bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Tissue Damage Using a User-Independent Machine Learning Algorithm vs. Tmax Threshold Maps
Authors: Hakim Arsany , Messerli Benjamin , Meier Raphael , Dobrocky Tomas , Bellwald Sebastian , Jung Simon , McKinley Richard , Wiest Roland
Published: November 2021

(1) Background: To test the accuracy of a fully automated stroke tissue estimation algorithm (FASTER) to predict final lesion volumes in an independent dataset in patients with acute stroke; (2) Methods: Tissue-at-risk prediction was performed in 31 stroke patients presenting with a proximal middle cerebral artery occlusion. FDA-cleared perfusion software using the AHA recommendation for the Tmax threshold delay was tested against a prediction algorithm trained on an independent perfusion software using artificial intelligence (FASTER). Following our endovascular strategy to consequently achieve TICI 3 outcome, we compared patients with complete reperfusion (TICI 3) vs. no reperfusion (TICI 0) after mechanical thrombectomy. Final infarct volume was determined on a routine follow-up MRI or CT at 90 days after the stroke; (3) Results: Compared to the reference standard (infarct volume after 90 days), the decision forest algorithm overestimated the final infarct volume in patients without reperfusion. Underestimation was observed if patients were completely reperfused. In cases where the FDA-cleared segmentation was not interpretable due to improper definitions of the arterial input function, the decision forest provided reliable results; (4) Conclusions: The prediction accuracy of automated tissue estimation depends on (i) success of reperfusion, (ii) infarct size, and (iii) software-related factors introduced by the training sample. A principal advantage of machine learning algorithms is their improved robustness to artifacts in comparison to solely threshold-based model-dependent software. Validation on independent datasets remains a crucial condition for clinical implementations of decision support systems in stroke imaging.
Algae and Cyanobacteria Diversity and Bioindication of Long-Term Changes in the Hula Nature Reserve, Israel
Authors: Barinova Sophia , Alster Alla
Published: November 2021

Lake Hula, the core of one of the most extensive wetland complexes in the Eastern Mediterranean, was drained in 1951–1958. However, about 350 hectares of papyrus marshes were allocated in the southwestern part of the previous lake and became the Hula Nature Reserve status, the first of two wetlands in Israel included in the Ramsar List of Wetlands of International Importance. The list of algae and cyanobacteria species of Lake Hula was compiled by us for the first time based on data from publications of 1938–1958, as well as our research in the Hula Nature Reserve, obtained within the framework of the monitoring program for 2007–2013. The list includes 225 species and intraspecies of algae and cyanobacteria belonging to eight phyla. The dynamics of the species richness of algae and cyanobacteria flora for 1938–2013 are shown. Species-bioindicators of water quality have been identified, and the change in their composition by ecological groups for a period of about a hundred years has been shown. Based on the species richness of algae communities, water quality indices were calculated with particular attention to changes in trophic status during the study period. The algae flora of Lake Hula and Hula Nature Reserve was found to be similar, but bioindication has revealed an increase in salinity and organic pollution in recent years.
Trends of Foodborne Diseases in Mississippi: Association with Racial and Economic Disparities
Authors: Akil Luma
Published: November 2021

Background: Foodborne diseases are a major source of concern in USA. These diseases are a burden on public health and significantly contribute to the cost of health care. There is an urgent need to understand the contributing factors for such outbreaks, especially in Mississippi (MS), an agricultural state with low socioeconomic status. Methods: Secondary data for the current study were obtained from the Mississippi State Department of Health (MSDH) Epidemiology department for the study period 2010–2018. Data were for individuals with reported foodborne diseases cases. The data were analyzed to determine the pathogens’ trend over time, the highest contributing pathogens to foodborne diseases, the significant geographical variation, and any significant differences in rates based on demographic variables. Results: Salmonella was the highest contributing pathogen to foodborne disease in MS. The study showed a seasonal variation in the trends of pathogens and a geographical variation, and no racial differences in the incidents of the foodborne diseases was observed. Conclusions: Incidence rates of foodborne illness remain high in the state of Mississippi. A better understanding of high levels of foodborne infections caused by Salmonella, Shigella, and Campylobacter resulting from cultural food handling practices or socioeconomic factors will allow to provide guidelines and food safety preventive measures.
Knowledge, Attitude, and Practices of Dentists in Caribbean Countries during the COVID-19 Pandemic: A Multicenter Cross-Sectional Study
Authors: Balkaran Ramaa , Bhat Meghashyam , Marchan Shivaughn , Smith William
Published: November 2021

