bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Relationships among High-Performance Organizations, Knowledge-Management Best Practices, and Innovation: Evidence from the Greek Public Sector
Authors: Xanthopoulou Styliani , Tsiotras George , Kafetzopoulos Dimitrios , Kessopoulou Eftychia
Published: September 2023

The paper aims to investigate the relationships among high-performance organizations (HPOs), knowledge-management (KM) best practices, and organizational innovation in the Greek public sector. To achieve this goal, we employed the PLS-SEM method to validate and assess the research model. A total of 270 responses were collected from employees in the Greek public sector. The results indicate that KM best practices serve as mechanisms for developing organizational innovation within the relationships between HPOs and organizational innovation in the Greek public sector. Additionally, positive relationships among the model constructs were observed. This research holds significant implications and contributions for both theory and practice. It offers novel theoretical insights by being the first study to investigate this relationship and explore the connections of HPOs with other managerial constructs such as KM. Moreover, the research findings hold importance for decision-makers in the public sector, equipping them with insights to formulate more-effective strategies for enhancing performance, quality, and innovation within their organizations.
Non-Linear Nexus of Technological Innovation and Carbon Total Factor Productivity in China
Authors: Xiu Jing , Zhao Tianyu , Jin Guangmin , Li Liang , Sun Huaping
Published: September 2023

Scientific and technological innovation is the main driving force of the growth in the 14th Five-Year Plan with the aim of “carbon peaking and neutralization.” This research analyzes the carbon total factor productivity (CTFP) improvement mechanism induced by micro-subject technological innovation and macro-technological progress (TP). This research constructed the Malmquist index based on a relaxed nonparametric DEA model, measured the TP level and CTFP in China, and considered the non-strict externalization of technological progress. The endogenous dynamic threshold model was used to test the nonlinear dynamic effect of TP driving the increase in CTFP. Through the intertemporal distance DEA model, undesired output model, and dynamic threshold regression model, we found that science and technology innovation of the TP drive the function of the carbon total factor productivity; there was a threshold effect (−0.556) on the driving impact of TP caused by technological innovation on CTFP, and the lag period of TP and CTFP had a positive driving role for CTFP. The driving effect on the left side of the threshold value was better than that on the right side. Considering the reality of slowing down the growth of capital and labor factor input in the 14th Five-Year Plan, it is essential to take active policy measures to promote the growth rate of TP by promoting the speed of micro-scientific and technological innovation. It is crucial to promote green TP in micro renewable energy enterprises, which, in turn, drive the growth of CTFP, improve the performance of low-carbon development, and reduce the negative impact of the “two-carbon” target on economic growth while realizing low-carbon transition.
Sustainable Construction through the Lens of Neoliberal Governance: The Case of Vernacular Building Systems in Catalonia, Spain
Authors: Alcindor Mónica , Jackson Delton
Published: September 2023

This paper asserts that neoliberal forms of governance are increasingly found in construction systems in Spain, a fact which becomes especially problematic when considering vernacular construction systems. Technological management and policy are both becoming more focussed on the promotion and consolidation of ‘expert systems’ at the expense of ‘different’ (and in particular) vernacular systems, which are processes which influence minds, and fundamentally shape subsequent actions. This paper adopts an ethnographic approach, undertaking investigation into the complexity of commonly found building systems, based upon empirical evidence gathered in the region of Catalonia. Focussing research on local vernacular construction systems reveals the extent to which the operation of distinct sets of managing ‘technologies’—embedded in specific practices such as auditing—becomes instrumental in shaping local construction practices. Currently, locally distinctive practices are deeply impacted by social influences generated far away, which have the consequences of significantly influencing, diluting, or even erasing vernacular building systems, even where these represent an important source of sustainable building techniques.
Impact of Natural Disasters on Household Income and Expenditure Inequality in China
Authors: Wang Weiwei , Zhao Yifan
Published: September 2023

Natural disasters have been demonstrated to cause devastating effects on economic and social development in China, but little is known about the relationship between natural disasters and income at the household level. This study explores the impact of natural disasters on household income, expenditure, and inequality in China as the first study of this nature for the country. The empirical analysis is conducted based on a unique panel dataset that contains six waves of the Chinese Household Income Project (CHIP) survey data over the 1988–2018 period, data on natural disasters, and other social and economic status of households. By employing the fixed effects models, we find that disasters increase contemporaneous levels of income inequality, and disasters that occurred in the previous year significantly increase expenditure inequality. Natural disasters increase operating income inequality but decrease transfer income inequality. Poor households are found to be more vulnerable to disasters and suffer significant income losses. However, there is no evidence to suggest that natural disasters significantly reduce the income of upper- and middle-income groups. These findings have important implications for policies aimed at poverty alleviation and revenue recycling, as they can help improve economic justice and enhance resilience to natural disasters.
A Differentiated Dynamic Reactive Power Compensation Scheme for the Suppression of Transient Voltage Dips in Distribution Systems
Authors: Dang Jie , Tang Fei , Wang Jiale , Yu Xiaodong , Deng Huipeng
Published: September 2023

