bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Capacity of the Water–Energy–Food Nexus in Enhancing Sustainable Agriculture and Food Security in Burundi
Authors: Mperejekumana Philbert , Shen Lei , Zhong Shuai , Muhirwa Fabien , Nsabiyeze Assa , Nsigayehe Jean Marie Vianney , Nyirarwasa Anathalie
Published: September 2023

In Burundi, a significant portion of the population heavily relies on agriculture for both sustenance and income. However, persistently low agricultural yields place approximately 1.8 million people at immediate risk of food insecurity. The purpose of this study was to explore the potential of the water–energy–food (WEF) nexus approach to strengthening agricultural sustainability and improving food security in Burundi. This study employs both the ARDL model and the ARIMA model to analyze the impact of water, energy, and land on agricultural yield while also projecting their future dynamics in Burundi. The results highlight a positive correlation between these resources and agricultural yield, demonstrating that a 1% increase in each of these variables would collectively result in a 3.74% increase in agricultural yield. Furthermore, the predictive findings reveal an anticipated decrease in agricultural yield by approximately 74.9 kg ha−1 and a reduction in agricultural land spanning up to 11.9 × 104 hectares by the year 2030. As a contribution to the body of knowledge, this study introduces a framework for the WEF nexus and sustainable agriculture, providing fresh perspectives to the literature on resource nexus studies in Burundi and among other practitioners in Africa.
Enhancing Student Motivation and Engagement through a Gamified Learning Environment
Authors: Hellín Carlos J. , Calles-Esteban Francisco , Valledor Adrián , Gómez Josefa , Otón-Tortosa Salvador , Tayebi Abdelhamid
Published: September 2023

Gamification is a viable strategy used to enhance motivation and engagement in programming classes among students. However, automated evaluation capabilities, which are crucial for giving students fast and correct feedback, are frequently lacking in currently available gamification technologies. This study proposes a novel web-based application that combines automated programming assessment features with gamification concepts; the aim is to provide students taking a programming course with an engaging learning environment. A survey conducted with 215 undergraduate students assessed how the tool affected the motivation and engagement of students. The findings show that the tool had a beneficial impact on students’ willingness to participate in class, study, increase their self-confidence, engage in healthy competition with peers, and learn from their mistakes. The qualitative feedback that students offered regarding the features of the tool that they liked best is also covered in the study. This paper contributes to the field of programming education by presenting a detailed gamified tool, incorporating automated evaluation and gamification in a web-based platform.
Sustainable Entrepreneurship Management and Digitalization: A Green Digital Innovation Radar
Authors: Petersen Nicolaj Hannesbo , Fuerst Sascha , Torkkeli Lasse
Published: September 2023

Today’s entrepreneurs and managers face challenges of a transformative character [...]
Examination in Accordance with Aptitude: Selection and Optimization of Curriculum Assessment Methods in Higher Education Adapted to the Teacher–Student Game Behaviors
Authors: Qu Ying , Chen Si , Cao Shugui
Published: September 2023

The relationship between teachers and students in higher education has now developed into a game of two-way interaction, with both sides often clashing over the choice of curriculum assessment methods. Curriculum examination is a crucial factor in evaluating the quality of higher education. Additionally, it significantly impacts the fairness of education and students’ motivation to learn. To resolve such conflicts, we analyze the teacher–student game psychology using the conflict analysis method. Then, based on the overall stability of the situation, we have come to the conclusion that we need to adopt “innovative examinations”. Specific recommendations were made to teachers and students through the analysis of the results, and then the integration of the influencing factors proposed optimization strategies aimed at ensuring the fairness of the examination, based on the choice of the type of course, with reference to the reality of teachers and students, and oriented to the educational and teaching environment. We provide practical guidance for selecting and optimizing assessment methods to improve their appropriateness for individualized teacher and student needs. This promotes the process of teaching reform and helps achieve sustainable development in education.
Financial Conditions and Borrowing Behavior of University Students during the COVID-19 Pandemic: Evidence from Bangladesh
Authors: Rabbani Naheed
Published: September 2023

The COVID-19 pandemic presented significant challenges to university students. This study explores the financial conditions and borrowing behavior of university students during the pandemic in Bangladesh. The study used a sample of 840 students from major public universities in Bangladesh and applied bivariate analyses and mean comparison tests. The findings reveal that a substantial portion of the students experienced job loss and financial problems during the pandemic. Approximately 50% of the students had substantial loan burdens, 16.31% borrowed from formal institutions, and 39.17% borrowed multiple times. Furthermore, about 20% perceived borrowing costs as high, and most struggled to make regular installment payments. Analyzing the subgroups, women leaned more on family support for income, while men had independent income sources. Job loss affected a greater percentage of females than males. Females also borrowed more from formal sources, while more males perceived borrowing costs as negligible. In terms of urban and rural comparisons, rural students relied more on family support, while urban students had independent income sources. Financially literate students encountered more job loss and financial trouble and borrowed more from informal and low-cost sources compared to their less financially literate counterparts. The study suggests grants, subsidies, and reduced educational expenses for students who faced job loss, financial trouble, and burdensome debt.
Geospatial Artificial Intelligence (GeoAI) and Satellite Imagery Fusion for Soil Physical Property Predicting
Authors: Hosseini Fatemeh Sadat , Seo Myoung Bae , Razavi-Termeh Seyed Vahid , Sadeghi-Niaraki Abolghasem , Jamshidi Mohammad , Choi Soo-Mi
Published: September 2023

