Investigation and Application of Water-Saving Monitoring Technology in Public Institutions by WANG Kang, ZHENG Yongjie, ZHANG Zhen, TANG Yanping, SONG Wenhao, GUO Xiaoming

“…Considering the characteristics of water use and the current situation of water facilities in public institutions,this study comprehensively employs the Internet of Things (IoT),cloud deployment,databases,three-dimensional (3D) visualization,and other advanced techniques to create a water-saving reconstruction scheme with integrated software and hardware for public institutions.Therefore,a smart water management platform for public institutions is built to implement advanced water-saving concepts and improve the water management level.The main research results are as follows:① By intelligent remote monitoring equipment,the multiclass water measurement network is designed to realize the fine collection of zonal water use data;② this study designs a reconstruction scheme of water facilities and explores the utilization mode of unconventional water sources to improve the utilization efficiency of water resources;③ multiple algorithms and statistical methods are used to analyze the time series of water use data,and thus this study realizes the analysis of pipeline network leakage and damage,identification of water use anomalies,and water-saving statistical analysis,and the investigation of water use laws;④ the platform with functions of monitoring and early warning is established to achieve real-time remote monitoring of water use,statistical analysis of historical water use,and identification and warning of pipe network leakage,so as to detect water anomalies in time and save water.The research results are first applied to the construction of the water-saving institution of the Pearl River Water Resources Commission to build a benchmark for the construction of water-saving institutions in the southern region.On the basis of application experience,the comprehensively integrated monitoring technology for water-saving in public institutions is developed,which provides a new idea for public institutions to save water.…”
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Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models by Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu

“…To enhance performance, we implemented an ensemble learning strategy that incorporated a reparameterized Gompertz function, which assigned fuzzy ranks based on each model’s prediction confidence for each test case. …”
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LucaPCycle: Illuminating microbial phosphorus cycling in deep-sea cold seep sediments using protein language models by Chuwen Zhang, Yong He, Jieni Wang, Tengkai Chen, Federico Baltar, Minjie Hu, Jing Liao, Xi Xiao, Zhao-Rong Li, Xiyang Dong

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Chemometrically assisted optimization and validation of the HPLC method for the analysis of alectinib and its related impurity with measurement uncertainty evaluation and whiteness... by Serkan Levent, Abeer Elriş, Hazal Avcı, Saniye Özcan, Nafiz Öncü Can

“…This made it possible to find and measure the sources of uncertainty as well as the factors that affected the chromatographic responses. …”
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Time frequency analysis of elastic wave PSO OMP for defects in flat steel of down conductors by Jing Zhang, Wei Liu, Minghui Bao, Peng Yang, Xuhua Liu, Zhihong Fu

“…Then calculate the correlation function of the reconstructed signal echo and apply a smooth pseudo Wigner Ville distribution for time-frequency analysis. …”
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Assessing the impact of a rare synonymous variant in the <i>KNG1</i> gene on the development of hereditary angioedema by N. A. Pechnikova, Yu. V. Ostankova, M. A. Saitgalina, A. M. Bebyakov, A. A. Totolian

“…The material was a whole blood sample obtained from a woman with clinical manifestations of hereditary angioedema without a decrease in the levels and function of the C1 inhibitor. The research methods included whole exome sequencing, bioinformatic analysis of the KNG1 gene mutation using a number of databases and web resources. …”
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Bayesian Denoising Algorithm for Low SNR Photon-Counting Lidar Data via Probabilistic Parameter Optimization Based on Signal and Noise Distribution by Qi Liu, Jian Yang, Yue Ma, Wenbo Yu, Qijin Han, Zhibiao Zhou, Song Li

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An atypical presentation of autoimmune hepatitis with delayed menarche in a Nigerian adolescent: a case report by Promise Udoka Asogwa, Bruno Basil, Winifred Njideka Adiri, Nelson Ugwu, Gideon Ekene Anigbo, Evaristus Offia, Casmir Orjioke

“…It emphasizes the need for increased awareness and better diagnostic resources to improve early detection and management of autoimmune hepatitis in sub-Saharan Africa. …”
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Advances in Wearable Biosensors for Wound Healing and Infection Monitoring by Dang-Khoa Vo, Kieu The Loan Trinh