Background: The COVID-19 pandemic has affected dentists globally, both financially and mentally. This study aimed to determine the knowledge, attitude, and practices of dentists in Caribbean countries during the COVID-19 pandemic. Methods: A non-probability sample was obtained from dentists in more than ten different Caribbean countries. They were invited to complete a self-reported questionnaire, which was conducted from December 2020 to March 2021. Ethics approval was sought and an exemption was received from the UWI ethics committee. Results: One hundred and fifty-two dentists responded. More than one-third (38.8%) were in the >35–45 age group, and 58.6% were females. Most (84.9%) were general dentists and 75% were stressed by the COVID-19 situation with 80.9% being affected financially. The majority, 94.7%, believed that the highest risk of transmission of COVID-19 was via aerosol-generating procedures and 87.5% were worried about contracting it clinically. The majority (69.1%) were willing to receive the vaccine, the main reason reported for vaccine hesitancy was due to the possible side effects (35.3%). Most (75%) consumed alcohol. When the locus of control was determined, 54.6% felt they were in control of protecting themselves while 52% felt that external factors controlled their lives. Conclusions: The findings suggest that most dentists in the Caribbean were knowledgeable about COVID-19 and followed current guidelines in their practice and were willing to receive the vaccine.
Summarizing Finite Mixture Model with Overlapping Quantification
Authors: Kyoya Shunki , Yamanishi Kenji
Published: November 2021

Finite mixture models are widely used for modeling and clustering data. When they are used for clustering, they are often interpreted by regarding each component as one cluster. However, this assumption may be invalid when the components overlap. It leads to the issue of analyzing such overlaps to correctly understand the models. The primary purpose of this paper is to establish a theoretical framework for interpreting the overlapping mixture models by estimating how they overlap, using measures of information such as entropy and mutual information. This is achieved by merging components to regard multiple components as one cluster and summarizing the merging results. First, we propose three conditions that any merging criterion should satisfy. Then, we investigate whether several existing merging criteria satisfy the conditions and modify them to fulfill more conditions. Second, we propose a novel concept named clustering summarization to evaluate the merging results. In it, we can quantify how overlapped and biased the clusters are, using mutual information-based criteria. Using artificial and real datasets, we empirically demonstrate that our methods of modifying criteria and summarizing results are effective for understanding the cluster structures. We therefore give a new view of interpretability/explainability for model-based clustering.
Relationship between Continuum of Hurst Exponents of Noise-like Time Series and the Cantor Set
Authors: Mariani Maria C. , Kubin William , Asante Peter K. , Guthrie Joe A. , Tweneboah Osei K.
Published: November 2021

In this paper, we have modified the Detrended Fluctuation Analysis (DFA) using the ternary Cantor set. We propose a modification of the DFA algorithm, Cantor DFA (CDFA), which uses the Cantor set theory of base 3 as a scale for segment sizes in the DFA algorithm. An investigation of the phenomena generated from the proof using real-world time series based on the theory of the Cantor set is also conducted. This new approach helps reduce the overestimation problem of the Hurst exponent of DFA by comparing it with its inverse relationship with α of the Truncated Lévy Flight (TLF). CDFA is also able to correctly predict the memory behavior of time series.
Bird Species Identification Using Spectrogram Based on Multi-Channel Fusion of DCNNs
Authors: Zhang Feiyu , Zhang Luyang , Chen Hongxiang , Xie Jiangjian
Published: November 2021

