Ghazni University

The present study was conducted in 2023 to evaluate the effect of nitrogen and potassium on the growth and yield of chili crop through a randomized completely block design with three replications. The experimental design contained twelve treatment combinations, namely, four nitrogen doses (0, 45, 90, and 135 kg/ha) and three potassium dosages (0, 25, and 50 kg/ha as basal). Nitrogen was applied in two splits (transplanting and first picking) at a dose of 45 kg/ha, and in three splits (transplanting, first, and third picking) at doses of 90 and 135 kg/ha. Compared to the other nitrogen rates, 135 kg/ha of nitrogen produced superior growth and yield-contributing parameters such as plant height (81.4 cm), number of branches per plant (4.80), number of leaves per plant (37.22), leaf area index (1.404), fruit length (6.20 cm), fruit diameter (0.64 cm), number of fruits per plant (70.2), average fruit weight (2.8 g), and weight of fruit per plant (201.0 g). With respect to potassium, the application of 50 kg K2O ha-1 produced comparatively higher plant growth parameters, including plant height (78.8 cm), number of branches per plant (4.77), number of leaves per plant (36.25), leaf area index (1.375), fruit length (5.88 cm), fruit diameter (0.60 cm), number of fruits per plant (68.0), average fruit weight (2.8 g), and fruit weight per plant (188.8 g). In addition, the application of 135 kg of N/ha and 50 kg of K2O/ha in chili resulted in increased production of green and red ripe fruits, which were 11.07 tons/ha and 10.71 tons/ha, respectively. In conclusion, the study recommends applying 135 kg of nitrogen in three splits and 50 kg of K2O at base application per hectare for chili production in Ghazin province.

Accurate prediction of peak ground acceleration (PGA) is crucial for seismic hazard assessment and earthquake-resistant design.Traditional regression-based ground motion prediction equations often fall short in capturing the complex, nonlinear interactions among earthquake parameters. This study proposes a machine learning approach using a random forest (RF) model to predict PGA based on five key input variables: moment magnitude (Mw), closest distance to the rupture plane (ClstD), hypocentral depth, rake angle, and average shear wave velocity in the top 30 meters (Vs30). A comprehensive dataset of 16,211 ground motion records from the Pacific Earthquake Engineering Research Center (PEER), Updated NGA-WEST2 Flatfile was used. The RF model was optimized through Grid Search and 5-fold cross-validation, achieving high predictive performance with R² scores of 0.948 on training data and 0.928 on test data. Feature importance analysis indicated Mw and ClstD as the most influential parameters. The study demonstrates the robustness, accuracy, and generalization capability of the RF model, confirming its potential as a valuable tool in seismic risk analysis and providing a foundation for future development of more adaptable, data-driven models in earthquake engineering. Received: 24 July 2025 | Revised: 25 November 2025 | Accepted: 5 December 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Asadullah Ziar: Conceptualization, Methodology, Software, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Project administration. Ender Basari: Conceptualization, Validation, Writing - review & editing, Supervision.

Climate change has intensified environmental challenges globally, with greenhouse gas emissions rising more rapidly in Organization of Islamic Cooperation (OIC) countries than the global average. Over half of the OIC member states face high climate vulnerability due to limited institutional and technological capacity for mitigation and adaptation. This study makes a novel contribution by analyzing the drivers of environmental quality in 36 OIC countries from 1996 to 2020 using the load capacity factor (LCF), a holistic indicator that balances ecological demand and biocapacity supply. Unlike prior studies that focus narrowly on CO₂ emissions, LCF provides a broader measure of sustainability. The analysis is stratified by income levels (high, upper-middle, and lower-middle income) to uncover income-specific dynamics. The CS-ARDL approach was employed to estimate both short- and long-run relationships. The findings reveal that economic expansion improves environmental quality in high-income but degrades it in upper- and lower-middle-income groups. Renewable energy consumption consistently enhances environmental sustainability across all income groups, while natural resource dependence undermines it. Economic globalization improves environmental quality in high-income but has adverse effects in middle-income economies. Notably, the rule of law emerges as a strong and consistent driver of environmental improvement across all groups. These findings underscore the need for income-specific strategies that prioritize renewable energy investment, promote sustainable natural resource management, strengthen institutional quality, and integrate environmental objectives into globalization and trade policies.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-16872-y.

کیفیت سبک تدریس و تطبیق آن با سبک‌های یادگیری در محیط یادگیری نقش بسزایی در فرایند یاددهی- یادگیری. پس این تحقیق، به هدف بررسی سبک‌های تدریس اساتید پوهنتون غور انجام شده است. از روش توصیفی- تحلیلی استفاده گردیده. جامعه آماری این تحقیق ۱۰۰ نفر استادان پوهنتون غور می‌باشد. از پرسشنامه سبک‌های تدریس گراشاد(۲۰۰۲) استفاده شده است. یافته‌ها نشان می‌دهد که سبک تخصصی با میانگین ۳۴.۱۰ در پوهنځی زراعت و سبک تسهیل گری با میانگین۳۳.۵۰ در پوهنځی شرعیات، سبک تدریس تعاملی با میانگین ۳۳.۵۵ در پوهنځی تعلیم وتربیه و در نهایت سبک تخصصی با میانگین ۳۳.۴۰ در پوهنځی کمپیوتر ساینس غالب بوده است. و همچنان رابطه بین سبک تدریس استادان و رتبه علمی در سطح معناداری (p<0.001 )، رابطه بین سبک تدریس و درجه تحصیلی در سطح معناداری (p<0,001) رابطه معنادار بدست آمده است. برمبنایی نتایج، سبک تخصصی در پوهنځی زراعت و کمپیوتر ساینس، سبک تسهیل‌گری در پوهنځی شرعیات و سبک تعاملی در پوهنځی تعلیم وتربیه سبک غالب اعلان می‌شود.