At present, with the construction of new power systems, the uncertainty of the system is increasing and the transient voltage stability of the power grid is becoming more and more complicated. For this reason, this paper proposes a differentiated dynamic reactive power compensation configuration method for suppressing transient voltage dip instability. The method first establishes a dynamic reactive power device configuration indicator system based on multiple-two-element notation, and then establishes a differentiated dynamic reactive power compensation device configuration model based on the node instability risk characteristics. The model takes the investment cost and suppression effect as the optimization objectives, and flexibly adjusts the optimization weights of its cost and suppression effect according to the high or low risk of the transient voltage instability of the compensation node, so as to realize the differentiated dynamic reactive power compensation. Compared with traditional compensation methods, differentiated compensation can significantly improve the economic benefits of reactive power compensation configuration. Finally, taking the IEEE39 node test system as an example, the improved TLBO algorithm is used to solve the model. The cost of differentiated compensation is reduced by 22.13%, with a similar suppression effect, which verifies the validity of the method proposed in this paper.
Investigation on Air Ventilation within Idealised Urban Wind Corridors and the Influence of Structural Factors with Numerical Simulations
Authors: Xu Wen , Zhao Lushuang , Zhang Yunwei , Gu Zhaolin
Published: September 2023

Wind corridors are expected to be effective in alleviating the canopy urban heat island effect and air pollution. However, investigations on airflow characteristics within wind corridors, especially the influences of structural factors, are still limited. This current work performed numerical simulations on a group of idealised wind corridor models with different aspect ratios (ARs) and varying heights and/or widths along the corridors. Simulations revealed that the AR value had a vital influence on the wind speed, and an AR value of 0.1 facilitated the best ventilation conditions within the wind corridor. Structural variations along the corridor have a critical influence on ventilation, where the width contraction (contraction structure) and high-rise buildings (protrusion structure) would considerably weaken the wind speed within the corridors. The results suggested that wider and step-up structural design along the corridor should be encouraged in urban wind corridor planning, which would be helpful in promoting ventilation efficiency; but contraction structures should be prevented for primary wind corridor design.
China’s Future Countryside Model Construction and Development Level Evaluation
Authors: Chen Zhiwen , Xu Yixin , Wang Song , Jiang Ling , Yan Dan
Published: September 2023

Communities and villages are holistic organisms, representing a complete system formed by natural space and human activities. Since the concept of “future community” was put forward by the Drucker Foundation in the United States at the end of the 20th century, “future community” has expanded from the city to the countryside. Governments and scholars of various countries have started the practical and theoretical research into “future community”. Based on the theory of “village organism”, this paper constructs the structural model of the future countryside, and then constructs the health evaluation index system of the future countryside. This effectively makes up for the shortcomings of previous studies, and provides a new perspective and systematic analysis method for the study of community and village issues. Using entropy weight method and TOPSIS method, Jindong District was used as a case to conduct the quantitative evaluation of the development level of 46 administrative villages in the region. The results showed that: (1) the development level of the villages in the region was not high, and far from the requirements of future countryside, indicating that countryside revitalization has a long way to go; (2) within the region, competitive convergence occurs in the development process of all villages; (3) of the two major countryside systems in the future, the health level of the physical space system is higher than that of the social system, indicating that the local government pays more attention to the construction of the “external” image of the countryside and ignores the improvement of the “internal” function of the countryside society; (4) in the prospective construction of nine scenes of future countryside, an observable trend towards “grouping” differentiation emerges. This phenomenon underscores existing deficiencies in countryside construction, indicating that countryside areas still fail to realize the function of being “self-hematopoietic”. The determination and selection of sample indicators exhibit regional cultural disparities, permitting various regions to customize indicators with their specific contextual circumstances. Nevertheless, the universal approach of treating countryside areas as holistic entities remains essential in scholarly inquiry.
Machine Learning for APT Detection
Authors: AL-Aamri Abdullah Said , Abdulghafor Rawad , Turaev Sherzod , Al-Shaikhli Imad , Zeki Akram , Talib Shuhaili
Published: September 2023

