bluuebunny/crossref_metadata_2025 huggingface dataset:
ParticleChromo3D+: A Web Server for ParticleChromo3D Algorithm for 3D Chromosome Structure Reconstruction
Authors: Vadnais David , Oluwadare Oluwatosin
Published: March 2023

Understanding the three-dimensional (3D) structure of chromatin is invaluable for researching how it functions. One way to gather this information is the chromosome conformation capture (3C) technique and its follow-up technique Hi-C. Here, we present ParticleChromo3D+, a containerized web-based genome structure reconstruction server/tool that provides researchers with a portable and accurate tool for analyses. Additionally, ParticleChromo3D+ provides a more user-friendly way to access its capabilities via a graphical user interface (GUI). ParticleChromo3D+ can save time for researchers by increasing the accessibility of genome reconstruction, easing usage pain points, and offloading computational processing/installation time.
Analysis of Snow Cover in the Sibillini Mountains in Central Italy
Authors: Gentilucci Matteo , Catorci Andrea , Panichella Tiziana , Moscatelli Sara , Hamed Younes , Missaoui Rim , Pambianchi Gilberto
Published: March 2023

Research on solid precipitation and snow cover, especially in mountainous areas, suffers from problems related to the lack of on-site observations and the low reliability of measurements, which is often due to instruments that are not suitable for the environmental conditions. In this context, the study area is the Monti Sibillini National Park, and it is no exception, as it is a mountainous area located in central Italy, where the measurements are scarce and fragmented. The purpose of this research is to provide a characterization of the snow cover with regard to maximum annual snow depth, average snow depth during the snowy period, and days with snow cover on the ground in the Monti Sibillini National Park area, by means of ground weather stations, and also analyzing any trends over the last 30 years. For this research, in order to obtain reliable snow cover data, only data from weather stations equipped with a sonar system and manual weather stations, where the surveyor goes to the site each morning and checks the thickness of the snowpack and records, it were collected. The data were collected from 1 November to 30 April each year for 30 years, from 1991 to 2020; six weather stations were taken into account, while four more were added as of 1 January 2010. The longer period was used to assess possible ongoing trends, which proved to be very heterogeneous in the results, predominantly negative in the case of days with snow cover on the ground, while trends were predominantly positive for maximum annual snow depth and distributed between positive and negative for the average annual snow depth. The shorter period, 2010–2022, on the other hand, ensured the presence of a larger number of weather stations and was used to assess the correlation and presence of clusters between the various weather stations and, consequently, in the study area. Furthermore, in this way, an up-to-date nivometric classification of the study area was obtained (in terms of days with snow on the ground, maximum height of snowpack, and average height of snowpack), filling a gap where there had been no nivometric study in the aforementioned area. The interpolations were processed using geostatistical techniques such as co-kriging with altitude as an independent variable, allowing fairly precise spatialization, analyzing the results of cross-validation. This analysis could be a useful tool for hydrological modeling of the area, as well as having a clear use related to tourism and vegetation, which is extremely influenced by the nivometric variables in its phenology. In addition, this analysis could also be considered a starting point for the calibration of more recent satellite products dedicated to snow cover detection, in order to further improve the compiled climate characterization.
Rendezvous Based Adaptive Path Construction for Mobile Sink in WSNs Using Fuzzy Logic
Authors: Banimelhem Omar , Al-Quran Fidaa
Published: March 2023

In this paper, an adaptive path construction approach for Mobile Sink (MS) in wireless sensor networks (WSNs) for data gathering has been proposed. The path is constructed based on selecting Rendezvous Points (RPs) in the sensing field where the MS stops in order to collect the data. Compared with the most existing RP-based schemes, which rely on fixed RPs to construct the path where these points will stay fixed during the whole network lifetime, we propose an adaptive path construction where the locations of the RPs are dynamically updated using a Fuzzy Inference System (FIS). The proposed FIS, which is named Fuzzy_RPs, has three inputs and one output. The inputs are: the remaining energy of the sensor nodes, the transmission distance between the RPs and the sensor nodes, and the number of surrounding neighbors of each node. The output of FIS is a weight value for each sensor node generated based on the previous three parameters and, thus, each RP is updated to its new location accordingly. Simulation results have shown that the proposed approach extends the network lifetime compared with another existing approach that uses fixed RPs. For example, in terms of using the first dead node as a metric for the network lifetime, when the number of deployed sensor nodes changes from 150 to 300, an improvement that ranges from 48.3% to 83.76% has been achieved compared with another related approach that uses fixed RPs.
Assessing Internet Surfing Behaviours and Digital Health Literacy among University Students in Ghana during the COVID-19 Pandemic
Authors: Britwum Francis , Anin Stephen Kofi , Agormedah Edmond Kwesi , Quansah Frank , Srem-Sai Medina , Hagan John Elvis , Schack Thomas
Published: March 2023

