A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…To accomplish this, the following article includes a description of a reduced order model (ROM) of an electric power grid based on a circuit model, an optimization formulation that describes the MPC, a collocation method for solving linear time-dependent differential algebraic equations (DAEs) that result from the ROM, and an overall strategy for iteratively refining the behavior of the MPC. …”
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Efficient recovery of phosphorus from phosphogypsum leachate based on struvite precipitation by MA Jingfeng, WU Xiang, FANG Haoyuan, MEI Ke, JIANG Shan, ZHU Shujing*

“…In this study, a struvite precipitation method was proposed to recover phosphorus sources from phosphogypsum and its leachate to prepare valuable percolate-based struvite crystal (PSL-S). …”
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Multi‐objective and multi‐stage low‐carbon planning of park integrated energy system considering random outages from superior power grid by Xunpu Jiang, Zhejing Bao, Jianwei Chen, Miao Yu

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The impact of spatial representation in energy transition modelling on systemwide energy return on investment by Hasret Sahin, Abebe Asfaw Solomon, Arman Aghahosseini, Christian Breyer

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Integrating the circular economy model into the management and treatment of Fischer–Tropsch effluents—a conversion of waste to energy (biogas) opportunity by Mabatho Moreroa, Thapelo P. Malematja, Grace Nkechinyere Ijoma

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Social Programs in the Structure of Expenditures of the Consolidated Budget of the Federa-tion Subject by A. S. Dmitriev, A. M. Stash

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Reducing the Break-even Time by Smart Power Managing in Data Center with Renewable Energy by somayyeh taheri, Maziar Goudarzi

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Sparse signal transmission under lossy wireless links based on double process of compressive sensing by Peng SUN, Gui-nan LI, Lian-tao WU, Zhi WANG

“…In resource-limited wireless sensor networks,links with poor quality hinder its large-scale applications seriously.Thanks to the inherent sparse property of signals in WSN,the framework of sparse signal transmission based on double process of compressive sensing was proposed,providing an insight into a new way of real-time,accurate and energy-efficient sparse signal transmission.Firstly,the random packet loss during transmission under lossy wireless links was modeled as a linear dimension-reduced measurement process of CS (a passive process of CS).Then,considering that a large packet was often adopted in WSN for higher transmission efficiency,a random linear dimension-reduced projection (a simple source coding operation) was employed at the sender node (an active process of CS) to prevent block data loss.Now,the raw signal could be recovered from the lossy data at the receiver node using CS reconstruction algorithms.Furtherly,according to the theory of CS reconstruction and the formula of packet reception rate in wireless communication,the minimum compression ratio and the maximum packet length allowed were obtained.Extensive simulations demonstrate that the reliability of data transmission and its accuracy,the data transmission volume,the transmission delay and energy consumption could be greatly optimized by means of proposed method.…”
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Enhancing access to underutilized ground water potential for improving livelihoods and conflict reduction in Kagera Sub-Basin, Tanzania by Estella Mgala, Joel Nobert, Edmund B. Mabhuye, Brown Gwambene

“…The study employed a mixed-methods approach, utilizing key informant interviews, household questionnaires, focus group discussions, direct observations, and secondary data sources. …”
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Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey by Yu Liu, Biao Sun, Yuru Wu, Yongxin Zhang, Jiahui Yang, Wen Wang, Naga Lakshmi Thotakura, Qian Liu, Yilu Liu

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Thermal Simulation in Wire Arc Additive Manufacturing of A 5356 Aluminium Single Track Deposited on 7108 Aluminium Substrate by Eman Shams, Noha Ramadan, Marwan Abdelwahed, Nahed ElMahallawy, Mohamed A Taha

“…An adapted version of Goldak’s heat source model is integrated with the material deposition strategy. …”
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High Current Accelerator-driven Neutron Sources - The HBS project for a next generation neutron facility [version 2; peer review: 3 approved, 1 approved with reservations] by Ralf Gebel, Olaf Felden, Romuald Hanslik, Andreas Lehrach, Oliver Meusel, Yannick Beßler, Holger Podlech, Thomas Gutberlet, Thomas Brückel, Johannes Baggemann, Klaus Lieutenant, Jingjing Li, Ulrich Rücker, Eric Mauerhofer, Paul Zakalek, Jörg Voigt