This study aims to predict vital soil physical properties, including clay, sand, and silt, which are essential for agricultural management and environmental protection. Precision distribution of soil texture is crucial for effective land resource management and precision agriculture. To achieve this, we propose an innovative approach that combines Geospatial Artificial Intelligence (GeoAI) with the fusion of satellite imagery to predict soil physical properties. We collected 317 soil samples from Iran’s Golestan province for dependent data. The independent dataset encompasses 14 parameters from Landsat-8 satellite images, seven topographic parameters from the Shuttle Radar Topography Mission (SRTM) DEM, and two meteorological parameters. Using the Random Forest (RF) algorithm, we conducted feature importance analysis. We employed a Convolutional Neural Network (CNN), RF, and our hybrid CNN-RF model to predict soil properties, comparing their performance with various metrics. This hybrid CNN-RF network combines the strengths of CNN networks and the RF algorithm for improved soil texture prediction. The hybrid CNN-RF model demonstrated superior performance across metrics, excelling in predicting sand (MSE: 0.00003%, RMSE: 0.006%), silt (MSE: 0.00004%, RMSE: 0.006%), and clay (MSE: 0.00005%, RMSE: 0.007%). Moreover, the hybrid model exhibited improved precision in predicting clay (R2: 0.995), sand (R2: 0.992), and silt (R2: 0.987), as indicated by the R2 index. The RF algorithm identified MRVBF, LST, and B7 as the most influential parameters for clay, sand, and silt prediction, respectively, underscoring the significance of remote sensing, topography, and climate. Our integrated GeoAI-satellite imagery approach provides valuable tools for monitoring soil degradation, optimizing agricultural irrigation, and assessing soil quality. This methodology has significant potential to advance precision agriculture and land resource management practices.
Spatio–Temporal Evolutionary Features and Drivers of Green Competitiveness of Cities Surrounding the Yellow River
Authors: Zhang Jiawen , Xu Zhenhua , Ci Fuyi
Published: September 2023

Based on the scientific concept of city green competitiveness, an integrated evaluation indicator system was established to use the entropy method in order to measure the green competitiveness index of 78 cities surrounding the Yellow River (YR) from 2006 to 2020. Further, the spatio–temporal features and drivers of city green competitiveness were analyzed using various methods. The research found the following: (1) Although the green competitiveness of cities surrounding the YR has been growing steadily, the overall level is not high. (2) The green competitiveness of cities surrounding the YR can be spatially characterized as “downstream > midstream > upstream”; the absolute and relative differences between cities are both increasing, and overall differences stem mainly from the hypervariable density. (3) The positive spatial correlation between the green competitiveness of cities surrounding the YR is significant, with the “cold spot” in southeastern Gansu and the “hot spot” in the Shandong Peninsular city cluster. (4) The level of city infrastructure construction, the level of urbanization, and science and technology innovation are the main drivers of the green competitiveness of cities surrounding the YR. In addition, the interaction forces of each factor were found to be much stronger than the effects of individual factors.
Progress of EU Member States Regarding the Bioeconomy and Biomass Producing and Converting Sectors
Authors: Firoiu Daniela , Ionescu George H. , Cojocaru Teodor Marian , Niculescu Mariana , Cimpoeru Maria Nache , Călin Oana Alexandra
Published: September 2023

The development of the bioeconomy on regional and national levels is heavily reliant on the establishment of precise and efficient governance frameworks. These structures encompass a wide range of components, spanning from financial support to regulatory tools and limitations. These mechanisms play a pivotal role in addressing the challenges that emerge during the bioeconomy’s growth. In this context, the necessity for continuous research to underpin and guide bioeconomy policies, while also bridging existing knowledge gaps, is glaringly evident. The current study brings a new perspective, using hierarchical cluster analysis as an exploratory approach and a technique for generating hypotheses. Its aim is to assess the progress of EU countries concerning the bioeconomy, including sectors involved in biomass production and conversion. The research draws on data published by the European Commission and Eurostat for the years 2015 and 2020, to capture the changes brought about by the adoption of the 2030 Agenda. The research findings furnish valuable insights into advancements in the bioeconomy and the clustering of countries based on their performance levels. Notably, Belgium and Denmark emerge as standout performers, potentially offering exemplary models of best practices.
Exploring the Determinants of Travelers’ Intention to Use the Airport Biometric System: A Korean Case Study
Authors: Kim Jun Hwan , Song Woon-Kyung , Lee Hyun Cheol
Published: September 2023