This study assessed the internet surfing behaviours and digital health literacy (DHL) among university students in Ghana during the COVID-19 pandemic. The research was guided by three major objectives: (1) examine the online information searching behaviours of university students during the COVID-19 pandemic, (2) investigate the thematic areas university students searched during COVID-19, and (3) examine the DHL level of university students. The study conveniently sampled 1014 university students to solicit their responses through questionnaire administration. Using frequency and percent counts, multiple response analysis, as well as mean and standard deviation, the study revealed that the predominant platforms university students used were search engines (n = 954, 94.1%), social media (n = 950, 93.7%), and WhatsApp (n = 950, 93.7%). Predominant themes among the thematic areas university students searched during COVID-19 were symptoms of COVID-19 (n = 701, 81.7%), COVID-19 vaccines (n = 689, 80.3%), and transmission routes of the coronavirus (n = 664, 77.4%). Further, other results showed that students enrolled in health-related programmes showed significantly higher levels of DHL compared to those in non-health-related programmes. The findings suggest the need to implement health education measures to strengthen students’ health literacy capacities and their DHL ability. This finding requires governments and health authorities to implement evidence-informed health communication strategies to provide valid and reliable health information concerning the COVID-19 pandemic and support individuals to make health-promoting decisions.
Vaccine Acceptance, Knowledge, Attitude and Practices Regarding the COVID-19 Pandemic: Cross-Sectional Study among Dentists in Trinidad and Tobago
Authors: Rafeek Reisha , Sa Bidyadhar , Smith William
Published: March 2023

Background: This study’s aim was to assess Trinidad and Tobago dentists’ vaccine acceptance, knowledge, attitude and practices regarding the COVID-19 pandemic. Methods: All dentists registered with the Trinidad and Tobago Dental Association were invited to complete an online anonymous questionnaire between June and October 2021. Results: A total of 46.2% of dentists responded. The majority of respondents had excellent knowledge of COVID-19 (94.8%), use of personal protective equipment (98.7%) and N95 masks (93.5%), but had poor knowledge about the reuse of N95 masks (27.5%). A total of 34.9% were comfortable providing emergency care to positive or suspected cases of COVID-19, and 64.5% were afraid of becoming infected from a patient. PPE usage was reported at 97.4% and 67.3% for N95 masks. All surfaces of waiting areas were disinfected every 2 h by 59.2%. A total of 90.8% agreed to be vaccinated straight away if a vaccine were made available. Conclusion: Dentists in Trinidad and Tobago have good levels of knowledge, attitude, practices regarding COVID-19. Dentists also have high levels of vaccine acceptance and can play a role in advocating for the COVID-19 vaccine.
Chaotic van der Pol Oscillator Control Algorithm Comparison
Authors: Ribordy Lauren , Sands Timothy
Published: March 2023

The damped van der Pol oscillator is a chaotic non-linear system. Small perturbations in initial conditions may result in wildly different trajectories. Controlling, or forcing, the behavior of a van der Pol oscillator is difficult to achieve through traditional adaptive control methods. Connecting two van der Pol oscillators together where the output of one oscillator, the driver, drives the behavior of its partner, the responder, is a proven technique for controlling the van der Pol oscillator. Deterministic artificial intelligence is a feedforward and feedback control method that leverages the known physics of the van der Pol system to learn optimal system parameters for the forcing function. We assessed the performance of deterministic artificial intelligence employing three different online parameter estimation algorithms. Our evaluation criteria include mean absolute error between the target trajectory and the response oscillator trajectory over time. Two algorithms performed better than the benchmark with necessary discussion of the conditions under which they perform best. Recursive least squares with exponential forgetting had the lowest mean absolute error overall, with a 2.46% reduction in error compared to the baseline, feedforward without deterministic artificial intelligence. While least mean squares with normalized gradient adaptation had worse initial error in the first 10% of the simulation, after that point it exhibited consistently lower error. Over the last 90% of the simulation, deterministic artificial intelligence with least mean squares with normalized gradient adaptation achieved a 48.7% reduction in mean absolute error compared to baseline.
COVID-19 Pandemic and Stock Performance: Evidence from the Sub-Saharan African Stock Markets
Authors: Ncube Mbongiseni , Sibanda Mabutho , Matenda Frank Ranganai
Published: March 2023

Emerging stock markets provide great opportunities for investment growth and risk diversification. However, they are more vulnerable to extreme market events. This study examines the effects of the COVID-19 pandemic on stock performance in sub-Saharan African stock markets. An event study method was used to determine whether there was any significant difference in sector returns before and during the pandemic, and panel data regression was used to determine the causal relationship between COVID-19 events and the abnormal returns observed. Four stock exchanges were chosen, including the two largest and two fastest-growing markets in sub-Saharan Africa. According to the study’s findings, the information technology, consumer staples, and healthcare sectors outperformed during the pandemic, while the industrials, materials, and real estate sectors underperformed. The financial and consumer discretionary proved to be the most stable sectors during the pandemic. We also observed that the imposition of lockdown had a negative impact on the performance of most sectors in sub-Saharan African markets, whereas government assistance in the form of economic stimulus packages had no significant positive impact on stock performance except in the South African market. Furthermore, we find that increases in COVID-19 cases and deaths had no negative impact on capital markets, where stocks have responded positively to economic recovery aid. The study concludes that during the COVID-19 pandemic, stocks reacted more to government actions than the occurrence of the pandemic itself.
Validation of the EPACODI-1 Scale: University Students’ Perceptions of Inclusive Education
Authors: Morales-Endrino José-Antonio , Molina-Saorín Jesús , Marín-Marín José-Antonio
Published: March 2023

