bluuebunny/crossref_metadata_2025 huggingface dataset:
Western Mediterranean Precipitation Extremes, the Result of Quasi-Resonant Sea–Atmosphere Feedbacks
Authors: Pinault Jean-Louis
Published: May 2023

The Mediterranean region has been identified as a climate change hotspot, and 13 case studies of extreme rainfall events (EREs) make it possible to categorize convective systems according to whether they are tropical-like or extratropical cyclones. This study, which focuses on the western Mediterranean basin from 2000 to 2021, is based on the cross-wavelet analysis in the period range of 11.4 to 45.7 days of (1) the height of precipitation at a particular place representative of the deep convective system used as the temporal reference and (2) the amount of precipitation in the western Mediterranean basin, as well as the sea surface temperature (SST) in the Mediterranean, the Adriatic, the Aegean Sea, the Black Sea, the Baltic, the North Sea and the Atlantic Ocean. Extratropical cyclones result from quasi-resonant atmospheric water and SST feedbacks, reflecting the co-evolution of the clustering of lows and the harmonization of thermocline depths and a relative stability of the atmospheric blocking circulation. When the SST anomaly in the western Mediterranean is greater than 0.5 °C, in its paroxysmal phase, the deep convective system is centered both over the southeast of France and the Mediterranean off the French coast. However, when the SST anomaly is weaker, deep convective systems can develop in different patterns, depending on SST anomalies in the peripheral seas. They can produce a low-pressure system extending from the Pyrenees to southern Italy or Sicily when the SST anomaly in the western Mediterranean is in phase opposition with EREs. In some cases, partial clustering of Atlantic and Mediterranean low-pressure systems occurs, producing a large cyclonic system. Tropical-like cyclones develop in the absence of any significant SST anomalies. Like extratropical cyclones, they occur in autumn or even winter, when the thermal gradient between the sea surface and the upper atmosphere is greatest but, this way, non-resonantly. Their return period is around 2 to 3 years. However, due to the gradual increase in the SST of the western Mediterranean in summer resulting from global warming, they can now lead to an ERE as happened on 21 January 2020.
Impacts of Quasi-Biennial Oscillation and El Niño–Southern Oscillation on Stratospheric Isentropic Mixing Process
Authors: Liang Jing , Wang Zhiting , Zhang Zhiyi , Luo Jiali
Published: May 2023

The present study investigates the influences of stratospheric quasi-biennial oscillation (QBO) and El Niño–Southern Oscillation (ENSO) on the intensity of stratospheric isentropic mixing based on ERA-Interim and MERRA-2 reanalysis products. It is found that isentropic mixing in the stratosphere is modulated by QBO and ENSO. An analysis of the QBO basis function in the multiple regression model reveals that isentropic mixing in the lower stratosphere is suppressed in the equatorial region in the WQBO phase, while the mixing enhances in the subtropical and mid-latitude regions. This result is not consistent with the Holton–Tan mechanism. However, isentropic mixing in the mid-latitudes becomes stronger in the middle stratosphere in the EQBO phase, which agrees well with the Holton–Tan effect. Composite analysis indicates that QBO-induced changes in the direction and speed of the stratospheric zonal wind can affect wave propagation and wave breaking. In the WQBO phase, zonal wind weakens, and a planetary wave is anomalously converging near 30°N, which leads to an increase in isentropic mixing; on the contrary, wind speed becomes large, and the upward propagation of planetary wave divergence, which lead to the isentropic mixing, becomes weak near 60°N. In the EQBO phase, the wind is relatively weak around 60°N, and the isentropic mixing is strong. Multiple regression analysis reveals the ENSO impact on the intensity of isentropic mixing, which shows weak mixing in the middle and high latitudes and strong mixing in the low latitudes of the lower stratosphere in the El Niño years. In the middle stratosphere, isentropic mixing enhances in the mid-latitude region due to intensified upward propagation of planetary waves but weakens in the polar region. Composite analysis reveals a clear relationship between the mixing strength zones of the El Niño and La Niña years with the position of the polar jet and changes in zonal wind speed.
Estimating Scalp Moisture in a Hat Using Wearable Sensors
Authors: Mao Haomin , Tsuchida Shuhei , Terada Tsutomu , Tsukamoto Masahiko
Published: May 2023

Hair quality is easily affected by the scalp moisture content, and hair loss and dandruff will occur when the scalp surface becomes dry. Therefore, it is essential to monitor scalp moisture content constantly. In this study, we developed a hat-shaped device equipped with wearable sensors that can continuously collect scalp data in daily life for estimating scalp moisture with machine learning. We established four machine learning models, two based on learning with non-time-series data and two based on learning with time-series data collected by the hat-shaped device. Learning data were obtained in a specially designed space with a controlled environmental temperature and humidity. The inter-subject evaluation showed a Mean Absolute Error (MAE) of 8.50 using Support Vector Machine (SVM) with 5-fold cross-validation with 15 subjects. Moreover, the intra-subject evaluation showed an average MAE of 3.29 in all subjects using Random Forest (RF). The achievement of this study is using a hat-shaped device with cheap wearable sensors attached to estimate scalp moisture content, which avoids the purchase of a high-priced moisture meter or a professional scalp analyzer for individuals.
Milling Surface Roughness Prediction Based on Physics-Informed Machine Learning
Authors: Zeng Shi , Pi Dechang
Published: May 2023