After the pandemic, there has been an increasing emphasis on customer convenience, with biometrics emerging as a key solution. This study empirically investigates the intention of Korean travelers to use airport biometric systems. The technology acceptance model (TAM) was employed to explore users’ perceptions of the system’s functional aspects, while technology familiarity, social influence, and trust in information protection were integrated into the model to understand users’ psychological aspects. The results reveal that perceived usefulness and ease of use have a positive relationship with the intention to use the biometric system and that perceived ease of use positively influences perceived usefulness. The impact of social influence and technology familiarity was not statistically significant but trust emerged as the most influential factor determining the intention to use the system. Furthermore, the study identified that gender moderates the effect of trust on the intention to use. This study contributes by identifying key determinants for airport biometric system adoption and by investigating the moderating influence of gender. As a primary result, airport biometric systems must have effective functionality and a user-friendly passenger environment while ensuring confidence in system security. These findings have significant implications for the sustainable implementation of airport biometric systems.
Enhancing the Automatic Recognition Accuracy of Imprinted Ship Characters by Using Machine Learning
Authors: Abdulraheem Abdulkabir , Suleiman Jamiu T. , Jung Im Y.
Published: September 2023

In this paper, we address the challenge of ensuring safe operations and rescue efforts in emergency situations, for the sake of a sustainable marine environment. Our focus is on character recognition, specifically on deciphering characters present on the surface of aged and corroded ships, where the markings may have faded or become unclear over time, in contrast to vessels with clearly visible letters. Imprinted ship characters encompassing engraved, embroidered, and other variants found on ship components serve as vital markers for ship identification, maintenance, and safety in marine technology. The accurate recognition of these characters is essential for ensuring efficient operations and effective decision making. This study presents a machine-learning-based method that markedly improves the recognition accuracy of imprinted ship numbers and characters. This improvement is achieved by enhancing data classification accuracy through data augmentation. The effectiveness of the proposed method was validated by comparing it to State-of-the-Art classification technologies within the imprinted ship character dataset. We started with the originally sourced dataset and then systematically increased the dataset size, using the most suitable generative adversarial networks for our dataset. We compared the effectiveness of classic and convolutional neural network (CNN)-based classifiers to our classifier, a CNN-based classifier for imprinted ship characters (CNN-ISC). Notably, on the augmented dataset, our CNN-ISC model achieved impressive maximum recognition accuracy of 99.85% and 99.7% on alphabet and digit recognition, respectively. Overall, data augmentation markedly improved the recognition accuracy of ship digits and alphabets, with the proposed classification model outperforming other methods.
Rheological, Mechanical, and Micro-Structural Property Assessment of Eco-Friendly Concrete Reinforced with Waste Areca Nut Husk Fiber
Authors: Hasan Noor Md. Sadiqul , Shaurdho Nur Mohammad Nazmus , Sobuz Md. Habibur Rahman , Meraz Md. Montaseer , Basit Md. Abdul , Paul Suvash Chandra , Miah Md Jihad
Published: September 2023

Fiber-reinforced concrete (FRC) has become one of the most promising construction techniques and repairing materials in recent times for the construction industry. Generally, plain concrete has a very low tensile strength and limited resistance to cracking prior to the ultimate load, which can be mitigated by the incorporation of fiber. Natural fibers have emerged as an appealing sustainable option in the last few decades due to their lower cost, energy savings, and minimized greenhouse effects. Areca fiber is one of the natural fibers that can be sourced from the waste-producing areca nut industry. Hence, this study aims to assess the mechanical, rheological, and micro-structural properties of areca fiber-reinforced concrete (AFRC). For this purpose, areca fiber was used in the concrete mix as a weight percentage of cement. In this regard, 1%, 2%, 3%, and 4% by weight of cement substitutions were investigated. As key findings, 2% areca fiber enhanced the compressive strength of concrete by 2.89% compared to the control specimen (fiber-free concrete). On the other hand, splitting tensile strength increased by 18.16%. In addition, scanning electron microscopy (SEM) images revealed that the cement matrix and fibers are adequately connected at the interfacial level. Energy dispersive X-ray spectroscopy (EDX) test results showed more biodegradable carbon elements in the areca fiber-mixed concrete as well as an effective pozzolanic reaction. The study also exhibited that adding natural areca fiber lowered the fabrication cost by almost 1.5% and eCO2 emissions by 3%. Overall, the findings of this study suggest that AFRC can be used as a possible building material from the standpoint of sustainable construction purposes.
Enhancing Security and Sustainability of e-Learning Software Systems: A Comprehensive Vulnerability Analysis and Recommendations for Stakeholders
Authors: Akacha Souheil Abdel-Latif , Awad Ali Ismail
Published: September 2023

The onset of the COVID-19 pandemic prompted educational institutions to swiftly integrate e-learning software systems, including learning management systems (LMSs), as essential tools for online education. This study aims to probe the inherent security vulnerabilities of three widely utilized e-learning platforms, namely, Moodle, Chamilo, and Ilias, spanning the pre-pandemic, pandemic, and post-pandemic periods. The rapid adoption of these platforms during the pandemic revolutionized online education but also unveiled security risks. This paper delves into these security vulnerabilities, offering insights before, during, and after the pandemic. Through an analysis of existing patches and security measures, areas for improvement are identified. Furthermore, the paper considers emerging cybersecurity technologies and trends, providing comprehensive recommendations to enhance system resilience against evolving cyber threats. The results obtained here can provide educational institutions with a guide for action to enable effective mitigation of e-learning software security vulnerabilities and ensure the continued security and sustainability of online education systems.
Environmental Regulation and Spatial Spillover Effect of Green Technology Innovation: An Empirical Study on the Spatial Durbin Model
Authors: Zhang Xin , Xu Feng
Published: September 2023