In the last fifteen years, changes have been taking place in education systems at the international and national levels that aim to achieve, in the near future, the objectives set by the UN International Convention on the Rights of Persons with Disabilities (hereafter CRPD). Spain is no stranger to these objectives, as recognized in the new Organic Law for the Modification of the Law on the Organization of Education. This situation makes it necessary to know the perceptions that professionals in training (about to graduate) from faculties of education have about the legal content established by articles 4.1.i and 24 of the CRPD on inclusive education. In order to ascertain these perceptions, the EPACO-DI-1 instrument was used in a quantitative and confirmatory study by means of a multivariate factor analysis (CFA), applying the parallel estimation method of ordinary least squares (OLS) and principal axes with polychoric correlation and promax oblique rotation. This study involved 552 fourth-year students between the ages of 21 and over 45 from the specializations offered by the Faculty of Education of the University of Murcia. The obtained results are consistent and show the validity of the EPACODI-1 scale for determining the perceptions of professionals in training on inclusive education.
Perception of Bullying in Early Childhood Education in Spain: Pre-School Teachers vs. Psychologists
Authors: Fernández-Alfaraz María-Luz , Nieto-Sobrino María , Antón-Sancho Álvaro , Vergara Diego
Published: March 2023

In this work, quantitative research is carried out on the perceptions of early childhood education teachers and child psychologists about the incidence of bullying behaviors in early childhood education (3 to 6 years old) and their knowledge and experience in this regard. For this purpose, two questionnaires were used, each of them oriented to one of the two groups of professionals analyzed, whose answers were subjected to statistical analysis. As for results, it has been obtained that early childhood education teachers express having received deficient training in school bullying and have little experience in its detection and treatment. Furthermore, the teachers’ conception of bullying occurring in their own schools is not realistic and differs from the knowledge they have of the existence of bullying behavior in other schools. Likewise, the existence of action plans against bullying in the school conditions the teachers’ assessments. The assessments held by psychologists differ significantly from those of teachers, mainly in the identification of the origin of bullying (which teachers attribute to the use of digital technologies and psychologists to the social and family environment of the aggressor). Finally, some implications and recommendations in terms of the training of educational professionals on bullying and the need for greater collaboration between teachers and psychologists are reported.
A Fast Lock-In Time, Capacitive FIR-Filter-Based Clock Multiplier with Input Clock Jitter Reduction
Authors: Zeng Zhaoquan , Zhang Ling , Gong Lijiao , Zhang Ning
Published: March 2023

This paper presents a fast lock-in time clock frequency multiplier without using traditional clock generation circuits such as PLLs and DLLs. We propose a novel technique based on capacitive finite impulse response (FIR) filters to generate clock phases while reducing the input clock phase noise at the same time. A new delay line circuit is also proposed for improving power supply rejection. In addition, to improve the matching quality as well as the end-effects tolerance of the on-chip capacitors, a single-value series/parallel algorithm is proposed. Designed in a 0.18 μm digital CMOS process, with a 20 MHz input clock frequency, the multiplier achieves a multiplication factor of 5 with a lock-in time of less than 4 clock cycles. The input clock jitter is reduced from 7ns RMS to 153 ps RMS after frequency multiplication.
UnTiCk: Unsupervised Type-Aware Complex Logical Queries Reasoning over Knowledge Graphs
Authors: Chen Deyu , Li Qiyuan , Gu Jinguang
Published: March 2023

For the task of answering complex logical queries on large-scale incomplete knowledge graphs, the promising approach is to embed the knowledge graph and complex logical queries into a low-dimensional space and perform iterative reasoning to find the final answers. The general problem is that these models do not include entity types as an important feature, which reduces the reasoning potential. However, explicit type information is not always available on large-scale knowledge graphs. We innovatively propose an embedding-based framework for Unsupervised Type-Aware Complex Logical Queries (UnTiCk). Our approach implements unsupervised type constraints on multi-hop complex logical query processing. Moreover, it can capture the different representations of type features when entities are in different locations in the logical path. We designed type compatibility measurement meta-operators combined with popular Existential Positive First-Order (EPFO) neural logical operators to achieve type-aware EPFO complex query embedding. We validated the effectiveness of our framework on popular large-scale knowledge graphs by using the same embedding dimensionality as complex logical embedding methods. The results showed an average relative improvement of 1.9–12.8% on Hit@3 and up to 42.1% on the certain logical pattern.
A Fast Resource Allocation Algorithm Based on Reinforcement Learning in Edge Computing Networks Considering User Cooperation
Authors: Jin Yichen , Chen Ziwei
Published: March 2023

