bluuebunny/crossref_metadata_2025 huggingface dataset:
Patent Data Analytics for Technology Forecasting of the Railway Main Transformer
Authors: Lee Yong-Jae , Han Young Jae , Kim Sang-Soo , Lee Chulung
Published: December 2022

The railway main transformer is considered one of the most important electrical equipment for trains. Companies and research institutes around the world are striving to develop high-performance railway main transformers. In order to be the first mover for railway main transformer technology, companies and research institutes should predict vacant technology based on the analysis of promising detailed technology areas. Therefore, in this study, a patent analysis to predict vacant technologies based on identified promising IPC technology areas is provided. In order to identify promising detailed IPC technology areas, the technology mapping analysis, the time series analysis, and the social network analysis are conducted based on the patent-IPC matrix, extracted from the data information of 707 patents from the patent database of Korea, China, Japan, United States, Canada, and Europe. Then, through the GTM analysis based on promising detailed IPC technology areas, one vacant technology node and three analysis target nodes surrounding the vacant technology node are obtained to predict vacant technologies. From the analysis, we predict the following three groups of vacant technologies: (1) blowerless technology, (2) oil-free technology, and (3) solid-state technology. This study provides insights on the technology trend in railway main transformers, as well as the analysis framework for the development of R&D strategies based on the patent data.
Evaluating Compost from Digestate as a Peat Substitute in Nursery for Olive and Hazelnut Trees
Authors: Calisti Roberto , Regni Luca , Pezzolla Daniela , Cucina Mirko , Gigliotti Giovanni , Proietti Primo
Published: December 2022

This study deals jointly with three aspects of environmental, agricultural and energy sustainability: (a) Biogas is a booming energy source worldwide, resulting in an increasing production of digestate, its main by-product; (b) The extraction of peat, mainly used for nursery substrates, is being banned due to the destruction of natural habitats and release of GHGs; (c) Compost can represent a replacement of peat and contributes to the containment of GHGs. This study has verified how a compost obtained from digestate can be used as a substitute for peat in the nursery sector. While previous studies have evaluated compost use on just one species at a time, this study compared the same compost on two very different species: olive tree and hazelnut tree, both with growing interest for new tree plantings. Two concentrations of compost in the potting substrate of nursery seedlings were evaluated: 30% and 45% by weight, measuring the effect on some growth parameters during the growing season. The trials showed responses positive for olive and substantially negative for hazelnut: olive trees manifested better growth parameters with 45% compost, as opposed to hazelnut, where the addition of 45% compost worsened all growth parameters. A general conclusion can be drawn: in the nursery sector, compost can be used to replace peat, but this replacement can almost never be 100 percent, having instead to calibrate the percentage of replacement according to the characteristics of the compost and the individual edaphic needs of the plant species.
Mining Braces of Innovation Linking to Digital Transformation Grounded in TOE Framework
Authors: Li Fumeng , Long Jiancheng , Zhao Wu
Published: December 2022

How firms drive innovation in digital transformation remains largely unanswered and this article is an attempt in that direction to deconstruct the digital innovation of small and medium-sized manufacturing enterprises (SMMEs) realizability condition and evolve the body of knowledge. We developed a TOE framework based on digital innovation theory to investigate the impact of the configuration effect of technology, organization and environment regarding the characteristic on a firm’s digital innovation. We performed fuzzy-set qualitative comparative analysis (fsQCA) on survey data collected from 141 SMMEs in China to examine configuration paths formed by different conditions. The results reveal that the success of a firm’s digital innovation practice is not driven by a single factor, but the result of multiple factors’ combined interaction, in which four sets of high digital innovation realization paths could be further summarized as “total factor driven”, “technology-environment oriented”, “organization-technology oriented”, and “organization oriented-environment”. These findings make sound theoretical and practical contributions to the usage of the TOE framework in the domain of developing a firm’s digital innovation. Bringing the SMMEs’ enlightenment is digital innovation, which is integral, systematic engineering, despite technology itself being the primary role of the whole process, more important is the organization’s agile strategy and digital positioning, as well as making full use of the advantages of the current environment for companies, thus better promoting the emergence and deepening digital innovation.
Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape
Authors: Saxena Archana , Singh Rajesh , Gehlot Anita , Akram Shaik Vaseem , Twala Bhekisipho , Singh Aman , Montero Elisabeth Caro , Priyadarshi Neeraj
Published: December 2022

