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The purpose of this paper is to present the multi-objective optimization of the dynamic response of isotropic and laminated composite folded plates. The dynamic analysis has been carried out using the finite element method based on the first-order shear deformation theory.

Hamilton’s principle has been employed for the derivation of the governing equations. Natural frequencies are obtained using the eigenvalue extraction method. The optimal combination of the crank angle, lamination scheme and boundary conditions on the natural frequencies of folded plates for their safe and optimal dynamic design has been obtained. The analysis has been carried out using finite element approach based on FSDT to obtain the dynamic equation of single- and double-fold laminated plates. In total, 15 experiments as per Taguchi’s standard L₁₅ orthogonal array have been performed. Further, standard deviation (SD) based TOPSIS method is used to perform multi-response optimization of folded plates in order to rank the combination of the input parameters.

SD integrated with TOPSIS reveals that Experiment No. 8 (crank angle=90° and anti-symmetric lamination scheme=0°/90°/0°/90°), Experiment No. 14 (crank angle=150° and anti-symmetric lamination scheme=0^o/90^o/0^o/90^o), Experiment No. 2 (crank angle=30° and anti-symmetric lamination scheme=0°/90°/0°/90°) and Experiment No. 3 (crank angle=30° and symmetric lamination scheme=0°/90°/0°/90°) occupy rank 1 for one fold, one end clamped, one fold, two ends clamped, two folds, one end clamped and two folds, two ends clamped conditions, respectively, in order to maximize the modal response corresponding to the fundamental mode.

SD-based technique for order of preference by similarity to ideal solution (TOPSIS) method is used to rank the process parameters. The optimum combination of the input parameters on the multi-response optimization of dynamics of the folded plates has also been evaluated using the analysis of mean (ANOM).

This study aims to investigate the challenges associated with the integration and implementation of blockchain technology in the education sector. The primary objective is to identify and categorize these challenges using the Technology-Organization-Environment (TOE) framework, shedding light on the technological, organizational and environmental factors that influence the adoption of blockchain solutions in educational settings.

A comprehensive literature review was conducted across multiple databases including Science Direct, Web of Science, Springer, IEEE Xplore and MDPI. The selected articles were analyzed based on the TOE framework to categorize challenges from the technological, organizational and environmental perspectives. The methodology involves a systematic search, analysis and synthesis of relevant articles to provide an in-depth understanding of the challenges hindering blockchain adoption in education.

This review revealed a predominant focus on technological challenges, emphasizing scalability issues, integration complexities, security and privacy concerns and data immutability. However, there is a notable research gap in the exploration of organizational and environmental challenges. The scarcity of studies addressing these perspectives may impact acceptance and resistance to blockchain adoption in educational settings.

This study contributes to the literature by systematically categorizing and analyzing the challenges associated with blockchain implementation in education using the TOE framework. It identifies the need for further research on organizational and environmental aspects, addressing a significant gap in the current scholarship on blockchain adoption in educational institutions.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

This study aims to evaluate impacts of construction professionals (CPs) conflict on performance in the Nigerian construction industry (NCI).

A quantitative method was used for this research. Questionnaires were sent to various CPs in Southwestern part of Nigeria. A total of 150 questionnaires were sent out, while 135 were gotten back from the partakers. The data received from the partakers were computed by applying descriptive and exploratory factor analysis.

In this study, conflict leads to the abandonment of the CPs’ task being rated highest by the participants. This was followed by conflict that results in insufficient communication, generates job pressure, results to frustrations and displeasure among the CPs, helps in early problem identification, causes work damage among professionals, helps in solving professional organization problems, improves productivity of professionals, improves communication among the professionals and so on.

This paper is limited to CPs that are members of professional bodies in Nigeria, and only 135 participants participated. Though, this paper suggests that a mixed-method approach should be utilized in further studies with a wider coverage.

The findings from this paper will increase the understanding of CPs in Nigeria on various impacts of conflict on performance in the construction industry, most specifically the professional bodies. Moreover, this study will increase the knowledge of CPs to always avoid whatever that leads to the abandonment of their tasks. Additionally, this study will benefit the CPs to avoid insufficient communication among themselves, in order to accomplish great performance and efficiency in their respective professional bodies.