In the 5G era, the amount of network data has grown explosively. A large number of new computation-intensive applications have created demand for edge computing in mobile networks. Traditional optimization methods are difficult to adapt to the dynamic wireless network environment because they solve the problem online, which is not suitable in edge computing scenarios. Therefore, in order to obtain a mobile network with better performance, we propose a network frame with a resource allocation algorithm based on power consumption, delay and user cooperation. This algorithm can quickly realize the optimization of a network to improve performance. Specifically, compared with heuristic algorithms, such as particle swarm optimization, ant colony algorithm, etc., commonly used to solve such problems, the algorithm proposed in this paper can reduce some aspects of network performance (including delay and user energy consumption) by about 10% in a network dominated by downlink tasks. The performance of the algorithm under certain network conditions was demonstrated through simulations.
A Novel Denoising Algorithm Based on Wavelet and Non-Local Moment Mean Filtering
Authors: Liu Caixia , Zhang Li
Published: March 2023

Denoising is the basis and premise of image processing and an important part of image preprocessing. Denoising can effectively improve image quality, which contributes to subsequent image processing such as image segmentation, feature extraction, and so on. In this paper, we propose a novel image denoising method based on wavelet transform and nonlocal moment mean filtering approach (NMM). The noisy image is firstly denoised by a wavelet-based soft-thresholding denoising technique and NMM is then utilized to further eliminate the rest noises. Meanwhile, the fusion of moment invariants increases the robustness of our denoising algorithm due to the invariance of image scaling, translation, and rotation of color moments. Experiments show that our algorithm achieves a better denoising effect compared with some other denoising approaches.
Consensus-Based Distributed Optimal Dispatch of Integrated Energy Microgrid
Authors: Luo Shanna , Peng Kaixiang , Hu Changbin , Ma Rui
Published: March 2023

In recent years, the energy form of microgrids is constantly enriching, while the decentralization requirements of microgrids are constantly developing. Considering the economic benefits of an integrated energy microgrid (IEM), this paper focuses on the distributed optimal dispatch of IEM based on a consensus algorithm. The microgrid structure and multi-agent system are combined organically to get the decentralized architecture of IEM. This paper takes the incremental cost rate of each unit in IEM as a consensus variable. Based on the consensus theory, iterative optimization is carried out to achieve the optimal economic operation and power supply-demand balance of IEM. The distributed optimal dispatch is realized, and the convergence of the algorithm is proved. The experiment is carried out with LabVIEW and MATLAB and verifies the effectiveness of the algorithm. The results show that the distributed optimal dispatch algorithm can effectively reduce the power generation cost of the integrated energy system.
Impact of Renewable and Non-Renewable Energy on EKC in SAARC Countries: Augmented Mean Group Approach
Authors: Voumik Liton Chandra , Hossain Mohammad Iqbal , Rahman Md. Hasanur , Sultana Raziya , Dey Rahi , Esquivias Miguel Angel
Published: March 2023

This study looks at the short- and long-term effects of fossil fuels, renewable energy, and nuclear energy on CO2 emissions in the South Asian Association for Regional Cooperation (SAARC) countries from 1982 to 2021. We assess the impacts of SAARC’s current and anticipated use of nuclear, fossil, and alternative energies by testing the environmental Kuznets curve (EKC) hypothesis. The study applied the second-generation unit root test, cointegration test, and the newly introduced AMG technique to handle the presence of cross-sectional dependence. The results indicate that EKC does not hold in SAARC, and a U-shaped quadratic link exists between GDP and environmental pollution. The findings also reveal that the environmental pollution in the SAARC is caused by fossil fuel, whereas using renewable (REN) and nuclear energy can cut long-term pollution. While renewable energy is critical to minimizing environmental deterioration in SAARC, empirical findings also show that more than rising national wealth is needed to meet environmental demands. According to the results of this study, SAARC countries should take the lead in achieving sustainable growth and the efficient use of clean energy.
Direct Numerical Simulations of Turbulent Flow over Low-Pressure Turbine Blades with Aeroelastic Vibrations and Inflow Wakes
Authors: Erfanian Nakhchi Mahdi , Win Naung Shine , Rahmati Mohammad
Published: March 2023