Nowadays, countries face a multitude of electronic threats that have permeated almost all business sectors, be it private corporations or public institutions. Among these threats, advanced persistent threats (APTs) stand out as a well-known example. APTs are highly sophisticated and stealthy computer network attacks meticulously designed to gain unauthorized access and persist undetected threats within targeted networks for extended periods. They represent a formidable cybersecurity challenge for governments, corporations, and individuals alike. Recognizing the gravity of APTs as one of the most critical cybersecurity threats, this study aims to reach a deeper understanding of their nature and propose a multi-stage framework for automated APT detection leveraging time series data. Unlike previous models, the proposed approach has the capability to detect real-time attacks based on stored attack scenarios. This study conducts an extensive review of existing research, identifying its strengths, weaknesses, and opportunities for improvement. Furthermore, standardized techniques have been enhanced to enhance their effectiveness in detecting APT attacks. The learning process relies on datasets sourced from various channels, including journal logs, traceability audits, and systems monitoring statistics. Subsequently, an efficient APT detection and prevention system, known as the composition-based decision tree (CDT), has been developed to operate in complex environments. The obtained results demonstrate that the proposed approach consistently outperforms existing algorithms in terms of detection accuracy and effectiveess.
Young Travellers and Green Travel in the Post-COVID Era
Authors: Nagaj Rafał , Žuromskaitė Brigita
Published: September 2023

The concept of sustainable mobility and related green travel will play an increasingly important role in the development of tourism and climate policy in the European Union. Initiated by the European Commission, Erasmus+ green travel is a new initiative and not yet researched by EU institutions or in the literature. However, it fits in with the literature research on green mobility. The aim of this paper was to assess whether young tourists are interested in green mobility, whether they are willing to use means of low-emission transport when making trips, what factors play a role in their means of transport choices, and whether risk aversion influences their choices. For the purpose of this work, the authors conducted a survey in Poland among 36 Polish and foreign people from Generation Z studying in Poland and taking advantage of the green travel program in the Erasmus+ program and an economic experiment regarding their level of risk taking. Based on these data, it was examined whether young tourists are interested in green mobility, what factors play an important role when choosing a low-emission means of transport, and whether the level of risk taking influences their choices. The results of the survey indicated that young tourists tend to choose means of high-emission transport or a mix of high- and low-emission transport. However, if they receive a financial incentive, they are willing to use means of low-emission transport when travelling. The results of this study also indicated that environmental factors do not influence the propensity of young tourists towards specific means of transport, including low-emission transport, and economic and cognitive factors play an important role. It was also found that there is some positive relationship between the level of risk taking of the traveller and the propensity to green travel.
PEMFC Current Control Using a Novel Compound Controller Enhanced by the Black Widow Algorithm: A Comprehensive Simulation Study
Authors: Silaa Mohammed Yousri , Barambones Oscar , Cortajarena José Antonio , Alkorta Patxi , Bencherif Aissa
Published: September 2023

Proton exchange membrane fuel cells (PEMFCs) play a crucial role in clean energy systems. Effective control of these systems is essential to optimize their performance. However, conventional control methods exhibit limitations in handling disturbances and ensuring robust control. To address these challenges, this paper presents a novel PI sliding mode controller-based super-twisting algorithm (PISMCSTA). The proposed controller is applied to drive the DC/DC boost converter in order to improve the PEMFC output power quality. In addition, the black widow optimization algorithm (BWOA) has been chosen to enhance and tune the PISMCSTA parameters according to the disturbance changes. The performance of the PISMCSTA is compared with the conventional STA controller. Comparative results are obtained from numerical simulations and these results show that the developed proposed PISMCSTA gives better results when compared to the conventional STA. A reduction of up to 8.7% in the response time could be achieved and up to 66% of the chattering effect could be eliminated by using the proposed controller. Finally, according to these results, the proposed approach can offer an improvement in energy consumption.
Modelling Hydrate Deposition in Gas-Dominant Subsea Pipelines in Operating and Shutdown Scenarios
Authors: Umuteme Oghenethoja Monday , Islam Sheikh Zahidul , Hossain Mamdud , Karnik Aditya
Published: September 2023

This study addresses a significant research gap related to hydrate formation in subsea gas pipelines, with a specific focus on deposition rates during shutdown scenarios, which has received limited attention in previous studies. Past research has employed various methodologies, including experimental, analytical, and computational fluid dynamics (CFD) approaches, to predict hydrate formation conditions, but none have tackled the prediction of hydrate deposition during shutdowns. In this study, we employ a multiple linear regression modeling approach using the MATLAB regression learner app. Four distinct regression models were developed using data generated from 81 CFD simulations, utilising a 10 m length by 0.0204 m diameter 3D horizontal pipe model in Ansys Fluent, as previously developed Through cross-validation against experimental data, the standard linear regression model emerged as the most reliable choice for predicting hydrate deposition rates, providing predictions within ±10% uncertainty bounds of experimental results up to pressures of 8.8 MPa at hydrate-forming temperatures. The uniqueness of this new model lies in its ability to estimate the risk of hydrate deposition in subsea gas pipelines, especially with low gas flow rates and during shutdown periods, which are critical for maintenance planning. Furthermore, by estimating depositional volumes, the model predicts hydrate slurry volumes at receiving facilities, contributing to energy sustainability and benefiting gas transport pipeline operators, particularly in aging gas fields with declining production.
Research on the Symbiotic Model of Supply Chains Based on the Logistic Expansion Model for E-Commerce Platforms
Authors: Zhang Wei , Fan Yangming , Yuan Ye
Published: September 2023