Cooperative Learning as a student-centered approach to learning has powerfully influenced language learning since 1970s. The Jigsaw strategy which is one of the widely used cooperative-based instructional methods has been highly effective in improving students’ academic performance, particularly in reading comprehension. This study was conducted to find the effect of jigsaw on Afghan EFL learners’ reading comprehension and explore their perceptions towards it. The study used one-group pre/post-test experimental design. Participants (N = 20), selected non-randomly, were intermediate EFL learners from a Private Language Learning Institute in Ghazni, Afghanistan. Prior to the study, a pre comprehension test was administered. Students then were engaged in jigsaw activity for eight weeks, and finally sat for a post comprehension test. Comparing the means of two tests, it was found that the jigsaw intervention significantly improved the participants’ reading comprehension by the mean difference of 2.20. A paired sample t-test was further conducted, results of which indicated statistically significant difference in participants’ performance after engaging in jigsaw as the t-value was quite large (6.18) and the p-value was low (<0.001). In addition, a Cohen’s d effect size was calculated to understand the practical significance of the findings. The effect size was very large (1.38), indicating that the improvement was also practically meaningful.

This research delves into the intriguing dynamics of a magneto-Sisko fluid within a two-dimensional realm, shaped by the influence of a nonlinearly stretchable sheet nestled in a porous medium. The investigation embraces the impacts of a steady magnetic field, thermal radiation, and heat generation, while artfully weaving in the phenomena of Brownian motion and thermophoresis diffusion. By applying a similarity transformation, the governing nonlinear partial differential equations morph into ordinary differential equations, which are deftly tackled using the Newton–Raphson shooting method in tandem with the Runge–Kutta–Fehlberg algorithm. The outcomes indicate that an increase in the Sisko fluid parameter amplifies velocity profiles, concurrently diminishing both temperature and concentration distributions. For example, elevating the Sisko parameter from 1.0 to 2.0 propels the velocity profile upward by approximately 20%, while the temperature and concentration profiles witness reductions of 10% and 8%, respectively. Moreover, escalating values of the power-law exponent and the nonlinear stretching coefficient contribute to a decline in velocity, temperature, and concentration. In particular, when the power-law index ascends from 1.2 to 1.8, the velocity experiences a decrease of 14%, and temperature and concentration diminish by 12% and 5%, respectively. The introduction of thermal radiation enhances the temperature profile by nearly 20%, underscoring its pivotal role in the transport of energy. These results resonate with prior research, highlighting the intricate dance of magnetic fields, viscosity fluctuations, and heat diffusion mechanisms in shaping the fluid’s behavior. The findings furnish invaluable perspectives for refining industrial applications such as polymer extrusion, metallurgical endeavors, and chemical engineering systems.

Deforestation exerts profound ramifications on soil quality and biodiversity, thereby exerting substantial economic repercussions. The depletion of organic matter and structural integrity of soil following tree removal for agricultural purposes underscores the severity of this issue. In elucidating the soil pollution stemming from deforestation, this research employs a sophisticated five-compartment SDIFR model integrating fractal dimension and fractional order dynamics. The rigorous analysis, including the application of Picard Lindelof’s fixed point theorem, establishes the existence and uniqueness of explicit solutions. Furthermore, the examination of local and global stability sheds light on the system’s behavior, delineating between pollution-free equilibrium and pollution-extinct equilibrium states. To regulate system behavior, an adaptive control framework grounded in fractal fractional order is proposed, leveraging the Adams-Bashforth numerical approximation scheme for implementation. Through numerical simulations, the study underscores the pivotal role of parameters, thus substantiating the significance of the proposed model in comprehensively addressing the complexities of soil pollution induced by deforestation.

Environmental challenges have intensified as a result of global warming and climate change, creating significant threats to environmental quality. The member nations of the Organization of Turkic States (OTS) are especially impacted by these issues, primarily because of their reliance on fossil fuels, leading to elevated carbon emissions. This study examines the influence of natural resources, renewable energy, technological innovation, and globalization on environmental degradation in five OTS member countries—Azerbaijan, Kazakhstan, Kyrgyzstan, Türkiye, and Uzbekistan—covering the years 1996 to 2020. The ecological footprint and CO2 emissions are employed as the main indicators of environmental harm. Through the application of the Method of Moments Quantile Regression (MMQR), the findings reveal that natural resources significantly contribute to CO2 emissions in the lower quantiles but show a lesser impact on the ecological footprint. Conversely, renewable energy consistently improves environmental quality across all quantiles, whereas technological innovation and globalization are both associated with increased environmental degradation. Additionally, the causality test reveals a bidirectional causality between renewable energy consumption and both CO2 emissions and the ecological footprint (EF), as well as between technological innovation and EF. Moreover, a unidirectional causal relationship is observed from globalization to EF. Based on the findings, policy recommendations for OTS member states include promoting the adoption of renewable energy, fostering green technological innovations, and addressing the negative environmental effects of globalization. Such measures are vital for achieving the Sustainable Development Goals and ensuring long-term environmental sustainability.