Deep convolutional neural networks (DCNNs) have achieved breakthrough performance on bird species identification using a spectrogram of bird vocalization. Aiming at the imbalance of the bird vocalization dataset, a single feature identification model (SFIM) with residual blocks and modified, weighted, cross-entropy function was proposed. To further improve the identification accuracy, two multi-channel fusion methods were built with three SFIMs. One of these fused the outputs of the feature extraction parts of three SFIMs (feature fusion mode), the other fused the outputs of the classifiers of three SFIMs (result fusion mode). The SFIMs were trained with three different kinds of spectrograms, which were calculated through short-time Fourier transform, mel-frequency cepstrum transform and chirplet transform, respectively. To overcome the shortage of the huge number of trainable model parameters, transfer learning was used in the multi-channel models. Using our own vocalization dataset as a sample set, it is found that the result fusion mode model outperforms the other proposed models, the best mean average precision (MAP) reaches 0.914. Choosing three durations of spectrograms, 100 ms, 300 ms and 500 ms for comparison, the results reveal that the 300 ms duration is the best for our own dataset. The duration is suggested to be determined based on the duration distribution of bird syllables. As for the performance with the training dataset of BirdCLEF2019, the highest classification mean average precision (cmAP) reached 0.135, which means the proposed model has certain generalization ability.
Understanding the Impact of Walkability, Population Density, and Population Size on COVID-19 Spread: A Pilot Study of the Early Contagion in the United States
Authors: Lima Fernando T. , Brown Nathan C. , Duarte José P.
Published: November 2021

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.
Importance of Official Geodata in Disaster Risk Management—Case Study of Croatia
Authors: Vučić Nikola , Cetl Vlado , Šantek Damir , Mađer Mario
Published: November 2021

Disaster risk management (DRM) has always been important, but nowadays, with the increasing number of disasters due to climate changes, it is becoming even more so. Every phase of DRM is heavily reliant on geodata. First of all, each disaster occurs at a specific location, and this location contains geodata, which can be used in DRM, e.g., cadastral data, GNSS data, aerial images, topographic data, elevation data, etc. Geodata are important for making faster and more accurate decisions in disaster situations. It is possible to collect these geodata from many different sources, e.g., the public sector, private sector and citizens. Nevertheless, official geodata coming from competent authorities should be the most accurate and reliable. In this paper, we investigate the importance of official geodata in DRM on several examples from recent disasters in Croatia. Official geodata produced by the Croatian State Geodetic Administration (SGA) were used in managing disasters such as floods, forest fires, earthquakes and war. Our research findings show that DRM is an area in which National Mapping and Cadastral Authorities (NMCAs) should focus more on collecting and sharing geodata and provide more dynamic and innovative products. In these challenging times, more and more geodata are becoming available from different sources, besides official ones. With this plethora of geodata, in order to be relevant and competitive, NMCAs must change their business models and offer more attractive and useful services in order to satisfy the increasing user needs and demands. This paper shows that the SGA in Croatia is on the path towards achieving this goal.
Multi-Monostatic Interferometric Radar with Radar Link for Bridge Monitoring
Authors: Miccinesi Lapo , Pieraccini Massimiliano , Beni Alessandra , Andries Ovidiu , Consumi Tommaso
Published: November 2021

In recent years, interferometric radars have been extensively used as sensors for static and dynamic monitoring of bridges. Generally speaking, a radar can only detect the displacement component along its view direction. As the movement of a real bridge or a large structure can be rather complex, this limitation can be a significant drawback in engineering practice. In order toovercome this limitation, in this article, a multi-monostatic interferometric radar with radio link is proposed. This radar is able to detect a second component of displacement using a transponder. The transponder is connected to the radar through a radio link. The radio link allows the installation of the transponder far away from the radar, and even in the opposite direction. The equipment is based on a MIMO radar, two transceivers for the radio link, and a transponder. The transceivers and the transponder are essentially two antennas and an amplifier system. The equipment is experimentally tested in controlled scenarios and in the case study of Indiano Bridge, Florence, Italy.
Predicting Out-of-Stock Using Machine Learning: An Application in a Retail Packaged Foods Manufacturing Company
Authors: Andaur Juan Manuel Rozas , Ruz Gonzalo A. , Goycoolea Marcos
Published: November 2021

For decades, Out-of-Stock (OOS) events have been a problem for retailers and manufacturers. In grocery retailing, an OOS event is used to characterize the condition in which customers do not find a certain commodity while attempting to buy it. This paper focuses on addressing this problem from a manufacturer’s perspective, conducting a case study in a retail packaged foods manufacturing company located in Latin America. We developed two machine learning based systems to detect OOS events automatically. The first is based on a single Random Forest classifier with balanced data, and the second is an ensemble of six different classification algorithms. We used transactional data from the manufacturer information system and physical audits. The novelty of this work is our use of new predictor variables of OOS events. The system was successfully implemented and tested in a retail packaged foods manufacturer company. By incorporating the new predictive variables in our Random Forest and Ensemble classifier, we were able to improve their system’s predictive power. In particular, the Random Forest classifier presented the best performance in a real-world setting, achieving a detection precision of 72% and identifying 68% of the total OOS events. Finally, the incorporation of our new predictor variables allowed us to improve the performance of the Random Forest by 0.24 points in the F-measure.
Power Conversion System Operation Algorithm for Efficient Energy Management of Microgrids
Authors: Na Kwang-Su , Lee Jeong , Kim Jun-Mo , Lee Yoon-Seong , Yi Junsin , Won Chung-Yuen
Published: November 2021