This study empirically examined the spatial spillover effect of various environmental regulations on green technology innovation using panel data from 284 cities at the prefecture level in China between 2007 and 2019. A geographical–economic spatial weight matrix was constructed, and the spatial Durbin model was employed to identify the specific characteristics of this spillover effect. The findings indicate that the spatial spillover effect of green technology innovation primarily occurs through geographical transmission. However, there is no significant spatial autocorrelation when using the economic distance weight matrix. Various types of environmental regulations influence the spatial spillover effect of green technology innovation in distinct ways. Specifically, market-motivated environmental regulation exhibits a U-shaped relationship with the spatial spillover effect, while command-controlled environmental regulation demonstrates an inverted U-shaped relationship, suggesting a complementary effect. Additional research shows that the upgrading of industrial structure acts as a mediator between command-controlled environmental regulation and the spatial spillover effect of green technology innovation. Government departments should comprehensively coordinate market-motivated environmental regulation and command-controlled environmental regulation, accurately assess the intensity of command-controlled measures, and prevent the migration of green technology innovation elements caused by excessive regulatory measures within enterprises.
Technical Feasibility for the Boosting of Positive Energy Districts (PEDs) in Existing Mediterranean Districts: A Methodology and Case Study in Alcorcón, Spain
Authors: Dell’Unto Martina , Sassenou Louise-Nour , Olivieri Lorenzo , Olivieri Francesca
Published: September 2023

The deployment of Positive Energy Districts (PEDs) is currently facing a set of diverse and complex challenges, mainly arising from their novelty and the lack of practical experience. In that sense, there is a clear need for translating concepts and strategies into instruments that support the design, planning and operation of PEDs. The present research aims to address this gap by introducing a methodology to assess the potential of an existing district to be converted into a PED in the specific context of Mediterranean cities, which, in addition to presenting similar climatic characteristics, share a common urban pattern and culture. The first step consists of analyzing the initial state of the district through the study of its bioclimatic and urban characteristics and estimation of its energy demand. Then, the second step allows for selecting and designing a set of passive and active strategies for the district. Finally, the technical feasibility of the scenario is evaluated by calculating its annual energy balance. The methodology is applied to a district of Alcorcón, Spain. Results show that the selected district could achieve an annual surplus of 4 GWh and, therefore, has the technical potential to be converted into a PED.
Assessing the Cross-Sectoral Economic–Energy–Environmental Impacts of Electric-Vehicle Promotion in Taiwan
Authors: Chen Chi-Hao , Huang Yun-Hsun , Wu Jung-Hua , Lin Hwa
Published: September 2023

Few studies have examined the cross-sectoral impacts of electric vehicles on the economy, energy, and the environment. This study adopted hybrid electric vehicles, plug-in hybrid electric vehicles, and pure-battery electric vehicles as research objects in establishing an input–output analysis framework of the electric-vehicle industry. Learning curves and scenario analysis were also used to explore the cross-sectoral economic–energy–environmental impacts of electric-vehicle promotion, using Taiwan as a case study. Our results indicated that by 2040, electric vehicles will create an output value of 157~186.7 billion NTD, while boosting employment and reducing energy expenditures but having a negligible impact on income. It is expected that by 2040, the adoption of electric vehicles will reduce energy consumption to 65~82% of the levels required for vehicles using internal-combustion engines. Electric vehicles are expected to reduce CO2 and NOX emissions but increase PM2.5 emissions, with little effect on SOX emissions.
Model for the Strategic Governance of the Integrated and Sustainable Local Development of the Portoviejo Canton in the Province of Manabí, Ecuador
Authors: Zirufo-Briones Blanca Victoria , Pelegrín-Entenza Norberto
Published: September 2023

Strategic models for achieving sustainable, resilient and socially responsible local development, based on inclusion and a higher level of social participation in all planning processes, as well as implementation and evaluation, constitute the main task of local governments at a time when globalization predominates together with the decentralization of public powers. The objective of the research is to propose a strategic model of governance to achieve an integrated local development, which contributes to the improvement of the economic, social and environmental situation of the territory in the Portoviejo canton. Various definitions related to the strategies and analysis of various models put forward by different schools of strategic thought are offered for the establishment of the relationship between models, planning and territorial ordering. Based on the premises supporting it (sustainability, resilience, social responsibility, inclusion, integrated territorial approach and participatory governance), a model linked to local development strategies is proposed, which takes the Portoviejo canton in the province of Manabí in the coastal region of Ecuador as a case study.
Systematically Constructing Mesoscopic Quantum States Relevant to Periodic Orbits in Integrable Billiards from Directionally Resolved Level Distributions
Authors: Chen Yung-Fu , Lin Song-Qing , Chang Ru-Wei , Yu Yan-Ting , Liang Hsing-Chih
Published: September 2023

