Explosive material detection considers the identification and classification of explosive materials using techniques from traditional sniffer dogs to cutting-edge sensing technology like thermal imaging, X-ray scanners, and chemical sensors. Explosive detection is applied in various locations, including airports, government buildings, and public areas, to prevent terrorist attacks and criminal actions that attempt to employ explosive devices. The effectiveness of these procedures is dependent on the detection materials, equipment, and environment, so new techniques are continuously explored to increase precision, sensitivity, and detection speed. Because explosive substances present a critical risk to infrastructure, security, and public safety, extensive analysis of existing detection methods is needed. This paper highlights key areas for further research and development in explosive materials detection by addressing identified limitations and challenges. Specifically, advancements in technology, interdisciplinary collaboration, and the integration of AI techniques offer significant opportunities for improving detection accuracy, reducing false positives, and ensuring safer environments for individuals and society.

This study aims to explain the role of Tri Hita Karana-based business strategies and digital marketing strategies in improving sustainable business performance. The population of this study was traditional tai-weaving SMEs in Bali. The sample size was 195 managers of traditional ikat weaving SMEs with a purposive sampling method. The analysis technique used is Path Analysis using SEM-PLS. The results show that government and environmental orientation had a positive and significant effect on sustainable business performance, while digital orientation had no significant effect on sustainable business performance. Environmental orientation had a positive and significant effect on Tri Hita Karana's business strategy, and environmental orientation had an insignificant effect on digital marketing strategy. Furthermore, Tri Hita Karana's business and digital marketing strategies positively and significantly affected sustainable business performance. Therefore, it is essential for traditional tai-weaving SMEs in Bali to intensify the implementation of Tri Hita Karana and digital marketing strategies to improve sustainable business performance.

Coffee shops have now evolved into an integral part of the modern lifestyle embraced by today's youth, especially by Generation Z. This study aims to understand the role of technology, specifically through Social Media Usage (SMU) and Electronic Word-Of Mouth (eWOM), and how trust as a mediator affects purchase intention and subsequently impacts customer loyalty. This study involved 282 respondents from diverse backgrounds. The sampling technique employed both snowballing and random sampling methods. For analysis, the Structural Equation Modeling (SEM) technique was utilized. In the study, several relationships were tested for their significance. The relationship between SMU and Trust was found to be significant. However, the relationship between eWOM and Trust was not significant. Trust significantly influenced Purchase Intention and Customer Loyalty. The direct relationship between Purchase Intention and Customer Loyalty was not significant. Moreover, the mediated relationships of SMU through Trust to Purchase Intention were significant, while the mediated relationship of eWOM through Trust to Purchase Intention was found to be non-significant. This investigation illuminates the distinct confluence of age-old values and contemporary digital interactions in sculpting consumer behavior within Indonesia. It accentuates the imperative for coffee shop enterprises to discern and synergize with these trends to guarantee enduring prosperity.

The development of social media technology has an impact on the welfare of users but has side effects on communication and behavior when used excessively. Excessive use of social networking sites impacts user behavior in obtaining fast information and sharing information with other users to show their strengths as a personal profile. Data was collected on young adults who made purchases on credit with pay letters as many as 210 users of social media Twitter, Facebook, and YouTube. The analysis used in the study used Partial Least Square version 4. The research data was obtained by distributing questionnaires via Google Forms. The study results show that excessive SNS use influences money attitudes, including money anxiety, trust, and power. The money trust that users have has an impact on money power. Money attitude affects credit application PayLater overuse behavior. The results showed that money trust did not impact increasing credit application PayLater overuse behavior, while money power and money anxiety influenced credit application PayLater overuse behavior. Research makes a practical contribution for SNS users to continue using it reflectively, so it does not interfere with work activities, family relationships, and the responsible use of money. The theoretical contribution enriches the theory of money behavior, e-payment, and money attitude using social media.

Global pandemic has provoked industries with unprecedented challenges. Stratagems to squash the COVID-19 bow like communal lockdown, social isolation, work at home, containment zones and all restraints sited on travel with stay home orders issued by the authorities led to sharp failure in revenues of service and manufacturing industries. The COVID-19 pandemic has shattered the transportation links with supply chain amongst suppliers, production amenities and consumers. Mostly the business executives are penetrating about passable strategies and plans for restoring production lines to encounter customer mandates. In this paper the pandemic effect of Indian business is considered which are affected by critical barriers of supply chains in the Indian scenario. These critical barriers are identified on a priority basis using the MADM approach. Furthermore, the study will help the scholars to grow conceptual models for maintaining a better supply chain to overwhelm this world-wide problem.

This research aims to explore the significance of supply chain (SC) resilience by integrating SC-Resilience and SC-Ambidexterity concepts. SC-Ambidexterity refers to the simultaneous application of SC-Adaptability and SC-Alignment capabilities within the supply chain. In line with the dynamic capabilities view (DCV) of the firm, this research adopts a quantitative approach to investigate the relationship between variables in the context of manufacturing and production companies in Pakistan, specifically in Karachi. The results of this case study have revealed a strong positive impact of SC-Ambidexterity on SC-Resilience, confirming the significance of adopting concurrent and synchronized supply chain capabilities. Furthermore, the analysis indicated that SC-Agility plays a crucial role as a mediator in the relationship between SC-Ambidexterity and SC-Resilience. The findings suggest that organizations that proactively invest in developing both ambidextrous capabilities and agility are more likely to achieve a higher level of supply chain resilience, enabling them to effectively navigate turbulent business environments.