Surface roughness is a key indicator of the quality of mechanical products, which can precisely portray the fatigue strength, wear resistance, surface hardness and other properties of the products. The convergence of current machine-learning-based surface roughness prediction methods to local minima may lead to poor model generalization or results that violate existing physical laws. Therefore, this paper combined physical knowledge with deep learning to propose a physics-informed deep learning method (PIDL) for milling surface roughness predictions under the constraints of physical laws. This method introduced physical knowledge in the input phase and training phase of deep learning. Data augmentation was performed on the limited experimental data by constructing surface roughness mechanism models with tolerable accuracy prior to training. In the training, a physically guided loss function was constructed to guide the training process of the model with physical knowledge. Considering the excellent feature extraction capability of convolutional neural networks (CNNs) and gated recurrent units (GRUs) in the spatial and temporal scales, a CNN–GRU model was adopted as the main model for milling surface roughness predictions. Meanwhile, a bi-directional gated recurrent unit and a multi-headed self-attentive mechanism were introduced to enhance data correlation. In this paper, surface roughness prediction experiments were conducted on the open-source datasets S45C and GAMHE 5.0. In comparison with the results of state-of-the-art methods, the proposed model has the highest prediction accuracy on both datasets, and the mean absolute percentage error on the test set was reduced by 3.029% on average compared to the best comparison method. Physical-model-guided machine learning prediction methods may be a future pathway for machine learning evolution.
Analysis of Movement Variability in Cycling: An Exploratory Study
Authors: Winter Lachlan , Bellenger Clint , Grimshaw Paul , Crowther Robert George
Published: May 2023

The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional aim was to determine if changes in the LyE existed across a trial. Twelve novice cyclists completed four sessions of cycling; one was a familiarisation session to determine a bike fit and become better accustomed to the time trial position and pacing of a 4000 m effort. IMUs were attached to the head, thorax, pelvis and left and right shanks to analyse segment accelerations, respectively, and reflective markers were attached to the participant to analyse neck, thorax, pelvis, hip, knee and ankle segment/joint angular kinematics, respectively. Both the IMU and VICON Nexus test-retest repeatability ranged from poor to excellent at the different sites. In each session, the head and thorax IMU acceleration LyE increased across the bout, whilst pelvic and shank acceleration remained consistent. Differences across sessions were evident in VICON Nexus segment/joint angular kinematics, but no consistent trend existed. The improved reliability and the ability to identify a consistent trend in performance, combined with their improved portability and reduced cost, advocate for the use of IMUs in analysing movement variability in cycling. However, additional research is required to determine the applicability of analysing movement variability during cycling.
Frequency Modulation Control of an FMCW LiDAR Using a Frequency-to-Voltage Converter
Authors: Lee Jubong , Hong Jinseo , Park Kyihwan
Published: May 2023

An FMCW LiDAR (frequency-modulated continuous-wave light detection and ranging) is a sensor that can measure distance using optical interference frequency (fb). This sensor has recently attracted interest because it is robust to harsh environmental conditions and sunlight due to the wave properties of the laser. Theoretically, when the frequency of the reference beam is linearly modulated, a constant fb is obtained with respect to the distance. However, when the frequency of the reference beam fails to be linearly modulated, the distance measurement is not accurate. In this work, linear frequency modulation control using frequency detection is proposed to improve the distance accuracy. The FVC (frequency to voltage converting) method is used to measure fb for high-speed frequency modulation control. The experimental results show that linear frequency modulation control using an FVC improves FMCW LiDAR performance in terms of control speed and frequency accuracy.
Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition
Authors: Monterroso Muñoz Alberto , Moron-Fernández Maria-Jose , Cascado-Caballero Daniel , Diaz-del-Rio Fernando , Real Pedro
Published: May 2023

Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies and promising algorithms in this field, there is currently a lack of research toward standardized, general-approach proposals. This issue has been stated in the literature as a limiting factor to be addressed in the future. The key starting point of this work is to identify a synergistic effect between professional photography and scientific fields by analyzing image acquisition issues. Subsequently, we discuss underwater image enhancement and quality assessment, image mosaicking and algorithmic concerns as the last processing step. In this line, statistics about 120 AUV articles fro recent decades have been analyzed, with a special focus on state-of-the-art papers from recent years. Therefore, the aim of this paper is to identify critical issues in autonomous underwater vehicles encompassing the entire process, starting from optical issues in image sensing and ending with some issues related to algorithmic processing. In addition, a global underwater workflow is proposed, extracting future requirements, outcome effects and new perspectives in this context.
Ozone Detection via Deep-Ultraviolet Cavity-Enhanced Absorption Spectroscopy with a Laser Driven Light Source
Authors: Puga Anthony , Yalin Azer
Published: May 2023