“…Wound healing is a complicated biological process that is important for restoring tissue integrity and function after injury. Infection, usually due to bacterial colonization, significantly complicates this process by hindering the course of healing and enhancing the chances of systemic complications. …”
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HIV-associated neurocognitive disorders in Africa: challenges, peculiarities, and future directions by Tobi Olajide, Evelyn Ogungbemi, Gideon Olajide, Deborah Ogundijo, Oluwanifemi Osakuade, Favour Moshood

“…This narrative review aims to elucidate the intricate relationship between HIV infection and neurocognitive function, particularly focusing on HIV-associated neurocognitive disorders (HAND), the effects of antiretroviral therapy (ART), and neuropathological changes. …”
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Secrecy Outage Analysis of Mixed RF-FSO Systems With Channel Imperfection by Hongjiang Lei, Haolun Luo, Ki-Hong Park, Zhi Ren, Gaofeng Pan, Mohamed-Slim Alouini

“…First, the cumulative distribution function and probability density function of FSO links with pointing error and two different detection technologies are derived. …”
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How to trace the origins of short-lived atmospheric species: an Arctic example by A. Da Silva, L. Marelle, J.-C. Raut, Y. Gramlich, K. Siegel, K. Siegel, S. L. Haslett, S. L. Haslett, C. Mohr, C. Mohr, J. L. Thomas

“…Knowing the exact modeled tracer emission sources in WRF-Chem enables a precise quantification of the source detection accuracy. …”
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Automated hypocenter determination of tectonic tremors in the Nankai subduction zone using convolutional neural networks combined with semblance analysis by Amane Sugii, Yoshihiro Hiramatsu, Takahiko Uchide, Kazutoshi Imanishi

“…The trained CNN model achieved high accuracy, with both precision and recall exceeding 97%, and correctly detected 96% of distant earthquakes. The probability of tectonic tremor as a function of the signal-to-noise ratio (SNR) increased steeply from 10 to 90% at an SNR of 4. …”
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An Efficient In Vitro Regeneration Protocol and the Feature of Root Induction with Phloroglucinol in <i>Paeonia ostii</i> by Keyuan Zheng, Luming Yao, Yumei Xie, Shuiyan Yu, Yonghong Hu, Mulan Zhu

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Data curation of extracellular enzyme activity spectrophotometric or fluorometric data by Niels Gudmand Christiansen, Paul Iturbe-Espinoza, Rumakanta Sapkota, Anne Winding

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Integrated assessment of soil quality and contaminant risks in salinized farmland adjacent to an oil-exploitation zone: insights from the Yellow River Delta by Xiaofan Xie, Jijin Cai, Xiaosong Yang, Hui Qiu, Yuexian Liu, Yuanxun Zhang

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Advanced signal processing algorithm for fault classification and localization in VSC-HVDC based Offshore wind farm by Rehana Perveen

“…This work provides real-time validation on the RTDS platform by the use of S-transform, Ensemble Empirical Mode Decomposition (EEMD), and SVM, for quick and reliable detection of AC/DC faults. Next for classification, features extracted through intrinsic mode function decomposed by EMD and EEMD and classified distinctly using support vector machine techniques. …”
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Evaluating LiDAR‐Derived Structural Metrics for Predicting Bee Assemblages in Managed Forests by Marissa H. Chase, Alexandra Harmon‐Threatt, Samuel F. Stickley, Brian Charles, Jennifer M. Fraterrigo

“…We investigated whether structural metrics derived from light detection and ranging (LiDAR) data could predict bee diversity and abundance, as well as bee functional trait composition within managed and unmanaged forests in the central hardwood region in southern Illinois, United States of America. …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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Maximum Entropy Principle Based on Bank Customer Account Validation Using the Spark Method by Xiaorong Qiu, Ye Xu, Yingzhong Shi, S. Kannadhasan Deepa, S. Balakumar

“…This approach will have a mapping from clustering and feature extraction to classification for accurate detection. Based on the analysis and simulation, it is observed that the proposed approach SNN-MFP has 87% accuracy and is 84.71% more functional than the classical method of using only the SNN. …”
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