Since previous studies on impacts of construction conflict in Nigeria were only focused on contractors and consultants in construction project, this current study filled the gap by evaluating the impacts of CPs’ conflict on performance in the NCI. Also, the method of analysis used for this study is exemptional because previous studies have overlooked the method. However, it is recommended that CPs must communicate more with others so as to ensure favorable conflict effects on performance.

Covid-19 pandemic is a unique and extraordinary situation for the globe, which has potentially disrupted almost all aspects of life. In this global crisis, the tourism and hospitality sector has collapsed in almost all parts of the world, and the same is true for India. Therefore, this paper aims to investigate the impact of Covid-19 on the Indian tourism industry.

This study develops an appropriate model to forecast the expected loss of foreign tourist arrivals (FTAs) in India for 10 months. Since the FTAs follow a seasonal trend, seasonal autoregressive integrated moving average (SARIMA) method has been employed to forecast the expected FTAs in India from March 2020 to December 2020. The results of the proposed model are then compared with the ones obtained by Holt-Winter's (H-W) model to check the robustness of the proposed model.

The SARIMA model seeks to manifest the monthly arrival of foreign tourists and also elaborates on the progressing expected loss of foreign tourists arrive for the next three quarters is approximately 2 million, 2.3 million and 3.2 million, respectively. Thus, in the next three quarters, there will be an enormous downfall of FTAs, and there is a need to adopt appropriate measures. The comparison demonstrates that SARIMA is a better model than H-W model.

Several studies have been reported on pandemic-affected tourism sectors using different techniques. The earlier pandemic outbreak was controlled and region-specific, but the Covid-19 eruption is a global threat having potential ramifications and strong spreading power. This work is one of the first attempts to study and analyse the impact of Covid-19 on FTAs in India.

The numerical solution of third-order boundary value problems (BVPs) has a great importance because of their applications in fluid dynamics, aerodynamics, astrophysics, nuclear reactions, rocket science etc. The purpose of this paper is to develop two computational methods based on Hermite wavelet and Bernoulli wavelet for the solution of third-order initial/BVPs.

Because of the presence of singularity and the strong nonlinear nature, most of third-order BVPs do not occupy exact solution. Therefore, numerical techniques play an important role for the solution of such type of third-order BVPs. The proposed methods convert third-order BVPs into a system of algebraic equations, and on solving them, approximate solution is obtained. Finally, the numerical simulation has been done to validate the reliability and accuracy of developed methods.

This paper discussed the solution of linear, nonlinear, nonlinear singular (Emden–Fowler type) and self-adjoint singularly perturbed singular (generalized Emden–Fowler type) third-order BVPs using wavelets. A comparison of the results of proposed methods with the results of existing methods has been given. The proposed methods give the accuracy up to 19 decimal places as the resolution level is increased.

This paper is one of the first in the literature that investigates the solution of third-order Emden–Fowler-type equations using Bernoulli and Hermite wavelets. This paper also discusses the error bounds of the proposed methods for the stability of approximate solutions.

Alongside the remarkable evolution of cellular communication to 5G networks, significant security and privacy challenges have risen which can affect the widespread adoption of advanced communication technologies. In this context, the purpose of this paper is to examine research within security and privacy for 5G-based systems highlighting contributions made by the research community and identify research trends within different subdomains of 5G security where open issues still exist.

This paper uses a bibliographic approach to review the state-of-the-art in the field of 5G security and is the pioneering effort to investigate 5G security research using this methodology. Specifically, the paper presents a quantitative description of the existing contributions in terms of authors, organizations, and countries. It then presents detailed keyword and co-citation analysis that shows the quantity and pattern of research work in different subfields. Finally, 5G security areas are identified having open challenges for future research work.

The study shows that China leads the world in terms of published research in the field of 5G security with USA and India ranked second and third respectively. Xidian University, China is ranked highest for number of publications and h-index followed by University Oulu and AALTO University Finland. IEEE Access, Sensors and IEEE Internet of Things Journal are the top publication venues in the field of 5G security. Using VOSViewer aided analysis with respect to productivity, research areas and keywords, the authors have identified research trends in 5G security among scientific community whilst highlighting specific challenges which require further efforts.

