bluuebunny/crossref_metadata_2025 huggingface dataset:
Rehabilitation of Memory Disorders
Authors: Schnider Armin , Ptak Radek
Published: February 2023

Memory disorders are common in clinical practice. This review focuses on the rehabilitation of anterograde amnesia, the inability to learn and retrieve new information, in non-degenerative brain disease. Diverse mnemonic strategies may be helpful in learning specific pieces of information. Their success also depends on the severity of associated cognitive failures, in particular, executive dysfunction. However, unless transfer to everyday activities is specifically trained, such strategies are of limited value in promoting independence in daily life. External memory aids are often necessary to allow for independent living. Learning to use them requires intact capacities such as procedural learning or conditioning. This review further discusses the rehabilitation of confabulation, that is, the emergence of memories of events that never happened. The rehabilitation of memory disorders needs to be tailored to patients’ individual capacities and needs.
“Well, to Be Honest, I Don’t Have an Idea of What It Might Be”—A Qualitative Study on Knowledge and Awareness Regarding Nonmelanoma Skin Cancer
Authors: Brokmeier Luisa Leonie , Diehl Katharina , Spähn Bianca Annika , Jansen Charlotte , Konkel Tobias , Uter Wolfgang , Görig Tatiana
Published: February 2023

Nonmelanoma skin cancer (NMSC) is the most common cancer type in Western industrialized countries. However, research into the knowledge and awareness in the general population regarding NMSC is still scarce. This qualitative study aims to fill this research gap. Face-to-face, semi-structured interviews with 20 individuals aged 55–85 years were conducted between February and October 2020. Transcribed interviews were analyzed using qualitative content analysis. The term “white skin cancer”—the German colloquial term of NMSC—was well-known, but the incidence was underestimated. None of the participants could give a precise definition of NMSC, and various alterations in the skin were, partially wrongly, stated as potential signs for NMSC. As risk factors for NMSC, solar radiation, and fair skin type were mentioned most often. The perceived individual risk of developing NMSC and risk compared to individuals of the same age and gender were low in our sample. Own knowledge about NMSC was mostly perceived to be insufficient, and the majority of the sample would like to receive more information on NMSC. Our results emphasize a need to inform about the signs and risks of NMSC not only in the studied older age group but also in younger people.
The Lipids and Volume in Satiation and Satiety (LIVES) Hypothesis: A Proposed Alternative Model for the Pathogenesis of Obesity
Authors: Warrilow Andrew , Pumpa Kate , Somerset Shawn , Naumovski Nenad
Published: February 2023

Obesity is one of the most important factors responsible for the marked increase in both the incidence and prevalence of type 2 diabetes mellitus (T2DM) in recent decades. Addressing the lifestyle factors associated with the progression to T2DM would present a potential rational early prevention strategy. The current evidence suggests that excessive energy intake is mediated via dietary fat. Biochemical signals released in response to the ingestion of food require supportive signalling from the presence of food in the stomach. The degree of supportive volume signalling emanating from the stomach influences both the satiation and satiety phases. The Lipids and Volume in Satiation and Satiety (LIVES) Hypothesis proposes that the biological feedback from fat intake appears to be influenced by the other macronutrients with which it is consumed. By identifying the various possible macronutrient combinations with fat, it is possible to construct a matrix of food composition/volume scenarios, which may help elucidate dysfunction in the human food energy regulation system within the context of the modern food environment.
A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network
Authors: Ishimaru Momoko , Okada Yoshifumi , Uchiyama Ryunosuke , Horiguchi Ryo , Toyoshima Itsuki
Published: February 2023

Recent studies have revealed mutually correlated audio features in the voices of depressed patients. Thus, the voices of these patients can be characterized based on the combinatorial relationships among the audio features. To date, many deep learning–based methods have been proposed to predict the depression severity using audio data. However, existing methods have assumed that the individual audio features are independent. Hence, in this paper, we propose a new deep learning–based regression model that allows for the prediction of depression severity on the basis of the correlation among audio features. The proposed model was developed using a graph convolutional neural network. This model trains the voice characteristics using graph-structured data generated to express the correlation among audio features. We conducted prediction experiments on depression severity using the DAIC-WOZ dataset employed in several previous studies. The experimental results showed that the proposed model achieved a root mean square error (RMSE) of 2.15, a mean absolute error (MAE) of 1.25, and a symmetric mean absolute percentage error of 50.96%. Notably, RMSE and MAE significantly outperformed the existing state-of-the-art prediction methods. From these results, we conclude that the proposed model can be a promising tool for depression diagnosis.
Communication Manager for Hyper-Connected RPAS Environments
Authors: Sanchez-Aguero Victor , Valera Francisco , Vidal Ivan , Nogales Borja
Published: February 2023

