CASPASE 3 expression exhibited a substantial increase, reaching 122-fold (40 g/mL) and 185-fold (80 g/mL) the initial level. The current investigation, therefore, implied that Ba-SeNp-Mo showed remarkable pharmacological properties.
This study employs social exchange theory to examine the influence of internal communication (IC), job engagement (JE), organizational engagement (OE), and job satisfaction (JS) on the development of employee loyalty (EL). The study collected data from 255 respondents at higher education institutions (HEIs) in Binh Duong province via a survey using an online questionnaire and employing convenience and snowball sampling techniques. The partial least squares structural equation modeling (PLS-SEM) approach was used to conduct data analyses and hypothesis testing. The results underscore significant validation across every relationship apart from that of JE and JS, which is not validated, according to the findings. Employing a novel approach, our study is the first to explore employee loyalty within the higher education institutions (HEIs) of Vietnam, an emerging economy. It develops and validates a research model through the incorporation of internal communication, employee engagement (job and organizational engagement), and job satisfaction. This study is projected to contribute to the theoretical discourse and further our insight into the various mechanisms whereby job engagement, organizational engagement, and job satisfaction might mediate the association between internal communication and employee loyalty.
Following the COVID-19 outbreak, industries experienced a surge in demand for contactless computing technologies and industrial automation systems. For such applications, Cloud of Things (CoT) stands out as a novel computing technology. The convergence of cutting-edge cloud computing and the Internet of Things is encapsulated in CoT. Industrial automation's progress has led to a high degree of interdependence, with cloud computing serving as the indispensable framework for IoT technology's operation. This facilitates data storage, analytics, processing, commercial application development, deployment, and adherence to security compliances. IoT's fusion with cloud technologies has revolutionized utility applications, creating smarter, more service-oriented, and secure systems that aid the sustainable development of industrial processes. The pandemic's effect on increased access to remote computing utilities has spurred a dramatic exponential growth in cyberattacks. Industrial automation's enhancement through CoT, coupled with the security considerations in circular economy solutions, is the focus of this paper. Traditional and non-traditional CoT platforms used in industrial automation have been analyzed for their security threats, with particular attention paid to the corresponding security features. Addressing the security issues and hurdles presented by IIoT and AIoT in industrial automation systems has also been accomplished.
Prescriptive analytics, a captivating segment of the broader analytics sphere, is attracting increasing interest among academicians and practitioners. From its inception to its current burgeoning position in the field, a critical appraisal of existing literature on prescriptive analytics is needed to assess its development. GMO biosafety A paucity of reviews exists within the related field, lacking a specific examination of prescriptive analytics in sustainable operations research, as assessed through content analysis. We addressed this knowledge gap by conducting a review of 147 peer-reviewed articles from academic journals, published from 2010 to August 2021. Our research, employing content analysis, has yielded five emerging research themes. Our study intends to contribute to the ongoing conversation in prescriptive analytics by identifying and suggesting promising research areas and future research trajectories. Through a synthesis of our literature review, we present a conceptual framework for exploring the effects of incorporating prescriptive analytics into sustainable supply chains, thereby affecting their resilience, performance, and competitive positioning. Finally, the paper contemplates the managerial outcomes, theoretical advances, and the boundaries of this research.
Efficiency evaluations of government responses to the COVID-19 pandemic are detailed via country-month indices. read more Our indices' scope includes 81 countries, and the period between May 2020 and November 2021. Governments, according to our framework, are predicted to enforce strict policies, as detailed in the Oxford COVID-19 Containment and Health Index, with the sole objective of preserving human life. Analysis indicates that institutions, democratic principles, political stability, trust, considerable public spending on healthcare, female employment rates, and economic equity exhibit positive and statistically significant correlations with our novel indices. Amongst the most efficient jurisdictions, those possessing a cultural foundation of high patience prove to be the most effective.
Research suggests that organizational capability is pivotal to operational performance, with a demonstrable impact from robust sensing and analytics capabilities. By establishing a framework, this study analyzes the impact of organizational competence on operational efficiency, emphasizing the execution of sensing and analytical capabilities. Employing a multifaceted approach encompassing the strategic fit theory, dynamic capability view, and resource-based view, we analyze how a data-driven culture (DDC) is strategically integrated by micro, small, and medium enterprises (MSMEs) with their organizational capabilities, leading to enhanced operational performance. To examine the moderating role of a DDC on the influence of organizational capability on operational performance, we utilize empirical research methods. Structural equation modeling applied to survey data collected from 149 MSMEs demonstrates a positive link between sensing and analytics capabilities and operational performance. The results highlight the positive moderating effect of a DDC on the relationship between organizational capability and operational performance. We delve into the theoretical and managerial ramifications of our findings, acknowledging study limitations and highlighting avenues for future research.
An extended SIS model allows us to examine the influence of infectious diseases and social distancing, accounting for stochastic shocks having probabilities that vary by state. Random jolts propagate a new disease strain, altering both the count of infected persons and the average biological properties of the causative pathogen. The likelihood of such shock events is contingent upon the prevalence of the disease, and we analyze how the properties of the state-dependent probability function influence the enduring epidemiological outcome, which is typified by a consistent probability distribution across varying levels of positive prevalence. Social distancing's effect on the steady-state distribution's support is twofold: it decreases the support's width, diminishing variability in disease prevalence, but simultaneously moves the support to the right, potentially yielding a higher ultimate number of infected individuals than in a system without control. Though this might be the case, social distancing proves to be an effective intervention, as it focuses the bulk of the distribution towards the lowest range of its support.
Revenue management for passenger rail transportation is vital for the financial sustainability of public transportation service providers. Passenger rail service providers can leverage the intelligent decision support system proposed in this study, incorporating dynamic pricing strategies, fleet management, and capacity allocation. Travel demand and the connection between price and sales are determined using the company's historical sales data. A multi-train, multi-class, multi-fare passenger rail transportation network's profitability is optimized using a mixed-integer non-linear programming model which factors in multiple cost types. Considering the prevailing market conditions and operational constraints, the model determines the assignment of each wagon to specific network routes, trainsets, and service categories for each day throughout the planning horizon. Because the mathematical optimization model's solution is not practical for large-scale scenarios in a timely manner, a fix-and-relax heuristic algorithm is employed. Real-world numerical applications reveal the promising potential of the proposed mathematical model for significantly improving overall profits in contrast to the company's existing sales policies.
The online edition includes supplementary materials linked to 101007/s10479-023-05296-4.
Included with the online version, and found at 101007/s10479-023-05296-4, are supplementary materials.
In the modern digital age, global demand for third-party food delivery services is exceptionally high. Medical Symptom Validity Test (MSVT) Ensuring the long-term viability of food delivery services, however, proves a formidable undertaking. Acknowledging the inconsistent viewpoints within the existing literature concerning sustainable third-party food delivery, we conducted a systematic review. The analysis elucidates recent advancements in this area and examines illustrative real-world implementations. To commence this study, the existing literature is examined, and the triple bottom line (TBL) framework is then applied to categorize past research into sub-categories of economic, social, environmental, and multi-dimensional sustainability. Three prominent research gaps emerge from our review: the lack of thorough investigation into restaurant preferences and decisions, the superficial treatment of environmental performance, and the limited study of multi-dimensional sustainability in third-party food delivery systems. In conclusion, drawing upon the literature reviewed and observed industrial practices, we propose five areas for future, in-depth investigation. Restaurant procedures, applications of digital technology, choices and behaviors, risk management, the TBL framework, and the post-coronavirus period demonstrate particular applications.