Access to safe drinking water is essential for human health. In Abbottabad, tap and bore water are commonly used, but there has been a recent increase in bottled water consumption. This study aimed to compare tap and bottled water quality in Jinnahabad, Abbottabad. Physicochemical and bacteriological analysis was conducted on water samples collected from various sources. Surveys and interviews were also conducted to assess consumer perceptions and costs. The study found that, on average, bottled water had better physicochemical quality, although both alternatives met WHO limits. Tap water had higher levels of E. coli due to a weak sanitation system. Interestingly, despite perceiving bottled water as safer, most respondents still consumed tap water daily. Shopkeepers reported higher bottled water purchases for travel but lower daily consumption. Tap water was the main source, according to the Cantonment Board Abbottabad, though resources were insufficient. Doctors confirmed tap water-related diseases. The study suggests further research into consumer behavior and recommends monitoring measures, staff evaluations, and penalties to reduce costs and waste.

This study delved into the repercussions of economic instability on household food security while aiming to construct a robust framework for enhancing the resilience of the food supply chain. It thoroughly analyzed diverse factors, including government policies, economic conditions, environmental variables, and social dynamics, to gauge their reciprocal impact on food security. The research employed a meticulously chosen probability-based sample to ensure the representativeness of findings within the population, specifically focusing on residents in the Tanjung Kupang region of Johor. The study holds paramount significance as it provides novel insights for researchers, academic practitioners, and policymakers, shedding light on the far-reaching consequences of economic uncertainty on household purchasing power and its pivotal role in upholding food security. Moreover, it aspires to devise a tailored and sustainable food supply chain framework for Malaysia's unique context. By employing a quantitative approach enriched with robust statistical analysis and insights gathered through a meticulously designed questionnaire, this study sought to illuminate the intricate dynamics at play. The findings underscore the profound impact of economic instability on diminishing the income of B40 households, thereby curtailing their purchasing power. These findings align with comprehensive literature reviews from authoritative sources, underscoring factors such as inflation, soaring prices of essential commodities, and stagnant incomes contributing to the decline in income among B40 households. The implications of this research extend to policymakers, offering invaluable insights and promoting public awareness of potential challenges, along with plausible solutions.

Nomophobia is a term describing a growing fear in today’s world, the fear of being without a mobile device or beyond mobile phone contact. It is the biggest non-drug addiction of the 21st century and is mainly affected by teen-aged students. Those experiencing nomophobia may feel a sense of panic, anxiety, or distress when they are separated from their mobile phones. This work uses different statistical tools to identify the risk factor of nomophobia and machine learning techniques to propose a fresh way to measure and understand nomophobia. To create a predictive model for nomophobia, we gathered information from a broad sample (n = 357) of smartphone users and used a variety of machine learning methods. Using a questionnaire on 17 different factors and performing a statistically significant test (p<0.05) and ordinal logistic regression analysis on respondents age, level of education, CGPA, self-evaluation, per-day mobile phone usage, and use of media, we can recognize the most important features causative of nomophobia. The context of maximum phone usage is an important feature that highly affects nomophobia. About 201 respondents are at a moderate level. To develop a predictive model, decision tree (DT), random forest (RF), Gaussian Naïve Bayes (NB), and support vector machine (SVM) are utilized in this study for recognition of nomophobia addiction. Proposing an ensemble method to refine the predictive performance. From the analysis, we have found that the SVM feature selector with ensemble algorithm has classified the extent of smartphone addiction with a 57% accuracy rate. Our findings show that nomophobia tendencies can be accurately captured and predicted by machine learning approaches. The model distinguished between students who had symptoms of nomophobia and those who did not with remarkable accuracy. This study of machine learning-based methods presents a viable tool for diagnosing and treating nomophobia in students, eventually assisting in the creation of focused interventions and preventive measures.

Recent organizational trends give more importance to the social and responsible behavior of organizations to their sustainability. Numerous factors are responsible for prioritizing social responsiveness and pro-environmental or employee-green behavior for organizational sustainability. Nevertheless, no studies have yet considered how voluntary green behavior (VGB) and socially responsible human resource management (SRHRM) influence this perception. Hence, this study determines the explanatory link of VGB along with the impacts of SRHRM on organizational sustainability (environmental [EnS], social [SS], and economic [ES] sustainability). Data was collected from a developing nation context. An explanatory research strategy was used for the present study. To acquire data from 100 Bangladeshi pharmaceutical manufacturing organizations, structured questionnaires were used. For testing the proposed hypotheses of the study, we used partial least squares structural equation modeling (PLS-SEM). The outcomes of the analysis reveal that SRHRM has a considerable impact, both positively and significantly, on organizational sustainability (EnS, SS, and ES). Once again, SRHRM has a substantial positive effect on VGB. Furthermore, VGB plays an influential role as a mediator in the relationship between SRHRM and organizational sustainability. The findings have significant implications for pharmaceutical manufacturing organization management in Bangladesh and other Southeast Asian contexts. Based on the findings, pharmaceutical company managers will have a stronger rationale to invest in SRHRM while simultaneously establishing strong ties with employees and CSR-oriented green behavior to accomplish their organizational sustainability objectives. This study contributes to the existing body of research on the sustainability of organizations and the triple bottom line, along with SRHRM and VGB, by providing evidence from a country that is rapidly industrializing and developing. In this work, SRHRM was measured as a whole, even though it has three dimensions. Since the sample consists of Bangladeshi pharmaceutical manufacturing organizations, it is also uncertain whether the results can be generalized.