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 rapid expansion of smart cities has led to the widespread deployment of Internet of Things (IoT) devices for real-time data collection and urban optimization. However, these interconnected systems face critical cybersecurity risks, including data tampering, unauthorized access, and privacy breaches. This paper proposes a blockchain-based framework designed to enhance the security, integrity, and resilience of IoT data in smart city environments. Leveraging a private blockchain, the system ensures decentralized, tamper-proof data storage, and transaction verification through digital signatures and a lightweight Proof of Work consensus mechanism. Smart contracts are employed to automate access control and respond to anomalies in real time. A Python-based simulation demonstrates the framework’s effectiveness in securing IoT communications. The system supports rapid transaction validation with minimal latency and enables timely detection of anomalous patterns through integrated machine learning. Evaluations show that the framework maintains consistent performance across diverse smart city components such as transportation, healthcare, and building security. These results highlight the potential of the proposed solution to enable secure, scalable, and real-time IoT ecosystems for modern urban infrastructures.

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. Ad

In Côte d’Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R² = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R² = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.

Potassium is an essential macronutrient for living creatures on earth and in plants, it plays a very significant role in determining the overall health of the plants. Although potassium is present in the soil, it is present in a form that is inaccessible to the plants, and hence synthetic harmful non-eco-friendly potassium fertilizers are used. To overcome this problem, the use of eco-friendly potassium-solubilizing bacteria comes into play. The goal of the present study was to assess the potassium-solubilizing bacteria that inhabit the farm rhizosphere, which demonstrate the presence of enzymes associated with plant growth promotion and antagonistic properties. A total of thirty-four isolates were isolated from the rhizosphere. All these isolates were subjected to a potassium solubilization test on Aleksandrov agar medium, out of which fourteen were found to possess potassium solubilizing ability. On the basis of the 16S rRNA gene sequencing, the most potential potassium-solubilizing bacterium was identified as Proteus mirabilis PSCR17. The plant growth promoting abilities and production of biocontrol enzymes of this isolate were evaluated, and the results indicated, in addition to potassium solubilization, the isolate was positive for indole acetic acid production, hydrogen cyanide production, amylase, catalase, cellulase, chitinase, and protease. The use of potassium fertilizers is harmful to the environment and ecosystem; hence, this study concludes that P. mirabilis PSCR17 can be used as a substitute for chemical potassium fertilizers to improve the growth and biocontrol traits of the plants in a sustainable manner after further research.

Two-dimensional hexagonal boron nitride nanosheets (h-BNNS) were synthesized on silver (Ag) substrates via a scalable, room-temperature atmospheric pressure plasma (APP) technique, employing borazine as a precursor. This approach overcomes the limitations of conventional chemical vapor deposition (CVD), which requires high temperatures (>800 °C) and low pressures (10⁻² Pa). The h-BNNS were characterized using FT-IR spectroscopy, confirming the presence of BN functional groups (805 cm⁻¹ and 1632 cm⁻¹), while FESEM/EDS revealed uniform nanosheet morphology with reduced particle size (80.66 nm at 20 min plasma exposure) and pore size (28.6 nm). XRD analysis demonstrated high crystallinity, with prominent h-BN (002) and h-BN (100) peaks, and Scherrer calculations indicated a crystallite size of ~15 nm. The coatings exhibited minimal disruption to UV-VIS reflectivity, maintaining Ag’s optical properties. Crucially, Vickers hardness tests showed a 39% improvement (38.3 HV vs. 27.6 HV for pristine Ag) due to plasma-induced cross-linking and interfacial adhesion. This work establishes APP as a cost-effective, eco-friendly alternative for growing h-BNNS on temperature-sensitive substrates, with applications in optical mirrors, corrosion-resistant coatings, energy devices and gas sensing.