We present a novel sensing approach for ambient ozone detection based on deep-ultraviolet (DUV) cavity-enhanced absorption spectroscopy (CEAS) using a laser driven light source (LDLS). The LDLS has broadband spectral output which, with filtering, provides illumination between ~230–280 nm. The lamp light is coupled to an optical cavity formed from a pair of high-reflectivity (R~0.99) mirrors to yield an effective path length of ~58 m. The CEAS signal is detected with a UV spectrometer at the cavity output and spectra are fitted to yield the ozone concentration. We find a good sensor accuracy of <~2% error and sensor precision of ~0.3 ppb (for measurement times of ~5 s). The small-volume (<~0.1 L) optical cavity is amenable to a fast response with a sensor (10–90%) response time of ~0.5 s. Demonstrative sampling of outdoor air is also shown with favorable agreement against a reference analyzer. The DUV-CEAS sensor compares favorably against other ozone detection instruments and may be particularly useful for ground-level sampling including that from mobile platforms. The sensor development work presented here can also inform of the possibilities of DUV-CEAS with LDLSs for the detection of other ambient species including volatile organic compounds.
A Dynamic Procedure to Detect Maximum Voluntary Contractions in Low Back
Authors: Wang Xun , Beltran Martinez Karla , Golabchi Ali , Tavakoli Mahdi , Rouhani Hossein
Published: May 2023

Surface electromyography (sEMG) is generally used to measure muscles’ activity. The sEMG signal can be affected using several factors and vary among individuals and even measurement trials. Thus, to consistently evaluate data among individuals and trials, the maximum voluntary contraction (MVC) value is usually calculated and used to normalize sEMG signals. However, the sEMG amplitude collected from low back muscles can be frequently larger than that found when conventional MVC measurement procedures are used. To address this limitation, in this study, we proposed a new dynamic MVC measurement procedure for low back muscles. Inspired by weightlifting, we designed a detailed dynamic MVC procedure, and then collected data from 10 able-bodied participants and compared their performances using several conventional MVC procedures by normalizing the sEMG amplitude for the same test. The sEMG amplitude normalized by our dynamic MVC procedure showed a much lower value than those obtained using other procedures (Wilcoxon signed-rank test, with p < 0.05), indicating that the sEMG collected during dynamic MVC procedure had a larger amplitude than those of conventional MVC procedures. Therefore, our proposed dynamic MVC obtained sEMG amplitudes closer to its physiological maximum value and is thus more capable of normalizing the sEMG amplitude for low back muscles.
Longitudinal Studies of Wearables in Patients with Diabetes: Key Issues and Solutions
Authors: Alhaddad Ahmad Yaser , Aly Hussein , Gad Hoda , Elgassim Einas , Mohammed Ibrahim , Baagar Khaled , Al-Ali Abdulaziz , Sadasivuni Kishor Kumar , Cabibihan John-John , Malik Rayaz A.
Published: May 2023

Glucose monitoring is key to the management of diabetes mellitus to maintain optimal glucose control whilst avoiding hypoglycemia. Non-invasive continuous glucose monitoring techniques have evolved considerably to replace finger prick testing, but still require sensor insertion. Physiological variables, such as heart rate and pulse pressure, change with blood glucose, especially during hypoglycemia, and could be used to predict hypoglycemia. To validate this approach, clinical studies that contemporaneously acquire physiological and continuous glucose variables are required. In this work, we provide insights from a clinical study undertaken to study the relationship between physiological variables obtained from a number of wearables and glucose levels. The clinical study included three screening tests to assess neuropathy and acquired data using wearable devices from 60 participants for four days. We highlight the challenges and provide recommendations to mitigate issues that may impact the validity of data capture to enable a valid interpretation of the outcomes.
Determinants of Indebtedness in Expanding Portuguese Hotels
Authors: Gomes Luís , Pereira Cláudia , Coelho Mário
Published: May 2023

The hotel industry has been one of the fastest-growing economic sectors in Portugal in recent years. According to the European Best Destinations website, Portugal has consolidated itself as a destination of excellence. The explanation of the capital structure of firms remains relevant in financial research. However, prior international empirical evidence is not exclusive and is still scarce in the Portuguese hotel sector, which motivated this research. This study aimed to analyse the influence of determinants on the capital structure of 821 Portuguese hotels between 2011 and 2019 (until the constraints of the COVID-19 pandemic affected the international tourism sector) and to determine whether strategies were conducted according to trade-off and pecking order theories. This study used an econometric approach based on the static panel data model, with tests recommending the fixed effects model estimated by the least squares dummy variables (LSDV) within. The analysed determinants were return on assets, size, tangibility, growth opportunities, risk and other tax benefits besides debt in order to explain the indebtedness through three alternative measures. The results of this research show that managers sought an optimal combination of equity and debt, which was weighted between tax savings and the cost of financial distress. However, they pursued this objective through the hierarchical sequencing of funding sources in order to minimise the costs of information asymmetry.
The Role of Green Training in the Ministry of Education’s Corporate Environmental Performance: A Mediation Analysis of Organizational Citizenship Behavior towards the Environment and Moderation Role of Perceived Organizational Support
Authors: Japir Bataineh Mohammed Ahmed , Ghasemi Matina , Ghadiri Nejad Mazyar
Published: May 2023

