This paper aims to shed light on community-based disaster mitigation and the challenges encountered by using the Pangandaran coast as a case study, one of Indonesia’s disaster-prone areas. Observations, in-depth interviews, and documentation studies were used to collect data. The findings of this study indicate that community-based disaster mitigation is well realized, as evidenced by community early preparedness forums collaborating with the government to provide socialization and education to the community. However, disaster preparedness still faces challenges, including; since some of the mitigation objects are tourists, mitigation efforts need to be carried out sustainably while not following the budget they have; mitigation support devices and facilities such as damaged or missing signs for evacuation routes, temporary shelters, assembly point locations, and Early Warning System (EWS) devices whose number is still not optimal; lack of participation of hotels or restaurants in disaster mitigation, especially in engaging in preventive actions to minimize disaster risk. This situation is a challenge in itself for disaster mitigation management, moreover, Pangandaran Village must maintain its status as a “Tsunami Ready” village.

The Malaysian government has been actively strengthening the information and communication industry’s ecosystem through talent retention to realize Malaysia 5.0 and transform the country into a developed human-centered society that balances economic advancement with the resolution of talent problems. This is done to recognize the significance of emerging in building a vibrant and dynamic economy for the country. Few of these studies, however, had developed comprehensive policy recommendations for keeping information specialists in Malaysia’s information businesses. To address this gap, a comprehensive literature review was conducted to understand the factors driving information professionals to leave the sector. The findings aim to inform talent retention strategies that will strengthen the industry’s sustainability and attract skilled leaders, ensuring the information sector’s readiness for a successful digital transition.

With the requirements of New English Curriculum Standards, English teaching has shifted towards organising content thematically, focusing not only on the transmission of linguistic knowledge but also on the improvement of students' comprehensive quality during language learning. This evolution undoubtedly raises higher demands on English instruction. Unit-based integrated teaching, as an innovative pedagogical model, is characterised by its holistic, interconnected, progressive, and comprehensive features. It can help students to build a correlated knowledge network facilitates the establishment of connections between disparate pieces of knowledge, deepens students' understanding and enhances their retention, improves their overall linguistic competence and learning ability, so as to foster the comprehensive development of core literacy. Therefore, this article takes the teaching of English in compulsory education as an example, and explores and elaborates on the design and implementation path of integrated teaching of English units under the new curriculum standards from four aspects: teaching objectives, teaching content, teaching process, and teaching evaluation, in order to provide reference for promoting integrated teaching of English units in compulsory education.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

This review provided a detailed overview of the different synthesis and characterization methods of polymeric nanoparticles. Nanoparticles are defined as solid and colloidal particles of macromolecular substances ranging in size under 100 nm. Different types of nanoparticles are used in many biological fields (bio-sensing, biological separation, molecular imaging, anticancer therapy, etc.). The new features and functions provided by nano dimensions are largely different from their bulk forms. High volume/surface ratio, improved resolution and multifunctional capability make these materials gain many new features. 

Recent times have seen significant advancements in AI and NLP technologies, poised to revolutionize logistical decision-making across industries. This study investigates integrating ChatGPT, an advanced AI language model, into strategic, tactical, and operational logistics. Examining its applicability, benefits, and limitations, the study delves into ChatGPT's capacity for strategic logistics planning, facilitating nuanced decision-making through natural language interactions. At the tactical level, it explores ChatGPT's role in optimizing route planning and enhancing real-time decision support. The operational aspect scrutinizes ChatGPT's capabilities in micro-level logistics and emergency response. Ethical implications, encompassing data security and human-AI trust dynamics, are also analyzed. This report furnishes valuable insights for the logistics sector, emphasizing AI's potential in reshaping decision-making while underscoring the necessity for foresight, evaluation, and ethical considerations in AI integration. In this publication, it is assumed that ChatGPT is not entirely reliable for decision-making in the logistics field: at the strategic level, it can be effectively used for "brainstormin" in preparing decisions, but at the tactical and operational level, the depth of the knowledge is not sufficient to make appropriate decisions. Therefore, the answers provided by ChatGPT to the defined logistic tasks are compared with real logistic solutions. The article highlights ChatGPT's effectiveness at different levels of logistics and clarifies its potential and limitations in the logistics field.