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Climate change resilience of freshwater supply on small islands: Research gaps and strategies for a case study in Grand Bahama

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Journal of Hydrology: Regional Studies 2025年 59卷

作者： Imig, Anne Welsh, Kristen Klausner, Sophia Hotta, Carolina Iwane McKenzie, Zeko Perosa, Francesca Stephens, Mark Turner, Amber Thomas, John Chaves, Henrique Marinho Leite Bowen-O′Connor, Clare Moxey, Andrew Dokou, Zoi Rein, Arno Chair of Hydrogeology School of Engineering and Design Technical University of Munich Germany State Key Laboratory of Soil Pollution Control and Safety School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Small Island Sustainability Research Complex University of The Bahamas Nassau Bahamas Geosciences Department Oberlin College Oberlin OH United States Chair of Hydrology and River Basin Management School of Engineering and Design Technical University of Munich Germany Department of Earth and Biological Sciences Loma Linda University Loma Linda CA United States School of Chemistry Environmental and Life Sciences University of The Bahamas Nassau Bahamas Strata Sustainability Nassau Bahamas Watershed Management Lab EFL – School of Technology University of Brasilia DF Brasilia Brazil Centre for Education Programmes the University of Trinidad and Tobago Arima Trinidad and Tobago School of Chemistry Environmental and Life Sciences University of The Bahamas Freeport Bahamas Department of Civil Engineering College of Engineering and Computer Science California State University Sacramento CA United States

Study region: Grand Bahama island, the Commonwealth of The Bahamas. Study focus: In Grand Bahama, due to its low elevation, sea level rise and flooding during hurricane events can lead to the salinization of groundwater, which is the only source of potable water for the island. In this study, we assessed available literature of Grand Bahama's groundwater resources to identify key challenges and knowledge gaps for the protection of the potable water supply of the island. A literature review guided our assessment of various sustainable groundwater management approaches for the island. Understanding the hydrogeology and identifying strategies to maintain the freshwater lenses in Grand Bahama are key to ensure the island remains habitable. New hydrological insights for the region: Existing hydrogeological data highlight the urgent need to improve the island's water supply system and to identify safe groundwater yields to sustain its drinking water supply. Based on analysis of these data, we propose the implementation of nature-based solutions, such as managed aquifer recharge and reforestation measures, aimed at restoring the groundwater ecosystem service of freshwater supply. Moreover, we suggest wellfields should be identified in elevated areas on the island to mitigate over-wash induced saltwater intrusion in the aquifer. Furthermore, to ensure effective water supply management in Grand Bahama, it is recommended that legislation and regulations be adapted to actively involve both institutions and the public in the decision-making process. © 2025 The Authors

关键词： Climate change Freshwater lenses Groundwater resources Island sustainability Small island nations The Bahamian Archipelago

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Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit

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Complex System Modeling and Simulation 2021年第4期1卷 308-321页

作者： Changtong Wang Zhaohua Liu Hualiang Wei Lei Chen Hongqiang Zhang School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China Department of Automatic Control and Systems Engineering the University of SheffieldSheffieldS13JDUK.

Accurate wind speed prediction has been becoming an indispensable technology in system security,wind energy utilization,and power grid dispatching in recent ***,it is an arduous task to predict wind speed due to its variable and random *** the objective to enhance the performance of forecasting short-term wind speed,this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit(GRU).The time series decomposition algorithm combines the following two parts:(1)the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),and(2)wavelet packet decomposition(WPD).Firstly,the normalized wind speed time series(WSTS)are handled by CEEMDAN to gain pure fixed-frequency components and a residual *** WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw ***,GRU networks are established for all the relevant components of the signals,and the predicted wind speeds are obtained by superimposing the prediction of each *** from two case studies,adopting wind data from laboratory and wind farm,respectively,suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm,and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.

关键词： deep learning complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) gated recurrent unit(GRU) short term wavelet packet decomposition wind speed prediction

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A Fully Implantable Stimulator with Wireless Power and Data Transmission for Experimental Use in Epidural Spinal Cord Stimulation

A Fully Implantable Stimulator with Wireless Power and Data ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Qi Xu Jun Li Wenjuan Han Houlun Zhou Key Laboratory of Image Processing and Intelligent Control Department of Control Science & Engineering Huazhong University of Science & Technology Department of Anatomy Tongji medical college Huazhong University of Science & Technology

ISBN: (纸本)9781424441211

Epidural spinal cord stimulation (ESCS) combined with partial weight bearing therapy (PWBT) has been reported to facilitate recovery of functional walking for individuals after chronic incomplete spinal cord injury. This paper describes a low cost, fully implantable, advanced ESCS stimulator that can be manufactured in a research laboratory for use in small animals. The system is composed of four main parts: an external personal digital assistant (PDA), an external controller, an implantable pulse generator (IPG), lead extension and electrode. The PDA allows the experimenter to program the stimulation parameters through a user-friendly graphical interface. The external controller placed on the rat back communicates with PDA via RF telemetry. The IPG generates the biphasic charge-balanced voltage-regulated pulses, which are delivered to the bipolar electrode by the lead extension to achieve chronic ESCS in freely moving rats. A RF carrier from the Class-E amplifier in the external controller provides both data and power for the implanted circuitry through a closely coupled inductive link. The IPG is hermetically packaged using a silicon elastomer and measures 22mm×23mm×7mm with a mass of ~3.78g.