Two-dimensional quantum billiards are one of the most important paradigms for exploring the connection between quantum and classical worlds. Researchers are mainly focused on nonintegrable and irregular shapes to understand the quantum characteristics of chaotic billiards. The emergence of the scarred modes relevant to unstable periodic orbits (POs) is one intriguing finding in nonintegrable quantum billiards. On the other hand, stable POs are abundant in integrable billiards. The quantum wavefunctions associated with stable POs have been shown to play a key role in ballistic transport. A variety of physical systems, such as microwave cavities, optical fibers, optical resonators, vibrating plates, acoustic waves, and liquid surface waves, are used to analogously simulate the wave properties of quantum billiards. This article gives a comprehensive review for the subtle connection between the quantum level clustering and the classical POs for three integrable billiards including square, equilateral triangle, and circular billiards.
Baire Category Soft Sets and Their Symmetric Local Properties
Authors: Ameen Zanyar A. , Alqahtani Mesfer H.
Published: September 2023

In this paper, we study soft sets of the first and second Baire categories. The soft sets of the first Baire category are examined to be small soft sets from the point of view of soft topology, while the soft sets of the second Baire category are examined to be large. The family of soft sets of the first Baire category in a soft topological space forms a soft σ-ideal. This contributes to the development of the theory of soft ideal topology. The main properties of these classes of soft sets are discussed. The concepts of soft points where soft sets are of the first or second Baire category are introduced. These types of soft points are subclasses of non-cluster and cluster soft sets. Then, various results on the first and second Baire category soft points are obtained. Among others, the set of all soft points at which a soft set is of the second Baire category is soft regular closed. Moreover, we show that there is symmetry between a soft set that is of the first Baire category and a soft set in which each of its soft points is of the first Baire category. This is equivalent to saying that the union of any collection of soft open sets of the first Baire category is again a soft set of the first Baire category. The last assertion can be regarded as a generalized version of one of the fundamental theorems in topology known as the Banach Category Theorem. Furthermore, it is shown that any soft set can be represented as a disjoint soft union of two soft sets, one of the first Baire category and the other not of the first Baire category at each of its soft points.
Comparative Numerical Analysis for the Error Estimation of the Fluid Flow over an Inclined Axisymmetric Cylinder with a Gyrotactic Microbe
Authors: Awwad Fuad A. , Ismail Emad A. A. , Khan Waris , Gul Taza , Khan Abdul Samad
Published: September 2023

The numerical investigation of bioconvective nanofluid (NF) flow, which involves gyrotactic microbes and heat and mass transmission analysis above an inclined extending axisymmetric cylinder, is presented in this study. The study aims to investigate the bioconvection flow of nanofluid under the influence of heat sources/sinks. Through proper transformation, all partial differential equations are transformed into a non-linear ODE scheme. A new set of variables is presented in the directive to get the first-order convectional equations and then solved numerically using bvp4c MATLAB, embedded in the function. The proposed model is validated after calculating the error estimation and obtaining the residual error. The influence of various factors on the velocity, energy, concentration, and density of motile microorganisms is examined and studied. The analysis describes and addresses all physical measures of concentration such as Skin Friction (SF), Sherwood number, the density of motile microorganisms, and Nusselt number. To validate the present study, a comparison is conducted with previous studies, and excellent correspondence is found. In addition, the ND-Solve approach is utilized to confirm the bvp4c. The mathematical model is confirmed through error analysis. This study provides the platform for industrial applications such as cooling capacity polymers, heat exchange, and chemical production sectors.
Symmetrical Impulsive Inertial Neural Networks with Unpredictable and Poisson-Stable Oscillations
Authors: Akhmet Marat , Tleubergenova Madina , Seilova Roza , Nugayeva Zakhira
Published: September 2023

This paper explores the novel concept of discontinuous unpredictable and Poisson-stable motions within impulsive inertial neural networks. The primary focus is on a specific neural network architecture where impulses mimic the structure of the original model, that is, continuous and discrete parts are symmetrical. This unique modeling decision aligns with the real-world behavior of systems, where voltage typically remains smooth and continuous but may exhibit sudden changes due to various factors such as switches, sudden loads, or faults. The paper introduces the representation of these abrupt voltage transitions as discontinuous derivatives, providing a more accurate depiction of real-world scenarios. Thus, the focus of the research is a model, exceptional in its generality. To study Poisson stability, the method of included intervals is extended for discontinuous functions and B-topology. The theoretical findings are substantiated with numerical examples, demonstrating the practical feasibility of the proposed model.
Dynamics of Competitive Two-Strain Stochastic SIR Epidemics on Heterogeneous Networks
Authors: Jing Xiaojie , Liu Guirong
Published: September 2023

