bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bi- level optimal configuration of hybrid energy storage for wind farms considering battery life
Authors: Wang Peng , Zhang Fuhua , Chen Qinghui 
Published: April 2022

Abstract
In the planning of hybrid energy storage in wind farms, considering the service life of the battery in the operation stage, a bi-level optimal configuration method of hybrid energy storage in wind farms considering the service life of the battery is proposed. The upper optimization model takes the optimal energy storage configuration cost as the goal, takes the configuration power and capacity of battery and supercapacitor as variables, and takes the configuration power and capacity of battery and supercapacitor satisfying their respective energy storage power instruction sequence as the constraint condition. The lower optimization model takes the maximum service life of the battery in the running stage as the goal, takes the power instruction sequence of the battery and the super-capacitor as variables, and takes the battery and supercapacitor power instruction sequence not exceeding the limit as the constraint condition. The upper optimization model is solved by the linear programming method, and the lower optimization model is solved by particle swarm optimization algorithm. Finally, the proposed method is compared with the energy storage configuration method based on frequency band demarcation. The results show that the proposed method can reduce the cost of energy storage configuration during planning and prolong the service life of the battery during operation.
Topology Optimization and Material Selection of Cooling Fin Structure in Submarine Data Center
Authors: Hao Guancheng , Jin Jianxiang , Zhong Chenghao 
Published: April 2022

Abstract
The optimization of fin heat dissipation structure has always been an interesting topic, and a good heat dissipation structure is conducive to the full function of electronic devices. In order to obtain the best heat dissipation structure, the COMSOL density penalty method and heat conduction model are adopted to study the topology optimization model of heat dissipation structure. On the basis of circular fins, the material types of fins are kept unchanged, and the optimized fins are obtained after topology optimization under various working conditions. The contact area and average temperature of the topological fin and circular fin are compared. The simulation results show that the topology fin has better heat dissipation performance when the heat source power and ambient temperature are similar. Compared with the circular fin profile, the contact length of the topological fin increases by 48%, and the average temperature is reduced by 14.7K. After obtaining the best heat dissipation structure, the entropy weight method is adopted to select the best heat dissipation material of heat dissipation fins and determine that the best heat dissipation material is lead.
Research on the Operation Specification of Arc Suppression and Resonance Elimination Device in Water Supply Distribution System
Authors: Shen Jie , Sun Jianwei , Wang Zheming , Zhao Wenbin , Miao Jing , Wu Yunfei 
Published: April 2022

Abstract
Arc suppression and resonance elimination device was used more and more widely in distribution power systems. The performance for limiting overvoltage and eliminating arc are better than arc suppression coil. But when the device not work properly,it would cause more great risk on the safe of the distribution network. It was analysed that an event of power failure of pair circuits distribution network installed with arc suppression and resonance elimination device. As an example, the simulation model was established with PSCAD software, and the working mechanism of the device was discussed. The overvoltage risk of the distribution system for water supply pump station was analysed. According to the analysing results, it is proposed that routine maintenance method and typical configuration of the device.
Study on layer system complementarity technology in Block N
Authors: Tang Yan 
Published: April 2022

Abstract
In view of the low permeability of oil reservoir, poor physical properties of crude oil, narrow strip development of channel sand, scattered development of plane sand body and serious heterogeneity in block n, there are some problems in water drive development, such as low well pattern control, low oil production rate, fast water cut rise rate and large production decline, the ideal stimulation effect can not be achieved by conventional measures, which restricts the potential of the block. In block n, 9 water injection wells and 16 production wells are selected to carry out layer series complementarity. Through the layer series complementarity of infill wells and basic well pattern, the well spacing is reduced, the injection production relationship of narrow sand body is improved, the water drive control degree and multidirectional connectivity ratio are improved, and the feasibility of improving the water drive development effect of block n is improved. In this paper, through the analysis of various remaining oil distribution types, the hole filling mode is optimized, so as to obtain better social and economic benefits.
A Novel Protection Scheme for Outgoing Line Fault of AC Transmission Line near the Inverter Station of AC/DC Hybrid Power Grid based on AC Filter Characteristics
Authors: Yang Lin , Wen Minghao , Chen Yu , Wang Xingzhu 
Published: April 2022

