Polytechnical University of Kabul

This research analyzed how Afghan EFL learners vary in or align with language learning strategies (LLS) by gender. The study addressed 140 undergraduate students majoring in English language and literature at Parwan University, distributed equally between 70 male and 70 female participants. Data were obtained using two tools: a demographic survey and Oxford’s Strategy Inventory for Language Learning (SILL). An independent samples t-test was implemented to compare the average strategy use of male and female students in terms of their inclinations and adoption of LLS. The results revealed that Afghan EFL students are moderately engaged in language learning strategies. Across the different categories, compensation and metacognitive strategies were used predominantly. On the other hand, cognitive and memory strategies were less commonly adopted among Afghan EFL learners. Furthermore, quantitative analysis indicated no meaningful gender-based contrasts in the overall implementation of LLS.

The scaling effect of machines from kW to MW greatly affects electromagnetic performance and needs to be investigated for different machines. Therefore, this paper presents a comprehensive comparative study on the intriguing electromagnetic performance of contra-rotating permanent-magnet vernier machines and dual-port, wound-field-excited, flux-switching machines at the MW power level for contra-rotating wind turbine applications. The analysis evaluates both machines across various slot/pole combinations while maintaining constant key design parameters. The electromagnetic performance analysis reveals that the permanent-magnet vernier machine (PMVM) exhibits superior torque and power, with minimal cogging torque compared to the wound-field flux-switching machine (WFFSM). Conversely, the WFFSM outperforms the PMVM in terms of power factor and efficiency. This study provides valuable perspectives on the strengths and weaknesses of each machine, highlighting their potential for contra-rotating turbine and wind power generation. Finally, to justify the findings of the finite element analysis and the proof of concept, an experimental prototype is tested to validate the study.

Natural disasters are increasing in frequency and intensity, causing escalating humanitarian crises and complex housing challenges globally. Traditional post-disaster housing solutions often fall short, being slow, costly, and ill-adapted to specific community needs. This study addresses these limitations by proposing an innovative, technology-driven model for post-disaster housing that integrates parametric design with 3D printing. The objective is to develop a flexible and adaptable system capable of providing both immediate temporary shelter and evolving permanent housing solutions. In this study, the methodology of the proposed model for post-disaster housing solutions is structured around three main phases: the development of the theoretical framework, the parametric design process, and the implementation phase. In the first phase, a comprehensive literature review and conceptual analyses were conducted to examine the concept of disaster, post-disaster housing approaches, and advanced technologies, thereby establishing the conceptual foundation of the model. In the second phase, parametric modeling was carried out for a modular system using algorithmic design tools such as Grasshopper; the model’s applicability across various scales and its flexibility were analyzed. In the final phase, material selection and digital prototyping of the gridal system were undertaken using 3D printing technology to evaluate the model’s feasibility for rapid on-site production, assembly, and disassembly. The model prioritizes user participation, modularity, and configurability to ensure rapid response and socio-cultural sensitivity. Findings indicate that this integrated approach offers substantial benefits, including accelerated construction, reduced labor and material waste, enhanced design flexibility, and the use of local, sustainable materials. This research highlights the transformative potential of advanced manufacturing in providing resilient, user-centered, and environmentally sustainable post-disaster housing, advocating for governmental financial support to overcome adoption barriers and foster broader implementation.

ABSTRACT This research aims to expound a typology of room arrangements and analyse functions of each space in both traditional and modern houses and classify the gathering places in Herat Old City, Afghanistan. The research covers a literature review, spatial analysis of house plans, questionnaires, and plotting site maps in GIS using a field survey data. Ninety-two houses were randomly selected for measurements during field survey, followed by typological classification and feature analysis. Physical features of both traditional and modern houses using guest houses as a significant indicator were expounded, gathering places were categorized, and the correlation between built area and family size in traditional and modern houses were found. The typological analyses of the room arrangements indicate that the arrangement of rooms in the form of D.Hk-G.R.L.B/G.L-B-B (Dining.Haw-waaj Khana-Guest Room.Living.Bedroom/Guest.Living-Bedroom-Bedroom) is the most popular pattern in traditional houses with independent guest rooms, and D-L.D.B-B.S-B is the most common type in traditional houses with dependent guest houses. The study also found that there were four types of gathering places in the area: Takht inside a house, Center of Gozar outside the house, Mojtama gathering place, and courtyard of mosques.