With the development of globalization and technology, e-commerce platforms provide a more convenient shopping experience while also increasing the complexity and difficulty of the supply chain. Managers of e-commerce platform operations need to think about and investigate how to optimize the supply chains of e-commerce platforms, reduce costs and improve efficiency. In this paper, we use the logistic population expansion model to explore the symbiotic relationship among the core populations, key populations and supporting populations within the supply chain ecosystem of e-commerce platforms and the conditions that affect the evolution direction of the symbiotic model. The results show the following: (1) The size of the symbiosis between the three types of populations determines the equilibrium state of the symbiotic evolution of the e-commerce platform supply chain ecosystem. (2) The value of the sum of the symbiotic interaction coefficients between subjects in the supply chain ecosystem of an e-commerce platform determines the result of the symbiotic evolution of the system. (3) The reciprocal symbiosis model can maximize the synergy of the three types of subjects and is the best goal direction for ecosystem evolution. This study can provide a theoretical basis and practical support for the development of e-commerce platform-related enterprises.
Spatio-Temporal Modeling of COVID-19 Spread in Relation to Urban Land Uses: An Agent-Based Approach
Authors: Tabasi Mohammad , Alesheikh Ali Asghar , Kalantari Mohsen , Mollalo Abolfazl , Hatamiafkoueieh Javad
Published: September 2023

This study aims to address the existing gaps in evidence regarding spatio-temporal modeling of COVID-19 spread, specifically focusing on the impact of different urban land uses in a geospatial information system framework. It employs an agent-based model at the individual level in Gorgan, northeast Iran, characterized by diverse spatial and demographic features. The interactions between human agents and their environment were considered by incorporating social activities based on different urban land uses. The proposed model was integrated with the susceptible–asymptomatic–symptomatic–on treatment–aggravated infection–recovered–dead epidemic model to better understand the disease transmission at the micro-level. The effect of various intervention scenarios, such as social distancing, complete and partial lockdowns, restriction of social gatherings, and vaccination was investigated. The model was evaluated in three modes of cases, deaths, and the spatial distribution of COVID-19. The results show that the disease was more concentrated in central areas with a high population density and dense urban land use. The proposed model predicted the distribution of disease cases and mortality for different age groups, achieving 72% and 71% accuracy, respectively. Additionally, the model was able to predict the spatial distribution of disease cases at the neighborhood level with 86% accuracy. Moreover, findings demonstrated that early implementation of control scenarios, such as social distancing and vaccination, can effectively reduce the transmission of COVID-19 spread and control the epidemic. In conclusion, the proposed model can serve as a valuable tool for health policymakers and urban planners. This spatio-temporal model not only advances our understanding of COVID-19 dynamics but also provides practical tools for addressing future pandemics and urban health challenges.
Exploring the Influence of Smart Product Service Systems on Enterprise Competitive Advantage from the Perspective of Value Creation
Authors: Hou Linna , Su Juning , Ye Yu
Published: September 2023

With the continuous development of information and communication technology, the development of smart product service systems (smart PSS) has become a crucial approach for enterprises to establish a competitive advantage. However, there is still a lack of clarity regarding the impact process of smart PSS on competitive advantage. This paper aims to explore the impact mechanism of smart PSS on competitive advantage from the perspective of value creation, using an intelligent connected vehicle supplier as a case study. The findings reveal that the composition of smart PSS, including smart technology, smart products, and smart services, influences competitive advantage through the value creation process, which involves relationship construction, relationship operation, and value release. Under the smart PSS environment, changes occur in subject relationships, resources, and key elements. In the context of smart PSS, deep cooperation between enterprises and partners focuses on ecological advantages, while general cooperation emphasizes benefit advantages. This research provides valuable insights into the impact of smart PSS composition on competitive advantage and offers reference values for organizations to establish competitive advantage objectives.
Accumulated Carbon Fractions in Tropical Sandy Soils and Their Effects on Fertility and Grain Yield in an Integrated Crop–Livestock System
Authors: Soares Deyvison de Asevedo , Sekiya Bianca Midori Souza , Modesto Viviane Cristina , Nakao Allan Hisashi , Freitas Leandro Alves , Souza Isabela Malaquias Dalto de , da Luz João Henrique Silva , Galindo Fernando Shintate , Lupatini Gelci Carlos , Pavan Mateus Gustavo , Bonini Carolina dos Santos Batista , Andrighetto Cristiana , Mendes Iêda de Carvalho , Pavinato Paulo Sergio , Andreotti Marcelo
Published: September 2023