关键词： Class-E amplifier Epidural spinal cord stimulation Incomplete spinal cord injury Inductive link Rat

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Microscopic characteristics of the methane occurrence state in coal

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International Journal of Materials and Structural Integrity 2018年第1-3期12卷 151-178页

作者： Huang, Zhian Ma, Zhenzhen Yang, Rui Gao, Yukun Zhang, Yinghua Gong, Xuejiao State Key Laboratory of High-Efficient Mining and Safety of Metal Mines University of Science and Technology Beijing Ministry of Education Beijing100083 China Work Safety Key Lab on Prevention and Control of Gas and Roof Disasters for Southern Coal Mines Hunan University of Science and Technology Xiangtan411201 China Publicity Department People's Government of Sijiqing Town of Beijing Beijing100195 China

The regulation of methane occurrence is critical for gas control. Through liquid nitrogen adsorption, isothermal adsorption/desorption of methane and electrical experiments with undeformed and deformed coal, this paper studies the microscopic characteristics of methane occurrence. The results show: the median-pore-dominant deformed coal has less specific surface area and pore volume than the undeformed coal, which has mainly micropores and small pores;the deformed coal has greater methane absorption ability than the undeformed coal, and the negative influence of temperature on the former is more notable;the resistivity of deformed coal is three to seven times that of undeformed coal, and when adsorbing the resistivity of both coals decreases before being stable, whereas their dielectric constant rises first, then slightly declines. The results of the three experiments are in good accordance. The research is basic for coalbed gas and may provide a new thought for gas control. © 2018 Inderscience Enterprises Ltd.

关键词： Pore structure

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Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market

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International Economics 2019年 158卷 77-90页

作者： Boako, Gideon Tiwari, Aviral Kumar Roubaud, David School of Business Kwame Nkrumah University of Science & Technology Kumasi Ghana African Finance & Economics Consult (AFEC)– Johannesburg South Africa Department of Finance Law and Control Montpellier Business School France

In this paper, we use vine copula approaches to model the co-dependence and portfolio value-at-risk (VaR)of six cryptocurrencies using data of daily periodicity from September 2015 to June 2018. We establish evidence of strong dependencies among the virtual currencies with a dynamic dependency structure. We find that among the class of cryptocurrencies examined, Ethereum offers the best optimal and economically risk-reward trade-off subject to a no-shorting constraint for portfolio investors using the efficient frontier. Given the paucity of empirical research on the cryptocurrency markets, this paper provides new insights, which could be useful in developing dependence and risk strategies for investment and hedging purposes, especially during more volatile periods in the markets. © 2019 CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), a center for research and expertise on the world economy

关键词： Cryptocurrency Dependence Value-at-risk Vine copula

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A Novel Cutting Fluids Performance Assurance System for CNC Machine Tools

A Novel Cutting Fluids Performance Assurance System for CNC ...

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2024 International Automatic control Conference, CACS 2024

作者： Chou, You-Syuan Chen, Yi-Shiang Chiang, Fu-Yu Yang, Chen-Yen Shi, Zhe-Xun Lin, Yu-Sheng Lin, Shang-Chih Su, Shun-Feng Huang, Yennun Feng Chia University Institute of Automatic Control Engineering Taichung407 Taiwan Feng Chia University Department of Automatic Control Engineering Taichung407 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei115 Taiwan

ISBN: (纸本)9798350354904

In the CNC machine tool industry, cutting fluid is a crucial component of the machining process. Nevertheless, as the duration of cutting fluid use increases, its performance progressively deteriorates, presenting a significant challenge that necessitates resolution. This study introduces an innovative intelligent monitoring system designed to optimize the preparation of cutting fluid in CNC machine tools. The aim is to extend the fluid's service life, mitigate tool wear, and address issues arising from fluid degradation. The system integrates a heating plate, sensors, pumping motors, and embedded systems to monitor and manage the cutting fluid effectively. Testing was conducted using a customdesigned container, and data analysis identified the optimal supply strategy, thereby extending the usable lifespan of the cutting fluid. This system enhances production longevity and allows for the configuration of containers with appropriate capacities based on specific requirements, ensuring consistent and high-quality production. © 2024 IEEE.

关键词： Cutting fluids

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Predicting Hospital Admission for Emergency department Patients: A Machine Learning Approach

Predicting Hospital Admission for Emergency Department Patie...

