Characteristics of pore-fracture structure and three-dimensional spatial distribution differences in deep and shallow coal reservoirs: A case study of Junggar Basin by WANG Pengxiang, ZHANG Zhou, YU Wanying, ZOU Qiang, YANG Zhengtao

“…In contrast, the deep coal samples showed relatively isolated pore-fracture development, more complex pore development in the mesopore and macropore stages, and significant mineral filling within pores and fractures. A pore network model for the samples was established using the maximal sphere algorithm to analyze the distribution pattern, morphology, and three-dimensional structural development of the connected pores and fractures. …”
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Analysing outcome variables with floor effects due to censoring: a simulation study with longitudinal trial data by Jos Twisk, Alette Spriensma, Iris Eekhout, Michiel de Boer, Jolanda Luime, Pascal de Jong, Melike Kaya Bahçecitapar, Martijn Heymans

“…Applying traditional methods such as linear mixed models to analyse this kind of longitudinal RCT data may result in bias of the regression parameters. …”
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Shared energy storage planning based on the adjustable potential of data center based on visual IOT platform by Lei Su, Wanli Feng, Haoyu Ma, Mingjiang Wei, RuoShi Gu, Ziya Chen, Junda Qin

“…Abstract To address the challenges of low utilization and poor economic efficiency associated with decentralized energy storage configurations in data centers, this study proposes a shared energy storage planning method for data center groups based on the adjustable potential of data center based on visual IOT platform, which leverages differences and complementarities in energy storage requirements under different scenarios to minimize investment costs while maximizing operational benefit. …”
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Habitat conditions of reef-forming corals directly affect the spatial distribution and stability in fish and macroinvertebrate communities: A case study of Mischief Reef by Peng Xu, Jianfeng Gan, Lintao Huang, Danping Xie, Feilong Li, Hui Huang

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Maternal and neonatal outcomes of in-water and out-of-water births in low-obstetric-risk labour: a retrospective observational study at Piacenza hospital. by Elisa Piccolo, Giacomo Biasucci, Mariasole Magistrali, Belinda Benenati, Daniela Russo, Marina Paola Mercati, Sonia Tesoriati, Marina Cicalla, Simona Illari, Cristiana Pavesi, Maurizio Beretta, Marina Bolzoni

“…However, the literature reports conflicting data and poor-quality evidence on maternal and neonatal outcomes. …”
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Pre-Filtering SCADA Data for Enhanced Machine Learning-Based Multivariate Power Estimation in Wind Turbines by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou, Haoxuan Luo

“…Therefore, developing efficient filtering methods is crucial to improving data quality and model performance. This paper proposes a novel filtering method that integrates the control strategies of variable-speed, variable-pitch wind turbines, such as maximum-power point tracking (MPPT) and pitch angle control, with statistical distribution characteristics derived from supervisory control and data acquisition (SCADA). …”
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Numerical Simulation of Storm Surge-Induced Water Level Rise in the Bohai Sea with Adjoint Data Assimilation by Liqun Jiao, Youqi Wang, Dong Jiang, Qingrong Liu, Jing Gao, Xianqing Lv

“…This study applied an adjoint data assimilation model capable of integrating wind fields to investigate a temperate storm surge event in the Bohai Sea region during October 18 to 21, 2024. …”
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Improved Deep Convolutional Generative Adversarial Network for Data Augmentation of Gas Polyethylene Pipeline Defect Images by Zihan Zhang, Yang Wang, Nan Lin, Shengtao Ren

“…Despite this, the method also encounters the problem of scarcity of defect samples and uneven data distribution in gas pipeline defect detection. …”
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The Hidden Diet: Determining the Distribution of the Threatened Julia Creek Dunnart (Sminthopsis douglasi) Using Eastern Barn Owl (Tyto javanica delicatula) Pellets by Dana A. Lockhart, Joshua J. Bon, Cameron L. Charley, Stephen G. Kearney, Pia Schoenefuss, Emma L. Gray, Andrew M. Baker

“…Owl pellet deposit sites were chosen to encompass areas of high, medium, and low likelihood of Julia Creek dunnart occurrence based on Australian Government habitat models for the species with the goal of better understanding the species' distribution. …”
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Extreme values of ET0 at Piracicaba, Brazil, for designing irrigation systems by Verônica G. M. L. de Melo, José A. Frizzone, Leonardo L. de Melo, Antonio P. de Camargo

“…Daily data from 1990 to 2019 were used to calculate ET0 using the Penman-Monteith model. …”
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REVIEW ON FOG COMPUTING – APPLICATIONS, SECURITY, AND SOLUTIONS by Varun Varma Sangaraju, SV Achuta Rao, Amjan Shaik, Prasuna VG, Nagaraju P B S.R.K.R.

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High‐Impedance Fault Detection in Distribution Networks Based on Support Vector Machine and Wavelet Transform Approach (Case Study: Markazi Province of Iran) by Mohammad Sadegh Attar, Mohammad Reza Miveh

“…Then, DWT decomposes it to extract the features of each sample in the data set. The extracted features from this part are used as input to the SVM classification algorithm. …”
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FDDM: unsupervised medical image translation with a frequency-decoupled diffusion model by Yunxiang Li, Hua-Chieh Shao, Xiaoxue Qian, You Zhang

“…The differences between MR and CT images lie in both anatomical structures (e.g. the outlines of organs or bones) and the data distribution (e.g. intensity values and contrast within). …”
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Copula Modeling of COVID-19 Excess Mortality by Jonas Asplund, Arkady Shemyakin

“…Previously proposed ARIMA models have low lags and no residual autocorrelation. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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AN EXPERIMENTAL MODEL FOR ASSESSING THE LEVEL OF DIGITIZATION IN BEEKEEPING by Tsvetan TSVETANOV, Krasimir DIMOV, Evgeni PETKOV

“…For evaluation on the degree of digitization of the apiaries we took under consideration only what software and hardware products are used. The results showed a low degree of digitization of the studied apiaries - in 27 out of 37 studied apiaries there were no data about the use of software and hardware applications, and the average level of digitization for the studied apiaries according to the model we developed was within 8-9 %. …”
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Integrating Bayesian classification and ANN for lithofacies classification using well and seismic data: Bahregansar case study by Hessam Mansouri Siahgoli, Mohammad Ali Riahi, Majid Nabi-Bidhendi, Seyedmohsen Seyedali

“…SQp), was generated to enhance the accuracy of facies discrimination in well log data. Based on the observed lithology and petrophysical evaluation, four facies were identified: shale, carbonate, high-porosity sand, and low-porosity sand. …”
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Validating attribute hierarchies in cognitive diagnosis models by Xueqin Zhang, Yu Jiang, Tao Xin, Yanlou Liu

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Focusing on scRNA-seq-Derived T Cell-Associated Genes to Identify Prognostic Signature and Immune Microenvironment Status in Low-Grade Glioma by Jiayu Wen, Qiaoyi Huang, Jiuxiu Yao, Wei Wei, Zehui Li, Huiqin Zhang, Surui Chang, Hui Pei, Yu Cao, Hao Li

“…In addition, bulk RNA data of 975 LGG samples were collected for model construction. …”
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Leveraging snow probe data, lidar, and machine learning for snow depth estimation in complex-terrain environments by D. Liljestrand, R. Johnson, B. Neilson, P. Strong, E. Cotter

“…This study aims to generate basin-scale snow depth estimates using a multistep, Gaussian-based machine learning model that combines snow probe depth measurements with static lidar terrain features from a single snow-free date, enabling rapid, high-resolution estimation at low institutional cost. …”
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