Recently, the relationship between green human resource management (GHRM) and environmental performance has received a lot of attention from scholars. Teaching, training, and research and development carried out in higher education institutions, which are crucial sources for the promotion of sustainability, encourage GHRM. Using signaling theory, this study aimed to deal with the different roles of green training in the Ministry of Education’s corporate environmental performance. The mediation analysis of organizational citizenship behavior towards the environment was considered and the moderation role of perceived organizational support was evaluated. A survey was prepared to analyze the opinions of managers and staff of the Ministry of Education in Iran. After collecting the surveys, 211 complete responses were analyzed and the most important results from these surveys concluded that: (1) the important tools in adopted strategies for green training improve organizational citizenship behavior towards the environment (OCB) and the Ministry of Educations’ environmental performance; (2) the role of OCB in mediating the effects of training on corporate environmental performance (CEP) is essential; (3) perceived organization support (POS) has a moderation role between green training and CEP.
Sustainable Consumption: Conceptualization and Characterization of the Complexity of “Being” a Sustainable Consumer—A Systematic Review of the Scientific Literature
Authors: Vargas-Merino Jorge Alberto , Rios-Lama Cristian Armando , Panez-Bendezú Miguel Humberto
Published: May 2023

Sustainable consumption is a key concept in society and the environment due to its direct relationship with sustainable development; its importance lies in the decoupling of consumption and economic growth with environmental damage and its involvement with various behavioral disciplines and ecological concepts. Therefore, this research aims to analyze scientific articles linked to key perspectives of the concept under discussion. Due to the scope of the objective of systematizing the existing scientific literature on sustainable consumption in Scopus and Web of Science, a systematic review was carried out, including 104 scientific articles considering criteria that respond to the questions posed. It is concluded that sustainable consumption is a complex and nebulous concept whose theoretical fragmentation gives it breadth but generates overlapping concepts. Likewise, the link between the consumer and the circular economy and the difficulties behind such interaction was denoted. The complexity of being a green consumer in current times and the aspects that comprise it were also covered, and the importance, role, and tools of the government in sustainable consumption. Thus, it is expected to generate a consistent theoretical framework facilitating the creation of new applied research, considering the perspectives highlighted through this analysis.
What do We Know about Vision? A Sustainability Lens
Authors: Kantabutra Sooksan
Published: May 2023

Given the paucity of knowledge on sustainability-related organizational vision, the present study’s objective is to examine the current state of the organizational vision knowledge base with a sustainability focus. It adapts the Integrated Systematic Literature Review approach. Five hundred and four journal articles from Scopus between 1981 and October 2022 are identified and reviewed. Influential journals, scholars and documents concerning organizational vision in the sustainability context are identified, along with four schools of thought on Organizational Vision: Vision Component, Vision Motivation, Transformational Vision and Educational Vision. Overall, findings suggest that organizational vision scholars have focused their efforts on organizational vision in a way that leads to organizational productivity as opposed to sustainability productivity. This knowledge gap is fundamentally critical for sustainability scholars and practitioners alike since (a) organizational culture with vision as a core component is a pre-condition for sustainable enterprise development and (b) sustainability transformations are fundamental changes in cultures that move socio-technical systems toward sustainable production and consumption. Drawing from the identified body of knowledge, a model linking organizational vision and sustainability-related organizational performance is derived as a major contribution of the present study. The model explains how vision components theoretically lead to improved sustainability performance, followed by theoretical, empirical and practical implications as significant contributions to the field of corporate sustainability.
Identifying Loss and Waste Hotspots and Data Gaps throughout the Wheat and Bread Lifecycle in the Fars Province of Iran through Value Stream Mapping
Authors: Ghaziani Shahin , Dehbozorgi Gholamreza , Bakhshoodeh Mohammad , Doluschitz Reiner
Published: May 2023