This paper investigates the operation of each power conversion system (PCS) for efficient energy management systems (EMSs) of microgrids (MGs). When MGs are linked to renewable energy sources (RESs), the reduction in power conversion efficiency can be minimized. Furthermore, energy storage systems (ESSs) are utilized to manage the surplus power of RESs. Thus, the present work presents a method to minimize the use of the existing power grid and increase the utilization rate of energy generated through RESs. To minimize the use of the existing power grid, a PCS operation method for photovoltaics (PV) and ESS used in MGs is proposed. PV, when it is directly connected as an intermittent energy source, induces voltage fluctuations in the distribution network. Thus, to overcome this shortcoming, this paper utilizes a system that connects PV and a distributed energy storage system (DESS). A PV-DESS integrated module is designed and controlled for tracking constant power. In addition, the DESS serves to compensate for the insufficient power generation of PV. The main energy storage systems (MESSs) used in MGs affect all aspects of the power management in the system. Because MGs perform their operations based on the capacity of the MESS, a PCS designed with a large capacity is utilized to stably operate the system. Because the MESS performs energy management through operations under various load conditions, it must have constant efficiency under all load conditions. Therefore, this paper proposes a PCS operation algorithm with constant efficiency for the MESS. Utilizing the operation algorithm of each PCS, this paper describes the efficient energy management of the MG and further proposes an algorithm for operating the existing power grid at the minimum level.
An Investigation of Clock Skew Using a Wirelength-Aware Floorplanning Process in the Pre-Placement Stages of MSV Layouts
Authors: Srinath B. , Verma Rajesh , Barnawi Abdulwasa Bakr , Raja Ramkumar , Muqeet Mohammed Abdul , Shukla Neeraj Kumar , Christy A. Ananthi , Bharatiraja C. , Munda Josiah Lange
Published: November 2021

Managing the timing constraints has become an important factor in the physical design of multiple supply voltage (MSV) integrated circuits (IC). Clock distribution and module scheduling are some of the conventional methods used to satisfy the timing constraints of a chip. In this paper, we propose a simulated annealing-based MSV floorplanning methodology for the design of ICs within the timing budget. Additionally, we propose a modified SKB tree representation for floorplanning the modules in the design. Our algorithm finds the optimal dimensions and position of the clocked modules in the design to reduce the wirelength and satisfy the timing constraints. The proposed algorithm is implemented in IWLS 2005 benchmark circuits and considers power, wirelength, and timing as the optimization parameters. Simulation results were obtained from the Cadence Innovus digital system taped-out at 45 nm. Our simulation results show that the proposed algorithm satisfies timing constraints through a 30.6% reduction in wirelength.
Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
Authors: Lakhan Abdullah , Li Jin , Groenli Tor Morten , Sodhro Ali Hassan , Zardari Nawaz Ali , Imran Ali Shariq , Thinnukool Orawit , Khuwuthyakorn Pattaraporn
Published: November 2021

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.
Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
Authors: Al-Ogaili Ali Saadon , Al-Shetwi Ali Q. , Al-Masri Hussein M. K. , Babu Thanikanti Sudhakar , Hoon Yap , Alzaareer Khaled , Babu N. V. Phanendra
Published: November 2021

In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks.
The Role of the Energy Sector in the Command and Control Function of Cities in Conditions of Sustainability Transitions
Authors: Raźniak Piotr , Dorocki Sławomir , Rachwał Tomasz , Winiarczyk-Raźniak Anna
Published: November 2021