Food production in sandy soils has evolved significantly, most notably through the advent of integrated crop–livestock systems (ICLSs). ICLSs increase soil cover, which maintains soil moisture and sequesters carbon (C). Here we investigate the influence of ICLSs on soil physical, chemical, and biochemical properties, and grain yield (GY) in tropical sandy soils in short-time. We compared seven ICLSs in two consecutive crops seasons (with soybean or maize as cash crops) in southeastern Brazil. These were (1) corn + Urochloa brizantha cv. BRS Paiaguás—soybean (ICL-Paiaguás); (2) corn + U. brizantha cv. BRS Piatã—soybean; (3) corn + U. ruziziensis—soybean; (4) corn–soybean under conventional tillage (CT) as a negative control; (5) corn–soybean under no-tillage (NT) as a positive control; (6) Paiaguás grass—continuous grazing (Perennial Paiaguás); (7) and Piatã grass—continuous grazing (Perennial Piatã). Soybean and corn GY data, soil physical and chemical attributes, and soil enzymatic activity were subjected to descriptive statistics and multivariate analysis. CT and NT shared high loadings of H + Al, Al, and soil temperature and low loadings of soil pH, SOM physical and chemical fractions, cationic exchange capacity, and arylsulfatase activity. ICL-Paiaguás and Perennial Piatã had a similarly high loading of total N, humin, total organic carbon, and mineral-associated carbon stocks. The fulvic acid fraction was the most sensitive to C accumulation in the sandy soil under ICLSs. Soil water and thermal regimes were limiting in both CT and NT. The study not only confirms the capacity of conservation mechanisms to enhance soil-based ecosystem functions, but it also highlights the potential of ICLSs to aid sustainable food production even in the context of tropical sandy soils, which frequently receive limited attention in intensive agricultural practices.
Bioresources in the Formation of New-Generation Products
Authors: Kolesnik Vladimir , Shcherbenko Eva , Valeeva Ylia
Published: September 2023

The development of new-generation products using the potential of Siberian bioresources is relevant in modern conditions. This process is aimed at protecting the health of people living in a polluted urban environment and the threat of the COVID-19 coronavirus pandemic. The article highlights and describes the characteristic distinctive features of the beneficial properties of the wild flora of Siberia, presents the results of the research conducted by the authors, and provides an assessment of the state and potential of the natural resource base and bioresources of the ecosystem of the Siberian taiga. The study summarizes the current trends of the active part of the population of developed countries towards a healthy lifestyle, indicating an annual increase in demand for natural products. The article presents an analysis of scientific developments and their advantages over previously used methods of protection against infections in an indoor air pool. With the help of laboratory tests, the authors evaluated and justified the feasibility of a new proposed product created using bioresources of wild flora of Siberia which are valuable and useful for humans. It is established that the proposed scientific and technical solutions improve the quality of the products offered, stimulate the consumer to preserve health, and encourage reasonable environmental management. The production and implementation of the developed anti-aging products will contribute to the reduction of consumer race and improve the quality of life of the population of large cities.
Research on Green Finance, Technological Innovation, and Industrial Structure Upgrading in the Yangtze River Economic Belt
Authors: Tang Decai , Yan Jing , Sheng Xin , Hai Yuehao , Boamah Valentina
Published: September 2023

Along with the fact that China is in a critical period of economic structural transformation, industrial structural upgrading and transformation are imminent. The empirical research in this paper mainly constructs four groups of fixed effects models. The purpose is to investigate the impact mechanisms of green finance (GF), technological innovation (TI), and industrial structure upgrading (ISU) in 11 provinces (cities) along the Yangtze River Economic Belt (YREB) from 2011 to 2020. Based on the research method of the fixed effects model, this paper can analyze the association between GF, TI, and ISU in a more concise and intuitive way. The research conclusions mainly include the following three points. Firstly, both GF and TI are able to significantly contribute to the ISU of the YREB. Furthermore, GF can also promote TI to a certain extent. Second, TI serves as a partial intermediary in the process of GF’s favorable contribution to the ISU. In other words, green finance can act as an intermediary by enhancing technological innovation capacity so as to effectively accelerate the ISU of the YREB. Thirdly, this paper finds that there exists a degree of regional heterogeneity in the process of GF and TI affecting ISU in the YREB. For one thing, GF in the eastern part of the YREB can strongly accelerate the ISU. However, there is no obvious impact effect in the central and western regions. For another, TI in the eastern part of the YREB has, likewise, contributed positively to the ISU. In comparison, TI in the central region has a clearly negative effect on the ISU while there is no significant influence effect in the western region. In conclusion, this paper innovatively integrates GF, TI, and ISU into a framework for research. This paper not only widens the theoretical research domain of industrial structure upgrading but also provides practical guidance for the restructuring and transformation of industries in the YREB.
Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling
Authors: Faezipour Misagh , Faezipour Miad , Pourreza Saba
Published: September 2023