Currently, sustainability is a vital aspect for every nation and organization to accomplish Sustainable Development Goals (SDGs) by 2030. Environmental, social, and governance (ESG) metrics are used to evaluate the sustainability level of an organization. According to the statistics, 53% of respondents in the BlackRock survey are concerned about the availability of low ESG data, which is critical for determining the organization’s sustainability level. This obstacle can be overcome by implementing Industry 4.0 technologies, which enable real-time data, data authentication, prediction, transparency, authentication, and structured data. Based on the review of previous studies, it was determined that only a few studies discussed the implementation of Industry 4.0 technologies for ESG data and evaluation. The objective of the study is to discuss the significance of ESG data and report, which is used for the evaluation of the sustainability of an organization. In this regard, the assimilation of Industry 4.0 technologies (Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data for obtaining ESG data by an organization is detailed presented to study the progress of advancement of these technologies for ESG. On the basis of analysis, this study concludes that consumers are concerned about the ESG data, as most organizations develop inaccurate ESG data and suggest that these digital technologies have a crucial role in framing an accurate ESG report. After analysis a few vital conclusions are drawn such as ESG investment has benefited from AI capabilities, which previously relied on self-disclosed, annualized company information that was susceptible to inherent data issues and biases. Finally, the article discusses the vital recommendations that can be implemented for future work.
Evaluation of Public Transport among University Commuters in Rural Areas
Authors: Alomari Ahmad H. , Khedaywi Taisir S. , Jadah Asalah A. , Marian Abdel Rahman O.
Published: December 2022

This study aimed to evaluate the quality of Public Transport (PT) in the Jordan University of Science and Technology (JUST) area, Irbid, Jordan. The study focused on two different analytical techniques. The first was the Partial Least Squares Structural Equation Model (PLS-SEM) method to analyze student satisfaction and loyalty toward using PT. The second method was binary logistic regression (BLR), which analyzed factors such as socioeconomic status and travel habits that might make someone choose PT or their car to travel to JUST. Data were collected through an electronic and paper-based questionnaire with 572 participants. This study concluded that the proposed structural model could explain 76% of the loyalty variance. Passenger satisfaction, perceived service quality, perceived costs, and environmental impact were four of the five factors directly influencing passenger loyalty that demonstrated significant impact. In addition, it was concluded that through Multi-Group Analysis (MGA), gender group was the most influential categorical moderator variable. Moreover, the indirect analysis showed that perceived service quality was the most important mediator between the observed constructs’ relationships. BLR showed that the mode of transportation at JUST was statistically correlated with occupancy, travel cost, travel time, average use of PT, and car ownership, with an overall model accuracy of 90.0%. In conclusion, by considering the discussed influencing factors, it is recommended that transportation agencies consider perceived costs, information, reliability, safety, and vehicle characteristics variables while improving PT service quality and travel time, especially in rural areas, which may raise passenger satisfaction, shift car users to PT, and lower emissions. Thus, research results can assist policymakers in implementing sustainable modes of PT.
Risk Management in University–Industry R&D Collaboration Programs: A Stakeholder Perspective
Authors: Fernandes Gabriela , Domingues Joana , Tereso Anabela , Micán Camilo , Araújo Madalena
Published: December 2022

Current knowledge of risk management (RM) is mainly limited to single organizations. This paper investigates RM practices from a stakeholders’ perspective applicable to university–industry R&D collaboration (UIC) programs, a particular form of inter-organizational relationship. With a view to reducing the negative impact of risk associated with such UICs, and, as a result, increasing the success rate of the related programs and projects, an RM methodology has been developed from the perspective of the main stakeholders. The results reported here are based on a large-scale UIC between the Bosch Car Multimedia in Portugal and the University of Minho. Three research methods were applied in a complementary way: participant observation over seven years, analysis of various documents supporting the management of the programs and projects, and focus group involving seven key participants from different roles. The proposed RM methodology takes into account the three main stakeholders and their respective RM roles—Program Manager, Program and Project Management Officer, and Project Manager—and helps to manage the risks incurred by a UIC program while, at the same time, emphasizing the importance of taking the stakeholders’ perspective. In inter-organizational contexts, particularly in the case of university and industry, where there is a cultural gap between members, misunderstandings may occur about the role each key stakeholder should play. This paper provides a comprehensive guideline for the application of the methodology by means of a proposed set of specific RM practices. However, the research was conducted using a single case study, therefore limiting the results’ potential for generalization.
Crisis Adaptation in a Thai Community-Based Tourism Setting during the COVID-19 Pandemic: A Qualitative Phenomenological Approach
Authors: Sann Raksmey , Lai Pei-Chun , Chen Chi-Ting
Published: December 2022