The largest companies that are part of the energy sector are defined by Forbes as those associated with the production of energy from nonrenewable sources and they play a very significant role in the world economy and in the generation of the command and control (C & C) function of cities. No comprehensive studies are available at the present time illustrating changes in financial performance in relation to the share of the largest firms in the energy sector in terms of their role in the generation of the C & C function. Thus, the aim of the paper is to show changes in financial performance and the impacts of energy sector companies on the C & C function of cities as well as to show spatial variances in the sector’s geography. The energy sector is developing most rapidly in Chinese cities, although it does not play a major role in the most important cities in the world via its impact on the C & C function—this may be due to rapid growth in other sectors of the economy. It is, however, very important in smaller cities. On the other hand, a large share of the energy sector involved in the development of renewable sources of energy may disturb the position of cities whose C & C function relies on energy sector companies. Thus, forecasts are needed for the sector and its impact on the command and control function of cities for the period of transition from nonrenewable sources to renewable ones. One new area of research is the formulation of methods that would allow the determination of the effects of economic recessions in the future on the financial health and C & C function impacts of the energy sector.
Sodium-Potassium Alloy Heat Pipe under Geyser Boiling Experimental Study: Heat Transfer Analysis
Authors: Zhang Hongzhe , Ye Fang , Guo Hang , Yan Xiaoke
Published: November 2021

In the geyser boiling mode, the working fluid state is divided into a boiling process and a quiet process, and the sodium-potassium (Na-K) alloy heat pipe can discontinuously transfer heat at each boiling. The overheating of the liquid working fluid at the bottom causes short-term boiling and forms slug bubble, the strong condensing ability quickly conducts heat from the evaporator section. And geyser boiling can occur before the working fluid forms continuous flow, so it transfers more heat at lower temperatures than natural convection cooling. In this study, the heat transfer process of a Na-K alloy heat pipe with forced convection cooling under different heating power was experimental studied. The geyser boiling mode can make the Na-K alloy heat pipe work below 650 °C and reduce the start-up time. In the process of geyser boiling, the heat transfer quantity was increased by the boiling frequency and the amount of vapor produced in a single boiling. The boiling temperature had no obvious change with the increased of heating power, and the condenser section temperature increased with the heating power.
Influence of the Refrigerant Charge on the Heat Transfer Performance for a Closed-Loop Spray Cooling System
Authors: Zhou Nianyong , Feng Hao , Guo Yixing , Liu Wenbo , Peng Haoping , Lei Yun , Deng Song , Wang Yu
Published: November 2021

With the rapid increase of heat flux and demand for miniaturization of electronic equipment, the traditional heat conduction and convective heat transfer methods could not meet the needs. Therefore, the spray cooling experiment was carried out to obtain the basic heat transfer and cooling process. In this experiment, the spray cooling system was set up to investigate the influence of refrigerant charge on heat transfer performance in steady-state, dynamic heating, and dissipating processes. In a steady-state, the heat transfer coefficient increased with the rise of the refrigerant charge. In the dynamic dissipating process, both heat flux and heat transfer coefficient decreased rapidly after the critical heat flux, and the surface temperature drop point of each refrigerant charge was presented. The optimum refrigerant charge was provided considering the cooling parameters and the system operating performance. When the refrigerant operating pressure was 0.5 MPa, the spray cooling process presented with the higher heat flux, heat transfer coefficient, and cooling efficiency in this experiment. Meanwhile, the suitable surface temperature drop point and more gentle heat flux curves in the nucleate boiling region were obtained. The research results will contribute to the spray cooling system design, which should be operated before departure from the nucleate boiling point for avoiding cooling failure.
Understanding Attitudes towards Renewable Energy Technologies and the Effect of Local Experiences
Authors: Buchmayr Astrid , Van Ootegem Luc , Dewulf Jo , Verhofstadt Elsy
Published: November 2021

For the planning of the energy transition, decision-makers need to be aware of the public attitudes towards renewable energy technologies (RETs) and the impacts of such energy facilities from a population’s perspective. To facilitate the comparison of RET attitudes, a uniform survey design was used for four case studies (onshore wind, offshore wind, waste-to-energy, and biomass power) situated in the region of Flanders, Belgium. The survey analysis showed differences between the energy facilities with regard to the perceived impact on population health (combustion facilities were perceived more negatively) and landscape impact (wind energy facilities were perceived more negatively). All groups recognized the contribution of the RET facility to the economic development of the region. The effect of such local experiences on the overall evaluation of energy technologies was investigated using ordinal regression models. Personal experiences were found to be more meaningful predictors than socio-economic population characteristics or the proximity to the energy facility. In all investigated energy neighborhoods, the personal relationship of the participants to the landscape was a significant predictor of technology attitude. This points to the importance of investigating place attachment rather than pure visibility to understand the acceptability of land use for energy provision.
Brain Response and Reaction Time in Natural and Comfort Conditions, with Energy-Saving Potential in an Office Environment
Authors: Budiawan Wiwik , Sakakibara Hirotake , Tsuzuki Kazuyo
Published: November 2021