The prevalence of skin diseases remains a concern, leading to a rising demand for the advancement of smart, portable, and non-invasive automated systems and applications. These sought-after technologies allow for the screening of skin lesions through captured images, offering improved and accessible healthcare solutions. Clinical methods include visual inspection by dermatologists; computer-aided vision-based image analysis at healthcare settings; and, lastly, biopsy tests, which are often costly and painful. Given the rise of artificial intelligence-based techniques for image segmentation, analysis, and classification, there remains a need to investigate the resiliency of personalized smartphone (hand-held) skin screening systems with respect to identified risks. This study represents a unique integration of distinct fields pertaining to smart vision-based skin lesion screening, resiliency, risk assessment, and system dynamics. The main focus is to explore the dynamics within the supply chain network of smart skin-lesion-screening systems. With the overarching aim of enhancing health, well-being, and sustainability, this research introduces a new framework designed to evaluate the resiliency of smart skin-lesion-screening applications. The proposed framework incorporates system dynamics modeling within a novel subset of a causal model. It considers the interactions and activities among key factors with unique mapping of capability and vulnerability attributes for effective risk assessment and management. The model has been rigorously tested under various case scenarios and settings. The simulation results offer insights into the model’s dynamics, demonstrating the fact that enhancing the skin screening device/app factors directly improves the resiliency level. Overall, this proposed framework marks an essential step toward comprehending and enhancing the overall resiliency of smart skin-lesion-screening systems.
Social Life Cycle Assessment of a Coffee Production Management System in a Rural Area: A Regional Evaluation of the Coffee Industry in West Java, Indonesia
Authors: Rahmah Devi Maulida , Purnomo Dwi , Filianty Fitry , Ardiansah Irfan , Pramulya Rahmat , Noguchi Ryozo
Published: September 2023

The demand for coffee in the local and global markets has encouraged massive production at upstream and downstream levels. The socioeconomic impact of coffee production still presents an issue, primarily related to the social benefit and economic value added for farmers. This study aims to identify the social impact of the coffee industry in rural areas in three different coffee industry management systems. Many coffee industries exist in rural areas, with various management systems: farmer group organizations, middlemen, and smallholder private coffee production. This study performed the social organization life cycle assessment to identify the social impact of the coffee industry in rural areas according to the management systems. The results indicated that the coffee industry managed by farmers is superior in providing a positive social impact to four stakeholders: workers, the local community, society, and suppliers, as indicated by the highest social impact scores of 0.46 for the workers, 0.8 for the local community, 0.54 for society, and 0.615 for the suppliers. The private coffee industry provides the highest social impact to consumers (0.43), and the middlemen were very loyal to the shareholders, with a total social impact score of 0.544. According to this social sustainability index analysis, the coffee industry managed by the farmer group has the highest endpoint of social impact at 0.64, which is categorized as the “sustainable” status. Meanwhile, the coffee industry managed by private companies and middlemen is categorized as “neutral or sufficient”. The coffee industry should implement improvement strategies to increase their social impact to all stakeholders in their business supply chain.
Reexamining the Impact of Global Value Chain Participation on Regional Economic Growth: New Evidence Based on a Nonlinear Model and Spatial Spillover Effects with Panel Data from Chinese Cities
Authors: Li Can , He Qi , Ji Han , Yu Shengguo , Wang Jiao
Published: September 2023

This study utilizes panel data drawn from 239 Chinese cities, and it employs fixed-effects models, mediation models, and spatial spillover models to reexamine the actual impact of the global value chain’s (GVC) participation on regional economic growth. The findings reveal that this impact exhibits a U-shaped nonlinear pattern, with the turning point of GVC occurring at 0.45, which is higher than that of 222 cities. Most cities are on the left side of the U-shaped curve, which corresponds with the second stage of the “in-out-in-again” GVC participation pattern (i.e., the “out” stage). During this stage, a decline in foreign value-added ratio (FVAR), with regard to exports (accompanied by an increase in the domestic value-added ratio), promotes economic growth. Innovation capability acts as a mediator in the relationship between GVC participation and economic growth. Furthermore, GVC participation has significant spillover effects on neighboring cities, with siphon and spillover effects coexisting. Thus, China should focus on establishing domestic value chains and innovation systems, achieving relative independence from existing GVCs dominated by developed countries, enhancing indigenous innovation capabilities, and laying the foundation for the third stage (in-again) of reintegration into GVCs, at the high value-added end, to achieve a higher level of openness. This study explores the nonlinear impact of GVC participation on regional economic growth in China from both theoretical and empirical perspectives, focusing on the finest divisions that remain feasible—cities. This approach expands and supplements the relevant field of research in valuable ways, yielding more realistic research conclusions and policy recommendations.
A Novel Adaptive UE Aggregation-Based Transmission Scheme Design for a Hybrid Network with Multi-Connectivity
Authors: Chen Huamin , Fang Ruijie , Chen Tao , Wang Peng , Wang Zhuwei , Lin Shaofu , Li Fan
Published: September 2023