Reducing wheat and bread loss and waste is crucial for ensuring global food security and sustainability. The importance of reducing wheat and bread loss is particularly significant in Iran, where wheat is a staple crop and a vital component of the country’s food security. A value stream mapping study was conducted to identify loss and waste hotspots and critical data gaps along the wheat and bread lifecycle (WBL). In October 2018, 14 experts were surveyed in Fars province, Iran’s second-largest wheat producer. The study presents a detailed cradle-to-grave overview of WBL and identifies farms, foodservice, and households as the loss and waste hotspots. The results revealed significant data gaps regarding on-farm wheat loss and household bread waste. Additionally, although data exist in other segments of WBL, they are not readily accessible nor utilized to report loss and waste, highlighting the need for transparency within the WBL system and further research to compile existing data and analyze wheat and bread loss and waste. Other researchers can employ the holistic approach of the present study to investigate loss and waste throughout the lifecycle of other food items in different geographical contexts. The methodology adopted in this study offers advantages for defining the scope of research in lifecycle assessment and circular economy studies.
A Comparative Analysis of Public Awareness Level about Drinking Water Quality in Guangzhou (China) and Karachi (Pakistan)
Authors: Hussain Imtiaz , Hayat Waseem , Gong Siyuan , Yang Xiangjing , Lai Wing-Fu
Published: May 2023

Safe drinking water is fundamental for the existence of life. The establishment of public awareness about drinking water quality is a most significant issue in the protection of health and the wellbeing of humans. The present study focuses on the assessment of community awareness level of, as well as public trust in, the government-provided information about drinking water quality in two highly populated underrepresented megacities of Asia, i.e., Guangzhou (China) and Karachi (Pakistan). The study was conducted to explore the respondents’ knowledge about the existing quality issues and the practices to remove the contaminants in drinking water in both cities, which was determined by numerical analysis using the scoring method system and multinomial regression model. The results show that the respective respondents’ percentage awareness level and positive attitude in Guangzhou were 46.2% and 30.0% compared with 23.1% and 7.4% in Karachi, respectively. The respective percentage of respondents’ trust in media stories/reports about water pollution accidents was 76.0% and 70.8%, while the trust in government-provided information was 79.3% and 39.7% in Guangzhou and Karachi, respectively. The p-values for drinking water quality according to public approval based on sociodemographic parameters (gender, age, family members, household income/month, education, etc.) of respondents in both cities were <0.05, which supports that the variations in acquired results were significant. The study advocates that increased awareness campaigns by government agencies and nongovernmental organizations (NGOs) in educational institutes and/or community centers can improve the public awareness level, which would subsequently help the governments to enhance the public trust, especially in Karachi. Moreover, the study’s findings have national significance and a worldwide scope, particularly in low- and middle-income regions.
Modeling and Dynamic Impact Analysis of Prismatic Lithium-Ion Battery
Authors: Qin Dongchen , Wang Peizhuo , Wang Tingting , Chen Jiangyi
Published: May 2023

Battery modules of new energy vehicles are frequently exposed to dynamic impacts during traffic accidents. However, current research on the mechanical safety of prismatic lithium-ion batteries (PLIBs) primarily focuses on quasi-static states, and the failure mechanism of batteries under dynamic impact remains incompletely understood. Therefore, to investigate the failure mechanism and critical failure displacement of PLIB under dynamic impacts, this study establishes a computational model of PLIB considering anisotropy based on experimental data and extends the simulation to the case of high-velocity battery collision. On this basis, the deformation feature, mechanical response, and failure mechanism of PLIB under different impact velocities are analyzed. The results show that the deformation feature of PLIB under dynamic impact differs from that under quasi-static loading. As the loading velocity increases, the inertial effect gradually becomes apparent, causing the deformation of PLIB to localize and the failure displacement to decrease. Three critical failure displacements were identified within the velocity range of 0–20 m/s. This study can serve as a reference for battery safety design.
Carbon Neutrality in Municipalities: Balancing Individual and District Heating Renewable Energy Solutions
Authors: Balode Lauma , Zlaugotne Beate , Gravelsins Armands , Svedovs Oskars , Pakere Ieva , Kirsanovs Vladimirs , Blumberga Dagnija
Published: May 2023

Carbon neutrality in municipalities can be achieved by combining individual heating and district heating solutions involving the use of renewable energy sources. Each approach has advantages and disadvantages, but the best solution depends on the specific circumstances of each municipality. As an environmentally friendly and efficient energy use, a decentralised heat supply contributes to achieving energy conservation and emissions reduction goals. Decentralised energy use, such as solar collectors with thermal energy storage or biomass as a resource, reduces dependence on centralised heat generation and transmission. The appropriate infrastructure for connection to district heating networks has not yet been built. On the other hand, it is easier to make investments to construct proper infrastructure in the case of large-scale centralised heat supplies. Moreover, a centralised heat supply with renewable energy sources can provide more inhabitants with renewable heat energy. Within the framework of the study, the possibilities of using renewable energy sources in one of the municipalities of Latvia—the Carnikava parish of Ādaži Municipality—are analysed. The study examines two scenario complexes including individual heating solutions in buildings or district heating solutions with a centralised approach. The study evaluates several alternatives to increase the share of RES (solar collectors, biomass, heat pumps, etc.) in the centralised heat supply. To evaluate individual RES solutions in various municipal buildings, this study evaluates alternatives with different technical solutions that increase the use of RES in heat supply.
Acute Effects of a Combat Sport Environment on Self-Control and Pain Perception Inhibition: A Preliminary Study in a New Ecological Framework
Authors: Invernizzi Pietro Luigi , Trecroci Athos , Scurati Raffaele , Signorini Gabriele , Formenti Damiano , Bosio Andrea , Rigon Marta , Benedini Stefano
Published: May 2023