Psychological adaptation to ambient temperatures is fascinating and critical, both theoretically and practically, for energy efficiency in temperate climates. In this study, we investigated and compared the brain response (event-related potentials with a late positive component and latency ~300 milliseconds; labeled “P300” in the present study) and reaction times of Indonesian participants (n = 11), as tropical natives living in Japan, and Japanese participants (n = 9) in natural (i.e., hot during the summer and cold during the winter) and comfort conditions (with cooling and heating). Thermal comfort under contrasting conditions was studied using both instruments and subjective ratings. P300 potential and reaction time were measured before and after a Uchida–Kraepelin (U–K) test (30 summation lines). The results showed that P300 potential and latency did not change between the pre- and post-U–K test among conditions in any of the groups. Furthermore, Indonesian participants showed lower P300 potential (hot conditions) and slower P300 latency (hot and cooling conditions) than Japanese participants. We also found that the reaction time of the Indonesian group significantly differed between the pre- and post-U–K test in an air-conditioned environment, with either cooling or heating. In this study, Indonesian participants demonstrated a resistance to P300 and worse reaction times during work in a thermally unfamiliar season, specifically indicated by the indifferent performances among contrasting environmental conditions. Indonesian participants also showed similar thermal and comfort sensations to Japanese participants among the conditions. In the winter, when the Indonesian neutral temperature is higher than Japanese’s, the energy consumption may increase.
Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission
Authors: Akter Homeyra , Howlader Harun , Saber Ahmed , Mandal Paras , Takahashi Hiroshi , Senjyu Tomonobu
Published: November 2021

Optimal sizing of the power system can drastically reduce the total cost, which is challenging due to the fluctuation in output power of RE (primarily wind and solar) and pollution from thermal generators. The main purpose of this study is to cope with this output power uncertainty of renewables by considering ADLC, residential PV, and BESS at the lowest cost and with the least amount of carbon emission, while putting less burden on consumers by minimizing the IL. This paper optimizes the cost and carbon emission function of a hybrid energy system comprising PV, WG, BESS, and DG at Aguni Island, Japan, using a multi-objective optimization model. To solve the proposed problem in the presence of ADLC, the ϵ-constraint method and MILP are utilized. After obtaining all possible solutions, the FSM selects the best possible solution among all solutions. The result shows that while case 1 has a lower energy cost than the other cases, the quantity of IL is quite significant, putting customers in a burden. In case 2 and case 3, the total energy cost is 11.23% and 10% higher than case 1, respectively, but the sum of the IL is 99% and 95.96% lower than case 1 as the ADLC is applied only for the consumers who have residential PV and BESS, which can reflect the importance of residential PV and BESS. The total cost of case 3 is 1.72% lower than case 2, but IL is higher because sometimes home PV power will be used to charge the home BESS.
Experimental Study on Hydroelectric Energy Harvester Based on a Hybrid Qiqi and Turbine Structure
Authors: Bao Bin , Wang Quan , Wu Yufei , Li Pengda
Published: November 2021

The Qiqi structure design can automatically upset and spill its content once it arrives at limit capacity under vertical water flow excitation. Considering this function, the Qiqi structure has been utilized for small hydroelectric energy harvesting lately. To investigate the tradeoff between the Qiqi structure and the turbine structure for small hydroelectric energy harvesting, an energy harvester based on a hybrid Qiqi and turbine structure is proposed for vertical water flow hydroelectric applications. The hybrid structure is composed of a rectangular Qiqi structure, with two blades inserted on both sides. Self-tipping function of the hybrid Qiqi structure and working principle of the structure is investigated in detail. The proposed structure has both the advantages of low flow velocity energy harvesting of the Qiqi structure and high flow velocity energy harvesting of the turbine structure. A hydroelectric energy harvesting application using the hybrid structure is given to demonstrate that the hybrid structure had a higher rotational speed than the Qiqi structure under vertical low water flow excitation and was able to work at relatively high flow rates. Thus, the investigated hybrid structure can help small rotational hydropower achieve better energy harvesting performance and work at wide-range flow rates under vertical ultra-low water flow applications. At 600 mL/min, 902 μJ of electrical energy was charged by the investigated structure, which is six times higher than that using the Qiqi structure alone.
Using Sine Function-Based Nonlinear Feedback to Control Water Tank Level
Authors: Zhao Jian , Zhang Xianku , Chen Yilin , Wang Pengrui
Published: November 2021