Abstract
Compared with traditional AC power grid, the fault characteristics of the AC/DC hybrid power grid are more complex and variable. Hence there is a problem of incorrect action for the fault detection elements used in traditional AC power grid which comes up when an outgoing line fault occurs on the AC transmission line in the vicinity of the inverter station. To distinguish the fault direction under the aforementioned situation, a directional protection scheme based on the characteristics of the AC filter is proposed in this paper. Considering the information can be measured by AC line relay, a method for estimating the current provided by the AC filter is given during an outgoing line fault. According to the difference of current characteristics between forward and reverse fault, the fault direction can be judged based on waveform similarity among the currents provided by the AC filter and measured by the AC line relay. Finally, a simulation model is built on the PSCAD/EMTDC platform for extensive performance evaluation. The reliability and effectiveness of the protection scheme are verified under different cases.
Recent Advances on Distributed Dispatching and Control Algorithms in Virtual Power Plant
Authors: Liu Hong , Li Zhiwei , Liu Pengde , Cheng Qing , Ji Yajuan , Qu Jiping 
Published: April 2022

Abstract
In recent years, the concept of Virtual Power Plant (VPP) is becoming more and more popular due to its capability of aggregating Distributed Energy Resources (DERs) and exploring its potential of providing flexibility to the existing power grid. Distributed algorithms have several potential advantages over centralized approaches, such as sharing limited amounts of information, performing parallel computations, and having strong robustness. In this context, this paper surveys the literature of distributed algorithms regarding VPP applications. Firstly, we established the VPP framework and operation control modes. Secondly, the basic distributed algorithms were given. Then, this paper studied distributed algorithms in VPP for economic dispatch, bidding optimization, autonomous control strategy within VPP, coordinated control strategy among muti-VPP, and interactive control strategy with grid side. Finally, the key issues and research potential were analyzed.
Research on the Access Capacity of Power System to Electric Vehicles Under Battery Swapping Modes
Authors: Cheng Jinmin , Xu Chao , Wang Weiyuan , Liu Boliang , Dou Fei , Gao Yifan , Xu Yiqing 
Published: April 2022

Abstract
In view of the access capacity of the power system to electric vehicles, not only whether the power generation side can meet the load demand of electric vehicles shall be considered, but also the changes in voltage quality, capacity of lines and transformers, short-circuit current after electric vehicles accessed shall be comprehensively taken into account. Considering the electric vehicles supplement energy by swapping batteries, in a multi-objective optimization method, through the service capacity analysis of charging stations and combined with economic indicators, an improved particle swarm optimization algorithm with mutation operator was applied, and a calculation method for maximum number of electric vehicles in power system was proposed. Finally, simulation for the power system of a certain district was performed, the maximum electric vehicle capacity that can be accessed to the power system was calculated, and the corresponding site selection of centralized charging stations and charging & battery swapping stations were given.
Test and simulation of primary frequency regulation of 600MW sub-critical thermal power units with wide load operation
Authors: Zhang Chunlei , Zhu Longfei , Yu Dahai , Si Paiyou , Liu Shuangbai , Mei Long , Zhao Ting , Zhang Jing , Zhang Tao , Hu Yuou 
Published: April 2022

Abstract
To reveal the performance of primary frequency regulation of the 600MW sub-critical thermal power units in a wide load range and accurately simulate the process, the primary frequency regulation performance of a 600MW sub-critical thermal power unit was studied with a wide load ranging from 20% to 90% under rated conditions. The model of steam turbine in BPA was modified in consideration of steam pressure and the valve throttling effect. The primary frequency regulation performance of the unit was simulated with the modified model. The research results show that the primary frequency regulation performance of the thermal power unit is poor at low load and the results of simulation with the modified model are highly consistent with the tested data due to consideration of steam pressure and valve throttling effect, meaning that the model can be used to simulate the primary frequency regulation of the thermal power unit with wide load operation accurately.
Coupling optimization model of hydropower station power dispatching based on complex dispatching constraints and cascade joint commissioning
Authors: Xie Liang , Zhang Feng 
Published: April 2022