In the present work, direct numerical simulation is employed to investigate the unsteady flow characteristics and energy performance of low-pressure turbines (LPT) by considering the blades aeroelastic vibrations and inflow wakes. The effects of inflow disturbance (0 < φ < 0.91) and reduced blade vibration (0 < f < 250 Hz) on the turbulent flow behavior of LPTs are investigated for the first time. The transient governing equations on the vibrating blades are modelled by the high-order spectral/hp element method. The results revealed that by increasing the inflow disturbances, the separated bubbles tend to shrink, which has a noticeable influence on the pressure in the downstream region. The maximum wake loss value is reduced by 16.4% by increasing the φ from 0.31 to 0.91. The flow separation is majorly affected by inflow wakes and blade vibrations. The results revealed that the maximum pressure coefficient in the separated flow region of the vibrating blade has been increased by 108% by raising φ from 0 to 0.91. The blade vibration further intensifies the vortex generation process, adding more energy to the flow and the downstream vortex shedding. The vortex generation and shedding are intensified on the vibrating blade compared to the non-vibrating one that is subject to inflow wakes. The results and findings from this paper are also useful for the design and modeling of turbine blades that are prone to aeroelastic instabilities, such as large offshore wind turbine blades.
Advanced Optimisation and Forecasting Methods in Power Engineering—Introduction to the Special Issue
Authors: Pijarski Paweł , Kacejko Piotr , Miller Piotr
Published: March 2023

Modern power engineering is struggling with various problems that have not been observed before or have occurred very rarely. The main cause of these problems results from the increasing number of connected distributed electricity sources, mainly renewable energy sources (RESs). Therefore, energy generation is becoming more and more diverse, both in terms of technology and location. Grids that have so far worked as receiving networks change their original function and become generation networks. The directions of power flow have changed. In the case of distribution networks, this is manifested by power flows towards transformer stations and further to the network with a higher voltage level. As a result of a large number of RESs, their total share in the total generation increases. This has a significant impact on various aspects of the operation of the power system. Voltage profiles, branch loads, power flows and directions of power flows between areas change. As a result of the random nature of RES generation, there are problems with the quality of electricity, source stability issues, branch overloading, voltage exceedances and power balance. The occurrence of various types of problems requires the use of more and more advanced methods to solve them. This review paper, which is an introduction to the Special Issue Advanced Optimisation and Forecasting Methods in Power Engineering, describes and justifies the need to reach for effective and available mathematical and IT methods that are necessary to deal with the existing threats appearing in the operation of modern power systems. It indicates exemplary, current problems and advanced methods to solve them. This article is an introduction and justification for the use of advanced calculation methods and algorithms. Engineering intuition and experience are often not enough due to the size and complexity of power grid operation. Therefore, it becomes necessary to use methods based on artificial intelligence and other advanced solutions that will facilitate and support decision making in practice.
Experimental/Numerical Investigation and Prediction of Fouling in Multiphase Flow Heat Exchangers: A Review
Authors: Ben-Mansour Rached , El-Ferik Sami , Al-Naser Mustafa , Qureshi Bilal A. , Eltoum Mohammed Ahmed Mohammed , Abuelyamen Ahmed , Al-Sunni Fouad , Ben Mansour Ridha
Published: March 2023

Fouling build-up is one of the most challenging problems for heat exchangers in industry. The presence of fouling leads to a degradation of system efficiency, an increase in operating cost, and possibly, a harmful environmental impact. For this reason, fouling analysis has become an extremely important research subject in order to have a safe and efficient operation. The analysis is more difficult where phase change of fluids is involved during the heat transfer process, as in the case of boilers and condensers, which are critical units in industrial facilities. Due to the lack of a comprehensive review of fouling analysis for the case of multiphase heat exchangers, this paper examines available approaches and techniques used for fouling characterization, modeling, monitoring, and prediction in heat exchangers for both single-phase and multiphase heat exchangers with a focus on fouling in thermal desalination systems. It also gives an overview of heat exchanger condition monitoring solutions available in the market.
An Improved Over-Speed Deloading Control of Wind Power Systems for Primary Frequency Regulation Considering Turbulence Characteristics
Authors: Zhang Xiaolian , Lin Baocong , Xu Ke , Zhang Yangfei , Hao Sipeng , Hu Qi
Published: March 2023

Wind power systems participating in primary frequency regulation have become a novel trend. In order to solve the problem of the over-speed deloading (OSD) control of wind power systems failing to provide reserved capacity for primary frequency regulation while under turbulent winds, this paper analyzes the influence mechanism of turbulence characteristics on the OSD control and the relationship between the reserve capacity of OSD control and the deloading power coefficient under turbulent wind speeds, while also quantifying the relationship between the turbulence characteristic index and deloading power coefficient. The range of the deloading power coefficient is obtained accordingly, based on which improved OSD control is proposed to dynamically optimize the deloading power coefficient according to the turbulence characteristics, which improves the frequency regulation performance of wind power systems under turbulent wind speed. According to the simulations and experimental results, the improved method proposed in this paper has good effectiveness and superiority in frequency regulation effect and rotor speed performance.
Research on Harmonic Management of Single-Phase AC Charging Pile Based on Active Filtering
Authors: Ding Xiangfu , Shi Haojie , Wang Yingjian , Zhuang Yong , Yuan Guangming , Zhu Shuzhen
Published: March 2023

