Research on shale lamination types and logging characterization methods: A case study of the Funing Formation Member 2 in Gaoyou Sag, Subei Basin by TANG Lei, LIAO Wenting, XIA Lianjun, MA Jie, ZHANG Juan

“…Moreover, the degree of lamination development indicated by the sedimentation rate variation correlates well with the overall proportion of lamination development obtained from thin section analysis, and is consistent with the lamination development detected by imaging logging in different intervals. …”
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Analogs of Precambrian microbial communities formed de novo in Caucasian mineral water aquifers by Daria G. Zavarzina, Alexey A. Maslov, Alexander Y. Merkel, Nataliya A. Kharitonova, Alexandra A. Klyukina, Ekaterina I. Baranovskaya, Elena A. Baydariko, Evgeniy G. Potapov, Kseniya S. Zayulina, Andrey Y. Bychkov, Nikolay A. Chernyh, Elizaveta A. Bonch-Osmolovskaya, Sergey N. Gavrilov

“…We analyzed the geological and hydrogeochemical parameters of the three aquifers and a recharge area of the YMWB and investigated their microbial communities using metagenomic and cultivation-based approaches within a long-term survey. Correlation analysis of the obtained data revealed stable and highly stratified microbial communities inhabiting four distinct ecosystems. …”
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A nomogram to predict postoperative new-onset cerebral infarction after revascularization of moyamoya disease in adults and its validation: a retrospective study by Zhen Wang, Jiacheng Yu, Yu Zhang, Jiaping Ruan, Xiaojie Liu, Sijia Ma, Jun Xie, Mimi Wu, Jinhua Bo, Yu’e Sun, Yu’e Sun

“…Its performance to predict POCI after revascularization of adult MMD was validated by calculating the area under the curve (AUC) and the decision curve analysis.ResultsUnivariate and multivariate logistic regression analyses showed that preoperative cerebral infarction (OR 2.548, 95% CI 1.357–4.787; p = 0.004), posterior cerebral artery anomalies (OR 2.106, 95% CI 1.157–3.834; p = 0.015), post-transit arterial development (OR 2.983, 95% CI 1.336–6.661; p = 0.008), pre-anesthesia mean arterial pressure > 102.830 mmHg (OR 3.329, 95% CI 1.938–5.721; p < 0.001), total operating time > 212.500 min (OR 2.256, 95% CI 1.239–4.140; p = 0.008), preoperative fibrinogen level > 2.750 g/L (OR 1.852, 95% CI 1.072–3.200; p = 0.027), and mean corpuscular hemoglobin concentration (OR 1.021, 95% CI 1.001–1.040; p = 0.038) were independent risk factors of POCI after revascularization of adult MMD. …”
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Values of heart rate variability indices recorded under conditions of active orthostasis for elite ski racers, as a reflection of sports vagotonia by D. A. Kataev, V. I. Tsirkin, A. N. Trukhin, S. I. Trukhina

“…It was found that elite skiers in all three periods (especially in the preparatory and competitive periods) are characterized by high median values of such ortho-HRV indices as TP, AMVLF, pNN50%, RRNN, RMSSD, SDNN, MxDn, and low median values of HR and SI., which, judging by the literature data, are significantly they differ from the ortho-KIG of nonathletes, novice skiers, and representatives of other sports not related to endurance development. …”
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The Causal Relationship between Inflammatory Cytokines and Liver Cirrhosis in European Descent: A Bidirectional Two-Sample Mendelian Randomization Study and the First Conclusions by Shiya Shi, Yanjie Zhou, He Zhang, Yalan Zhu, Pengjun Jiang, Chengxia Xie, Tianyu Feng, Yuping Zeng, He He, Yao Luo, Jie Chen

“…In this study, we conducted a bidirectional Mendelian randomization (MR) analysis at a summarized level to illuminate the potential causal relationship between the two variables. …”
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Optimized Motion Capture for Cricket Shot Classification Using Minimal Hardware and Machine Learning by J. Ishan Randika, Kanishka Rajamanthri, Avishka Kothalawala, Niroshan Gunawardana, Ashan Induranga, Pathum Weerakkody, Kaveendra Maduwantha, B. T. G. S. Kumara, Kaveenga Koswattage