The revolution of Remotely Piloted Aircraft Systems (RPASs), both in the commercial and the research field, has accelerated the arrival of innovative and complex services to the civilian environment within non-segregated airspace. The extensive deployment of these services will still require solving relevant challenges in several topics, such as regulation, security, or diverse technical defiance. In particular, the services to be provided increasingly demand network resources and performance improvements. This scenario will be strongly exacerbated by the upcoming resources provided by the 5G/6G architectures, where Remotely Piloted Aircrafts (RPAs) will likely support multiple communication interfaces and will be able to establish multi-hop network connectivity with numerous devices leading to an unprecedented hyper-connected RPA environment. In addition, future RPASs will have to enhance the management of their connectivity capabilities to comply with the latest regulations, which demand an uninterrupted link for the Control and Non-Payload Communications (CNPC). This article presents a flexible Communication Infrastructure Manager (CIM) based on Software-Defined Networking (SDN) and virtualization technologies capable of handling the complexity inherent to this ecosystem and being adapted to different operation requirements to cope with all these communication challenges. Finally, the article shows several validation experiences to demonstrate the potential of the CIM versus the standard approach.
Change-Point Detection in a High-Dimensional Multinomial Sequence Based on Mutual Information
Authors: Xiang Xinrong , Jin Baisuo , Wu Yuehua
Published: February 2023

Time-series data often have an abrupt structure change at an unknown location. This paper proposes a new statistic to test the existence of a change-point in a multinomial sequence, where the number of categories is comparable with the sample size as it tends to infinity. To construct this statistic, the pre-classification is implemented first; then, it is given based on the mutual information between the data and the locations from the pre-classification. Note that this statistic can also be used to estimate the position of the change-point. Under certain conditions, the proposed statistic is asymptotically normally distributed under the null hypothesis and consistent under the alternative hypothesis. Simulation results show the high power of the test based on the proposed statistic and the high accuracy of the estimate. The proposed method is also illustrated with a real example of physical examination data.
Design and Analysis of Joint Group Shuffled Scheduling Decoding Algorithm for Double LDPC Codes System
Authors: Chen Qiwang , Ren Yanzhao , Zhou Lin , Chen Chen , Liu Sanya
Published: February 2023

In this paper, a joint group shuffled scheduling decoding (JGSSD) algorithm for a joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is presented. The proposed algorithm considers the D-LDPC coding structure as a whole and applies shuffled scheduling to each group; the grouping relies on the types or the length of the variable nodes (VNs). By comparison, the conventional shuffled scheduling decoding algorithm can be regarded as a special case of this proposed algorithm. A novel joint extrinsic information transfer (JEXIT) algorithm for the D-LDPC codes system with the JGSSD algorithm is proposed, by which the source and channel decoding are calculated with different grouping strategies to analyze the effects of the grouping strategy. Simulation results and comparisons verify the superiority of the JGSSD algorithm, which can adaptively trade off the decoding performance, complexity and latency.
Design and Application of Deep Hash Embedding Algorithm with Fusion Entity Attribute Information
Authors: Huang Xiaoli , Chen Haibo , Zhang Zheng
Published: February 2023

Hash is one of the most widely used methods for computing efficiency and storage efficiency. With the development of deep learning, the deep hash method shows more advantages than traditional methods. This paper proposes a method to convert entities with attribute information into embedded vectors (FPHD). The design uses the hash method to quickly extract entity features, and uses a deep neural network to learn the implicit association between entity features. This design solves two main problems in large-scale dynamic data addition: (1) The linear growth of the size of the embedded vector table and the size of the vocabulary table leads to huge memory consumption. (2) It is difficult to deal with the problem of adding new entities to the retraining model. Finally, taking the movie data as an example, this paper introduces the encoding method and the specific algorithm flow in detail, and realizes the effect of rapid reuse of dynamic addition data model. Compared with three existing embedding algorithms that can fuse entity attribute information, the deep hash embedding algorithm proposed in this paper has significantly improved in time complexity and space complexity.
Awareness and Adoption of Evidence-Based Instructional Practices by STEM Faculty in the UAE and USA
Authors: Albuquerque Melinda Joy Biggs , Awadalla Dina Mustafa Mohammad , de Albuquerque Francisco Daniel Benicio , Aly Hassan Ashraf
Published: February 2023

There has been a widespread call for improvement in undergraduate STEM education, leading to what are known as evidence-based instructional practices (EBIPs). However, EBIP usage in STEM is a more recent phenomenon in the United Arab Emirates, which is historically known for its passive teaching practices but is now taking strides to transform its educational system. This study sought to assess (i) STEM faculty EBIP awareness, adoption, and ease-of-implementation perceptions from STEM faculty at a leading university in the United Arab Emirates and the demographic factors correlated with faculty responses, and (ii) the contextual factors that influence faculty EBIP adoption. Data was compared to that of STEM faculty at a top-tier research and teaching university in the United States of America. Finally, this study sought to provide a snapshot of current STEM faculty teaching practices when both a leader (United States of America) and a newcomer (United Arab Emirates) in STEM EBIPs were considered. A survey containing 16 teaching practices—3 traditional, 13 EBIPs—along with 20 contextual factors was developed and completed by faculty. EBIP awareness and usage were positively affected by time spent on teaching, teaching experience, and teaching workshop participation, and negatively affected by more class time spent lecturing. Significant contextual factors point to potential factors for consideration in efforts to improve EBIP adoption.
A Multi-Channel Contrastive Learning Network Based Intrusion Detection Method
Authors: Luo Jian , Zhang Yiying , Wu Yannian , Xu Yao , Guo Xiaoyan , Shang Boxiang
Published: February 2023