Intense sports activities affect cognitive, perceptual, and physiological domains, possibly concurring in reducing pain perception and anxiety. Within a framework for a new socio-ecological narrative that considers opposition (such as fighting) and collaboration (cooperative learning) as carriers of self-control and pain perception inhibition, we investigated the acute effects of a judo-specific session on cognitive (inhibitory control and simple reaction time), perceptual (pain and fatigue), affective (anxiety) and physiological (hormone profile) domains. Eleven male black belt judokas (age 39.0 ± 13.9 years; training experience: 23.2 ± 14.4 years) were recruited and tested before and after judo randori and resting sessions. Inhibitory control and simple reaction time were assessed via the Flanker task and clinical reaction time test, pain and fatigue were assessed using Borg’s category-ratio scale (CR-10), and the state–trait anxiety inventory Y-1 test assessed anxiety. Glucose, insulin, cortisol, creatinine, and irisin levels were measured. Cognitive performance, perception of fatigue and physiological variables increased after randori bouts, while pain decreased. Inhibitory control, perception of pain, perception of fatigue and glucose, cortisol, and creatinine significantly differed (p < 0.05) between randori and resting sessions. A high-intensity randori may induce acute beneficial effects on cognitive, perceptual, and physiological domains. Further studies should compare the results with the outcomes from a collaborative and non-agonist environment and confirm the socio-ecologic framework.
An ANFIS-Fuzzy Tree-GA Model for a Hospital’s Electricity Purchasing Decision-Making Process Integrated with Virtual Cost Concept
Authors: Panagiotou Dimitrios K. , Dounis Anastasios I.
Published: May 2023

In deregulated electricity markets, accurate load and price prediction play an essential role in the Demand Response (DR) context. Although electrical load and price demonstrate a strong correlation which is not linear, price prediction may be a task much more challenging than load prediction due to several factors. The volatility of electricity price compared to load makes price prediction a complex procedure. To perform purchasing decisions commercial consumers may rely on short term price and load prediction. A system which combines Adaptive Neuro-Fuzzy Systems (ANFIS) which predict Load Marginal Prices (LMPs) and electricity consumption is presented in this study. Furthermore, the Virtual Cost (VC) concept, which is the sum of the products between the predicted hourly consumption values and their respective predicted LMPs is introduced. Virtual Cost is assessed with a Fuzzy Decision Tree (FDT) compared to a threshold set by the customer. If needed, the amount of electrical energy that a healthcare facility must purchase at every hour of the day may be scheduled using Genetic Algorithm (GA) to meet the threshold criterion. This hybrid model proved economically beneficial for the facility, which is of great importance since the saved resources may be utilized to improve its infrastructures or for other purposes with social impact. The novelty of the proposed method is the utilization of ANFIS, Fuzzy Decision Trees and Genetic Algorithms combined as tools to improve the hospital’s energy and economic efficiency, achieving a reduction of the electricity costs up to 21.95 percent. The contribution of the study is to provide a reliable decision-making tool to everyone who participates in the electricity market in order to perform profitable energy scheduling automatically and accurately.
Transforming Saudi Arabia’s Energy Landscape towards a Sustainable Future: Progress of Solar Photovoltaic Energy Deployment
Authors: Ali Amjad
Published: May 2023

The Kingdom of Saudi Arabia’s electricity sector has undergone several distinct phases, and the country’s commitment to renewable energy development has resulted in a modern phase that includes the deployment of renewable energy power plants since 2010. Due to Saudi Arabia’s diverse topographical position, the exploration of renewable energy technologies is of interest, particularly solar energy, and its progress in renewable energy development could serve as a model for other countries seeking to transition to clean energy. This article explores the progress of solar photovoltaic (PV) energy deployment in Saudi Arabia, with a focus on the policies and regulations that have facilitated its growth. The article provides an overview of the energy landscape in Saudi Arabia and investigates the progress of solar PV deployment in Saudi Arabia, analyzing growth trends, capacity additions, and the role of policies and regulations in supporting the sector. The focus on renewable energy development in Saudi Arabia, particularly solar PV technology, could have far-reaching implications globally as the world seeks to transition to cleaner sources of energy. This research article highlights the importance of a comprehensive renewable energy policy for transforming the country’s energy landscape towards a sustainable future.
Spatiotemporal Evolution and Multi-Scenario Prediction of Carbon Storage in the GBA Based on PLUS–InVEST Models
Authors: Wang Ruei-Yuan , Cai Huina , Chen Lingkang , Li Taohui
Published: May 2023