“…The proposed model achieved an accuracy of 95% in classifying various batting shots, demonstrating the feasibility and effectiveness of the system as an economical alternative for sports motion analysis.…”
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Health impacts associated with community exposure to animal feeding operations: a protocol for a systematic review by Elizabeth A. Chatpar, Richard D. Semba, Iman Habib, Brent F. Kim, Elizabeth E. Sharp, David C. Love, Sara N. Lupolt, Andrew L. Thorne-Lyman, Lori Rosman, Joan A. Casey, Juleen Lam, Keeve E. Nachman

“…The Navigation Guide methodology will be used to conduct a risk of bias assessment. Meta-analysis for selected outcomes will be conducted if possible; other quantitative or qualitative approaches will also be utilized to summarize the outcome data.Discussion This systematic review will provide an updated assessment of the association between community exposure to animal feeding operations and the health of people living in adjacent communities.…”
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Clinical Guide Adaptation for Amalgam Waste Management in Dental Settings in Iran by Mahsa Eshrati, Fatemeh Momeniha, Nafiseh Momeni, Elham Ahmadi, Atieh Hashemian, Homa Kashani, Mojgan Alaeddini

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Journey across extrinsic tactics for power improvements of triboelectric energy harvesting beyond intrinsic materials and device structures: A concise review by Ahmed Mahfuz Tamim, Yebin Lee, Jung Hwan Park, Geon-Tae Hwang, Chang Kyu Jeong

“…Rather than concentrating solely on approaches such as material selection, surface modification, or chemical modification, this review explores various strategies for enhancing output power and power density based on solid-solid interactions and alternating current (AC) TENGs. This comprehensive analysis provides valuable insights into current developments in TENG technology, paving the way for future innovations aimed at creating high-performance, self-powered systems for next-generation applications.…”
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Multi-Objective Optimal Scheduling of Water Transmission and Distribution Channel Gate Groups Based on Machine Learning by Yiying Du, Chaoyue Zhang, Rong Wei, Li Cao, Tiantian Zhao, Wene Wang, Xiaotao Hu

“…This study develops a synergistic optimization method of multiple gates integrating hydrodynamic simulation and data-driven methods, with the goal of improving the accuracy of water distribution and regulation efficiency. …”
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Scaled‐Up Graphene Growth Through Chemical Vapor Deposition Over Large‐Area Liquid Cu Catalysts by Mahesh K. Prabhu, Christos Tsakonas, Yilei Tian, Marc deVoogd, Kees E. Kolmeijer, Anastasios Manikas, Gertjan vanBaarle, Grégory F. Schneider, Costas Galiotis, Irene M. N. Groot

“…An empirical model, developed from experimental data, reliably predicts the fastest graphene growth on large liquid Cu substrates. …”
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P75NTR activation limits CD21lo B cell subsets expansion in response to autoimmune-inducing challenges by Cong Luo, An-Hui Zha, Ru-Yi Luo, Zhao-Lan Hu, Wei-Yun Shen, Ru-Ping Dai

“…Interestingly, p75NTR deficiency led to a further expansion of CD21lo B cells and enhanced their pro-inflammatory characteristics. RNA-seq data revealed notable transcript alterations associated with CD21lo B cells, including increased Tbx21 expression. …”
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KASP Markers for Identifying Roselle (<i>Hibiscus sabdariffa</i> L.) Key Varieties Based on Genetic Polymorphisms Revealed by ddRAD-Seq by Shih-Jie Huang, Jheng-Yang Ou, Yao-Cheng Lin, Jing-Wen Chen, Kai-Yi Chen, Yu-Lin Wu, Chun-Hao Hu, Ju-Yin Lee, Jia-Wei Wu, Fu-Chiun Hsu