Network intrusion data are characterized by high feature dimensionality, extreme category imbalance, and complex nonlinear relationships between features and categories. The actual detection accuracy of existing supervised intrusion-detection models performs poorly. To address this problem, this paper proposes a multi-channel contrastive learning network-based intrusion-detection method (MCLDM), which combines feature learning in the multi-channel supervised contrastive learning stage and feature extraction in the multi-channel unsupervised contrastive learning stage to train an effective intrusion-detection model. The objective is to research whether feature enrichment and the use of contrastive learning for specific classes of network intrusion data can improve the accuracy of the model. The model is based on an autoencoder to achieve feature reconstruction with supervised contrastive learning and for implementing multi-channel data reconstruction. In the next stage of unsupervised contrastive learning, the extraction of features is implemented using triplet convolutional neural networks (TCNN) to achieve the classification of intrusion data. Through experimental analysis, the multichannel contrastive learning network-based intrusion-detection method achieves 98.43% accuracy in dataset CICIDS17 and 93.94% accuracy in dataset KDDCUP99.
CAE-Net: Cross-Modal Attention Enhancement Network for RGB-T Salient Object Detection
Authors: Lv Chengtao , Wan Bin , Zhou Xiaofei , Sun Yaoqi , Hu Ji , Zhang Jiyong , Yan Chenggang
Published: February 2023

RGB salient object detection (SOD) performs poorly in low-contrast and complex background scenes. Fortunately, the thermal infrared image can capture the heat distribution of scenes as complementary information to the RGB image, so the RGB-T SOD has recently attracted more and more attention. Many researchers have committed to accelerating the development of RGB-T SOD, but some problems still remain to be solved. For example, the defective sample and interfering information contained in the RGB or thermal image hinder the model from learning proper saliency features, meanwhile the low-level features with noisy information result in incomplete salient objects or false positive detection. To solve these problems, we design a cross-modal attention enhancement network (CAE-Net). First, we concretely design a cross-modal fusion (CMF) module to fuse cross-modal features, where the cross-attention unit (CAU) is employed to enhance the two modal features, and channel attention is used to dynamically weigh and fuse the two modal features. Then, we design the joint-modality decoder (JMD) to fuse cross-level features, where the low-level features are purified by higher level features, and multi-scale features are sufficiently integrated. Besides, we add two single-modality decoder (SMD) branches to preserve more modality-specific information. Finally, we employ a multi-stream fusion (MSF) module to fuse three decoders’ features. Comprehensive experiments are conducted on three RGB-T datasets, and the results show that our CAE-Net is comparable to the other methods.
A Fully Differential Difference Transconductance Amplifier Topology Based on CMOS Inverters
Authors: Silva Otávio Soares , Braga Rodrigo Aparecido da Silva , Pinto Paulo Marcos , Ferreira Luís Henrique de Carvalho , Colletta Gustavo Della
Published: February 2023

This manuscript presents a fully differential difference transconductance amplifier (FDDTA) architecture based on CMOS inverters. Designed in a 130-nm CMOS process it operates in weak inversion when supplied with 0.25 V. In addition, the FDDTA requires no supplementary external calibration circuit, like tail current or bias voltage sources, since it relies on the distributed layout technique that intrinsically matches the CMOS inverters. For analytical purposes, we carried out a detailed investigation that describes all the concepts and the whole operation of the FDDTA architecture. Furthermore, a comparison between the modeling equations and measured data assures high performance.
Water Energy Nexus and Energy Transition—A Review
Authors: Helerea Elena , Calin Marius D. , Musuroi Cristian
Published: February 2023

The new perspectives of the water–energy nexus, water-for-energy and energy-for-water, emphasize the current and future need to find ways to produce as much energy with as low an amount of water as possible and to obtain as much water with as little energy as possible. In order to promote and implement the concept of sustainable development, the understanding of the dynamic and complex relationship between water and energy is crucial, especially in the context of energy transition. This paper presents a comprehensive analysis of the recent approaches regarding water and energy and the interlink during implementation, operation and servicing of various water and energy production systems. This endeavor is placed in the context of current energy transition from fossil fuels to renewable energy sources. A qualitative and quantitative analysis is performed with various literature solutions from water-for-energy and energy-for-water perspectives for a broader view of the impact of implementing novel technologies in terms of resource use. Technological and managerial innovations are discussed and placed in a transdisciplinary context with a focus on establishing key approaches for achieving sustainable development goals.
A Comprehensive Review of Power Converters for E-Mobility
Authors: Nkembi Armel Asongu , Cova Paolo , Sacchi Emilio , Coraggioso Emanuele , Delmonte Nicola
Published: February 2023