In the context of sustainable development and dual-carbon construction, in order to clarify the future changes in land use and carbon storage in the GBA, this study used the PLUS and InVEST models as well as Geoda software to simulate and predict the spatial development pattern of land use as well as the changes in carbon stocks in the GBA in 2030 under multiple scenarios. The results show that (1) From 1990 to 2020, carbon storage decreased year by year. (2) In 2030, except for the EPS, the future carbon storage prediction values of the remaining scenarios are lower than those in 2020, especially the carbon storage prediction value under the EDS, which is the lowest at 8.65 × 108 t. (3) The spatial distribution of carbon storage in the GBA has significant spatial heterogeneity. The high-value areas of carbon storage are distributed in the east and west wings as well as southwest of the GBA, while the low-value areas are concentrated in the middle and east. The research results can provide a reasonable scientific basis for the territorial space resource planning of the GBA under the goal of “dual carbon”.
Green Bond Pricing and Optimization Based on Carbon Emission Trading and Subsidies: From the Perspective of Externalities
Authors: Hu Yuanfeng , Tian Yixiang , Zhang Luping
Published: May 2023

In this paper, we establish a model based on real options theory and fractional Brownian motion (FBM) with jumps to price green bonds, and thus alleviate the externalities of green bonds. We assume that the floating value of green bonds is linked to the carbon price. The carbon emission trading mechanism and government subsidy policy are introduced into this model, and the expression is derived from the stochastic differential utility framework based on the fast Fourier transform method. Based on the numerical analysis and the simulations, this paper analyzes when governments are facing financial and carbon emission constraints and how policymakers balance the allocation between carbon allowances and government subsidies to help green bonds reach the exogenous equilibrium price. Our results have implications in terms of optimizing the distribution of economic resources by the reasonable pricing of green bonds. It is in line with the current theme of global energy conservation and emission reduction, and also has certain guiding significance for the development of the carbon emission trading market.
Investigation of Community Energy Business Models from an Institutional Perspective: Intermediaries and Policy Instruments in Selected Cases of Developing and Developed Countries
Authors: Mohammadi Naimeh
Published: May 2023

Community energy development and the empowerment of customers as producers are the main contributors to decentralized market solutions in energy transition policy. Despite the growing literature on community energy projects from the perspectives of various business models, drivers, and barriers, few studies display the impact of institutional factors on the community energy business model configuration. Using insights from Ostrom’s institutional framework, this study develops a conceptual framework comprising policy instruments and the intermediaries that configure the various community energy business models, and it examines this framework in the developed world of northwestern European countries (Germany, Denmark, Belgium, and the UK) and in selected cases in developing countries (Rural Central America, South Africa, Iran, and Indonesia). The findings indicate that ambitious renewable energy consumption targets and national policies in northern EU countries have resulted in political and financial incentives, as well as greater financial security than other investment markets, which encourage citizens to contribute to the proliferation of community energy. On the other hand, in the studied developing countries, top-down energy policies and a centralized energy system are insufficient for participatory energy planning. Due to unsupportive policies, a lack of appropriate regulatory frameworks, and a lack of institutional support in these countries, the initiation of community energy projects requires the presence of intermediaries such as developers who work ‘in-between’ other actors, such as energy providers, users, or regulators.
Electrostatic Precipitator Design Optimization for the Removal of Aerosol and Airborne Viruses
Authors: Chen Yen-Tang , Lu Cheng-Lung , Lu Shang-Jung , Lee Da-Sheng
Published: May 2023

In the midst of the COVID-19 pandemic, new requirements for clean air supply are introduced for heating, ventilation, and air conditioning (HVAC) systems. One way for HVAC systems to efficiently remove airborne viruses is by filtering them. Unlike disposable filters that require repeated purchases of consumables, the electrostatic precipitator (ESP) is an alternative option without the drawback of reduced dust collection efficiency in high-efficiency particulate air (HEPA) filters due to dust buildup. The majority of viruses have a diameter ranging from 0.1 μm to 5 μm. This study proposed a two-stage ESP, which charged airborne viruses and particles via positive electrode ionization wire and collected them on a collecting plate with high voltage. Numerical simulations were conducted and revealed a continuous decrease in collection efficiencies between 0.1 μm and 0.5 μm, followed by a consistent increase from 0.5 μm to 1 μm. For particles larger than 1 μm, collection efficiencies exceeding 90% were easily achieved with the equipment used in this study. Previous studies have demonstrated that the collection efficiency of suspended particles is influenced by both the ESP voltage and turbulent flow at this stage. To improve the collection efficiency of aerosols ranging from 0.1 μm to 1 μm, this study used a multi-objective genetic algorithm (MOGA) in combination with numerical simulations to obtain the optimal parameter combination of ionization voltage and flow speed. The particle collection performance of the ESP was examined under the Japan Electrical Manufacturers’ Association (JEMA) standards and showed consistent collection performance throughout the experiment. Moreover, after its design was optimized, the precipitator collected aerosols ranging from 0.1 μm to 3 μm, demonstrating an efficiency of over 95%. With such high collection efficiency, the proposed ESP can effectively filter airborne particles as efficiently as an N95 respirator, eliminating the need to wear a mask in a building and preventing the spread of droplet infectious diseases such as COVID-19 (0.08 μm–0.16 μm).
Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist
Authors: Han Suhyeon , Park Shinyoung , An Sejin , Choi Wonjun , Lee Mina
Published: May 2023