Architecture studios are essential in teaching design skills. Exploring how different design methodologies impact student performance helps improve education, fostering creativity, critical thinking, and better learning outcomes in architecture programs. The objective of the research is to examine the impact of various design methodologies on student achievement in architecture studios, identifying effective teaching approaches that enhance creativity, critical thinking, and overall performance in architectural education. The research involved 526 architecture students as participants. Data were collected using structured surveys to identify design methodologies and academic performance records. The software IBM SPSS Statistics version 17.0 was used to perform these statistical analyses including correlation coefficients, multiple linear regressions (MLR), ANOVA and paired t-test to examine the relationship between teaching methodologies and student achievement, providing insights into their impact on performance. Examined five factors: collaborative learning, iterative processes, instructor feedback, problem-solving skills, and time management. These factors were analyzed to determine their influence on student creativity, critical thinking, and overall achievement in architecture studio projects. The outcomes revealed a significant positive correlation among specific design methodologies and student achievement. Collaborative and iterative approaches showed the strongest impact on creativity and performance. Collaborative and iterative methodologies significantly enhance student achievement, highlighting the importance of effective teaching strategies in architecture studios.

Emotion-Cause Pair Extraction (ECPE) aims to identify and extract emotion clauses and their corresponding cause clauses from unannotated emotional texts. Previous approaches primarily leveraged contextual features or attention weights as semantic information to enhance feature representations. However, these methods often overlook the additional causal information that external knowledge can bring to ECPE. Given the evident inferential relationship between emotions and their causes, we propose a novel model called Rhetorical Structure Theory and Inference-Aware Graph networks (RSTIAG) to address the challenges posed by ECPE. This model constructs a semantic dependency space grounded in discourse-level rhetorical structure theory and a symbolic reasoning space based on an inference-aware graph. By integrating the introduced knowledge through a space fusion co-attention mechanism and modeling the dependencies between these two spaces, the model enables clauses to simultaneously capture diverse knowledge from both spaces. Additionally, we enrich the information dimensions of emotion-cause pairs by instantiating the reasoning process from the perspectives of causality and implicit inference. To substantiate the effectiveness of our proposed RSTIAG model, we undertake comprehensive experiments. The results demonstrate that it significantly outperforms 11 baseline models on an English benchmark corpus, confirming its effectiveness.

Bronzes, as crucial cultural relics, face preservation challenges from chloride-induced corrosion. This study develops a composite inhibitor system using 2-acetylamino-5-mercapto-1,3,4-thiadiazole (AMT) and disodium ethylenediaminetetraacetate (EDTA) to protect corroded bronzes through surface passivation and structural optimization. The artificially corroded bronze (R0) has a loose and porous layer with main compositions of Cu2O and Cu2(OH)3Cl. The corroded bronzes after treated by single AMT inhibitor (R1) and AMT-EDTA composite inhibitors (R2) possess the flatter corrosion layers than R0. Furthermore, the chelation effect of EDTA removes unstable corrosion products on R2, creating a denser structure with lower roughness and weaker water-droplet wettability than R1. The denser layer reduces reactive areas for corrosive reactions on bronzes, and the weaker wettability can suppress the diffusion of corrosive mediums, endowing R2 with the optimal corrosion resistance. These findings advance understanding of bronze corrosion inhibition and provide a scientific basis for developing new protective agents.

Abstract Evaluating the concentration of waste discharge across an exponential stretching surface is crucial for its environmental impact. In both ecological and industrial networks, wastewater management is crucial. The present study focuses on the prevention and analysis of the contamination of fluid assets by harmful chemicals. By analyzing these interactions, the present study examines steady, incompressible Casson fluid circulation under the influence of waste discharge concentration via a three-dimensional exponentially stretching sheet. The influence of thermophoresis, Brownian motion, and magnetic field was also examined. Governing equations can be transformed into the form of ordinary differential equations by utilizing the proper similarity operations. These simplified equations are resolved computationally using Runge–Kutta–Felhberg-45 and the shooting approach. The impacts of dimensionless parameters on each person’s profile are being examined using graphs. Furthermore, certain essential engineering coefficients are being explored. The predominant results are that in both directions, the magnetic and Casson fluid decreases velocities. Buoyancy constraint will increase the velocity while thermophoresis and Brownian contribute to an increase in temperature. An 8.04% increase in temperature is seen for thermophoresis. Skin friction increases with a significant increase in magnetic and Casson parameters, where thermophoresis and local pollutant decreases the rate of mass transmission.