Existing studies have focused on surveys covering state-of-the art research in secure 5G network (Zhang et al. 2019), physical layer security (Wu et al., 2018), security and privacy of 5G technologies (Khan et al., 2020) and security and privacy challenges when 5G is used in IoT (Sicari et al. 2020). However, our research has revealed no existing bibliometric studies in this area and therefore, to our best knowledge, this paper represents pioneering such effort for security within 5G.

Suicide and attempted suicide is an important health issue and the number of people who die of suicide exceeds that of conflicts. Kashmir has been suffering from a low intensity war since last 20 years in which thousands have been killed or injured. There has been phenomenal increase in cases of psychological disorders along with suicide and and suicide attempters. Suicide in a conflict zone is viewed with indifference due to focus on the physical part of trauma. Difficulties faced by the suicidal patient and his attendants are seldom highlighted. 1408 patients who reported to emergency room for suicide attempt from 2000 to 2008 were taken for the study. All the patients underwent the hospital protocol for poisoning management. Patients were subjected to detailed psychiatric evaluation and questions were specifically asked about the difficulties encountered during management. Most of the cases were females with 92.11% belonging to the Muslim religion. 76.20% cases were from a rural background. 32.5% had been referred because of the lack of specific antidotes. Forty-three percent required arrangement of transportation by their own family members. Fifty-seven percent had been stopped for security checks along the way. Seventy-three percent felt that the attitude of the staff hostile. Twenty-three percent of patients had to share a bed. Almost all patients were questioned by security agencies within the hospital. More than 68% patient reported hostility amongst their neighbors. Suicidal poisoning is a significant health problem in Kashmir and management of these cases is fraught with difficulties across the spectrum of health care. Educating the doctors at primary care about first aid, improvement in community services followed by long term resolution of the conflict would go some way in alleviating the difficulties faced by a suicidal patient and his family in a conflict zone.

The main aim of this study is to investigate the impact of climate change and water salinity on farmer’s income risk with future outlook mitigation. Salinity and climate change are a threat to agricultural productivity worldwide. However, the combined effects of climate change and salinity impacts on farmers' income are not well understood, particularly in developing countries.

The response-yield function and general maximum entropy methods were used to predict the impact of temperature, precipitation and salinity on crop yield. The target minimization of total absolute deviations (MOTAD)-positive mathematical programming model was used to simulate the impact of climate change and salinity on socioeconomic and environmental indicators. In the end, a multicriteria decision-making model was used, aiming at the selection of suitable climate scenarios.

The results revealed that precipitation shows a significantly decreasing trend, while temperature and groundwater salinity (EC) illustrate a significantly increasing trend. Climate change and EC negatively impact the farmer's income and water shadow prices. Maximum reduction in income and water shadow prices was observed for A2 scenario (−12.4% and 19.4%) during 2050. The environmental index was the most important, with priority of 43.4% compared to socioeconomic indicators. Subindex amount of water used was also significant in study area, with 28.1% priority. The technique for order preference by similarity to ideal solution ranking system found that B1 was the best climatic scenario for adopting climate change adaptation in the research region.

In this study, farmers' income threats were assessed with the aspects of different climate scenario (A1, A1B and B1) over the horizons of 2030, 2040 and 2050 and three different indicators (economic, social and environmental) in Northwestern region of Pakistan. Only in arid and semiarid regions has climate change raised temperature and reduced rainfall, which are preliminary symptoms of growing salinity.

The purpose of this paper is to examine the long-run and short-run relationship between factor accumulation (i.e. physical capital and human capital) and economic growth by calculating the stocks of human capital and real physical capital.

The study uses endogenous growth model, where GDP per worker is the dependent variable and factor accumulation (real physical capital per worker and human capital) is the explanatory variable under the autoregressive distributive lag framework from 1973 to 2014 for Pakistan.

The results suggest that there is a long-run relationship between factor accumulation and GDP per worker in Pakistan. Findings of the study are consistent with the endogenous growth model suggesting that accumulation of human capital increases labor productivity, employment level and per capita income, and causes economic growth.

Developing countries like Pakistan should increase share of human capital for economic development. Government should invest in the education sector because investment in human capital has a large potential of productivity growth and welfare increase in developing countries.

This study challenges the notion of human capital and real physical capital stock used by different researchers. Considering human capital as a core factor of production, a series of human capital as average year of schooling is calculated by utilizing the perpetual inventory method.