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作者： Feretzakis, Georgios Sakagianni, Aikaterini Loupelis, Evangelos Karlis, Georgios Kalles, Dimitris Tzelves, Lazaros Chatzikyriakou, Rea Trakas, Nikolaos Petropoulou, Stavroula Tika, Aikaterini Rakopoulou, Zoi Dalainas, Ilias Kaldis, Vasileios School of Science and Technology Hellenic Open University Patras Greece Department of Quality Control Research and Continuing Education Sismanogleio General Hospital Marousi Greece IT Department Sismanogleio General Hospital Marousi Greece

ISBN: (纸本)9781643682501

The objective of this study was to establish a machine learning model and to evaluate its predictive capability of admission to the hospital. This observational retrospective study included 3204 emergency department visits to a public tertiary care hospital in Greece from 14 March to 4 May 2019. We investigated biochemical markers and coagulation tests that are routinely checked in patients visiting the Emergency department (ED) in relation to the ED outcome (admission or discharge). Among the most popular classification techniques of the scikit-learn library through a 10-fold cross-validation approach, a GaussianNB model outperformed other models with respect to the area under the receiver operating characteristic curve. © 2022 The authors and IOS Press.

关键词： Machine learning

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Comparison of black box implementations of two algorithms of processing of NMR spectra, Gaussian mixture model and singular value decomposition 8

Comparison of black box implementations of two algorithms of...

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8th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2015

作者： Staniszewski, M. Binczyk, F. Skorupa, A. Boguszewicz, L. Sokol, M. Polanska, J. Polanski, A. Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Institute of Informatics Akademicka 16 Gliwice Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Institute of Automatic Control Akademicka 16 Gliwice Poland Maria Skodowska-Curie Memorial Cancer Center Institute of Oncology Gliwice Branch Department of Medical Physics ul. Wybrzeze Armii Krajowej Gliwice Poland

ISBN: (纸本)9789897580697

Analysis of NMR spectra is a multi-stage computational process performed with the use of appropriately chosen sequence of algorithms. Initial stages of this process, called pre-processing, including filtering, baseline correction, phase correction and removal of unwanted components, are aimed at improving the quality of NMR spectral signal by rejection of noise, removing unnecessary spectral components and irregularities. After pre-processing the basic operations on NMR spectra are aimed at estimation of levels of certain metabolites by analysis of appropriate structural properties of NMR spectral signals. In this paper authors present design and implementation of two signals modelling methods. The first one is based on singular value decomposition of the induction decay signal. The second is done with use of mixture model constructed for frequency spectrum. Authors present all assumption that need to be satisfied and processing steps that must be performed before final analysis. The methods studied in the paper are implemented under the black-box assumption;i.e., prior knowledge of parameters of metabolites in the spectra is not used. As a second part of the project authors present a comparison of obtained result with popular modelling techniques and software LCmodel and Tarquin, based on experimental phantom dataset. Comparisons between different methods are based on the commonly used quality indexes, mean squared errors corresponding to levels of detected metabolites and specificities and sensitivities of the process of detection of metabolites. Using the presented comparisons we authors are able to characterize advantages and drawbacks of the studied approaches.

关键词： Metabolites

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Linear Model Predictive control for Hammerstein System with Unknown Nonlinearities *

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IFAC Proceedings Volumes 2013年第13期46卷 302-306页

作者： Haokun Wang Jun Zhao Zuhua Xu Zhijiang Shao State Key Laboratory of Industrial Control Technology Department of Control Science and Engineering Zhejiang University Hangzhou 310027 China

A linear model predictive control (MPC) scheme for Hammerstein system with unknown nonlinearities is presented. The Hammerstein model is firstly transformed into a linear system with unknown input, and then a minimum variance unbiased (MVU) filter is used to estimate the state and the unknown input. This approach does not need prior knowledge of the nonlinearities in Hammerstein model, and the nonlinear block is treated as a black box. This enables the design of the MPC system remains in a linear framework. Compared with the existing approaches, the proposed method has the advantage of simple implementation and low online computational cost. It is shown that offset-free control can be guaranteed in the presence of asymptotically constant disturbances. An example is given to demonstrate the effectiveness of the proposed approach.

关键词： Model predictive control Hammerstein system Unknown nonlinearities Minimum variance unbiased filter Unknown input estimation Offset-free control

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An Efficient Fusion Algorithm on Conflicting Evidence

An Efficient Fusion Algorithm on Conflicting Evidence

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International Conference on Computer and Information science (ACIS)

作者： Jinyuan Yang Xinhan Huang Min Wang Department of Control Science & Engineering Hubei Normal University Huangshi China Department of Control Science & Engineering Huazhong University of Science and Technology Wuhan China

DSmT would resolve the issue of evidence portfolios when the high conflict of evidences appeared. But the computation oversized more easily because more focus elements were additional in the DSmT rules. And the fusion result was worse than that of DST when the low conflict situation was occurred. In order to efficiently combine high conflicting evidences, an improved fusion algorithm on conflict evidence is proposed. The method uses conflict mass as a basis for judgment in conflict situations. DST rules are adopted when conflict mass is lower. And DSmT fusion algorithm was adopted while opposition. During the switch between DST and DSmT, a mutual belief degree and support degree of the evidence is calculated firstly. Then the weight is obtained. Finally the conflict mass redistributed to every focus element weightily. Compared with the exist methods, this new algorithm has the advantage of better performance and more rational.

关键词： Switches Information science Portfolios Explosions

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