The penetration of electric vehicles is becoming more and more widespread and recently electric buses and trains are fetching the attention of researchers and developers. In this review, we examine the charging systems applied to the fast charging of electric vehicles and buses as well as the charging strategies, mainly applied to electric buses. We also briefly delve into power topologies for a more electrified railway system where we discuss their different supply systems as well as their motor drive systems. Problems and charge challenges for electric buses and trains are discussed too.
Experimental Investigation on the Deformation Characteristics and Mechanical Behaviors of Tectonic Coal under Complex Unloading Confining Pressure
Authors: Gao Deyi , Sang Shuxun , Liu Shiqi , Wang Wenkai , Mo Hang
Published: February 2023

Conventional and cyclic unloading tests with different unloading rates were conducted to study the influences of unloading patterns and rates on the deformation characteristics and mechanical properties of tectonic coal. The results demonstrate that, under continuous unloading, a lower unloading rate promotes an increase in the circumferential strain but inhibits increases in axial strain. A lower unloading rate was found to be able to promote volume expansion under the cyclic unloading path, and the axial, circumferential, and volume strains increased stepwise with the unloading levels, but the increment of the strains decreased with the number of cycles in the same unloading level. It was easier for tectonic coal to reach the elastic limit by a low speed unloading rate when the unloading level was small, and volume dilatation was promoted when the unloading level was large. In both unloading patterns, the tangential modulus and the Poisson ratio were proportional to the unloading rate. Compared with continuous unloading, the cyclic unloading pattern was found to have a significant delaying and inhibiting effect on damage expansion, and thus higher mechanical strength and more structurally stable tectonic coal responses were observed.
Blanket Cooling of a Fusion Reactor
Authors: Beaufait Robert , Fischer Ludger
Published: February 2023

Nuclear fusion is the gateway to a whole new paradigm of energy and is a strong candidate for the decarbonization of electricity generation on a global scale. With recent developments in high-temperature super-conducting magnets, the race is on to develop sub-systems which will support a commercially viable fusion reactor for use as a thermal power plant. The fusion of lighter elements creates an enormous amount of heat which must be transferred away from the reactor core. These intense conditions require novel approaches to efficiently transfer very high heat loads into useable thermal energy without compromising the structural integrity of the reactor core and the surrounding components. This report outlines the concept of a fundamental approach to solve the heat transfer problem as proposed by Commonwealth Fusion System’s design for a fusion reactor. A literature review was conducted for other applications that could serve as inspirations, as well as material properties and machining methods for the proposed power exhaust system. A dive into the theoretical thermodynamic and fluid dynamic characteristics of plate heat exchangers and finned surfaces was conducted from a fundamental perspective. A laminar flow regime was studied for the purpose of setting the floor for energy needed to pump coolant while simultaneously representing the least favorable heat transfer regime between a solid surface and a fluid. The results served as a basis for dimensioning and executing numerical simulations as a means for a first look into a solution of this heat transfer problem. The results were compared with the theoretical conclusions and judged based on constraints of the system. Recommendations were made for the continued development of a corresponding system.
On State Estimation Modeling of Smart Distribution Networks: A Technical Review
Authors: Xu Junjun , Jin Yulong , Zheng Tao , Meng Gaojun
Published: February 2023

State estimation (SE) is regarded as an essential tool for achieving the secure and efficient operation of distribution networks, and extensive research on SE has been conducted over the past three decades. Nonetheless, the high penetration of distribution generations (DGs) is accompanied by uncertainties and dynamics, and the extensive application of intelligent electronic devices (IEDs) is associated with data processing issues, all of which raise new challenges, and these issues must be taken care of for further development of SE in smart distribution networks. This paper attempts to present a comprehensive literature review of numerous works that address various issues in SE, examining key technical research issues and future perspectives. Hopefully, it will be able to meet the needs for the development of smart distribution networks.
Parameter Identification of Asynchronous Load Nodes
Authors: Kryukov Andrey , Suslov Konstantin , Ilyushin Pavel , Akhmetshin Azat
Published: February 2023