Mathematical modeling in epidemiology, biology, and life sciences requires the use of stochastic models. In this paper, we derive a competitive two-strain stochastic SIR epidemic model by considering the change in state of the epidemic process due to an event. Based on the density-dependent process theory, we construct a six-dimensional deterministic model that can be used to describe the diffusion limit of the stochastic epidemic on a heterogeneous network. Furthermore, we show the explicit expressions for the variances of infectious individuals with strain 1 and strain 2 when the level of infection is increasing exponentially. In particular, we find that the expressions of the variances are symmetric. Finally, simulations for epidemics spreading on networks are performed to confirm our analytical results. We find a close agreement between the simulations and theoretical predictions.
On the Functions of Marcinkiewicz Integrals along Surfaces of Revolution on Product Domains via Extrapolation
Authors: Al-Qassem Hussain , Ali Mohammed
Published: September 2023

In this paper, we establish certain Lp bounds for several classes of rough Marcinkiewicz integrals over surfaces of revolution on product spaces. By using these bounds and using an extrapolation argument, we obtain the Lp boundedness of these Marcinkiewicz integrals under very weak conditions on the kernel functions. Our results represent natural extensions and improvements of several known results on Marcinkiewicz integrals.
Digital Transformation: Moderating Supply Chain Concentration and Competitive Advantage in the Service-Oriented Manufacturing Industry
Authors: Tana Gegen , Chai Junwu
Published: September 2023

One of the service-based manufacturing concepts emphasizes relationship orientation and building strong customer relationships, while Industry 4.0 enables companies to be proactive in the supply chain. However, to achieve digitally driven growth, service-based manufacturing requires a shift away from the traditional upstream and downstream hierarchy toward a collaborative model. In this study, service-oriented manufacturing companies in the packaging and printing industries are selected as case studies to examine the relationship between supply chain concentration, digital transformation, and corporate competitive advantage from the perspectives of power control and equilibrium. The results show that a high supply chain concentration harms firms’ competitive advantage, especially when power is unevenly distributed. Moreover, digital transformation plays a moderating role in this relationship, suggesting that it is possible to improve firms’ competitiveness and further equalize the power balance by applying digital technologies to supply chain processes. The study revealed significant heterogeneity within the group of companies in terms of ownership type, dual management roles, and company size. In summary, this study makes a unique contribution to the growing research field of supply chain digital transformation. It provides valuable insights from a power balance perspective for service-oriented manufacturing companies seeking to enhance their competitive advantage in a rapidly changing market environment.
RAD-XP: Tabletop Exercises for Eliciting Resilience Requirements for Sociotechnical Systems
Authors: Dorton Stephen L. , Barrett Emily , Fersch Theresa , Langone Andrew , Neville Kelly J.
Published: September 2023

Despite noble intentions, new technologies may have adverse effects on the resilience of the sociotechnical systems into which they are integrated. Our objective was to develop a lightweight method to elicit requirements that, if implemented, would support sociotechnical system resilience. We developed and piloted the Resilience-Aware Development Exercise Protocol (RAD-XP), a method to generate tabletop exercises (TTXs) to elicit resilience requirements. In the pilot study, this approach generated 15 requirements from a one-hour TTX, where the majority of requirements were found to support resilience. Participants indicated via survey that RAD-XP was effective and efficient, and that they would want to use RAD-XP regularly throughout the agile development process. We discuss future research and development to refine this approach to eliciting resilience requirements.
Strategic Orientation of Romanian Healthcare Organizations from a Contingency Theory Perspective Based on Porter’s Generic Strategy Model
Authors: Ștefan Simona Cătălina , Popa Ion , Tărăban Irina
Published: September 2023

Under limited financial and human resources, factors such as technological progress, increased life expectancy, and increased medical needs argued that health organizations should define their strategic direction in line with these challenges. The purpose of this paper is to determine the types of competitive advantage that Romanian healthcare organizations seek, as well as the types of organizational strategy, according to Porter’s Generic Strategy Model, from a Contingency Theory Perspective For this purpose, the collection and analysis of primary data, resulting from the answers provided by a sample relevant to the topic addressed, respectively, employees from the health system were enrolled. Scales measuring the orientation of health organizations toward obtaining competitive advantages through differentiation and through costs, as well as the range of strategic activities, were validated by exploratory factor analysis, and for the analysis of the results used the independent samples t test; additionally, one-way multivariate analysis of variance (One-Way MANOVA) and Hotelling’s T2 test were also used. The results of the research highlighted that, in general, healthcare units aim to achieve superior performance compared to competitors by differentiating the products/services offered, rather than reducing costs, and the tendency to aim to achieve one (or both) type(s) of competitive advantage, as well as the scope of strategic activities in which it is achieved, differ according to several contingency factors, including location in a certain geographical area, the type of health organization, and their age and size.
Leveraging Digital Empowerment for Green Product Innovation: Unraveling the Mediating Role of Resource Integration and Reconfiguration in Chinese Manufacturing Enterprises
Authors: Liu Yi , Mao Monuo , Zhang Yi , Xie Xiaoqing
Published: September 2023

