“…The course included a series of didactic lectures by consultants in paediatric surgery, followed each by a hands-on session, with a 1:2 instructor-to-trainee ratio. Data were collected through post-course structured assessment questionnaires distributed to the candidates directly after the course, regarding each surgical skill and the entire content of the course. …”
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Application and realization of key technologies in China railway e-ticketing system by Xinghua Shan, Zhiqiang Zhang, Fei Ning, Shida Li, Linlin Dai

“…Design/methodology/approach – Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. …”
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Predicting biomass transportation costs: A machine learning approach for enhanced biofuel competitiveness by Ali Omidkar, Razieh Es’haghian, Hua Song

“…A pivotal component within the biofuel supply chain is the substantial financial burden associated with transporting biomass feedstocks to biorefineries for subsequent fuel production. For many low-cost or residue-based biomass feedstocks, the transportation cost represents a substantial portion of the total delivered price, often dominating the overall feedstock cost—especially when sourced from widely distributed or small-scale suppliers. …”
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A contrastive learning and knowledge distillation-based framework for efficient federated intrusion detection in IoT by Li Ma, Jicheng He, Kai Lu, Dan Wang, Long Yin, Zhaokun Li

“…KF-IDS, as an additional (but optional) subsequent step of CF-IDS, based on knowledge distillation and mutual information theory, provides a off-line IDS solution by distillating CF-IDS into lite models. Through local deployment on low-computational-power end devices, KF-IDS avoiding upload raw data to the cloud. …”
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Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007-2018. by Wanwan Sun, Xiaobo Liu, Wen Li, Zhiyuan Mao, Jimin Sun, Liang Lu

“…First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. …”
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Edge-FLGuard: A Federated Learning Framework for Real-Time Anomaly Detection in 5G-Enabled IoT Ecosystems by Manuel J. C. S. Reis

“…The rapid convergence of 5G networks and Internet of Things (IoT) technologies has unlocked unprecedented connectivity and responsiveness across smart environments—but has also amplified cybersecurity risks due to device heterogeneity, data privacy concerns, and distributed attack surfaces. …”
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The Extreme Value Support Measure Machine for Group Anomaly Detection by Lixuan An, Bernard De Baets, Stijn Luca

“…In this way, unusual group behavior with a number of points located in low-density regions is not fully detected. In this paper, we propose a systematic approach based on <i>extreme value theory</i> (EVT), a field of statistics adept at modeling the tails of a distribution where data are sparse, and <i>one-class support measure machines</i> (OCSMMs) to quantify anomalous group behavior comprehensively. …”
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Research on ecological quality and restoration of fragile mining areas in the Yellow River Basin—The case of Xiegou coal mine by Xin Sui, Yiming Sun, Xuan Wang, Jin Yuan

“…The results show that (1) the overall ecological quality of the study area shows a decreasing trend, and the change in ecological quality is closely related to urban development and coal mining. (2) The distribution of ecological quality is correlated, with high-value areas concentrated in the gently sloping vegetation areas in the south and north, and most urban and peri-urban areas are low-value areas. (3) Among the drivers of ecological quality, Net Primary Productivity mainly positively affects the central urban area and negatively affects the steep-slope areas in the north and south. …”
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Deep Ensemble Learning With Pruning for DDoS Attack Detection in IoT Networks by Makhduma F. Saiyedand, Irfan Al-Anbagi

“…The upsurge of Internet of Things (IoT) devices has increased their vulnerability to Distributed Denial of Service (DDoS) attacks. DDoS attacks have evolved into complex multi-vector threats that high-volume and low-volume attack strategies, posing challenges for detection using traditional methods. …”
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Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis by Hsiang-Ho Chen, Chieh-Wei Wu, Yen Cheng, Mao-Chieh Su, Yu-Jhen Chen, Po-Liang Lai

“…The focus is on establishing a prediction model for the structural strength of the L1 vertebral body using patient-specific CT data, thereby aiding in the prediction of vertebral fracture risk. …”
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