This manuscript addresses the feasibility and significance of using a sine function to modify the system error of a normal linear feedback control to achieve more efficient capabilities in terms of energy-saving. The associated mathematic modeling and assessment were demonstrated by presenting a case analysis on the capabilities of controlling water level for a single tank. The principle of robust control and the theories and detailed algorithm of Lyapunov stability were applied to assess the result derived by novel nonlinear feedback in the form of sine function for optimizing the robustness of the PID (Proportional–Integral–Derivative) controller and economizing energy. Two control simulations are compared: nonlinear feedback control using a sine function and conventional fuzzy control. The results reveal that using the nonlinear feedback controller, a reduction of up to 32.9% of the average controlled quantity is achieved, and the performance index is improved by 24.0% with satisfactory robustness. The proposed nonlinear feedback control using a sine function provides simplicity, convenient implementation, and energy efficiency.
Characteristics of Pore Structure and Gas Content of the Lower Paleozoic Shale from the Upper Yangtze Plate, South China
Authors: Zou Xiaoyan , Li Xianqing , Zhang Jizhen , Li Huantong , Guo Man , Zhao Pei
Published: November 2021

This study is predominantly about the differences in shale pore structure and the controlling factors of shale gas content between Lower Silurian and Lower Cambrian from the upper Yangtze plate, which are of great significance to the occurrence mechanism of shale gas. The field emission scanning electron microscopy combined with Particles (Pores) and Cracks Analysis System software, CO2/N2 adsorption and the high-pressure mercury injection porosimetry, and methane adsorption were used to investigate characteristics of overall shale pore structure and organic matter pore, heterogeneity and gas content of the Lower Paleozoic in southern Sichuan Basin and northern Guizhou province from the upper Yangtze plate. Results show that porosity and the development of organic matter pores of the Lower Silurian are better than that of the Lower Cambrian, and there are four main types of pore, including interparticle pore, intraparticle pore, organic matter pore and micro-fracture. The micropores of the Lower Cambrian shale provide major pore volume and specific surface areas. In the Lower Silurian shale, there are mesopores besides micropores. Fractal dimensions representing pore structure complexity and heterogeneity gradually increase with the increase in pore volume and specific surface areas. There is a significant positive linear relationship between total organic carbon content and micropores volume and specific surface areas of the Lower Paleozoic shale, and the correlation of the Lower Silurian is more obvious than that of the Lower Cambrian. The plane porosity of organic matter increases with the increase in total organic carbon when it is less than 5%. The plane porosity of organic matter pores is positively correlated with clay minerals content and negatively correlated with brittle minerals content. The adsorption gas content of Lower Silurian and Lower Cambrian shale are 1.51–3.86 m3/t (average, 2.31 m3/t) and 0.35–2.38 m3/t (average, 1.36 m3/t). Total organic carbon, clay minerals and porosity are the main controlling factors for the differences in shale gas content between Lower Cambrian and Lower Silurian from the upper Yangtze plate. Probability entropy and organic matter plane porosity of the Lower Silurian are higher than those of Lower Cambrian shale, but form factor and roundness is smaller.
A Flexible Top-Down Numerical Modeling of an Air-Cooled Finned-Tube CO2 Trans-Critical Gas Cooler
Authors: Maiorino Angelo , Aprea Ciro , Del Duca Manuel Gesù
Published: November 2021