With the progress of the eras and the development of science and technology, the requirements of device-to-device (D2D) connectivity increased rapidly. As one important service in future systems, ultra-reliable low-latency communication (URLLC) has attracted attention in many applications, especially in the Internet of Things (IoT), smart cities, and other scenarios due to its characteristics of ultra-low latency and ultra-high reliability. However, in order to achieve the requirement of ultra-low latency, energy consumption often increases significantly. The optimization of energy consumption and the latency of the system in the communication field are often in conflict with each other. In this paper, in order to optimize the energy consumption and the latency jointly under different scenarios, and since the detailed requirements for latency and reliability are diverse in different services, we propose an adaptive UE aggregation (AUA)-based transmission scheme that explores the diversity gain of multiple simultaneous paths to reduce the overall latency of data transmission, wherein multiple paths correspond to multiple coordination nodes. Furthermore, it could provide the feasibility of link adaptation by adjusting the path number according to the real transmission environment. Then, unnecessary energy waste could be avoided. To evaluate the performance, the energy-delay product (EDP) is proposed for the latency and energy comparison. The provided simulation results align with the numerical data. Through the analysis, it can be proven that the proposed scheme can achieve a joint optimization of latency and energy consumption to meet different types of URLLC services.
Vertical Symmetry Is Special to Infants; Vertical Symmetry in Upright Human Faces More So
Authors: Bornstein Marc H. , Mash Clay , Arterberry Martha E. , Esposito Gianluca
Published: September 2023

Symmetry has long been viewed as a feature of objects that facilitates ease of perception. Three experiments investigated 4- to 5-month-old infants’ detection and processing of vertical symmetry, oblique symmetry, and asymmetry in novel patterns and faces. In Experiment 1, infants showed the fewest shifts in visual fixations to vertical symmetry in patterns and faces, supporting the view that vertical symmetry is processed more efficiently than oblique symmetry or asymmetry. In Experiment 2, stimulus presentation disallowed more than a single visual fixation, and infants looked longer at a face that is vertically symmetrical compared to obliquely symmetrical or asymmetrical, and they looked equally to patterns regardless of symmetry. In Experiment 3, where pattern exposures were prolonged and inverted faces viewed, infants discriminated vertical symmetry in patterns but lost the advantage with vertical symmetry in faces. Thus, symmetry in patterns requires more processing time from infants, and inverting the face costs infants the normal perceptual advantage of symmetry, even though components of the face remain symmetrical. These findings suggest that infants are prepared to exploit symmetry in their everyday perceptual worlds.
Accurate Electromagnetic Force Analysis of Offshore Wind Power Transformer Windings Based on Fractional Order Lumped Parameter Model
Authors: Zhong Hui , Zuo Yuheng , Wang Runze , Zhang Li , Ouyang Xiaoshan
Published: September 2023

Accurate calculation of the electromagnetic force distribution of transformer windings under different loads and fault conditions is of great significance for transformer maintenance, condition evaluation and life prediction. Due to the influence of offshore wind power systems, offshore wind power transformers have high harmonic content and large changes in load rates, which can easily cause the coil destabilization, winding deformation or even damage because of the uneven distribution of the electromagnetic force. To improve the accuracy of electromagnetic force calculation, this paper proposes a fractional order numerical method. First, a three-dimensional axisymmetric transformer model and a symmetrical lumped parameter equivalent circuit model are established, respectively, based on field-circuit coupling. Second, the fractional order approximation of circuit components is realized by using the improved Oustaloup filter. In the fractional order model, the transformer is replaced by the lumped parameter equivalent circuit model. Third, as in the calculation process for integer order electromagnetic force, the integer order current has a large error, and the current waveform does not match the actual power frequency. The fractional order current and electromagnetic force at the 0.9 order are closer to the rated value. Finally, the effects of different load rates, three-phase short circuits and harmonic conditions are studied with the fractional order model. Compared with the traditional integer order finite element electromagnetic model, the fractional order equivalent circuit model established in this paper is more accurate and suitable for electromagnetic force calculation. The proposed method is significant for the structural design and state detection of transformers and also could be applied in the analysis of other dry-type transformers.
Generation of Stable Entanglement in an Optomechanical System with Dissipative Environment: Linear-and-Quadratic Couplings
Authors: Rafeie Mehran , Tavassoly Mohammad Kazem
Published: September 2023