Introduction: COVID-19 has severely impacted industries and individual lives globally. Due to travel restrictions and social distancing to reduce the spread of the disease, it has seriously affected the travel and tourism industry in Thailand, especially its community-based tourism. The impact of travel bans has magnified employment and income loss to most local families and their communities, negatively impacting the development of local tourism economies. Purpose: The main objective of this study is to investigate the impacts of COVID-19 on community-based tourism as well as its adaptation solutions using a case study from a specific region in Thailand. Design/methodology/approach: Using a phenomenological approach, a series of qualitative face-to-face, semi-structured interviews were undertaken with 42 stakeholders involved in community-based tourism. Findings: The study results indicate that job relocation, temporary business closures, reducing fixed costs, and increasing different sale channels represent the most critical factors impacting CBT operational activities directly affected by the COVID-19 crisis and requiring immediate action. Other supplementary actions involve government financial support, business compensation, early vaccination, reduction of agricultural debt, and increasing agricultural product value. Social implications: These study findings offer direction for Thai governmental policy makers and CBT leaders for the establishment of actionable practices designed to respond rapidly and appropriately to local communities and entrepreneurs during crises such as the COVID-19 pandemic. Originality: The originality of this research was obtained from local stakeholders’ insights on the impacts of COVID-19 upon community-based tourism in the northeast region of Thailand, where tourism represents significant economic value in terms of salaries, wages, and employment generation.
The Effect of Banana Rhizosphere Chemotaxis and Chemoattractants on Bacillus velezensis LG14-3 Root Colonization and Suppression of Banana Fusarium Wilt Disease
Authors: Yang Lihua , Zhou You , Guo Lijia , Yang Laying , Wang Jun , Liang Changcong , Huang Junsheng
Published: December 2022

Fusarium oxysporum f. sp. cubense (Foc) causes banana Fusarium wilt disease, which is a destructive soil-borne disease. Many plants can recruit rhizosphere microorganisms using their root exudates, thereby shaping the rhizosphere microbiome to resist pathogen infection. Therefore, this study was conducted to explore the role of root exudates in the process of biocontrol strain colonization and resistance to pathogens. In this study, the banana root exudates used as chemoattractants were obtained by hydroponics. Bacillus velezensis strain LG14-3 was isolated from the infected area of the root system of banana and showed significant chemotaxis to banana root exudates and strong inhibition of Fusarium oxysporum f. sp. cubense. Further analysis found that LG14-3 showed chemotaxis toward the components of banana root exudates, such as citric acid, succinic acid, glycine, D-galactose and D-maltose, and glycine and citric acid, which resulted in more significant chemotaxis of LG14-3. Moreover, banana root exudates enhanced the swarming motility and biofilm formation of LG14-3. Pot experiments showed that glycine and citric acid enhanced the colonization ability of Bacillus velezensis LG14-3 in the banana rhizosphere and reduced the disease severity index of banana fusarium wilt. Glycine and citric acid enhanced the growth-promoting ability of LG14-3 under pathogen stress. Our results showed that the addition of chemotactic substances enhanced the biocontrol potential of Bacillus velezensis LG14-3 to prevent banana Fusarium wilt.
Perception and Deception in Nurses’ Clinical and Work-Related Professional Autonomy: Case Study for a Hospital in Romania
Authors: Bădileanu Marina , Ionel Ileana Paula , Aurelian Justin , Cristian Daniel Alin , Jude Cornelia , Georgescu Luminița-Izabell , Răpan Ivona
Published: December 2022

The continuous expansion of the nursing scope of practice, the undeniable growth of the nurses’ role in the healthcare crisis, the shortage of labor, especially in rural areas and marginalized urban csommunities, and last but not least, the lack of literature on Romanian nursing autonomy are some of the background factors in this study. This study’s purpose is to assess nurses’ perceptions of their medical care independence. The main hypothesis is that more advanced levels of education generate a greater inclination toward autonomous interventions. The quantitative research is based on a survey using a self-designed questionnaire as a tool (based on a nurse-focused structure and process indicators following the Donabedian model) applied in a Romanian clinical hospital. Based on a literature review, three composite indicators were developed and tested for reliability using the Cronbach alpha coefficient. These indicators reflect autonomy from three perspectives: clinical practice independence, autonomy in relation to work, and autonomy through digitalization. This scientific approach revealed a major impact of the regulatory framework on nurses’ perceptions of their autonomy, below the expectations of use, and the acceptance of digital technologies among nurses. Finally, it was observed that college graduate nurses perceive lower levels of independence than post-secondary ones.
Updated Prediction of Air Quality Based on Kalman-Attention-LSTM Network
Authors: Zhou Hao , Wang Tao , Zhao Hongchao , Wang Zicheng
Published: December 2022

