In the past, Sabah has often been reported as Malaysia’s poorest state, with the recorded highest incidence of absolute poverty among all the other states. The consumption patterns of households in Sabah have been significantly impacted by such circumstances. This further draws light on the adverse impact on the broader economy, as low levels of spending may restrict demand for products and services, stifling economic growth. The understanding of households’ consumption functions based on the Permanent Income Hypothesis (PIH) will advance knowledge in identifying the key factors that influence the households’ spending decisions. Pointing out the scant number of past studies done within this very context, and focusing on the Sabah state in particular, further motivated this study, this paper aims to develop a conceptual framework that can estimate and examine the households’ consumption functions in Sabah. As such, the methodology of drawing upon narrative reviews from research in the past will be used in this paper to develop the conceptual framework. The result of this study built upon the framework developed will help in identifying the factors that explain the households’ consumption patterns, in particular, whether the function estimated will be consistent with the Permanent Income Hypothesis (PIH). It is hoped that the conceptual framework built will aid in providing valuable empirical insight for policymakers in designing effective policies that can uplift households that are living in poverty.

Introduction: Food well-being of the population is one of the priorities of the Togolese government, which relies on the agricultural investment and food security Programme to increase national food production. In addition, the country relies on food imports to make up the shortfall. At the same time undernourishment and malnutrition remain high among the country’s population. This research analyzes food supply and its implications for household consumption in Grand Lomé, Togo. [Methods] The methodology used documents, a survey of 963 heads of household randomly sampled households and semi-structured interviews with 10 households and with Togolese food safety agency (ANSAT). Quantitative data were processed and analyzed using Excel spreadsheets R and R-Studio, while content analysis was applied to the verbal applied to the verbal statements collected. Results: Firstly, the results show that domestic agricultural production contributed an average of 91% of food supply between 2014–2017. The deficit is made up by food imports, which rose from 13.5% in 2014 to 15.4% in 2017. This translated into an acceptable food energy consumption of 2337 Kcal/head/day in 2017. Secondly, 81% of respondents recognize a strong food presence at consumer markets, except that the chi-square test applied to the data at the 5% threshold shows (p-value < 2.2 × 10⁻¹⁶), indicates that this satisfaction is a function of place of residence. Despite this, persistent shortages affect more staple crops, livestock and dairy products, leading households to deprive themselves and buy food at affordable prices. Finally, we observe non-diversified diets marked by regular consumption of “cereals/legumes”, vegetables and beverages to the detriment of “tubers/roots”, “meat/fish”, “fruit” and “dairy products”. Conclusion: This research shows that food supply, although adequate, is not sufficient to ensure balanced, nutritious and culturally appropriate food consumption by urban households. Recommendations: To meet these challenges, the central government, in collaboration with urban communes and consumer advocates, must mobilize resources to create urban agricultural farms, strengthen food protection systems, distribute staple products directly to households and limit the importation of food that is hazardous to health.

The world has changed to a massive degree in the past thousands of years. Most of the time, the amount of carbon dioxide in the atmosphere remains constant. In the late 18th century, according to the sources of CDIAC and NOOA, the level of carbon dioxide began to rise, and then in the 20th century, it went through the roof, reaching levels that had not been seen in nature for millions of years. The increase in carbon in the atmosphere is the major contributing factor to climate change. The key to reversing the damage is restoring the earth’s delicate, balanced carbon cycle. As carbon cycle depicts the way carbon moves around the earth. It consists of sources that emit the carbon component into the atmosphere. The biological side of the carbon cycle is well balanced due to respiration, where carbon dioxide is released into the atmosphere, then plants, bacteria, and algae take carbon dioxide out of the atmosphere during photosynthesis and the process they use to generate chemical energy. On the other hand, oceans are the best sources and sinks; carbon dioxide is endlessly being absorbed into the ocean and released from the oceans almost exactly at the same rate, which is rapidly influencing the carbon cycle. Similarity is a methodology that has many applications in the real world. The current research article is destined to study how statistics of carbon emission metrics are alike and belong to one cluster. In the current study, the research is destined to derive a similarity analysis of several countries’ carbon emission metrics that are alike and often fall in the range of [0, 1]. And deriving the proximity of the carbon emission metrics leading to similarity or dissimilarity. In the current context of data matrices of numerical data, an Euclidian measure of distance between two data elements will yield a degree of similarity. The current research article is destined to study the similarity analysis of carbon emission metrics through fuzzy entropy clustering.

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.

Providing and using energy efficiently is hampered by concerns about the environment and the unpredictability of fossil fuel prices and quantities. To address these issues, energy planning is a crucial tool. The aim of the study was to prioritize renewable energy options for use in Mae Sariang’s microgrid using an analytical hierarchy process (AHP) to produce electricity. A prioritization exercise involved the use of questionnaire surveys to involve five expert groups with varying backgrounds in Thailand’s renewable energy sector. We looked at five primary criteria. The following four combinations were suggested: (1) Grid + Battery Energy Storage System (BESS); (2) Grid + BESS + Solar Photovoltaic (PV); (3) Grid + Diesel Generator (DG) + PV; and (4) Grid + DG + Hydro + PV. To meet demand for electricity, each option has the capacity to produce at least 6 MW of power. The findings indicated that production (24.7%) is the most significant criterion, closely followed by economics (24.2%), technology (18.5%), social and environmental (18.1%), and structure (14.5%). Option II is strongly advised in terms of economic and structural criteria, while option I has a considerable advantage in terms of production criteria and the impact on society and the environment. The preferences of options I, IV, and III were ranked, with option II being the most preferred choice out of the four.

This paper highlights the complex relationship between entrepreneurship, sustainable development, and economic growth in 41 European countries, using a reliable K-Means cluster analysis. The research thoroughly evaluates three key factors: the SDG Index for sustainable development, GDP per capita for economic well-being, and the New Business Density Rate for entrepreneurial activity. Our methodology reveals three distinct narratives that embody varying degrees of economic vitality and sustainability. Cluster 1 comprises the financially stable and sustainability-oriented countries of Western and Northern Europe. Cluster 2 showcases the variegated economic and sustainability initiatives in Central and Southern Europe. Cluster 3 envelopes the economic titans with noteworthy business expansion but with the potential for better sustainable practices. The analysis reveals a favourable association between economic prosperity and sustainable development within clusters, although with nonlinear intricacies. The research concludes with a series of strategic imperatives specifically crafted for each cluster, promoting economic variation, increased sustainability, invention, and worldwide collaboration. The resulting findings highlight the crucial need for policy-making that considers the specific context and the potential for combined European resilience and sustainability.