This research explores the interactions within supply chains in the manufacturing sector, with a special emphasis on the distinctive obstacles encountered by the mosquito coil industry. The study is motivated by the need to comprehensively understand and address the multifaceted challenges encountered by manufacturers in their supply chain processes. The mosquito coil industry holds significant importance in Malaysia, primarily due to the country’s tropical climate, which is conducive to mosquito proliferation and the transmission of mosquito-borne diseases. Nowadays, there are growing complexities and disruptions experienced by the mosquito coil sector’s supply chain, prompting an in-depth investigation. The main objective is to identify the challenges and resilience strategies employed by manufacturers in this sector, providing an understanding that contributes to the broader discourse on supply chain dynamics. Employing a qualitative case study methodology, this research engages in extensive data collection through interviews, document analysis, and direct observations within the selected mosquito coil manufacturing entity. This methodology allows for an immersive exploration of the challenges faced, revealing insights into the factors influencing the supply chain dynamics. The study reveals a wide array of challenges, from obtaining raw materials to managing distribution logistics, underscoring the unique complexities specific to the sector. As a result, the research identifies and analyzes resilience strategies implemented by the mosquito coil manufacturer to mitigate challenges, such as procurement challenges faced in financial related issues, logistical complexities occurred from recent years’ worldwide pandemic, production disruptions from company’s human resource-related issues, global factors from the company’s competitors and market challenges, and technology integration from rapid technological advancements. Thus, implications of this study extend beyond the mosquito coil sector, contributing valuable knowledge to the academic community, practitioners, and policymakers involved in supply chain management. The research not only addresses the identified challenges but also serves as a foundation for enhancing the overall understanding of manufacturing supply chain dynamics, thereby fostering informed decision-making for improved industry resilience.

The creation of points where law, politics and education policies take intersection is a very complex and dynamic environment determined by philosophical shifts, economic problems, and social dynamics. This study dissects various complicated challenges facing the process of the framing of educational policies and their implementation which have become rampant due to the rapid political transformations. The researched evaluation is applied via both qualitative and quantitative methods, including juridical research, case and best practices studies and surveys, with the descriptive nature of the research as the main tool. The heart of the essay is three main themes - the contention between the rigidity of the academic standards and the holistic growth of students, its possible effects when students are too identified with a test-centric approach as their knowledge is sacrificed for their test scores, and the inclusion of rights and protections for underrepresented populations even when faced with a government’s resistance. Similarly, the research examines the perils of creating legislation too quickly, especially, because of unexpected side effects and interpretation conflicts. Findings show profound demographic differentials over districts which implies the designing and implementation of policies need to be modified accordingly. Unless a certain policy brings the best outcomes in the learning process, then nobody should choose it even if it means disrupting student well-being and decreasing their involvement. It is also emblematic of how cross-party cooperation and stakeholders’ understanding are important aspects of fairly dealing with complicated policy environments.

Based on the resource-based view and institutional theory, this study investigates the impact of their environmental management capabilities and environmental, social, and governance (ESG) pressure on the non-financial performance of small and medium-sized enterprises (SMEs). In particular, it examines the interaction effect of ESG pressures on the relationship between SMEs’ environmental management capabilities and non-financial performance. For this study, a total of 1865 SME lists were obtained through Jeonnam Techno Park and Jeonnam Small Business Job and Economy Promotion Agency. Based on this, a total of 127 questionnaires were returned as a result of a telephone, e-mail, and online survey, and finally, an empirical analysis was conducted based on 120 questionnaires. We conducted an empirical analysis of Korean SMEs and obtained the following results: First, environmental management capabilities have a significant, positive effect on SMEs’ non-financial performance. Second, ESG pressure has a significant, negative effect on the non-financial performance of SMEs. Next, we analyzed the moderating effect of ESG pressures and observed that ESG pressures strengthen the positive effect of environmental management capabilities on non-financial performance. Based on the resource-based perspective and institutional theory, this study provides meaningful academic implications by examining environmental management capabilities and ESG pressures, which have not been identified in previous studies, as factors of non-financial performance that are becoming important under the new management paradigm, such as climate change and ESG. Furthermore, while ESG pressure has a significant negative effect on non-financial performance, we find that it is a moderating variable that strengthens the relationship between SMEs’ environmental management capabilities and non-financial performance, which has useful academic and practical implications for ESG and strategic management.

Currently there is a great acceptance in medicine and dentistry that clinical practice should be “evidence-based” as much as possible. That is why multiple works have been published aimed at decreasing radiation doses in the different types of imaging modalities used in dentistry, since the greater effect of radiation, especially in children, forces us to take necessary measures to rationalize its use, especially with Cone Beam computed tomography (CBCT), the method that provides the highest doses in dentistry. This review was written using such an approach with the purpose of rationalizing the radiation dose in our patients. In order to formulate recommendations that contribute to the optimization of the use of ionizing radiation in dentistry, the SEDENTEXCT project team compiled and analyzed relevant publications in the literature, guidelines that have demonstrated their efficiency in the past, thus helping to see with different perspectives the dose received by patients, and with this, it is recommended taking into account this document so as to prescribe more adequately the complementary examinations that we use on a daily basis.

Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.