In an effort to bridge the gap of economic and social inequality among the community, rural areas in Indonesia are encouraged to be self-sufficient in generating income. This makes the central government create various policies so that the regional government maximizes the management of its potential as an economic resource for the well-being of its people. One of the ways to manage this potential is to encourage rural areas to create tourism products that can be sold to the public. The Indonesian governments openly use the tourism sector as a tool for the development in many rural areas. Next, efforts to achieve successful development of the district will be closely related to the strategic planning and long-term cooperation of each local government with stakeholders in its implementation. These two points are the basic elements of the new regionalism theory. This theory states that the role of local governments is very important in initiating and making policies for new economic activities for a significant improvement in the quality of their population. Therefore, this study tries to explore how the new theory of regionalism can include rural development from a tourism perspective as a way to stimulate the fading economy in rural area of Indonesia. The study found that the new theory of regionalism needs support from various aspects such as social-cultural, community participation, the three pillars of sustainable development namely economic, social, and environmental as well as basic aspects to shape sustainable rural development through tourism.

The destructive geohazard of landslides produces significant economic and environmental damages and social effects. State-of-the-art advances in landslide detection and monitoring are made possible through the integration of increased Earth Observation (EO) technologies and Deep Learning (DL) methods with traditional mapping methods. This assessment examines the EO and DL union for landslide detection by summarizing knowledge from more than 500 scholarly works. The research included examinations of studies that combined satellite remote sensing information, including Synthetic Aperture Radar (SAR) and multispectral imaging, with up-to-date Deep Learning models, particularly Convolutional Neural Networks (CNNs) and their U-Net versions. The research categorizes the examined studies into groups based on their methodological development, spatial extent, and validation techniques. Real-time EO data monitoring capabilities become more extensive through their use, but DL models perform automated feature recognition, which enhances accuracy in detection tasks. The research faces three critical problems: the deficiency of training data quantity for building stable models, the need to improve understanding of AI's predictions, and its capacity to function across diverse geographical landscapes. We introduce a combined approach that uses multi-source EO data alongside DL models incorporating physical laws to improve the evaluation and transferability between different platforms. Incorporating explainable AI (XAI) technology and active learning methods reduces the uninterpretable aspects of deep learning models, thereby improving the trustworthiness of automated landslide maps. The review highlights the need for a common agreement on datasets, benchmark standards, and interdisciplinary team efforts to advance the research topic. Research efforts in the future must combine semi-supervised learning approaches with synthetic data creation and real-time hazardous event predictions to optimise EO-DL framework deployments regarding landslide danger management. This study integrates EO and AI analysis methods to develop future landslide surveillance systems that aid in reducing disasters amid the current acceleration of climate change.

Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area's most susceptible to erosion. The outcome of the study reveals that 3371.23 km2, which constitutes 91% of the district's total area, is identified as having mild soil erosion; in contrast, 154 km2, or 4%, is classified as moderate soil erosion, while 92 km2, representing 2.5%, falls under the high soil erosion category. Additionally, 50 km2, or 1.35%, is categorized as very high soil erosion and around 30 km2 of the study area is classified as experiencing severe soil erosion. The analysis further discovers that the annual soil loss in the district varies between 0 and 151 tons per hectare per year. This study indicates that most of the district is classified under low soil erosion; only a tiny fraction of the area is categorized as experiencing high and very high soil erosion. The study provides significant insights into soil erosion for policymakers and human society to bring their attention to the need for sustainable soil conservation practices in the undulating terrain/topography and agriculturally dominated district of Anuppur.

This study compares Human Resource Development (HRD) in Vietnam and Malaysia, looking at their methods, problems, and institutional frameworks in the context of ASEAN economic integration and Industry 4.0. Based on Cho and McLean’s (2004) integrated HRD model, this paper looks at recent research (from 2018 to 2023) to look at important topics such globalization, demographic changes, vocational training alignment, and technology disruption. Vietnam has a vast workforce, but it still has problems with low productivity, skill mismatches, and not being ready for the global market. On the other hand, Malaysia’s institutional HRD structures are making more progress, even though its workforce is getting older and not everyone is adapting to digital transformation at the same rate. The study shows that we need HRD policies that are tailored to each industry, training that is delivered in a decentralized way, and stronger relationships between the public and commercial sectors. It also stresses how important it is for national HRD policies to include global competences and initiatives that help everyone learn new skills. The study adds a unique framework for comparing HRD and gives policymakers, educators, and practitioners useful information, even though it is constrained by its use of secondary data. Future study should use mixed-methods to confirm results and look into interventions that work in specific situations. The study shows that Vietnam and Malaysia need personalized, inclusive, and forward thinking HRD systems to produce strong and competitive workforces in the post-pandemic, digital driven global economy.

Instant and accurate evaluation of drug resistance in tumors before and during chemotherapy is important for patients with advanced colon cancer and is beneficial for prolonging their progression-free survival time. Here, the possible biomarkers that reflect the drug resistance of colon cancer were investigated using proton magnetic resonance spectroscopy (1H-MRS) in vivo. SW480[5-fluorouracil(5-FU)-responsive] and SW480/5-FU (5-FU-resistant) xenograft models were generated and subjected to in vivo 1H-MRS examinations when the maximum tumor diameter reached 1–1.5 cm. The areas under the peaks for metabolites, including choline (Cho), lactate (Lac), glutamine/glutamate (Glx), and myoinositol (Ins)/creatine (Cr) in the tumors, were analyzed between two groups. The resistancerelated protein expression, cell morphology, necrosis, apoptosis, and cell survival of these tumor specimens were assessed. The content for tCho, Lac, Glx, and Ins/Cr in the tumors of the SW480 group was significantly lower than that of the SW480/5-FU group (p < 0.05). While there was no significant difference in the degree of necrosis and apoptosis rate of tumor cells between the two groups (p > 0.05), the tumor cells of the SW480/5-FU showed a higher cell density and larger nuclei. The expression levels of resistance-related proteins (P-gp, MPR1, PKC) in the SW480 group were lower than those in the SW480/5-FU group (p < 0.01). The survival rate of 5-FU-resistant colon cancer cells was significantly higher than that of 5-FUresponsive ones at 5-FU concentrations greater than 2.5 μg/mL (p < 0.05). These results suggest that alterations in tCho, Lac, Glx1, Glx2, and Ins/Cr detected by 1H-MRS may be used for monitoring tumor resistance to 5-FU in vivo.

This study investigates the impact of Corporate Social Responsibility (CSR) on employee job satisfaction within Pakistan's construction industry, with a focus on the mediating role of organizational commitment and the moderating role of perceived organizational support (POS). Employing survey data collected from a diverse range of construction firms across Pakistan, the quantitative analysis reveals that CSR initiatives significantly enhance employee job satisfaction, primarily through the mediating influence of organizational commitment. The findings suggest that when employees perceive their organization as socially responsible and engaged in community betterment, they exhibit greater commitment to the organization, which in turn fosters higher levels of job satisfaction. Although POS does not significantly moderate the CSR—job satisfaction relationship, it remains a critical factor in cultivating a supportive and positive work environment. This study contributes to the growing literature on CSR and employee outcomes by offering empirical evidence from a developing economy context. The results have practical implications for construction firms aiming to enhance employee morale and reduce turnover by leveraging CSR as a strategic tool to improve organizational commitment and overall job satisfaction.