Nowadays, AC charging piles are widely used, and with the increasing number of charging piles, the harmonic pollution generated by them becomes more serious and affects the power quality of the grid. Aiming at the problem of harmonic control of the single-phase AC charging pile, it is decided to apply the active filter technology. The single-phase parallel active filter (PAPF) is selected according to the characteristics of the charging pile. The single harmonic detection method is studied based on instantaneous reactive power theory, and a new adaptive low-pass filter with fixed-step size is proposed to improve the performance of harmonic detection by combining the least mean square (LMS) and the least fourth-order moment (LMF) adaptive algorithms. The PAPF control part adopts the composite control strategy of inner and outer loop combined with repetitive control to complete the voltage stabilization control, harmonic tracking, and compensation. Based on MATLAB/SIMULINK, the output waveforms of the low-pass filter link are simulated and analyzed, and the prototype experiment is carried out. The results verify that the algorithm can improve the performance of harmonic detection. Finally, the single-phase PAPF system simulation is established and the harmonic compensation capability of system is analyzed by the Fast Fourier Transform (FFT). The results demonstrate that single-phase PAPF can effectively manage harmonics and the total harmonic distortion (THD) is reduced to less than 5%.
Parallel Communication Optimization Based on Graph Partition for Hexagonal Neutron Transport Simulation Using MOC Method
Authors: Zheng Jingchao , Wang Zhiqiang , Xie Zeyi , Peng Xingjie , Zhao Chen , Wu Wenbin
Published: March 2023

OpenMOC-HEX, a neutron transport calculation code with hexagonal modular ray tracing, has the capability of domain decomposition parallelism based on an MPI parallel programming model. In this paper, the optimization of inter-node communication was studied. Starting from the specific geometric arrangement of hexagonal reactors and the communication features of the Method of Characteristics, the computation and communication of all the hexagonal assemblies are mapped to a graph structure. Then, the METIS library is used for graph partitioning to minimize the inter-node communication under the premise of load balance on each node. Numerical results of an example hexagonal core with 1968 energy groups and 1027 assemblies demonstrate that the communication time is reduced by about 90%, and the MPI parallel efficiency is increased from 82.0% to 91.5%.
To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
Authors: Bosello Michael , Falcomer Carlo , Rossi Claudio , Pau Giovanni
Published: March 2023

Electric vehicles (EVs) are spreading fast as they promise to provide better performance and comfort, but above all, to help face climate change. Despite their success, their cost is still a challenge. Lithium-ion batteries are one of the most expensive EV components, and have become the standard for energy storage in various applications. Precisely estimating the remaining useful life (RUL) of battery packs can encourage their reuse and thus help to reduce the cost of EVs and improve sustainability. A correct RUL estimation can be used to quantify the residual market value of the battery pack. The customer can then decide to sell the battery when it still has a value, i.e., before it exceeds the end of life of the target application, so it can still be reused in a second domain without compromising safety and reliability. This paper proposes and compares two deep learning approaches to estimate the RUL of Li-ion batteries: LSTM and autoencoders vs. CNN and autoencoders. The autoencoders are used to extract useful features, while the subsequent network is then used to estimate the RUL. Compared to what has been proposed so far in the literature, we employ measures to ensure the method’s applicability in the actual deployed application. Such measures include (1) avoiding using non-measurable variables as input, (2) employing appropriate datasets with wide variability and different conditions, and (3) predicting the remaining ampere-hours instead of the number of cycles. The results show that the proposed methods can generalize on datasets consisting of numerous batteries with high variance.
Small-Scale Phase Change Materials in Low-Temperature Applications: A Review
Authors: Weiss Leland , Jha Ramanshu
Published: March 2023

Significant efforts have explored the field of Phase Change Materials (PCMs) for various applications. Research and real-world applications explore length scales that range from infrastructure to micro systems. A commonality of these efforts is the desire to utilize the phase change capability of the PCM to provide a steady temperature heat sink for thermal storage. Smaller scale efforts and materials are presented in this present review. A general challenge to the use of these PCMs regardless of application is the low thermal conductivity present as a baseline material property. Efforts to improve thermal conductivity have included the addition of underlying metal foam structures, heat pipes, or metallic fins inserted into the base PCM. Other efforts have investigated alterations to the base materials themselves by employing additives such as graphite to supplement thermal performance. Other additives are used to obtain form stability in the PCM as it melts. While the field of PCM research has been well established, the use of new materials and approaches that employ the use of natural materials continues to move research forward. This review captures significant efforts and presents a thoughtful comparison of common themes across centimeter and smaller-scale PCM use.
Experimental Investigation of High-Pressure Liquid Ammonia Injection under Non-Flash Boiling and Flash Boiling Conditions
Authors: Fang Yuwen , Ma Xiao , Zhang Yixiao , Li Yanfei , Zhang Kaiqi , Jiang Changzhao , Wang Zhi , Shuai Shijin
Published: March 2023

