Government of Nepal

Accurately representing three-dimensional (3D) canopy structure is essential for Earth System Models (ESMs) and radiative transfer schemes that link vegetation to climate–carbon feedback. Leaf area density (LAD) and related structural metrics are widely retrieved from remote sensing using Beer–Lambert (BL) transmittance inversions, yet these approaches commonly assume randomly distributed foliage and woody material. In real canopies, plant material is spatially aggregated (clumped), violating random mixing and introducing systematic LAD bias. Although clumping has been corrected using canopy or crown scale clumping indices (CI), voxel-based LAD retrievals from terrestrial laser scanning (TLS) and other 3D sensing approaches require clumping information that is defined at the same spatial scale as the inversion. The lack of a physically grounded voxel-resolved CI remains a key methodological gap, particularly for dense and heterogeneous canopy regions. Here, we develop a voxel-scale effective reference clumping index (CI_ref) retrieval method that is structurally consistent with voxel-based BL retrievals. We used digital twin 3D tree meshes from the RAMI-V benchmark forest scenes, spanning six contrasting crown forms and six leaf inclination angle distribution (LIAD) variants (36 canopy geometries). Each tree was partitioned into regular voxel grids at four sizes (0.2, 0.5, 1.0, and 2.0 m). Within each voxel, we performed multi-directional (18 bin viewing angle) ray tracing on every voxel-clipped mesh to directly quantify within-voxel gap probability, leaf projection function G(θ), and path-length statistics required for transmittance-based LAD inference. Directional CI estimates were derived for each viewing angle and then aggregated through a hierarchical pooling strategy that reduces sampling noise and directional variability (all angles → azimuth pooled → zenith-pooled). This procedure yields a single, robust CI_ref per voxel that is independent of viewing angle and suitable as a reference label for operational LAD retrieval algorithm development from LiDAR data.We then quantified the practical impact of voxel-scale clumping correction on BL LAD retrieval using simulated TLS point clouds. LAD was estimated per voxel under two assumptions: (i) the conventional random-foliage case (CI = 1) and (ii) clumping-corrected inversion using CI_ref. Across all crown forms, LIAD variants, and voxel sizes, the CI = 1 assumption produced predominantly negative LAD errors relative to mesh-derived reference LAD, consistent with systematic underestimation when clumping is ignored. Incorporating CI_ref shifted LAD errors toward zero and improved agreement, evidenced by reduced bias and normalized RMSE. Improvements were most pronounced for planophile canopies, where directional foliage aggregation is strongest and for coarser voxel sizes (1.0–2.0 m), where greater within-voxel heterogeneity amplifies departures from random mixing, demonstrating that clumping-induced bias is strongly scale dependent.These results provide practical recommendations for 3D canopy modelling: specifically, that voxel-scale clumping correction becomes increasingly essential as voxel size increases, especially when within-voxel heterogeneity grows. The proposed CI_ref framework strengthens scale consistency between local canopy structure and voxel-based radiative transfer, enabling unbiased LAD retrievals and providing physically grounded labels for future deep learning model-based CI prediction from TLS point clouds.

Humans, who were once able to wait for news of loved ones for a long time, are now anxious to receive information within minutes and seconds. Technology may contribute to this change in human nature, as technology and social media have become an integral part of human life. While their appropriate use can certainly be beneficial, studies and research indicate that excessive and inappropriate use has brought disadvantages to many aspects of human life. Excessive use has not only led to a kind of addiction in many people but has also unnaturally altered human behavior. Is it possible that technology and social media are causing a decline not only in human behavior but also in patience and overall human capability? The main objective of this article is to analyze the changes in human behavior and their effects caused by mobile phones and social media, and to provide suggestions on focusing on their proper use. The article is based on facts obtained from the study and review of secondary materials. Although this explanatory and analytical article has been prepared using this methodology, it does not include facts and data from primary sources. It is believed that the article will be useful for those interested in the use of mobile phones and social media and their effects.