The WRF-CMAQ (Weather research and forecast-community multiscale air quality) simulation system is commonly used as the first prediction model of air pollutant concentration, but its prediction accuracy is not ideal. Considering the complexity of air quality prediction and the high-performance advantages of deep learning methods, this paper proposes a second prediction method of air pollutant concentration based on the Kalman-attention-LSTM (Kalman filter, attention and long short-term memory) model. Firstly, an exploratory analysis is made between the actual environmental measurement data from the monitoring site and the first forecast data from the WRF-CMAQ model. An air quality index (AQI) was used as a measure of air pollution degree. Then, the Kalman filter (KF) is used to fuse the actual environmental measurement data from the monitoring site and the first forecast results from the WRF-CMAQ model. Finally, the long short-term memory (LSTM) model with the attention mechanism is used as a single factor prediction model for an AQI prediction. In the prediction of O3 which is the main pollutant affecting the AQI, the results show that the second prediction based on the Kalman-attention-LSTM model features a better fitting effect, compared with the six models. In the first prediction (from the WRF-CMAQ model), for the RNN, GRU, LSTM, attention-LSTM and Kalman-LSTM, SE improved by 83.26%, 51.64%, 43.58%, 45%, 26% and 29%, respectively, RMSE improved by 83.16%, 51.52%, 43.21%, 44.59%, 26.07% and 28.32%, respectively, MAE improved by 80.49%, 56.96%, 46.75%, 49.97%, 26.04% and 27.36%, respectively, and R-Square improved by 85.3%, 16.4%, 10.3%, 11.5%, 2.7% and 3.3%, respectively. However, the prediction results for the Kalman-attention-LSTM model proposed in this paper for other five different pollutants (SO2, NO2, PM10, PM2.5 and CO) all have smaller SE, RMSE and MAE, and better R-square. The accuracy improvement is significant and has good application prospects.
The Effects of Hosting Mega Sporting Events on Local Stock Markets and Sustainable Growth
Authors: Ferris Stephen P. , Koo Sulgi , Park Kwangwoo , Yi David T.
Published: December 2022

We examine the economic effects of the Summer and Winter Olympic Games and the FIFA World Cup on the economies of host countries. We found that in the short run, hosting the Olympic Games has a significant positive announcement effect on the host country’s equity market. Our results also revealed a positive effect on the stock market in non-G7 countries hosting a mega sporting event and an insignificant effect in G7 countries hosting such events, indicating that hosting a mega sporting event can provide additional momentum for developing or emerging economies. We did find, however, that while the countries hosting the Summer Olympic Games initially experienced significant positive GDP growth, the effect rapidly diminished after the event. Our results suggest that hosting a mega sporting event such as the Summer Olympic Games is most likely to result in a short-term positive economic momentum, however it hinders sustainable growth for the host countries’ economies.
Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks
Authors: Medina-Gaitán Daniel Federico A. , Rozo-Rodriguez Ian Dwrley , Montoya Oscar Danilo
Published: December 2022

The black hole optimization (BHO) method is applied in this research to solve the problem of the optimal reactive power compensation with fixed-step capacitor banks in three-phase networks considering the phase-balancing problem simultaneously. A master–slave optimization approach based on the BHO in the master stage considers a discrete codification and the successive approximation power flow method in the slave stage. Two different evaluations are proposed to measure the impact of the shunt reactive power compensation and the phase-balancing strategies. These evaluations include a cascade solution methodology (CSM) approach and a simultaneous solution methodology (SSM). The CSM approach solves the phase-balancing problem in the first stage. This solution is implemented in the distribution network to determine the fixed-step capacitor banks installed in the second stage. In the SSM, both problems are solved using a unique codification vector. Numerical results in the IEEE 8- and IEEE 27-bus systems demonstrate the effectiveness of the proposed solution methodology, where the SSM presents the better numerical results in both test feeders with reductions of about 32.27% and 33.52%, respectively, when compared with the CSM. To validate all the numerical achievements in the MATLAB programming environment, the DIgSILENT software was used for making cross-validations. Note that the selection of the DIgISLENT software is based on its wide recognition in the scientific literature and industry for making quasi-experimental validations as a previous stage to the physical implementation of any grid intervention in power and distribution networks.
Simulation Evaluation of a Current Limiting Scheme in an Urban Rail Transit Network
Authors: Hu Hexin , Li Jitao , Wu Shuai
Published: December 2022

The formulation of the current limiting scheme of an urban rail transit network is a complex multi-objective planning problem as the effect of the current limiting scheme is unknown before implementation. In this article, a method combining discrete event simulation and agent simulation is used to study the simulation scheduling principle of the current limiting scheme, and a modeling method based on an abstract agent group is proposed. Based on the AnyLogic simulation platform, a meso-scale simulation model for evaluating the current limiting scheme of urban rail transit networks was developed, and a logical framework for the operation simulation of the intelligent group and urban rail network system with stations, passengers, and trains as units was constructed. Furthermore, the data exchanges between stations, trains, and passengers were controlled through discrete events of driving. The results show that the constructed simulation model can effectively replace the actual system to evaluate the current limiting scheme and reduce the computational redundancy of passenger agents flowing in the urban rail network system and the cost of model transformation.
Pricing of the Bus-Truck Co-Delivery Mode of Last Mile Delivery Considering Social Welfare Maximization
Authors: He Yunzhu
Published: December 2022