In responding to climate change, the world is focusing on technology development. Korea also continues to invest in R&D to reduce greenhouse gas emissions and adapt to climate change. However, compared to the government’s continuous investment in R&D, there is a lack of systematic analysis of R&D investment performance. Rather than simply reducing and increasing the investment in R&D to respond to climate change in terms of high and low efficiency, we aim to improve the efficiency of national R&D projects by analyzing the causes of low efficiency and deriving improvement directions. In this study, data envelopment analysis (DEA) was used to analyze the efficiency of climate change response technology development projects conducted by the Ministry of Science and ICT in Korea. The efficiency of 1500 projects conducted during the 2014–2020 period was analyzed from a static and dynamic perspective, focusing on project information. Through static efficiency analysis, total efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) were measured, and the causes of inefficiency were identified. In addition, the results of the dynamic efficiency analysis using the Malmquist analysis were presented, and alternatives for each field were suggested by presenting the static and dynamic results as an integrated model.
Research on the Sustainable Development Strategy of Online Learning: A Case Study of YouTube Users
Authors: Gao Liqian , Liu Ziyang
Published: May 2023

Amid the COVID-19 pandemic and the widespread adoption of mobile devices, video-based online learning has emerged as a critical mode of education. However, empirical research on the determinants of online learning behavior and intention among video users remains scarce. To explore the factors influencing the continuous intention of users to engage in YouTube video-based online learning, the present study drew on the perceived value theory and the ECM perspective to construct a model. This study is a quantitative study in which 669 valid data were collected from online users of online learning and communication communities through online questionnaires distributed by non-probability sampling, and the constructed model was tested using SPSS 27.0 and AMOS 27.0. The results revealed that perceived value had a positive direct effect on continuous intention and an indirect effect through satisfaction on continuous intention. Therefore, to effectively and sustainably promote video-based online learning, measures should be taken to enhance users’ continuous intention and retention. Thereafter, suggestions for further research were proposed.
Applying Machine Learning Techniques in Air Quality Prediction—A Bucharest City Case Study
Authors: Cican Grigore , Buturache Adrian-Nicolae , Mirea Radu
Published: May 2023

Air quality forecasting is very difficult to achieve in metropolitan areas due to: pollutants emission dynamics, high population density and uncertainty in defining meteorological conditions. The use of data, which contain insufficient information within the model training, and the poor selection of the model to be used limits the air quality prediction accuracy. In this study, the prediction of NO2 concentration is made for the year 2022 using a long short-term memory network (LSTM) and a gated recurrent unit (GRU). this is an improvement in terms of performance compared to traditional methods. Data used for predictive modeling are obtained from the National Air Quality Monitoring Network. The KPIs(key performance indicator) are computed based on the testing data subset when the NO2 predicted values are compared to the real known values. Further, two additional predictions were performed for two days outside the modeling dataset. The quality of the data is not as expected, and so, before building the models, the missing data had to be imputed. LSTM and GRU performance in predicting NO2 levels is similar and reasonable with respect to the case study. In terms of pure generalization capabilities, both LSTM and GRU have the maximum R2 value below 0.8. LSTM and GRU represent powerful architectures for time-series prediction. Both are highly configurable, so the probability of identifying the best suited solution for the studied problem is consequently high.
Effect of Hydrogen-Rich Syngas Direct Injection on Combustion and Emissions in a Combined Fuel Injection—Spark-Ignition Engine
Authors: Shang Zhen , Sun Yao , Yu Xiumin , He Ling , Ren Luquan
Published: May 2023

To utilize the high efficiency of gasoline direct injection (GDI) and solve the high particulate number (PN) issue, hydrogen-rich syngas has been adopted as a favorable sustainable fuel. This paper compares and analyzes the effects of the injection configurations (GDI, gasoline port injection combined with GDI (PGDI), and gasoline port injection combined with hydrogen-rich syngas direct injection (PSDI)) and fuel properties on combustion and emissions in a spark-ignition engine. The operational points were fixed at 1800 rpm with a 15% throttle position, and the excess air ratio was 1.1. The conclusions show that PSDI gained the highest maximum brake thermal efficiency (BTE) at the MBT point, and the maximum BTE for GDI was only 94% of that for PSDI. PSDI’s CoVIMEP decreased by 22% compared with GDI’s CoVIMEP. CO and HC emissions were reduced by approximately 78% and 60% from GDI to PSDI among all the spark timings, respectively, while PSDI emitted the highest NOX emissions. As for particulate emissions, PSDI emitted the highest nucleation-mode PN, while GDI emitted the lowest. However, the accumulation-mode PN emitted from PSDI was approximately 52% of that from PGDI and 5% of that from GDI. This study demonstrates the benefits of PSDI for sustainability in vehicle engineering.