Chinese pangolin (Manis pentadactyla Linnaeus, 1758) is a nocturnal, solitary, and highly threatened mammal belonging to the order Pholidota and family Manidae. This study assessed habitat preference, distribution, and major threats to the Chinese pangolin in the Terai and Chure community forests of Morang District, eastern Nepal, to support evidence-based conservation strategies. Field surveys were conducted using a block transect method (900 × 500 m²) whenever burrows or indirect signs were detected. Within each block, a 900 m central transect was established, and five 100 × 100 m² plots were laid at 100 m intervals to record habitat variables. A total of 104 burrows were documented, with 25 located in the Terai and 79 in the Chure region, indicating greater occurrence in the Chure forests. The species showed a clear preference for Shorea robusta-dominated forests. Burrows were frequently associated with specific herb and shrub species and were recorded at elevations ranging from 150 to 1200 m, with the highest density between 600–900 m. Pangolin burrows were most commonly found on slopes of 25°–50°, in areas with moderate canopy cover (25–50%), and predominantly in yellow soil. Ground cover was generally sparse (0–25%). Aspect analysis showed that burrows mainly faced northeast in the Terai and east to southeast in the Chure region. Burrow density decreased with increasing distance from water sources, highlighting the importance of water availability in habitat selection. Conversely, burrow occurrence increased with distance from roads and settlements, indicating sensitivity to anthropogenic disturbance. Interviews and field observations identified illegal hunting, habitat fragmentation, mining activities, and deforestation as major threats to the species in the study area. These findings provide quantitative evidence of habitat preferences and human-induced pressures affecting Chinese pangolins in Morang District. Strengthening law enforcement, promoting community awareness, and implementing sustainable forest management practices are essential to ensure long-term conservation of this critically endangered species.

Background Access to adequate sanitation and hygiene is an important global health issue and remains a serious problem in Nepal. Objective This study aimed to apply the alliance model to manage a sanitation and hygiene project. The project sought to increase sanitation access and improve households’ basic knowledge of sanitation and hygiene, as well as the hygiene practices of household members, in Dhading District, a remote area of Nepal. Methods A mixed-method design was applied for data collection. The study sample included 18 alliance members and 492 household respondents. The alliance model consisted of three steps: (1) Preparation, including a situation assessment, formation of the alliance, and baseline measurement of study variables; (2) Action research using a one-group pre-test–post-test design to strengthen the management capacity of alliance members through planning, implementation, and evaluation of the sanitation and hygiene project; and (3) Reinforcement of capacity strengthening through a one-day review and reflection workshop with key alliance members and a final evaluation of post-alliance outcomes. Results Six months after implementing the model, the overall management capacity of alliance members increased significantly ( p < 0.001). Households’ access to sanitation, basic knowledge of sanitation and hygiene, and hygiene practices also increased significantly ( p < 0.001). The prevalence of diarrhea in the project area significantly decreased ( p < 0.05) nine months after implementing the model. Discussion The model addressed key management issues within the alliance, fostered collaboration among major stakeholders, established a clear goal and action plan, mobilized resources, and secured the active participation of local residents in improving sanitation and hygiene in the Village Development Committee. Conclusions The model can be applied to strengthen alliance members' management capacity, thereby improving the effectiveness of rural sanitation and hygiene practices.