The rapid digital transformation and the imperative for sustainable practices have made it crucial for Chinese manufacturing enterprises to adapt and achieve green product innovation by effectively utilizing digital technologies. This study takes a resource-based perspective from strategic management and develops a chain mediation model to examine how Chinese manufacturing enterprises can achieve green product innovation through digital empowerment. A questionnaire survey was conducted with 229 managers, and a multiple mediation model was employed to test the hypotheses. The findings highlight that a higher level of digital business intensity positively influences green product innovation, with resource integration playing a significant mediating role. However, the mediating effect of resource reconfiguration is found to be non-significant. Furthermore, there exists a sequential chain mediation effect of resource integration and resource reconfiguration in the relationship between digital business intensity and green product innovation. To ensure successful green product innovation, Chinese manufacturing enterprises need to focus on accumulating R&D experience and knowledge through resource integration, enabling them to identify latent market demand and develop corresponding green products. This approach facilitates an organic fusion of incremental and breakthrough innovation. The study contributes to the advancement of management paradigms driven by digitalization and the theory of green product innovation, offering valuable insights for Chinese manufacturing enterprises seeking to achieve green innovation through the effective utilization of digital technologies. Additionally, it provides practical implications for enhancing the adaptability of Chinese manufacturing enterprises to market demand and promoting the adoption of “dual carbon” practices.
Heavy Metals in Surface Sediment of Plateau Lakes in Tibet, China: Occurrence, Risk Assessment, and Potential Sources
Authors: Su Qiongyuan , Shahab Asfandyar , Huang Liangliang , Ubaid Ali Muhammad , Cheng Yanan , Yang Jiahuan , Xu Hao , Sun Zhicheng , Zou Qi , Chen Zhongbing , Kang Bin
Published: September 2023

Tibetan Plateau lakes have high ecological value and play a crucial role in maintaining ecological balance. This research aimed to study the pollution characteristics, ecological risk, and potential sources of eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in the surface sediments of 12 Tibetan Plateau lakes. The results of the toxicity risk index (TRI) showed that only Gongzhu Tso (28.09) and La’ ang Tso (20.25) had heavy metals that could pose a very high risk of toxicity to aquatic organisms. Hg posed the highest potential ecological risk to aquatic organisms. Based on the results of multiple analyses, we inferred that the contents of Cr, Cu, Hg, and Ni in sediments of Tibetan lakes were influenced by industrial and agricultural development; Cd, Pb, and Zn were influenced by transport and atmospheric transport; and As was derived from geothermal activity and rock weathering.
Scanning Electron Microscopy and EDX Spectroscopy of Commercial Swabs Used for COVID-19 Lateral Flow Testing
Authors: Aparicio-Alonso Manuel , Torres-Solórzano Verónica , Méndez-Contreras José Francisco , Acevedo-Whitehouse Karina
Published: September 2023

The chemical composition of COVID test swabs has not been examined beyond the manufacturer’s datasheets. The unprecedented demand for swabs to conduct rapid lateral flow tests and nucleic acid amplification tests led to mass production, including 3D printing platforms. Manufacturing impurities could be present in the swabs and, if so, could pose a risk to human health. We used scanning electron microscopy and energy dispersive X-ray (EDX) spectroscopy to examine the ultrastructure of seven assorted brands of COVID test swabs and to identify and quantify their chemical elements. We detected eight unexpected elements, including transition metals, such as titanium and zirconium, the metalloid silicon, as well as post-transition metals aluminium and gallium, and the non-metal elements sulphur and fluorine. Some of the elements were detected as trace amounts, but for others, the amount was close to reported toxicological thresholds for inhalation routes. Experimental studies have shown that the detrimental effects of unexpected chemical elements include moderate to severe inflammatory states in the exposed epithelium as well as proliferative changes. Given the massive testing still being used in the context of the COVID pandemic, we urge caution in continuing to recommend repeated and frequent testing, particularly of healthy, non-symptomatic, individuals.
Laboratory-Induced Bifenthrin, Flonicamid, and Thiamethoxam Resistance and Fitness Costs in Rhopalosiphum padi
Authors: Gul Hina , Haq Ihsan ul , Güncan Ali , Ullah Farman , Desneux Nicolas , Liu Xiaoxia
Published: September 2023

The bird cherry-oat aphid, Rhopalosiphum padi (L.) (Hemiptera: Aphididae) is one of the most economically important pests of wheat crops worldwide. Thiamethoxam, bifenthrin, and flonicamid are extensively used insecticides for controlling this key pest. However, the indiscriminate use of chemical insecticides has led to the development of resistance in insects. In this study, we assessed the development of selection-induced resistance to bifenthrin, flonicamid, and thiamethoxam under controlled laboratory conditions. Additionally, we employed the age-stage, two-sex life table method to examine the fitness of R. padi. After ten generations of selection, bifenthrin-, flonicamid-, and thiamethoxam-resistant strains of R. padi were developed with resistance levels of 34.46, 31.97, and 26.46-fold, respectively. The life table analysis revealed a significant decrease in adult longevity and fecundity in these resistant strains compared to susceptible strain. Furthermore, the key demographic parameters such as net reproductive rate (R0) and reproductive days exhibited a significant reduction in all resistant strains, while the intrinsic rate of increase (r) and finite rate of increase (λ) were decreased only in resistant strains to bifenthrin and thiamethoxam. Taken together, these findings provide a comprehensive understanding of laboratory-induced insecticide resistance evolution and the associated fitness costs in R. padi. This knowledge could help to design resistance management strategies against this particular pest of wheat.
Protective Effects of Alginate and Chitosan Oligosaccharides against Clostridioides difficile Bacteria and Toxin
Authors: Mavrogeni Maria Eleni , Asadpoor Mostafa , Judernatz Jo H. , van Ark Ingrid , Wösten Marc M. S. M. , Strijbis Karin , Pieters Roland J. , Folkerts Gert , Braber Saskia
Published: September 2023