In order to solve the problems of low delivery efficiency and high cost at the end of express delivery, and the impact of express trucks on urban road traffic, the co-delivery mode of trucks and buses is proposed. In this mode, without affecting the normal operation of the bus, it uses the idle resources of the bus to cooperate with the trucks to complete the delivery. The express company pays the bus delivery service fee to the bus operator, so as to improve the revenue of the bus operator. At the same time, the delivery efficiency can be improved, the express delivery cost can be reduced, and the impact of express trucks on urban traffic can be lower. A two-layer optimization model is constructed to solve the bus delivery service pricing and express space-time path selection scheme under the co-delivery mode. An example analysis is carried out through the actual bus routes and express delivery demand in Dalian. The results show that the co-delivery mode can provide consumers with more efficient services, reduce costs for express companies, provide additional revenue for bus operators, and improve social welfare. Unless the timeliness of delivery is extremely considered, the measure of using the co-delivery mode is better than the measure of relaxing restrictions on express delivery vehicles.
Grapevine Resistant Cultivars: A Story Review and the Importance on the Related Wine Consumption Inclination
Authors: Mian Giovanni , Nassivera Federico , Sillani Sandro , Iseppi Luca
Published: December 2022

Pest and disease management in the grapevine sector has become difficult due to several instances (e.g., pathogen resistance, agrochemicals withdrawals). Therefore, viticulture switched to more environmentally friendly practices. On these bases, the most promising tool is the use of a resistant variety of grapes. Luckily, genetic and genomic selection have made great steps in accelerating plant breeding. In recent years, several resistant varieties of grape were created and the wine obtained began to grow. This allowed vine growers and wine makers to drastically reduce the chemical inputs in vineyards. However, this specific wine market faces trouble regarding the consumer attitude towards buying the related crafted wines. In order to make these innovations acceptable, we undertook a literature review of the history and creation methods of the hybrid grapevines. We investigated young wine drinkers across north-east Italy using specific questionaries to better analyse consumer perception of wine from resistant vines and the related environmentally friendly issues to understand if consumers are prone towards this product. Our results clearly indicate that consumer attitude towards this type of beverage pays great attention to the reduction in agrochemicals.
Identifying a Period of Spatial Land Use Conflicts and Their Driving Forces in the Pearl River Delta
Authors: Zhao Yanru , Zhao Xiaomin , Huang Xinyi , Guo Jiaxin , Chen Guohui
Published: December 2022

Spatial land use conflicts (SLUCs) are a critical issue worldwide due to the scarcity of land resources and diversified human demand. Despite many time-series studies of SLUCs, comprehensive research on SLUCs and their driving factors over a long period remain limited. This study was conducted in the Pearl River Delta urban agglomeration, Guangdong Province, China. We constructed a landscape ecological risk assessment model to calculate annual SLUC values and analyze their spatiotemporal distribution over 30 years. K-means clustering analysis was used to cluster SLUC values for 1990–2005 and 2006–2020, yielding comprehensive conflict intensity data for each period. The major factors driving the spatial differentiation of SLUCs and their interactions in each period were identified using an optimal parameter-based geographical detector model. The results show that SLUCs varied significantly over time, with an overall decreasing trend and distinct spatial heterogeneity. Comprehensive conflict intensity for each period was characterized by low values in the peripheral regions and high values in central parts of the study area, which tended to decrease from 1990–2005 to 2006–2020. SLUCs were heavily dependent on topographical (slope and elevation) and environmental (normalized difference vegetation index) factors. Socio-economic factors (gross domestic product and population density) were also major contributors to the spatial differentiation of SLUCs. The explanatory power of multiple interacting factors on SLUCs was enhanced compared with that of individual factors. The explanatory power of the driving factors varied, and their interactions decreased over time. The results may facilitate the rational government planning of regional land use and thus effectively mitigate SLUC intensity at the macro level.
The Correlation Effects and Mechanisms of Rural Restructuring and Transformation: A Case Study of the Jianghan Plain in China
Authors: Li Zhuofan
Published: December 2022