Liquid ammonia is an ideal zero-carbon fuel for internal combustion engines. High-pressure injection is a key technology in organizing ammonia combustion. Characteristics of high-pressure liquid ammonia injection is lack of research. Spray behaviors are likely to change when a high-pressure diesel injector uses liquid ammonia as its fuel. This study uses high-speed imaging with a DBI method to investigate the liquid penetration, width, and spray tip velocity of high-pressure liquid ammonia injection up to 100 MPa. Non-flash and flash boiling conditions were included in the experimental conditions. Simulation was also used to evaluate the results. In non-flash boiling conditions, the Hiroyasu model provided better accuracy than the Siebers model. In flash boiling conditions, a phenomenon was found that liquid penetration and spray tip velocity were strongly suppressed in the initial stage of the injection process, this being the “spray resistance phenomenon”. The “spray resistance phenomenon” was observed when ambient pressure was below 0.7 MPa during 0–0.05 ms ASOI and was highly related to the superheated degree. The shape of near-nozzle sprays abruptly changed at 0.05 ms ASOI, indicating that strong cavitation inside the nozzle caused by needle lift effects is the key reason for the “spray resistance phenomenon”.
Mass Transfer Behaviors and Battery Performance of a Ferrocyanide-Based Organic Redox Flow Battery with Different Electrode Shapes
Authors: Zhang Pengfei , Liu Xi , Fu Junjie , Chu Fengming
Published: March 2023

The ferrocyanide-based organic redox flow battery (ferrocyanide-based ORFB), based on electrochemistry, has become a potential energy storage technology due to its low price, eco-friendliness, safety, and convenience. However, its low efficiency and poor mass transfer performance hinder the application of the ORFB. The influence of the electrode shape (trapezoid, sector, and rectangle) on the mass transfer and battery performance are studied based on a numerical model, which is verified by the experiments. The results show that battery performance of the trapezoid electrode is better than that of the sector and rectangle electrode. The discharge voltage of the rectangle battery is the lowest, and the discharge voltage of the trapezoid battery is the highest. The discharge voltage of the rectangle battery is 4.47% lower than that of the trapezoid battery. The uniformity factor value of the trapezoid battery is 26.9% higher than that of the rectangle battery. The trapezoid shape is the best design for the electrode, contributing to the application of the ferrocyanide-based ORFBs.
Impact Assessment of Dynamic Loading Induced by the Provision of Frequency Containment Reserve on the Main Bearing Lifetime of a Wind Turbine
Authors: Singh Narender , Boruah Dibakor , De Kooning Jeroen D. M. , De Waele Wim , Vandevelde Lieven
Published: March 2023

The components of an operational wind turbine are continuously impacted by both static and dynamic loads. Regular inspections and maintenance are required to keep these components healthy. The main bearing of a wind turbine is one such component that experiences heavy loading forces during operation. These forces depend on various parameters such as wind speed, operating regime and control actions. When a wind turbine provides frequency containment reserve (FCR) to support the grid frequency, the forces acting upon the main bearing are also expected to exhibit more dynamic variations. These forces have a direct impact on the lifetime of the main bearing. With an increasing trend of wind turbines participating in the frequency ancillary services market, an analysis of these dynamic forces becomes necessary. To this end, this paper assesses the effect of FCR-based control on the main bearing lifetime of the wind turbine. Firstly, a control algorithm is implemented such that the output power of the wind turbine is regulated as a function of grid frequency and the amount of FCR. Simulations are performed for a range of FCR to study the changing behaviour of dynamical forces acting on the main bearing with respect to the amount of FCR provided. Then, based on the outputs from these simulations and using 2 years of LiDAR wind data, the lifetime of the main bearing of the wind turbine is calculated and compared for each of the cases. Finally, based on the results obtained from this study, the impact of FCR provision on the main bearing lifetime is quantified and recommendations are made, that could be taken into account in the operation strategy of a wind farm.
Anaerobic Digestion of Dairy Effluent in New Zealand, Time to Revisit the Idea?
Authors: Hull-Cantillo Marianne , Lay Mark , Kovalsky Peter
Published: March 2023

The anaerobic digestion of New Zealand low-input dairy farms has previously been evaluated for energy production, but farming systems have recently become more intensive with increased feed supplementation and feed replacement; therefore, we are studying how these changes affect the overall energy production for water heating. A combination of literature review, surveys, chemical analyses, biomethane potential analysis, and modeling were used for this study. On a case study farm with a solid separator, it was found that 558 MJ/day and 176–861 MJ/day could be produced with the solid and liquid portions of effluent, respectively. There is enough biogas to satisfy the dairy farm’s water heating requirements with a tankless water heater.
Optimal Energy Management for Virtual Power Plant Considering Operation and Degradation Costs of Energy Storage System and Generators
Authors: Borisoot Kanjanapon , Liemthong Rittichai , Srithapon Chitchai , Chatthaworn Rongrit
Published: March 2023

