Kabul University

Electrification is vital for economic growth, poverty reduction, and improved quality of life. Over 80% of Afghanistan's rural population lacks electricity. Despite increasing interest in decentralized energy systems, there remains a lack of site-specific studies that jointly assess the technical, economic, and policy feasibility of decentralized solar PV for rural electrification in Afghanistan. This study addresses that gap through a mixed-method case study of Syahgel, Ghazni, combining a household survey of 30 households, PVsyst-based system sizing, economic evaluation, and policy analysis. The study compares multi-tier Solar Home Systems (SHSs) with a community microgrid under local demand and affordability conditions. The results show that SHSs, with entry-level costs starting from USD 95, are more suitable for small, dispersed settlements, while microgrids remain relevant for larger or more concentrated communities. Financing mechanisms, including subsidies and interest-free loans, can improve affordability by up to 75%, while electrification can reduce annual fuelwood expenditure by approximately USD 51.5 per household and generate broader health, educational, and livelihood benefits. The findings highlight the need for integrated policy reform, targeted financial support, and context-sensitive system design to support sustainable and inclusive rural electrification in Afghanistan.

Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multi-level governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.

Parabolic trough solar collectors (PTSCs) are a mature concentrating solar technology, but their performance is limited by solar intermittency. Integration with phase change materials (PCMs) can mitigate this limitation, yet conventional PCMs suffer from low thermal conductivity. Nano-enhanced PCMs (NePCMs) offer improved heat transfer, but most existing studies rely on simplified transient models and lack comprehensive annual performance assessment under realistic climatic conditions. To address this gap, this study develops a fully transient optical–thermal–phase-change model to investigate the annual performance of a PTSC integrated with NePCM. The coupled governing equations are discretized using a semi-implicit finite-difference scheme, while the melting and solidification processes are captured via a Stefan moving-boundary formulation and solved iteratively using a Gauss–Seidel algorithm. Hourly climatic data for Yazd (8760 h) are applied to resolve seasonal and diurnal variations. The results show that adding aluminum oxide (Al 2 O 3 ) nanoparticles significantly enhances system performance: at 1 wt% concentration, the annual thermal efficiency increases by 10% (to 52%) compared to pure paraffin, and the annual exergy efficiency reaches 31% (an improvement of 15% over the baseline). Monthly useful energy output rises to 440 kWh, and the levelized cost of heat is reduced to 0.085 $/kWh th , yielding the minimum payback period of about 5.2 years. Although the 3 wt% case achieves the highest instantaneous and monthly energy output (up to 470 kWh/month) and Carbon Dioxide (CO 2 ) avoidance (peaking at 120 kg/month), its economic performance deteriorates due to higher material costs. Overall, the results demonstrate that a 1 wt% nanoparticle loading offers the most favorable balance between thermodynamic performance, environmental benefit, and economic feasibility.

Biochar yield prediction plays a critical role in optimizing pyrolysis processes and advancing sustainable biomass utilization. This study introduces a hybrid machine learning framework that integrates Decision Tree models with four optimization strategies including Tabu Search, Ant Colony Optimization, Evolutionary Strategies, and Batch Bayesian Optimization (DT-BBO). A curated dataset of 211 samples was preprocessed using Leverage outlier detection and normalization to ensure model robustness. Among all tested models, the DT-BBO approach achieved the highest accuracy, with an R2 of 0.98, an MSE of 1.9, and an AARE% of 2.2%, outperforming the other optimization techniques. SHAP analysis revealed that pyrolysis temperature, residence time, and ash content were the most influential parameters governing biochar yield. Comparative benchmarking against previously published models confirmed the superior predictive capability and stability of the proposed framework. The results demonstrate that the DT-BBO model offers a scalable, interpretable, and high-performing solution for biochar yield prediction, contributing to methodological innovation and sustainable biomass valorization.

The gut microbiome has become a primary controller of host immunity as well as the pathogenesis of human immunodeficiency virus (HIV) infection. Commensal microbes in healthy persons keep the intestinal and other body barriers intact and regulate mucosal and systemic immune responses and generate metabolites, including short-chain fatty acids and indole derivatives that suppress inflammation and stimulate epithelial healing. These functions are impaired by HIV infection via depletion of gut CD4 + T cells, damage caused to epithelium, microbial translocation, and microbiota disruption. In this review article, we summarize recent studies suggesting that a balanced microbiome can mitigate HIV susceptibility and progression by preserving mucosal defenses, limiting systemic immune activation, and generating antiviral compounds. Other interventions, including probiotics, prebiotics, dietary modulation, and fecal microbiota transplantation (FMT), have been trialed with mixed outcomes in most cases, showing small but significant changes in the gut microbial composition and/or inflammatory markers. Current evidence highlights the potential of microbiome-targeted strategies to support HIV management; however, substantial gaps remain. Future research should focus on defining protective microbial signatures, developing next-generation live biotherapeutics, exploring metabolite-based therapies, and conducting large, mechanistically driven clinical trials. Harnessing the microbiome’s protective functions could offer novel approaches to reducing HIV transmission, mitigating inflammation, and improving immune reconstitution in infected individuals.