Objective: This research aims to investigate the legal dynamics of leasing agricultural land plots integrated with protective plantings, motivated by recent legislative changes that significantly influence both agricultural productivity and environmental conservation. Methods: The authors of the article used the methods of axiological, positivist, dogmatic, historical, and comparative-legal analysis. Results: The study considers the recent legislative amendments that grant agricultural producers the right to lease land with forest belts without the need for bidding. It traces the historical development of forest plantations, highlighting their major role in intensifying agricultural production. Our results reveal that the new legislative framework allows agricultural producers to lease lands with protective forest belts without bidding, a change that highlights the complexities of balancing economic efficiency with ecological sustainability. Conclusions: The research emphasizes the unique legal challenges and opportunities presented by forest belt leasing in the agricultural context. It stipulates the need for a balanced legal framework that preserves environmental integrity, protects property rights, and supports sustainable agricultural practices. This study dwells on the evolving legal landscape of forest belt leasing and its implications for agricultural land management in Russia and similar regions. The significance of this research in its comprehensive analysis of the legal, economic, and ecological dimensions of land leasing, offering a nuanced understanding of how legislative changes shape land use strategies.

Falling is one of the most critical outcomes of loss of consciousness during triage in emergency department (ED). It is an important sign requires an immediate medical intervention. This paper presents a computer vision-based fall detection model in ED. In this study, we hypothesis that the proposed vision-based triage fall detection model provides accuracy equal to traditional triage system (TTS) conducted by the nursing team. Thus, to build the proposed model, we use MoveNet, a pose estimation model that can identify joints related to falls, consisting of 17 key points. To test the hypothesis, we conducted two experiments: In the deep learning (DL) model we used the complete feature consisting of 17 keypoints which was passed to the triage fall detection model and was built using Artificial Neural Network (ANN). In the second model we use dimensionality reduction Feature-Reduction for Fall model (FRF), Random Forest (RF) feature selection analysis to filter the key points triage fall classifier. We tested the performance of the two models using a dataset consisting of many images for real-world scenarios classified into two classes: Fall and Not fall. We split the dataset into 80% for training and 20% for validation. The models in these experiments were trained to obtain the results and compare them with the reference model. To test the effectiveness of the model, a t-test was performed to evaluate the null hypothesis for both experiments. The results show FRF outperforms DL model, and FRF has same accuracy of TTS.

In the process of forest recreation value development, there are some characteristics, such as large amount of investment capital, long financing recovery cycle and high potential risks, which lead to limited capital source and prominent financing risks. To achieve sustainable development, forest recreational value development enterprises must solve the financing dilemma, therefore, it is very urgent to identify the financing risk factors. The research constructed financing risk evaluation index system through WSR (Wuli-Shili-Renli) methodology (from affair law, matter principle and human art dimensions), taking S National Forest Park at Fujian Province as a case study, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method were used for empirical analysis. The results showed that for the first level indicators, operational risk should be paid close attention to, followed by political risk and environmental risk. Among the secondary level indicators, policy changes, financing availability and market demand need attention, which are consistent with the result of field survey. Based on that, countermeasures were put forward such as the multiple collaborative linkage and effective internal control; reduction on operating costs and broaden financing channels; encouragement diversification of investment entities and improvement of financial and credit support; strengthening government credit supervision, optimizing financing risk evaluation, and building a smart tourism financing information platform, to reduce and control financing risks, then promote the development of forest recreation value projects.

The need for forest products, agricultural expansion, and dependency on biomass for the household energy source has largely influenced Ethiopia’s forest resources. Consequently, the country lost its forest resources to less than 6% until the millennium. In this study, quantitative and qualitative historical data analysis was employed to understand the socioeconomic benefits of large dam construction to Ethiopia and downstream countries. Moreover, remotely sensed data was also used to analyze the trends of vegetation cover change in the Nile catchment since the commencement of the dam; focusing on areas where there are high settlement and urban areas. It was identified that Ethiopia has one of the lowest electricity consumption per capita in Africa; about 91% of the source of household energy supply depends on fuelwood today and more than 55.7% of the population does not have access to electricity. The normalized difference vegetation index result shows an increment of vegetation area in the Nile catchment and a reduction of no vegetation area from 2011–2021 by 37.1%; which is directly related to the protection of the dam catchment for its sustainability in the last decade. The hydroelectric dam construction has prospects of multi-benefit to Ethiopia and downstream countries either through the direct benefit of hydropower energy production, related socioeconomic values, and reducing risks of destructive flood from Ethiopian highlands. Generally, it explains the reason why to not say ‘No’ to the reservoir as it is an ever more vital tool for fulfilling growing energy demand and supporting ecological stability.