Abstract
In order to increase the average power generation of a hydropower station and reduce its water consumption, this paper proposes a hydropower dispatching coupling optimization model based on complex dispatch constraints and cascade-connected dispatching. The power generation water consumption and the remaining load of the power grid are used as the objective function to construct a power dispatch coupling optimization model. After all the constraints are met to solve the objective function, the improved genetic algorithm and the coupling constraint adjustment strategy are combined to form a hybrid search method to realize the genetic operation. The strategy is improved to complete the optimization of power dispatch. The experimental results show that the above model can effectively realize the optimization of power dispatch and increase the average power generation of hydropower stations. It is hoped that the model can reasonably optimize the power dispatch during the flood season and the dry season, thereby effectively reducing the water consumption of the cascade and increasing the power generation of the cascade.
Research on the Method of Improving the Current-carrying Capacity of Power Cable
Authors: Tang Jipeng , Fang Xiangyang , Luo Xiqun , Qin Tao , Yang Tao , Ma Congzhi , Zhang Yong 
Published: April 2022

Abstract
The inadvertent current carrying capacity of power cable is bound to be affected by many factors, such as air temperature, ground temperature, backfill sand, soil covering depth, grounding mode, soil thermal resistance coefficient, number of circuits, ventilation design, laying mode, groundwater, metal sheath circulation, layout mode, solar radiation, surrounding heat source . This paper analyzes the common factors in the work, and expounds the mode of flow promotion through the analysis and numerical calculation of power cable ampacity. It also compares the effects of the two methods, hoping to provide new ideas for the follow-up research on related issues.
Operation control and capacity configuration optimization of CCHP system based on high temperature phase change heat storage
Authors: Xu GuiZhi , Ma MeiXiu , Hu Xiao , Chen Mengdong , Yao Wenzhuo , Zhang Kang , Lv Hongkun , Ding Liwei 
Published: April 2022

Abstract
The existing regional integrated energy system with thermal storage electric boiler as the main body cannot solve the cooling problem. In this paper, LiBr refrigerators were added on its basis to realize an energy supply mode that integrates heating and cooling. Established a multi-party win-win mechanism to ensure the minimum risk and obtain the maximum benefit. The results shown that the power grid load reduction ratios in winter and summer were 39% and 31%, respectively. When the subsidy price was 0.1CNY/kWh, the spending gap between sensitive and insensitive users reached 40%. A case of 100 office buildings in Beijing shown that the optimal capacity of phase change heat storage was 80MWh.
Development of a direct-sampling RF receiver for precision beam charge measurements in the MOLLER experiment
Authors: Mei Y. , Li S. , Arrington J. , Camilleri J. , Cuda A. , Egelhoff J. , Kolomensky Yu.G. , Sichtermann E.P. 
Published: April 2022

Abstract
We have developed and tested a direct-sampling RF receiver
capable of measuring the amplitude of a 1497 MHz sinusoidal beam
signal in 0.5 ms integration windows with a relative uncertainty of
better than 10 parts per million. The receiver is intended for
measuring signals from beam current monitoring cavities on the
beamline of the Continuous Electron Beam Accelerator Facility
(CEBAF) at Jefferson Lab. The beam signal strength, frequency, and
integration window fulfill the thus far unmet requirements of the
upcoming MOLLER experiment to measure the beam charge for different
helicity states.
Afforestation affects rain-on-snow climatology over Norway
Authors: Mooney P A , Lee H 
Published: April 2022