Clostridioides difficile infection is expected to become the most common healthcare-associated infection worldwide. C. difficile-induced pathogenicity is significantly attributed to its enterotoxin, TcdA, which primarily targets Rho-GTPases involved in regulating cytoskeletal and tight junction (TJ) dynamics, thus leading to cytoskeleton breakdown and ultimately increased intestinal permeability. This study investigated whether two non-digestible oligosaccharides (NDOs), alginate (AOS) and chitosan (COS) oligosaccharides, possess antipathogenic and barrier-protective properties against C. difficile bacteria and TcdA toxin, respectively. Both NDOs significantly reduced C. difficile growth, while cell cytotoxicity assays demonstrated that neither COS nor AOS significantly attenuated the TcdA-induced cell death 24 h post-exposure. The challenge of Caco-2 monolayers with increasing TcdA concentrations increased paracellular permeability, as measured by TEER and LY flux assays. In this experimental setup, COS completely abolished, and AOS mitigated, the deleterious effects of TcdA on the monolayer’s integrity. These events were not accompanied by alterations in ZO-1 and occludin protein levels; however, immunofluorescence microscopy revealed that both AOS and COS prevented the TcdA-induced occludin mislocalization. Finally, both NDOs accelerated TJ reassembly upon a calcium-switch assay. Overall, this study established the antipathogenic and barrier-protective capacity of AOS and COS against C. difficile and its toxin, TcdA, while revealing their ability to promote TJ reassembly in Caco-2 cells.
Okadaic Acid Is at Least as Toxic as Dinophysistoxin-1 after Repeated Administration to Mice by Gavage
Authors: Park Se Yong , Kang Ju-Hee , Jung Hyun Jin , Hwang Jung Ho , Chun Hyang Sook , Yoon Yeo Sung , Oh Seung Hyun
Published: September 2023

Okadaic acid (OA) and its analogues cause diarrhetic shellfish poisoning (DSP) in humans, and risk assessments of these toxins require toxicity equivalency factors (TEFs), which represent the relative toxicities of analogues. However, no human death by DSP toxin has been reported, and its current TEF value is based on acute lethality. To properly reflect the symptoms of DSP, such as diarrhea without death, the chronic toxicity of DSP toxins at sublethal doses should be considered. In this study, we obtained acute oral LD50 values for OA and dinophysistoxin-1 (DTX-1) (1069 and 897 μg/kg, respectively) to set sublethal doses. Mice were treated with sublethal doses of OA and DTX-1 for 7 days. The mice lost body weight, and the disease activity index and intestinal crypt depths increased. Furthermore, these changes were more severe in OA-treated mice than in the DTX-1-treated mice. Strikingly, ascites was observed, and its severity was greater in mice treated with OA. Our findings suggest that OA is at least as toxic as DTX-1 after repeated oral administration at a low dose. This is the first study to compare repeated oral dosing of DSP toxins. Further sub-chronic and chronic studies are warranted to determine appropriate TEF values for DSP toxins.
Assessing Larval Zebrafish Survival and Gene Expression Following Sodium Butyrate Exposure and Subsequent Lethal Bacterial Lipopolysaccharide (LPS) Endotoxin Challenge
Authors: Wang Mary X. , Shandilya Umesh K. , Wu Xiang , Huyben David , Karrow Niel A.
Published: September 2023

As aquaculture production continues to grow, producers are looking for more sustainable methods to promote growth and increase fish health and survival. Butyrate is a short-chain fatty acid (SCFA) with considerable benefits to gut health, and in recent years, butyrate has been commonly used as an alternative to antimicrobials in livestock production. In this study, we aimed to assess the protective effects of sodium butyrate (NaB) on larval zebrafish subjected to a lethal Pseudomonas aeruginosa lipopolysaccharide (LPS) endotoxin challenge and to elucidate potential protective mechanisms of action. Larval zebrafish were pre-treated with 0, 3000, or 6000 μM NaB for 24 h at 72 h post-fertilization (hpf), then immune challenged for 24 h with 60 μg/mL of LPS at 96 hpf. Our results demonstrate that larval zebrafish pre-treated with 6000 μM of NaB prior to lethal LPS challenge experienced significantly increased survival by 40%, and this same level of NaB significantly down-regulated the expression of pro-inflammatory Tumor Necrosis Factor α (TNF-alpha). Findings from this study are consistent with the beneficial effects of NaB on other vertebrate species and support the potential use of NaB in aquaculture.