Even though generating electricity from Renewable Energy (RE) and electrification of transportation with Electric Vehicles (EVs) can reduce climate change impacts, uncertainties of the RE and charged demand of EVs are significant challenges for energy management in power systems. To deal with this problem, this paper proposes an optimal energy management method using the Virtual Power Plant (VPP) concept for the power system considering solar PhotoVoltaics (PVs) and Electric Vehicle Charging Stations (EVCS). The Differential Evolution (DE) algorithm is applied to manage energy in the power system to minimize the operation cost of generators and degradation costs in Energy Storage Systems (ESS) and generators. The effectiveness of the proposed approach is examined and tested on the IEEE 24 bus Reliability Test System (RTS 24) using the MATPOWER tool on the MATLAB program for calculating Optimal Power Flow (OPF). In this study, two situations before and after applying the proposed method are considered. The simulation results demonstrate that a branch constraint violation occurs before using optimal energy management using the VPP concept. In order to solve this issue, the DE algorithm for optimal energy management using the VPP concept is applied by dividing the studied case into two subcases as follows. For the first subcase, two objectives consisting of the minimization of the generator operation cost and the minimization of the battery degradation cost in ESS are considered. In the second case, three objectives comprising the two mentioned objectives with the minimization of generator degradation cost are considered. The results demonstrate that branch constraint violations can be avoided by applying optimal energy management using the VPP concept. This study also suggests considering the generator degradation cost in the objective function, which can minimize the total costs by 7.06% per day compared with the total cost of the first case.
Energy Security: New Threats and Solutions
Authors: Gitelman Lazar , Magaril Elena , Kozhevnikov Mikhail
Published: March 2023

The article presents the conceptual features of energy security management under a radically changed context, increasing crisis phenomena, and threats of various natures. The authors substantiate the claim that energy security is a complex category, which expresses the ability of the fuel and energy complex of the region to supply the required amount and range of energy resources to the domestic market at stable and reasonable prices; to promptly mitigate unexpected fluctuations in demand for fuel and energy resources; and to ensure uninterrupted energy supply and energy carrier parameters in real time. Based on an analysis of scientific publications and practical energy security models, the authors developed theoretical provisions, methodological principles, and management tools for energy security that meet modern requirements. In particular, the authors developed the terminological apparatus and identified the types and forms of modern energy threats and risks. The authors analyzed the impact of structural shifts in the electric power industry on the cost of electricity. The authors proposed a set of measures to neutralize negative scenarios in the field of energy security, which had appeared because of geopolitical factors, structural changes in the economy, and high volatility in energy prices. In addition, the authors considered the impact of the transition to low-carbon energy production on energy security, and developed the organizational and technical concept of the energy transition, which aimed to provide energy systems and individual energy facilities with properties of self-protection from emerging threats. The results of the study are of practical interest in the development of regional energy policy, plans, and specific actions that aim to ensure energy security in a turbulent global environment.
Tokenization in the Theory of Knowledge
Authors: Friedman Robert
Published: March 2023

Tokenization is a procedure for recovering the elements of interest in a sequence of data. This term is commonly used to describe an initial step in the processing of programming languages, and also for the preparation of input data in the case of artificial neural networks; however, it is a generalizable concept that applies to reducing a complex form to its basic elements, whether in the context of computer science or in natural processes. In this entry, the general concept of a token and its attributes are defined, along with its role in different contexts, such as deep learning methods. Included here are suggestions for further theoretical and empirical analysis of tokenization, particularly regarding its use in deep learning, as it is a rate-limiting step and a possible bottleneck when the results do not meet expectations.
Hot Air Convective Drying of Ginger Slices: Drying Behaviour, Quality Characteristics, Optimisation of Parameters, and Volatile Fingerprints Analysis
Authors: Bai Ruoxi , Sun Jieru , Qiao Xuguang , Zheng Zhenjia , Li Meng , Zhang Bin
Published: March 2023

Ginger is one of the most popular spices and medical herbs with its unique pungent flavour and taste. Although there has been much research into the drying methods of ginger, the effect of drying parameters in hot air convective drying on ginger quality needs to be explored in depth. This study investigated the differences in drying behaviour and quality characteristics of ginger with the variables of temperature, thickness, and loading density. The moisture states and diffusion pattern in the different stages during the drying process were analysed using low-field NMR techniques. The results of quality evaluation showed that the temperature greatly influenced the colour and gingerol content of dried ginger, and the thickness of a ginger slice greatly influenced the rehydration rate. Optimal drying conditions were determined by considering a combination of specific energy consumptions with quality retention based on the response surface methodology: a temperature of 66.41 °C, thickness of 2 mm, and loading density of 5 kg/m2. HS-GC-IMS combined with multivariate chemometrics was used to achieve the characterisation of flavour profiles and fingerprinting of dried ginger. The principal component analysis and correlation analysis revealed that the alterations in ginger quality were intimately related to moisture diffusion during drying.