“…Cluster analysis of the SNP data effectively grouped varieties with similar genetic backgrounds. …”
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Cost-Effectiveness of Catheter Ablation for Rhythm Control of Atrial Fibrillation by Gord Blackhouse, Nazila Assasi, Feng Xie, Kathryn Gaebel, Kaitryn Campbell, Jeff S. Healey, Daria O'Reilly, Ron Goeree

“…At the end of the initial 12 month phase of the model, patients are classified as being in normal sinus rhythm or with AF, based on data from a meta-analysis. In the 5-year Markov phase of the model, patients are at risk of ischemic stroke each 3-month model cycle. …”
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Artificial intelligence in urban science: why does it matter? by Xinyue Ye, Tan Yigitcanlar, Michael Goodchild, Xiao Huang, Wenwen Li, Shih-Lung Shaw, Yanjie Fu, Wenjing Gong, Galen Newman

“…However, integrating artificial intelligence (AI) into urban science presents challenges, including data availability, ethical considerations, and the ‘black-box’ nature of many AI models. …”
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Vegetation Dynamics and Response to Climate Change in Yarlung Tsangpo River Basin During 1981–2020 by Fang Liu, Junlong Tang, Jing Guo, Leilei Zhang, Xuefeng Sang, Weijian Guo, Tianling Qin

“…The evapotranspiration data were corrected by combining the characteristics of the vegetation in the region in order to systematically explore the relationship between the vegetation change and climate change response in the YTRB. …”
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iSKIN: Integrated application of machine learning and Mondrian conformal prediction to detect skin sensitizers in cosmetic raw materials by Weikaixin Kong, Jie Zhu, Peipei Shan, Huiyan Ying, Tongyu Chen, Bowen Zhang, Chao Peng, Zihan Wang, Yifan Wang, Liting Huang, Suzhen Bi, Weining Ma, Zhuo Huang, Sujie Zhu, Xueyan Liu, Chun Li

“…However, with growing concerns over animal ethics and bans on such experiments globally, alternative methods like machine learning are gaining prominence for their efficiency and cost‐effectiveness. In this study, to develop a robust sensitizer detector model, we first constructed benchmark data sets using data from previous studies and a public database, then 589 sensitizers and 831 nonsensitizers were collected. …”
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Resolved Stellar Mass Estimation of Nearby Late-type Galaxies for the SPHEREx Era: Dependence on Stellar Population Synthesis Models by Jeong Hwan Lee, Minjin Kim, Taehyun Kim, Hyunjin Shim, Luis C. Ho, Ho Seong Hwang, Hyunmi Song, Dohyeong Kim, Yujin Yang, Woong-Seob Jeong

“…The upcoming all-sky infrared spectrophotometric SPHEREx mission is set to provide spatially resolved stellar mass maps of nearby galaxies, offering more detailed insights than integrated light observations. In this study, we develop a strategy for estimating stellar mass using SPHEREx by examining the dependence on different stellar population synthesis (SPS) models and proposing new scaling relations based on simulated SPHEREx data. …”
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Transformation of a Large Ancient Oil Reservoir to a Dry Gas Reservoir: A Case Study of the Kela-2 Gas Field in the Kuqa Foreland Basin, NW China by Xuesong Lu, Zhichao Yu, Keyu Liu, Mengjun Zhao, Junjia Fan, Xiaowen Guo, Qingong Zhuo, Lili Gui

“…However, the scale of the ancient oil reservoir remains unclear, as does the process by which the reservoir evolved into the present dry gas field. Here, using data from analyses of fluid inclusions, petrography, laser Raman spectroscopy, and quantitative fluorescence, the hydrocarbon accumulation history of the Kela-2 gas field is reconstructed. …”
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Fluid pressure gradient characteristics and petroleum geological significance in Shahejie Formation of Bonan Sag in Jiyang Depression by Peng LIU, Tao MENG, Fatang YAN, Zhongxin LI, Chengcheng SHAN

“…Based on drilling, logging, mud logging, seismic and geochemical analysis data, various technical methods were integrated to characterize the spatiotemporal distribution of fluid pressure gradients by mapping both paleo and present-day fluid pressures. …”
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