The rural decline accompanying industrialization and urbanization is a lingering puzzle in human society, while promoting rural restructuring and transformation is considered the primary task of contemporary rural development. It is the historical mission of rural geography research in the new era to scientifically understand the characteristics of contemporary rural development and accurately explain the patterns of rural reconstructing and transformation. In this paper, the Jianghan Plain in China is selected for the case study. Characteristic indexes are selected based on the “structure–function” correlation to interpret rural restructuring. Measurement benchmarks are unified through functional value marketization to interpret rural transformation. Multiple statistical analysis is adopted to identify the action paths and decipher the correlation mechanisms. The case study yields the following findings. (1) The rural restructuring on Jianghan Plain has spatial and temporal differences. Rural restructuring has roughly gone through the social restructuring-led, economic restructuring-led, and spatial restructuring-led evolution stages, showing spatially divergent patterns with high rural comprehensive restructuring index (RRC) areas concentrated around the main traffic arteries and linear low RRC areas along the Yangtze River banks. (2) Rural restructuring and transformation on Jianghan Plain show significant correlation effects. During the study period, the rural transformation magnitude (RTM) continues to increase and shows a spatial map similar to that of rural restructuring, with economic-spatial restructuring-led and economic-social restructuring-led as the main modes of rural transformation. (3) The correlation mechanism of rural restructuring and transformation on Jianghan Plain has characteristics typical of less-developed agricultural areas. The economic restructuring led by agricultural land changes and the social restructuring led by rural population outward migration remain the main paths of rural transformation, and the agricultural function still plays an important role in some rural areas. The quantitative measurement of rural region functions in this study need further optimization, and the refinement and accuracy of regional function accounting needs further exploration. The research results are expected to provide a scientific basis for stimulating rural development and promoting sustainable rural development in contemporary developing countries.
Socio-Economic Security of the Region in the Context of Human Capital Development
Authors: Yakovenko Nataliya V. , Semenova Lyudmila , Tsoy Marina Ye. , Zavyalova Galina I. , Semenova Elena A. , Belenok Irina A.
Published: December 2022

Socio-economic security is a highly critical issue that is addressed by every country in the world. In order to counteract challenges and threats faced by Russia, the Economic Security Strategy of the Russian Federation has been formulated. The development of human capital was proclaimed as one of the key areas to be targeted by the state policy. In this regard, the primary task is to identify destabilizing factors of socio-economic security in the development of human capital, which determined the relevance of the article. The article analyzes the research approaches to defining the key features of socio-economic security and human capital. It highlights the main principles of the theory of human capital on the basis of which a systematic approach to the study of human capital is justified. The proposed approach aims to identify negative factors that weaken regional security. By adopting this approach to the data in hand, the socio-economic security of the Voronezh Region, the old-developed region of the Central Black Earth Region in Russia, has been assessed. The data used for the analysis were collected from the Federal State Statistics Service. The mapping of the results of socio-economic differentiation was carried out by methods of GIS-technology, in particular Quantum GIS 12. For the processing of the initial information, the of multivariate statistical and econometric analysis SPSS Statistic 20.0 was used. As a result, factors that will have a negative impact on the development of human capital in the foreseeable future have been identified, namely the deterioration of the demographic situation, in particular the aging of the population and its natural decline; the decline in the quality of education, imbalances in the labor market, declining living standards, and deteriorating public health. It is concluded that to overcome the critical situation in the sphere of human capital and to ensure socio-economic security, it is necessary to carry out preventive measures.
Modeling a New Supplier Preference Paradigm: A Business-to-Business and African Developing Economy Context
Authors: Duffett Rodney , Wakeham Myles
Published: December 2022

The recent COVID-19 pandemic, and subsequent invasion of Ukraine by Russia, has demonstrated to the world the volatile and fragile nature of global supply chains. Hence, this study is based on research gaps that propose new sustainable business-to-business (B2B) procurement/supplier models that consider different factors across industries and uses the triple bottom line (TBL) framework as the theoretical underpinning. The study used a quantitative methodological approach and convenience sampling to survey 445 organizations in a B2B procurement context in South Africa. The data were analyzed via structural equation modeling. The inquiry revealed that service quality was important to determine access to personnel and environmental sustainability, which had a favorable influence on personal relationships and gifts and, in turn, positively influenced relationships with salespeople and management. Culture, employment equity, and affirmative action positively affected Black Economic Empowerment status which had a favorable influence on the preference of suppliers’ salespeople. Several other positive associations were revealed, which resulted in a unique theoretical supplier preference contribution to the TBL framework. The study also provides organizations with a number of practical benefits stemming from the associations between the new sustainable B2B procurement/supplier constructs that are important as value-added business activities in an African developing economic context.
Spectral Methods in Nonlinear Optics Equations for Non-Uniform Grids Using an Accelerated NFFT Scheme
Authors: Rodríguez Pedro , Romero Manuel , Ortiz-Mora Antonio , Díaz-Soriano Antonio M.
Published: December 2022

In this work, we propose the use of non-homogeneous grids in 1D and 2D for the study of various nonlinear physical equations using spectral methods. As is well known, the use of spectral methods allow a faster resolution of the problem via the application of the ubiquitous Fast Fourier Transform (FFT) algorithm. We will center our investigation on the search of fast and accurate schemes to solve the spectral operators in the Fourier space. In particular, we will use the Conjugate Gradient (CG) iterative method, with a preconditioning matrix to accelerate the inversion process of the non-uniform Fast Fourier Transform (NFFT). As it will be shown, the results obtained are in good agreement with the expected values.
Model-Based Regional Control with Anomalous Diffusion of Multi-Drug Combined Cancer Therapy for Volume Predictions
Authors: Ionescu Clara Mihaela , Ghita Maria
Published: December 2022