Asynchronous loads (AL), because of their low negative-sequence resistance, produce the effect of reduced unbalance at their connection points. Therefore, proper modeling of unbalanced load flows in power supply systems requires properly accounting for AL. Adequate models of the induction motor can be realized in the phase frame of reference. The effective use of such models is possible only if accurate data on the parameters of induction motor equivalent circuits for positive and negative sequences are available. Our analysis shows that the techniques used to determine these parameters on the basis of reference data can yield markedly disparate results. It is possible to overcome this difficulty by applying parameter identification methods that use the phase frame of reference. The paper proposes a technique for parameter identification of models of individual induction motors and asynchronous load nodes. The results of computer-aided simulation allow us to conclude that by using parameter identification, we can obtain an equivalent model of an asynchronous load node, and such a model provides high accuracy for both balanced and unbalanced load flow analysis. By varying load flow parameters, we demonstrate that the model proves valid over a wide range of their values. We have proposed a technique for the identification of asynchronous load nodes with such asynchronous loads, including electrical drives equipped with static frequency converters. With the aid of the AL identification models proposed in this paper, it is possible to solve the following practical tasks of management of electric power systems: increasing the accuracy of modeling their operating conditions; making informed decisions when taking measures to reduce unbalance in power grids while accounting for the balancing adjustment effect of AL.
Recent Advances on Alternative Aviation Fuels/Pathways: A Critical Review
Authors: Detsios Nikolaos , Theodoraki Stella , Maragoudaki Leda , Atsonios Konstantinos , Grammelis Panagiotis , Orfanoudakis Nikolaos G.
Published: February 2023

The Paris Agreement’s objectives related to climate change put aviation under great pressure and environmental inspection. In particular, the aviation industry is committed to achieving a 50% reduction in CO2 emissions by 2050 compared to 2005 levels. A shift to alternative aviation fuels seems imperative. The International Air Transport Association (IATA) has identified the production of drop-in sustainable liquid fuels (SAFs) as the most promising strategy, at least short term, to reduce the environmental impact of the sector. Within this review, a critical summary of the current alternative aviation fuels/pathways is presented and a comparative analysis of the dominant technologies is performed considering techno-economic assessment, environmental evaluation, and future projections. The impact of the ‘ReFuelEU Aviation’ initiative on the current dominant policies and market incentives is assessed. Hydroprocessed esters and fatty acids (HEFA), Fischer–Tropsch (FT) synthesis, alcohol-to-jet (AtJ) conversion, and e-fuel pathways are put under the microscope. A wide range of potential fuel selling prices (0.81–5.00 EUR/L) was observed due to the presence of multiple routes, while some pathways seem able to secure more than 90% emission savings compared to the fossil jet reference. The accelerated scale-up of SAF production is a reasonable demand for the aviation industry. The establishment of a sustainable scale-up framework and the alignment of all of the involved aviation stakeholders is an immediate challenge.
Flexible and Low-Cost Emulation of Control Behaviors for Testing and Teaching of AC Microgrid
Authors: Wang Jiashi , Liu Tingting , Ma Ke
Published: February 2023

The fast development of distributed generations enables the microgrid a popular solution for the construction of the modern power grid, where the control behaviors of power electronics converters play a crucial role. Under this scenario, the emulation of microgrid control behaviors is becoming an emerging need for the testing and teaching of the AC microgrid. However, conventional approaches, such as the dynamic simulation test and the Power-Hardware-In-Loop, are still costly or bulky to flexibly recreate the correct characteristics of microgrid including different layers of controls and the interactions among multiple converters. The dynamic simulation test is bulky and costly to emulate various types of control behaviors since all physical components in the test system may need to be adjusted. The high cost of Power-Hardware-In-Loop is mainly caused by the high-performance real-time simulator and power amplifier. In this paper, a novel emulation system is proposed for the testing of the AC microgrid. A low-cost circuit configuration, which includes two face-to-face connected DC–AC converters and some passive loads, is introduced with the possibility of flexibly emulating most of the typical control schemes in an AC microgrid. In addition, a user interface for the real-time operation and measurement of the hardware platform is introduced on a host computer to further facilitate the testing process. Finally, various control schemes in microgrids, including the voltage control, current control, droop control, and secondary control, are validated in the experiment setup based on the proposed emulation approach.
Ensemble-Learning-Based Decision Support System for Energy-Theft Detection in Smart-Grid Environment
Authors: Mohammad Farah , Saleem Kashif , Al-Muhtadi Jalal
Published: February 2023

Theft of electricity poses a significant risk to the public and is the most costly non-technical loss for an electrical supplier. In addition to affecting the quality of the energy supply and the strain on the power grid, fraudulent electricity use drives up prices for honest customers and creates a ripple effect on the economy. Using data-analysis tools, smart grids may drastically reduce this waste. Smart-grid technology produces much information, including consumers’ unique electricity-use patterns. By analyzing this information, machine-learning and deep-learning methods may successfully pinpoint those who engage in energy theft. This study presents an ensemble-learning-based system for detecting energy theft using a hybrid approach. The proposed approach uses a machine-learning-based ensemble model based on a majority voting strategy. This work aims to develop a smart-grid information-security decision support system. This study employed a theft-detection dataset to facilitate automatic theft recognition in a smart-grid environment (TDD2022). The dataset consists of six separate electricity thefts. The experiments are performed in four different scenarios. The proposed machine-learning-based ensemble model obtained significant results in all scenarios. The proposed ensemble model obtained the highest accuracy of 88%, 87.24%, 94.75%, and 94.70% with seven classes including the consumer type, seven classes excluding the consumer type, six classes including the consumer type, and six classes excluding the consumer type. The suggested ensemble model outperforms the existing techniques in terms of accuracy when the proposed methodology is compared to state-of-the-art approaches.
Techno-Economic and Environmental Assessment of a Hybrid Renewable Energy System for a Hospital Using Multi-Criteria Decision-Making Method
Authors: Peirow Setare , Razi Astaraei Fatemeh , Saifoddin Asl Amirali
Published: February 2023