Abstract
Rain-on-snow (ROS) events are most commonly found in sub-polar and alpine climates where they pose a considerable threat to society and nature. While the relationship between ROS frequency and large-scale climate features have been identified, little is known about the role of localised factors, such as land cover, in ROS frequency. Importantly, the impact of future land cover changes, such as afforestation, on ROS frequency is also unknown. In this study, we use gridded observational products and kilometer-scale regional climate simulations to investigate the comparative roles of forests and open spaces in ROS frequency, and to identify the impact of afforestation on ROS frequency. The seNorge gridded observational products generally show that evergreen forests have a higher ROS frequency than open spaces despite the large discrepancies in land cover between different datasets. The observed behaviour was well simulated by a regional climate model, albeit with a more pronounced difference between ROS frequency in forests and open spaces. Model-based results show that future changes in ROS frequency are larger in evergreen forests than in open spaces, and afforestation will increase the frequency of ROS events. Our results demonstrate the relationship between land cover and ROS frequency, and highlight the need to include unique features of the local climate system, such as ROS events, in studies on climate and land use land cover change. Importantly, our study shows that afforestation policies in sub-polar and alpine regions should carefully consider the impacts of such policies on ROS frequency and the downstream consequences for society and nature.
Winding number statistics of a parametric chiral unitary random matrix ensemble*
Authors: Braun Petr , Hahn Nico , Waltner Daniel , Gat Omri , Guhr Thomas 
Published: April 2022

Abstract
The winding number is a concept in complex analysis which has, in the presence of chiral symmetry, a physics interpretation as the topological index belonging to gapped phases of fermions. We study statistical properties of this topological quantity. To this end, we set up a random matrix model for a chiral unitary system with a parametric dependence. We analytically calculate the discrete probability distribution of the winding numbers, as well as the parametric correlations functions of the winding number density. Moreover, we address aspects of universality for the two-point function of the winding number density by identifying a proper unfolding procedure. We conjecture the unfolded two-point function to be universal.
Boost-RS: boosted embeddings for recommender systems and its application to enzyme–substrate interaction prediction
Authors: Li Xinmeng , Liu Li-Ping , Hassoun Soha 
Published: April 2022

Abstract

Motivation
Despite experimental and curation efforts, the extent of enzyme promiscuity on substrates continues to be largely unexplored and under documented. Providing computational tools for the exploration of the enzyme–substrate interaction space can expedite experimentation and benefit applications such as constructing synthesis pathways for novel biomolecules, identifying products of metabolism on ingested compounds, and elucidating xenobiotic metabolism. Recommender systems (RS), which are currently unexplored for the enzyme–substrate interaction prediction problem, can be utilized to provide enzyme recommendations for substrates, and vice versa. The performance of Collaborative-Filtering (CF) RSs; however, hinges on the quality of embedding vectors of users and items (enzymes and substrates in our case). Importantly, enhancing CF embeddings with heterogeneous auxiliary data, specially relational data (e.g. hierarchical, pairwise or groupings), remains a challenge.

Results
We propose an innovative general RS framework, termed Boost-RS that enhances RS performance by ‘boosting’ embedding vectors through auxiliary data. Specifically, Boost-RS is trained and dynamically tuned on multiple relevant auxiliary learning tasks Boost-RS utilizes contrastive learning tasks to exploit relational data. To show the efficacy of Boost-RS for the enzyme–substrate prediction interaction problem, we apply the Boost-RS framework to several baseline CF models. We show that each of our auxiliary tasks boosts learning of the embedding vectors, and that contrastive learning using Boost-RS outperforms attribute concatenation and multi-label learning. We also show that Boost-RS outperforms similarity-based models. Ablation studies and visualization of learned representations highlight the importance of using contrastive learning on some of the auxiliary data in boosting the embedding vectors.