Symmetry breaking in the anatomical lung is triggered by tumorigenesis and disrupted by delivering single or multiple drugs to stop the progression of the tumor and treat cancer. In this study, a prior model of combined drug therapy is augmented to introduce tissue heterogeneity when the drug is applied in multi-drug therapy of lung cancer. Patient-related drug resistance and synergy are investigated as a function of diffusion intensity as drug molecules reach the tumor site. The results indicate that diffusion of drug molecules plays an important role next to other factors such as patient sensitivity to the drug and drug synergy effects. We conclude that the minimal model provides meaningful predictions on tumor growth at the intermediate mesoscale level. With such models at hand, it is now possible to employ model-based control algorithms to optimize the dose profiles in terms of time and amount. In this paper, we present a theoretical framework for control employing networked game theory optimality. Specific situations are discussed in terms of finding optimality at Nash equilibrium in relation to patient response and drug synergy effects.
A Ferroelectric Memristor-Based Transient Chaotic Neural Network for Solving Combinatorial Optimization Problems
Authors: Lin Zhuosheng , Fan Zhen
Published: December 2022

A transient chaotic neural network (TCNN) is particularly useful for solving combinatorial optimization problems, and its hardware implementation based on memristors has attracted great attention recently. Although previously used filamentary memristors could provide the desired nonlinearity for implementing the annealing function of a TCNN, the controllability of filamentary switching still remains relatively poor, thus limiting the performance of a memristor-based TCNN. Here, we propose to use ferroelectric memristor to implement the annealing function of a TCNN. In the ferroelectric memristor, the conductance can be tuned by switching the lattice non-centrosymmetry-induced polarization, which is a nonlinear switching mechanism with high controllability. We first establish a ferroelectric memristor model based on a ferroelectric tunnel junction (FTJ), which exhibits the polarization-modulated tunnel conductance and the nucleation-limited-switching (NLS) behavior. Then, the conductance of the ferroelectric memristor is used as the self-feedback connection weight that can be dynamically adjusted. Based on this, a ferroelectric memristor-based transient chaotic neural network (FM-TCNN) is further constructed and applied to solve the traveling salesman problem (TSP). In 1000 runs for 10-city TSP, the FM-TCNN achieves a shorter average path distance, a 32.8% faster convergence speed, and a 2.44% higher global optimal rate than the TCNN.
Iterative Numerical Methods for a Fredholm–Hammerstein Integral Equation with Modified Argument
Authors: Micula Sanda
Published: December 2022

Iterative processes are a powerful tool for providing numerical methods for integral equations of the second kind. Integral equations with symmetric kernels are extensively used to model problems, e.g., optimization, electronic and optic problems. We analyze iterative methods for Fredholm–Hammerstein integral equations with modified argument. The approximation consists of two parts, a fixed point result and a quadrature formula. We derive a method that uses a Picard iterative process and the trapezium numerical integration formula, for which we prove convergence and give error estimates. Numerical experiments show the applicability of the method and the agreement with the theoretical results.
Confidence Interval Estimation for the Common Mean of Several Zero-Inflated Gamma Distributions
Authors: Kaewprasert Theerapong , Niwitpong Sa-Aat , Niwitpong Suparat
Published: December 2022

In this study, we propose estimates for the confidence interval for the common mean of several zero-inflated gamma (ZIG) distributions based on the fiducial generalized confidence interval (GCI) and Bayesian and highest posterior density (HPD) methods based on the Jeffreys rule or uniform prior. Their performances in terms of their coverage probabilities and expected lengths are compared via a Monte Carlo simulation study. For almost all of the scenarios considered, the simulation results show that the fiducial GCI performed better than the Bayesian and HPD methods. Daily rainfall data from Chiang Mai Province, Thailand that contains several zero entries and follows a ZIG distribution is used to test the efficacies of the methods in real-world situations.
Open or Not? Operation Strategies of Competitive eCommerce Platforms from an Ecosystem Perspective
Authors: Song Bo , Xu Hongda , Zhao Liangjie
Published: December 2022

According to the traditional theory of industrial organizations, differentiated competition leads to higher returns. However, Chinese eCommerce platforms tend to homogenize in the choice of operational strategies, which deviates from the principle of differentiated competition. Some competitive eCommerce platforms were described based on the hotelling model, and a sequential game model for the competition of ecosystems was built to analyze the choice of operation strategies. From the perspective of a business ecosystem, this paper studied the impact of the strategy choice of the core platform on the ecological profit. The results showed that an open strategy would always improve the performance of business ecosystems and could even benefit the competitive ecosystem because of its spillover effect. The equilibrium of the competitive platforms was related to the game strategies, independent of the distribution contracts of the suppliers. We found that the platforms’ positions deviated from the maximum difference principle due to network externalities, and differentiation did not improve the profits of platforms.
Evolutionary Game Analysis of Participations in Museum Public–Private Partnership Projects Based on System Dynamics
Authors: Wang Siyi , Yu Liying , Qiu Ran
Published: December 2022