Implementing hybrid renewable energy systems in hospitals, as an applicable solution to improve the sustainability of power systems, was studied. Several hybrid renewable configurations with detailed technical and economic information were proposed by HOMER Pro software, and the most cost-effective system was introduced as a combination of PV (350 kW), WT (1 unit, 25 kW), and DG (700 kW), with a total net present cost of USD 3.25 million and cost of energy of USD 0.0543/kWh. To consider all aspects of sustainability for choosing the optimal system, a Multi-Criteria Decision-Making approach, considering technical, environmental, economic, and energy security criteria, was applied using the TOPSIS method. According to ISO 21929, the weighting of the criteria was performed depending on how indicators affected the key areas of protection. By using the TOPSIS technique, a system with a larger renewable proportion, more variety, and less reliance on diesel was chosen. Thus, the optimal choice for this process was the configuration of PV (350 kW)/WT (1 unit, 25 kW)/DG (600 kW)/Bat (100 kWh). Comparing the results of economic optimization with MCDM optimization shows that the COE increased by approximately USD 0.025/kWh in the MCDM approach, while a decline of more than 27% in environmental impacts, as well as reduced reliance on conventional resources, were achieved.
Review on Soft Computing-Based Controllers for Frequency Regulation of Diverse Traditional, Hybrid, and Future Power Systems
Authors: Singh Balvender , Slowik Adam , Bishnoi Shree Krishan
Published: February 2023

In recent decades the power system has become a complex network, to design a load frequency control (LFC) requires solving a complex equation. Optimisation techniques are essentially required to optimise the parameters of different controllers used for LFC issues in the power system. In a unified power system, the LFC is examined from all angles using different optimisation strategies to optimise the conventional PI, PID, cascaded, and fuzzy controllers as well as recently designed controllers. This manuscript specifically reviews the use of soft computing techniques in the frequency regulation of the power system with single/multiple areas that include conventional, renewable, and combinations of both, with FACTS devices and certain energy storage devices such as superconductor magnetic energy storage (SMES) and battery sources. Furthermore, deregulated power systems and microgrids are also considered for the study. To regulate LFC under various disturbances such as generation rate constraints (GRC) and dead band control, a few additional control approaches are utilised. Models of the power system are discussed and analysed. In addition, the merits and drawbacks of the studied techniques/structures that address design and implementation issues—as well as control issues that relate to the LFC problems—have been discussed.
A Comparison of Grid-Connected Local Hospital Loads with Typical Backup Systems and Renewable Energy System Based Ad Hoc Microgrids for Enhancing the Resilience of the System
Authors: Ali Majid , Vasquez Juan C. , Guerrero Josep M. , Guan Yajuan , Golestan Saeed , De La Cruz Jorge , Koondhar Mohsin Ali , Khan Baseem
Published: February 2023

Extreme weather conditions and natural disasters (ND) are the main causes of power outages in the electric grid. It is necessary to strengthen the electrical power system’s resilience during these catastrophic occurrences, and microgrids may be seen as the best way to achieve this goal. In this paper, two different energy system scenarios were proposed for increasing the resiliency of the electric power system during random outages. In the first scenario, a diesel generator (DG) was used to deliver energy to key loads during grid disruptions, in conjunction with a utility electric grid (UEG) and local electric load (ELL). A grid-connected ad hoc microgrid (MG) with a photovoltaic (PV) system, a battery energy storage (BES) system, and local electric loads made up the second scenario. The PV system and the BES system were used to supply the key loads with electricity during the outage. The major aim of this research was to compare the two resilient-based systems from the perspectives of technology, economics, and the environment. Given that it requires greater resilience than the other loads during severe weather, a hospital load on Indonesia’s Lombok Island was chosen as the critical load. The objective function considers the system’s predefined constraints to reduce the overall net present cost (NPC) and the cost of energy in order to maximize the system resilience (COE). The Optimization of Multiple Energy Resources (HOMER) Grid simulated a 3-day outage in August 2021, and the results demonstrated that the resiliency enhancement for both scenarios was nearly identical. The first scenario resulted in fewer CO2 emissions; however, the second scenario delivered lower operating costs and COE. The simulation’s findings showed that system 1 created an annual emission of 216.902 kg/yr while system 2 only produced an emission of 63.292 kg/yr. This study shows that since RES-based MGs don’t burn fossil fuels to generate power, they are more environmentally friendly resources.
Energy Intensity, Energy Efficiency and Economic Growth among OECD Nations from 2000 to 2019
Authors: Sueyoshi Toshiyuki , Goto Mika
Published: February 2023