Cloud computing is currently playing an essential role in supporting emerging sectors such as smart energy, intelligent transportation, and large-scale distributed systems. The scalability and adaptability features of cloud computing are efficiently enable resource utilization and continuous data exchange in dynamic and heterogeneous environments. However, the increasing demand for cloud services has raised the energy consumption of cloud data centers, which has a critical environmental impact. Therefore, sustainable resource management tactics have become crucial in today's world. Dynamic Virtual Machine (VM) consolidation is one of the major tactics for sustainable resource management in the green cloud computing environment. Herein, a novel dynamic Energy-Aware Cosine Similarity Learning Network (ECSLN) is proposed to predict the overutilized host. Further, an Impact Factor-Based VM Selection (IFBVMS) method is proposed to select VMs for migration, and an ECSLN-Packed Placement method for VM placement into hosts. The main aim of the proposed VM consolidation is to maximize energy efficiency while preserving compliance with Service Level Agreements (SLAs) for sustainable environments. The experimental evaluation using real-world traces like PlanetLab, Bitbrains, and Alibaba Cluster 2020 workload validates that the proposed VM consolidation methods significantly reduce energy consumption and SLA violation compared to the existing methods for sustainable environments. The evaluation shows that the proposed ECSLN-based consolidation framework enables green cloud infrastructure by intelligently balancing energy consumption, SLA violation, and performance of cloud data centers.

Sustainable Development Goal (SDG) Target 3.d focuses on measuring a country’s strengthening of self-contained early warning, risk assessment and management, and health risk reduction through core International Health Regulations (IHR). IHR is an instrument of international law, adopted pursuant to Article 21 of the World Health Organisation (WHO) Constitution, and is legally binding on 196 States Parties, including all 194 Member States of WHO. This paper examines how Nepal endeavours to achieve this target in the context of the country’s transition to a federal governance system. A performance audit was conducted, utilising data from secondary sources (2016 onwards), including government publications, reports from international agencies, and peer-reviewed academic articles. A specific case study on the response to COVID-19 was included. Analysis was conducted in accordance with the International Organisation of Supreme Audit Institutions (INTOSAI) guidelines for self-contained report evaluations, focusing on possible divergence and convergence, the Leave No One Behind (LNOB) principles, cross-domain considerations, and structural finance. Progress is undermined by a controlled information vacuum. Since the last IHR was issued in 2015, the country has been in a state of stagnation, albeit self-sustaining. Although the country has a constitutional basis for health, policy and implementation levels are characterised by widespread vertical and horizontal misunderstandings among federal, provincial, and local governments. The COVID-19 response relegated the issue of ‘proliferated temporary control mechanisms’ or missing rational command systems. Financial analysis showed what appeared to be “firefighting” models, which allocated declining investments to the core preparedness functions like epidemic control, which fell to 2% of the federal health budget in 2021/22, and spending for COVID-19 emergencies, which constituted 36% of the federal health budget in 2021/22. The overarching Target 3.d monitoring and evaluation mechanisms were weak and lacked specified operations for subnational units. The systemic governance and financing issues inherent to transition federalism, which are inescapable for Nepal, pose acute challenges to achieving SDG Target 3.d by 2030. Scaling the governance system while strengthening IHR financing and core systems, and monitoring discretion through proactive mechanisms, is imperative for the resilience of the National Public Health System.

Groundwater plays a vital role in sustaining agriculture, domestic supply, and ecological balance in Nepal’s mid‑hill regions, where surface water availability is highly seasonal. This study assesses groundwater potential in part of Kavrepalanchowk District using the Cosine Amplitude Method (CAM), a statistical approach that integrates multiple thematic layers to delineate potential zones. In this study, multiple thematic layers such as elevation, slope, aspect, curvature, topographic position index (TPI), topographic wetness index (TWI), drainage density, geology and lineament density, were weighted and combined within a GIS framework to delineate groundwater potential map. The resulting map classified the area into five distinct groundwater potential zones: very low, low, moderate, high, and very high. Among the controlling parameters, lineament density (15.8%) and the Topographic Wetness Index (14.4%) were the most influential parameters, underscoring the critical role of structural features and surface saturation in groundwater occurrence. Other factors such as aspect, drainage density, and elevation contributed significantly, while geology and curvature exhibited comparatively lower influence. These findings demonstrate that geomorphological and hydrological factors exert greater control over groundwater potential than lithological characteristics in the study area. The outcomes provide a scientific basis for prioritizing recharge interventions and developing effective groundwater management strategies.