In China, the number of public–private partnership (PPP) projects in the museum field is relatively small, and the success rate is quite low, which highlights the drawback of an insufficient depth of overall promotion. To break through this dilemma, this paper objectively analyzes the interest demands and behavior-oriented conflicts between two stakeholders and constructs a game model based on limited rationality for the evolution of participation behaviors in museum PPP projects. In addition, different levels of government incentives are introduced along with the modeling and simulation of system dynamics (SD) to further clarify the dynamic evolution process of participants’ behavioral strategies. There are multiple complex scenarios associated with the system evolution according to the study. In a museum PPP project, the strategic choices of social forces and museums may have a mutual effect under different scenarios. Under the premise of guaranteeing the benefits of both sides of the game, there are two evolutionary stability strategies. Incentives from the government have a significant impact on the evolution of the game system at different stages of implementation. This paper hopes to provide reference and guidance to facilitate the formation of an appropriate action mechanism for participants and then ensure the sustainable promotion and development of the projects.
Social Life Cycle Analysis of Textile Industry Impacts for Greater Social Sustainability of Global Supply Chains
Authors: Muñoz-Torres María Jesús , Fernández-Izquierdo María Ángeles , Ferrero-Ferrero Idoya , Escrig-Olmedo Elena , Rivera-Lirio Juana María
Published: December 2022

Solutions will be effective if they are aligned with the problems that they are trying to solve. This paper studied the most relevant social impacts of the textile industry and how appropriately textile companies manage these social impacts, in order to achieve greater social sustainability in global supply chains. Therefore, we attempted to determine whether companies belonging to the textile product lifecycle identify and manage social impacts in keeping with the most relevant social hotspots in the supply chain of the textile industry. A consistency analysis was conducted based on the management of social indicators at the company level (identified through the analysis of contents of their sustainability reporting) connected with social impact categories defined in the Guidelines for Social Life Cycle Assessment of products provided by the United Nations Environment Programme, and the Society of Environmental Toxicology and Chemistry, and on the technical results obtained by the textile sector through the Social Hotspots Database. The results showed a predominant inconsistency between the main social hotspots of the textile industry showed in the footprint analysis and the social indicators specifically reported by the sector. This paper contributes to the literature about what sustainability management implies along global supply chains, emphasizing the need to advance in a consistent and science-based integration of social hotspots at the sectoral level and social management practices at the company level. In addition, the study could be relevant for companies belonging to complex and global supply chains, since it contributes towards enhancing the knowledge of science-based methodologies, as social life cycle assessments, for identifying, managing, and reporting their social hotspots.
Ocean Acidification-Mediated Food Chain Transfer of Polonium between Primary Producers and Consumers
Authors: Behbehani Montaha , Uddin Saif , Dupont Sam , Fowler Scott W. , Gorgun Aysun U. , Al-Enezi Yousef , Al-Musallam Lamya , Kumar Vanitha V. , Faizuddin Mohammad
Published: December 2022

Phytoplankton and zooplankton are key marine components that play an important role in metal distribution through a food web transfer. An increased phytoplankton concentration as a result of ocean acidification and warming are well-established, along with the fact that phytoplankton biomagnify 210Po by 3–4 orders of magnitude compared to the seawater concentration. This experimental study is carried out to better understand the transfer of polonium between primary producers and consumers. The experimental produced data highlight the complex interaction between the polonium concentration in zooplankton food, i.e. phytoplankton, its excretion via defecated fecal pellets, and its bioaccumulation at ambient seawater pH and a lower pH of 7.7, typical of ocean acidification scenarios in the open ocean. The mass of copepods recovered was 11% less: 7.7 pH compared to 8.2. The effects of copepod species (n = 3), microalgae species (n = 3), pH (n = 2), and time (n = 4) on the polonium activity in the fecal pellets (expressed as % of the total activity introduced through feeding) was tested using an ANOVA 4. With the exception of time (model: F20, 215 = 176.84, p < 0.001; time: F3 = 1.76, p = 0.16), all tested parameters had an impact on the polonium activity (copepod species: F2 = 169.15, p < 0.0001; algae species: F2 = 10.21, p < 0.0001; pH: F1 = 9.85, p = 0.002) with complex interactions (copepod x algae: F2 = 19.48, p < 0.0001; copepod x pH: F2 = 10.54, p < 0.0001; algae x pH: F2 = 4.87, p = 0.009). The experimental data underpin the hypothesis that metal bioavailability and bioaccumulation will be enhanced in secondary consumers such as crustacean zooplankton due to ocean acidification.