This study examines the energy intensity (EI), energy efficiency (EE), and economic growth, measured by the type of returns to scale (RTS), of 37 nations in the Organization for Economic Co-operation and Development (OECD) from 2000 to 2019. We apply a non-parametric approach to estimate the three measures from their consumption of four primary energy sources, such as coal, gas, oil, and zero emission (e.g., renewable and nuclear power) as inputs and gross domestic product (GDP) as an output. In this study, we have the two types of efficiency measures over time: window-based and cross-sectional-based measures. Three findings are identified from our empirical study. First, the operationally efficient group, including France, Iceland, Japan, Switzerland, UK, and USA, presented a stable status of full efficiency in the window-based efficiency measure. Iceland and Switzerland were also in the higher efficiency group based on the cross-sectional measure. Their efficiencies were high and stable over the observed periods. Second, zero-carbon-emission (e.g., renewable and nuclear) energies outperformed other energy sources (coal, gas, and oil) in terms of a potentiality of EI/EE improvement. In other words, OECD nations can improve on their EI/EE measures by reducing fuel consumption of coal, gas, and oil while maintaining their high GDP levels. Finally, four industrial nations (France, Japan, UK, and USA) had a status of unity in their EI/EE measures for zero-carbon-emission energies with decreasing RTS. These nations would increase zero-carbon emission for energy consumption to increase GDP while keeping optimal EI/EE because such changes in consumption would not largely affect EI/EE due to their constant RTS status. Iceland showed increasing RTS. The nation may improve the EI level by increasing zero-carbon-emission energy consumption and economic size. The four nations can increase zero-emission energy consumption to achieve further economic growth without observing a large deterioration of EI/EE because it is very close to constant RTS. The examination of RTS provides policy directions for the improvement of EI and EE. Switzerland showed decreasing RTS and may deteriorate the EI/EE by increasing energy consumption and the size of each economy. The remaining countries, whose degree of EI/EE measures was less than unity, showed increasing or decreasing RTS. The examination of RTS provides important implications for energy policy to enhance the degree of EI/ EE.
Predictive Controller Based on Paraconsistent Annotated Logic for Synchronous Generator Excitation Control
Authors: Da Silva Filho João Inácio , de Oliveira Raphael Adamelk Bispo , Rodrigues Marcos Carneiro , Côrtes Hyghor Miranda , Rocco Alexandre , Mario Mauricio Conceição , Garcia Dorotéa Vilanova , Abe Jair Minoro , Torres Claudio Rodrigo , Ricciotti Viviane B. Duarte , Ricciotti Antonio Carlos Duarte , de Carvalho Arnaldo , Lambert-Torres Germano
Published: February 2023

This study presents a new Model Predictive Controller (MPC), built with algorithms based on Paraconsistent Annotated Logic (PAL), with application examples in the excitation control of a synchronous generator. PAL is a non-classical evidential and propositional logic that is associated with a Hasse lattice, and which presents the property of accepting the contradiction in its foundations. In this research, the algorithm was constructed with a version of the PAL that works with two information signals in the degrees of evidence format and, therefore, is called Paraconsistent Annotated Logic with annotation of two values (PAL2v). For the validation of the algorithmic structure, the computational tool MATLAB® Release 2012b, The MathWorks, Inc., Natick, MA, United States was used. Simulations were performed which compared the results obtained with PPC-PAL2v to those obtained in essays with the AVR (Automatic Voltage Regulator) controls in conjunction with the PSS (Power System Stabilizer) and the conventional MPC of fixed weights. The comparative results showed the PPC-PAL2v to display superior performance in the action of the excitation control of the synchronous generator, with a great efficiency in response to small signals.
Energy Saving Practices in the IT Area as a Factor of Sustainable Development of the Organization: A Case Study of Poland
Authors: Kwasek Artur , Maciaszczyk Magdalena , Kocot Maria , Rzepka Agnieszka , Kocot Damian , Gąsiński Hubert , Prokopowicz Dariusz
Published: February 2023

Today’s company has to operate in a turbulent market environment, where the policy of sustainable development is still gaining importance. Therefore, it has been forced to look for a strategic orientation that would allow it to face the growing demands of the changing reality. Each organization must therefore adapt to the changes in the environment. These changes include the need to implement sustainable energy usage practices. This article presents determinants that build such an attitude in a company and thus contribute to the sustainable development of the organization. This article is based on the results of an empirical study conducted in December 2021 on a sample of 690 respondents (later, due to the purpose of the study, the sample was narrowed to 578 working people) using a survey questionnaire. A structural model was estimated using the maximum likelihood method. It allowed us to determine the variables that influence the degree to which companies use energy saving practices, as well as to illustrate the strength of influence between endogenous variables. Establishing these relationships will allow us to determine the factors that are determinants of the implementation of the idea of sustainable development in the company.
Deterioration of Microstructures and Properties in Ancient Architectural Wood from Yingxian Wooden Pagoda (1056 AD) during Natural Aging
Authors: Long Keying , Chen Kaiqiang , Lin Lanying , Fu Feng , Zhong Yong
Published: February 2023