Availability and implementation
A Python implementation for Boost-RS is provided at https://github.com/HassounLab/Boost-RS. The enzyme-substrate interaction data is available from the KEGG database (https://www.genome.jp/kegg/).
Data integration: exploiting ratios of parameter estimates from a reduced external model
Authors: Taylor Jeremy M G , Choi Kyuseong , Han Peisong 
Published: April 2022

SummaryWe consider the situation of estimating the parameters in a generalized linear prediction model, from an internal dataset, where the outcome variable $Y$ is binary and there are two sets of covariates, $X$ and $Z$. We have information from an external study that provides parameter estimates for a generalized linear model of $Y$ on $X$. We propose a method that makes limited assumptions about the similarity of the distributions in the two study populations. The method involves orthogonalizing the $Z$ variables and then borrowing information about the ratio of the coefficients from the external model. The method is justified based on a new result relating the parameters in a generalized linear model to the parameters in a generalized linear model with omitted covariates. The method is applicable if the regression coefficients in the $Y$ given $X$ model are similar in the two populations, up to an unknown scalar constant. This type of transportability between populations is something that can be checked from the available data. The asymptotic variance of the proposed method is derived. The method is evaluated in a simulation study and shown to gain efficiency compared to simple analysis of the internal dataset, and is robust compared to an alternative method of incorporating external information.
Repurposing ibudilast to mitigate Alzheimer’s disease by targeting inflammation
Authors: Oliveros Giovanni , Wallace Charles H , Chaudry Osama , Liu Qiao , Qiu Yue , Xie Lei , Rockwell Patricia , Figueiredo-Pereira Maria E , Serrano Peter A 
Published: April 2022

Abstract
Alzheimer’s disease is a multifactorial disease that exhibits cognitive deficits, neuronal loss, amyloid plaques, neurofibrillary tangles and neuroinflammation in the brain. Hence, a multi-target drug would improve treatment efficacy. We applied a new multi-scale predictive modelling framework that integrates machine learning with biophysics and systems pharmacology to screen drugs for Alzheimer’s disease using patients’ tissue samples. Our predictive modelling framework identified ibudilast as a drug with repurposing potential to treat Alzheimer’s disease. Ibudilast is a multi-target drug, as it is a phosphodiesterase inhibitor and toll-like receptor 4 (TLR4) antagonist. In addition, we predict that ibudilast inhibits off-target kinases (e.g. IRAK1 and GSG2). In Japan and other Asian countries, ibudilast is approved for treating asthma and stroke due to its anti-inflammatory potential.
Based on these previous studies and on our predictions, we tested for the first time the efficacy of ibudilast in Fisher transgenic 344-AD rats. This transgenic rat model is unique as it exhibits hippocampal-dependent spatial learning and memory deficits and Alzheimer’s disease pathology, including hippocampal amyloid plaques, tau paired-helical filaments, neuronal loss and microgliosis, in a progressive age-dependent manner that mimics the pathology observed in Alzheimer’s disease patients. Following long-term treatment with ibudilast, transgenic rats were evaluated at 11 months of age for spatial memory performance and Alzheimer’s disease pathology.
We demonstrate that ibudilast-treatment of transgenic rats mitigated hippocampal-dependent spatial memory deficits, as well as hippocampal (hilar subregion) amyloid plaque and tau paired-helical filament load, and microgliosis compared to untreated transgenic rat. Neuronal density analysed across all hippocampal regions was similar in ibudilast-treated transgenic compared to untreated transgenic rats. Interestingly, RNA sequencing analysis of hippocampal tissue showed that ibudilast-treatment affects gene expression levels of the TLR and ubiquitin-proteasome pathways differentially in male and female transgenic rats. Based on the TLR4 signalling pathway, our RNA sequencing data suggest that ibudilast-treatment inhibits IRAK1 activity by increasing expression of its negative regulator IRAK3, and/or by altering TRAF6 and other TLR-related ubiquitin ligase and conjugase levels.
Our results support that ibudilast can serve as a repurposed drug that targets multiple pathways including TLR signalling and the ubiquitin/proteasome pathway to reduce cognitive deficits and pathology relevant to Alzheimer’s disease.