“…Methods A project was launched at the Jülich Centre for Neutron Science for the development, design and demonstration of such an innovative high-current accelerator driven neutron source termed “High-Brilliance neutron Source” (HBS). …”
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High Current Accelerator-driven Neutron Sources - The HBS project for a next generation neutron facility [version 3; peer review: 3 approved, 1 approved with reservations] by Ralf Gebel, Olaf Felden, Romuald Hanslik, Andreas Lehrach, Oliver Meusel, Yannick Beßler, Holger Podlech, Thomas Gutberlet, Thomas Brückel, Johannes Baggemann, Klaus Lieutenant, Jingjing Li, Ulrich Rücker, Eric Mauerhofer, Paul Zakalek, Jörg Voigt

“…Methods A project was launched at the Jülich Centre for Neutron Science for the development, design and demonstration of such an innovative high-current accelerator driven neutron source termed “High-Brilliance neutron Source” (HBS). …”
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Comparison of methods for the quantification of cell-free DNA isolated from cell culture supernatant by Abel Jacobus Bronkhorst, Vida Ungerer, Stefan Holdenrieder

“…Although these are interesting findings, it can also be a great source of experimental confusion and emphasizes the importance of method optimization and standardization. …”
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Construction of Knowledge Graph for Marine Diesel Engine Faults Based on Deep Learning Methods by Xiaohe Tian, Huibing Gan, Yanlin Liu

“…In this paper, we propose a BiLSTM-CRF-based knowledge graph construction method for ship diesel engine faults, aiming at integrating multi-source heterogeneous data through deep learning and knowledge graph technology, and mining the deep semantic associations among fault phenomena, causes, and solutions. …”
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Study on modified Whitley model with different number and various methods of forming elite individuals by N. S. Krivoshey, V. G. Kobak

“…Materials and Methods. All the algorithms implemented under the development of the software tool for solving the optimization scheduling problem are considered. …”
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Data and methods for assessing urban green infrastructure using GIS: A systematic review. by Xiaomian Wu, Jianquan Liu, Yukun Hou

“…A comprehensive review of this field clarifies the research methods, application scope, trends, and challenges associated with using GIS to advance UGI development. …”
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Computational Tool for Curve Smoothing Methods Analysis and Surface Plasmon Resonance Biosensor Characterization by Mariana Rodrigues Villarim, Andréa Willa Rodrigues Villarim, Mario Gazziro, Marco Roberto Cavallari, Diomadson Rodrigues Belfort, Oswaldo Hideo Ando Junior

“…To address these limitations, this study presents the development of an open-source computational tool to optimize SPR biosensor characterization, implemented using MATLAB App Designer (Version R2024b). …”
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Performance analysis of advanced deep learning technics: Application to solar energy forecasting and management in several cities in Chad by Osée Mounkang, Claude Vidal Aloyem Kaze, Nzoko Tayo Dieudonné, Ghislain Junior Bangoup Ntegmi, Duclair Paul Edouard Pountounynyi, Hervice Roméo Fogno Fotso, Armel Zambou Kenfack, Germaine Kenmoe Djuidje, René Tchinda

“…To achieve this, eight deep learning algorithms were used to optimize energy management. This study proposes a hybrid artificial intelligence model that combines LLM and LSTM methods, utilizing the Adam optimization algorithm to make hourly solar radiation predictions over a seven-day period. …”
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Research on adaptive motion methods of flexible knee joints based on the artificial potential field by LUO Tianhong, LI Chaoyang, MA Xiangyu, FU Qiang, FANG Shangchen

“…ObjectiveConsidering the tracking error of the motion trajectory of the flexible knee joint and the influence of the flexibility on the joint motion, an adaptive impedance control method based on the artificial potential field (APF) was proposed.MethodsThe method took the pneumatic artificial muscle as the power source, and by establishing a kinetic model between the human-machine interaction moment and the knee joint motion angular velocity, the size of the impedance control parameter could be adjusted in real time, so as to realize the following of the motion of the exoskeleton knee joint and the human leg; the control parameter was optimized using the APF concept to enhance the effect of the motion following, and the effectiveness of the algorithm was verified by simulation and test.ResultsThe results show that the proposed APF-based adaptive impedance control method enables the exoskeleton to adaptively track the human motion trajectory and can reduce the error of trajectory tracking, thus improving the suppleness of the flexible knee joint control and enhancing the human-machine synergy of the system.…”
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