The Yingxian Wooden Pagoda (1056 AD), located in Shanxi province, China, is a unique architectural pure-wooden artifact standing for a millennium. Despite its longevity, the structures and properties of the ancient architectural woods used in its construction have been significantly degraded due to long-term natural aging, which has profoundly impacted the preservation of this valuable cultural heritage. To better understand this degradation, we studied the deterioration of a baluster (Larix principis-rupprechtii Mayr.) from Yingxian Wooden Pagoda. The study employed various analytical techniques, including optical microscopy, atomic force microscopy, Fourier-transform infrared spectroscopy, solid-state 13C nuclear magnetic resonance spectroscopy, X-ray diffraction, and nanoindentation technology, to evaluate the microstructures and properties of the ancient architectural woods. Results indicated that the destruction of wood cell walls was primarily transverse transwall destruction and interfacial debonding and that the degradation of chemical components was primarily in the hemicellulose (xylan) and amorphous region of cellulose. The reduced elastic modulus and hardness of tracheid cell walls in the ancient architectural woods were higher than in recent larch woods. This study would help deepen understanding of wood deterioration during long-term natural aging for the subsequent preservation and protection of wooden cultural heritages and longer use of ancient timber constructions.
Critical Factors Affecting Fire Safety in High-Rise Buildings in the Emirate of Sharjah, UAE
Authors: Omar Musab , Mahmoud Abdelgadir , Abdul Aziz Sa’ardin Bin
Published: February 2023

The purpose of this paper is to identify the critical factors affecting fire accidents in high-rise residential buildings in the Emirate of Sharjah in order to find solutions that contribute to reducing injuries and deaths from fire accidents. A large urban expansion of the Emirate of Sharjah has taken place in the form of high-rise buildings, and the Emirate is now third in the UAE in terms of the number of high-rise buildings and is home to 19% of the population. As a consequence, an increase in the rate of fire accidents has also been observed. As such, there is a need to conduct research on enhancing fire safety in high-rise buildings by conducting a literature review, in which nineteen factors affecting fire globally were identified. Because the fire characteristic is unique in every country, to identify the nature of fire in the Emirate of Sharjah, we consulted sixteen subject matter experts in the field of fire in the Emirate of Sharjah to identify the factors applicable to the Emirate. We used the failure mode, effect, and criticality analysis methodology to accomplish this goal. The outcome of the consultations resulted in the three main factor categories, which are management factors, human factors, and technical factors, and the critical factors affecting the high-rise buildings in the Emirate of Sharjah were identified, which are: fire regulations, fire enforcement regulations, accident investigation, rescue speed, human behavior, lack of proper maintenance, fire training, building design, fire knowledge, combustible materials, fire culture of society, and urbanization. Using the Analytical Hierarchy Process (AHP) tools implemented to measure the effect level of the sub-critical fire factors, 45 effects were identified, and the most common effects were: the building is fully covered by cladding, the effect of stopping activities in HRBs that are non-compliant with fire regulations, the residents practice activities related to fire knowledge, fire regulations efficiency, the training of new employees by their employers, and the residents have fire-related knowledge.
Fish Viscera Silage: Production, Characterization, and Digestibility of Nutrients and Energy for Tambaqui Juveniles
Authors: Santana Thiago Macedo , Dantas Francisco de Matos , Monteiro Dos Santos Driely Kathriny , Kojima Juliana Tomomi , Pastrana Yugo Moraes , De Jesus Rogério Souza , Gonçalves Ligia Uribe
Published: February 2023

Fish viscera can be an important source of protein and energy for aquafeed, and its use contributes to circular aquaculture. The aim of this study was to produce acid and fermented silage from fish viscera to determine their nutritional value and the apparent digestibility coefficient of nutrients and energy for juvenile tambaqui (Colossoma macropomum). An acid silage and three fermented silages with different sources of carbohydrates (molasses, wheat bran, and cassava waste) were produced with 0.25% sorbic acid as an antifungal in the formulation. Silages presented an average of 55% dry matter, 62.9% lipids, and 12% crude protein. Leucine and lysine predominated as essential amino acids in the acid silage and fermented silages. Fish viscera silages presented EPA and DHA content from 5.4 to 17.8 and 1.7 to 8.9 mg.g−1 of lipids, respectively. The apparent digestibility coefficient (ADC) (indirect method) was above 82% for gross energy for all the formulations. The ADCs for protein were similar for the fermented silages, with a maximum 92% level for the fermented wheat bran silage. The bioconversion of fish viscera into silage makes it an energy ingredient for aquafeed that is well digested by tambaqui juveniles.