Carbon dioxide trans-critical refrigeration systems have been deeply investigated over the last years, with the aim to improve their performance by using several possible technical solutions. However, most of them lead to a more complex and expensive system, and therefore a trade-off is always needed to identify the best viable solution. Therefore, many efforts have also been focused on the study of a critical component of the basic carbon dioxide trans-critical cycle, which is the gas cooler, especially by numerical simulations. This work shows a new flexible approach to numerically model an air-cooled finned-tube CO2 trans-critical gas cooler integrating a Top-Down methodology with a Finite Difference Method to solve the governing equation of the thermodynamic processes involved. The model was developed to reproduce the behavior of an experimental CO2 refrigeration system, which provided the experimental data used for its validation. In detail, the model showed a good agreement with the experimental data, with average deviations of 1 K (0.3%), 0.9 bar (1%) and 0.15 kW (2.8%) regarding the refrigerant outlet temperature, the refrigerant outlet pressure and the rejected heat, respectively. The Top-Down numerical approach slightly outperformed the performance of previous numerical models available in the literature. Furthermore, the analysis of the refrigerant temperature and pressure along the tubes and rows also shows that the model can reproduce their behavior consistently and accordingly to data reported in the literature. The proposed approach can be used for detailed thermo-economic analysis of the whole refrigeration system, with the aim to optimize the design of the gas cooler.
Characterization of Microschist Rocks under High Temperature at Najran Area of Saudi Arabia
Authors: Ahmed Haitham M. , Ahmed Hussin A. M. , Adewuyi Sefiu O.
Published: November 2021

Rocks’ physical, mechanical, and mineralogical properties are essential in the design process of underground applications. To understand changes in these rocks’ properties at high temperatures, numerous studies have been conducted on several rock types, with little being known about microschist rock. This paper presents experimental study on the physical (e.g., density and P-wave velocity), mechanical (uniaxial compressive strength (UCS)), and microstructural behavior of microschist rock at room temperature (22 °C) and at high temperatures, i.e., 400, 600, and 800 °C. The results indicated that as the temperature increases, the microschist’s color changed, and dry density decreased by 0.97% at 800 °C. Additionally, the average P-wave velocity of microschist decreased by 4.14, 7.07, and 34.23%, at 400, 600, and 800 °C, respectively. Similarly, at these temperatures, the UCS of the microschist decreased by 34.4, 56.9, and 80.1%, respectively. Further findings from microscopic studies reveal that the observed changes in physical and mechanical properties were due to the structural deformation of the microschist at high temperatures.
Analyzing Electricity Markets with Increasing Penetration of Large-Scale Renewable Power Generation
Authors: Johnathon Chris , Agalgaonkar Ashish Prakash , Kennedy Joel , Planiden Chayne
Published: November 2021

Global electricity markets are undergoing a rapid transformation in their energy mix to meet commitments towards sustainable electric grids. This change in energy mix engenders significant challenges, specifically concerning the management of non-dispatchable energy resources. System and market operators are required to meet power system security and reliability requirements whilst providing electricity at competitive prices. An overview of electricity markets is provided in this paper with a critical appraisal of each market’s ability to manage the large-scale energy mix transition. This paper provides a commentary on the distinct features of electricity market models implemented around the world and highlights the barriers within these market models that are hindering the energy mix transition. Various researchers and policymakers are proposing solutions and market reforms for the smooth transitioning of the energy mix. This paper presents a systematic review of the proposed solutions in the literature and critiques the effectiveness and ease of implementation of the reviewed solutions. Research gaps and future research directions are indicated to promote further exploration towards the effective integration of large-scale renewable energy technologies.
A New Anelasticity Model for Wave Propagation in Partially Saturated Rocks
Authors: Wu Chunfang , Ba Jing , Zhong Xiaoqin , Carcione José M. , Zhang Lin , Ruan Chuantong
Published: November 2021

Elastic wave propagation in partially saturated reservoir rocks induces fluid flow in multi-scale pore spaces, leading to wave anelasticity (velocity dispersion and attenuation). The propagation characteristics cannot be described by a single-scale flow-induced dissipation mechanism. To overcome this problem, we combine the White patchy-saturation theory and the squirt flow model to obtain a new anelasticity theory for wave propagation. We consider a tight sandstone Qingyang area, Ordos Basin, and perform ultrasonic measurements at partial saturation and different confining pressures, where the rock properties are obtained at full-gas saturation. The comparison between the experimental data and the theoretical results yields a fairly good agreement, indicating the efficacy of the new theory.
Monetising Air Pollution Benefits of Clean Energy Requires Locally Specific Information
Authors: Mazaheri Mandana , Scorgie Yvonne , Broome Richard A. , Morgan Geoffrey G. , Jalaludin Bin , Riley Matthew L.
Published: November 2021

Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2–229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.