In this paper, we present a theoretical scheme for the generation and manipulation of bipartite atom–atom entanglement in a dissipative optomechanical system containing two atoms in the presence of linear and nonlinear (quadratic) couplings. To achieve the goal of paper, we first obtain the interaction Hamiltonian in the interaction picture, and then, by considering some resonance conditions and applying the rotating wave approximation, the effective Hamiltonian, which is independent of time, is derived. In the continuation, the system solution was obtained via solving the Lindblad master equation, which includes atomic, optical and mechanical dissipation effects. Finally, bipartite atom–atom entanglement is quantitatively discussed, by evaluating the negativity, which is a well-known measure of entanglement. Our numerical simulations show that a significant degree of entanglement can be reached via adjusting the system parameters. It is noticeable that the optical and mechanical decay rates play an important role in the quasi-stability and even stability of the obtained atom–atom entanglement.
Nonlocal Modification of the Kerr Metric
Authors: Frolov Valeri P. , Soto Jose Pinedo
Published: September 2023

In the present paper, we discuss a nonlocal modification of the Kerr metric. Our starting point is the Kerr–Schild form of the Kerr metric gμν=ημν+Φlμlμ. Using Newman’s approach, we identify a shear free null congruence l with the generators of the null cone with apex at a point p in the complex space. The Kerr metric is obtained if the potential Φ is chosen to be a solution of the flat Laplace equation for a point source at the apex p. To construct the nonlocal modification of the Kerr metric, we modify the Laplace operator ▵ by its nonlocal version exp(−ℓ2▵)▵. We found the potential Φ in such an infinite derivative (nonlocal) model and used it to construct the sought-for nonlocal modification of the Kerr metric. The properties of the rotating black holes in this model are discussed. In particular, we derived and numerically solved the equation for a shift of the position of the event horizon due to nonlocality. AlbertaThy 5–23.
Statistical Modeling of Financial Data with Skew-Symmetric Error Distributions
Authors: Jimichi Masayuki , Kawasaki Yoshinori , Miyamoto Daisuke , Saka Chika , Nagata Shuichi
Published: September 2023

Based on corporate financial data for almost all companies listed on the Prime Market of the Tokyo Stock Exchange in fiscal year 2021, we gradually refine a model to explain firms’ sales by the number of employees and total assets. Starting from a Cobb–Douglas-type functional form linearized by a log transformation, the assumption of a skew-symmetric distribution in the error structure and the introduction of industry dummies are shown to be useful not only in searching for a good-fitting model, but also in ensuring the accuracy of important parameters such as the labor share. The introduction of industry dummies helps to improve the accuracy of the model as well as to allow for interpretation as sector-wise total factor productivity.
Atangana-Baleanu Fractional Dynamics of Predictive Whooping Cough Model with Optimal Control Analysis
Authors: Butt Azhar Iqbal Kashif
Published: September 2023

Whooping cough, or pertussis, is an infectious disease that causes serious threats to people of all ages, specifically to infant and young children, all over the world. Due to the severe impact on health, it is necessary to construct a mathematical model that can be used to predict future dynamics of the disease, as well as to suggest strategies to eliminate the disease in an optimal way. For this, we constructed a new Atangana–Baleanu fractional model for whooping cough disease to predict the future dynamics of the disease, as well as to suggest strategies to eliminate the disease in an optimal way. We prove that the proposed model has a unique solution that is positive and bounded. To measure the contagiousness of the disease, we determined the reproduction number R0 and used it to examine the local and global stability at equilibrium points that have symmetry. Through sensitivity analysis, we determined parameters of the model that are most sensitive to R0. The ultimate aim of this research was to analyze different disease prevention approaches in order to find the most suitable one. For this, we included the vaccination and quarantine compartments in the proposed model and formulated an optimal control problem to assess the effect of vaccination and quarantine rates on disease control in three distinct scenarios. Firstly, we study the impact of vaccination strategy and conclude the findings with a graphical presentation of the results. Secondly, we examine the impact of quarantine strategy on whooping cough infection and its possible elimination from society. Lastly, we implement vaccination and quarantine strategies together to visualize their combined effect on infection control. In addition to the study of the optimal control problem, we examine the effect of the fractional order on disease dynamics, as well as the impact of constant vaccination and quarantine rates on disease transmission and control. The numerical results reveal that the optimal control strategy with vaccination and quarantine together would be more effective in reducing the spread of whooping cough infection. The implementation of the Toufik–Atangana-type numerical scheme for the solution of the fractional optimal control problem is another contribution of this article.