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Climate Change and Its Adverse Impacts on Plant Growth in South Asia:Current Status and Upcoming Challenges

Phyton-International Journal of Experimental Botany 2022年第4期91卷 695-711页

作者： Mohammad Saidur Rhaman Tahjib-ul-Arif Mohammad Golam Kibria Anamul hoque Department of Seed Science and Technology Bangladesh Agricultural UniversityMymensingh2202Bangladesh Department of Biochemistry and Molecular Biology Bangladesh Agricultural UniversityMymensingh2202Bangladesh Department of Soil Science Bangladesh Agricultural UniversityMymensingh2202Bangladesh

Socioeconomic development,adaptive capacity of the population,and demographic conditions across the states of South Asia make it more vulnerable to climate *** Asia is daily going to be more vulnerable to climate change and climatic *** region is facing multiple challenges in terms of climate change,dilapidation of ecosystems,and food *** is the primary determining factor for agricultural output,which unswervingly influences food production across the *** Asia is mainly an agricultural foundation based region and thus the economy of these regions directly depends on agriculture and agricultural *** to the extensive dependence on natural assets for thriving,it makes the people of this region more vulnerable to climate *** region is now under serious risk from sea-level rising and growing incidences of extreme events such as flash floods,enhanced temperature,drought,salinity,cyclones,storms,landslides,and irregularity of *** abiotic stresses continuously disturb plant growth and *** is now the time to take urgent action on these issues towards a sustainable,inclusive and resource efficient way to overcome *** this review,we summarize the overall situation of climate change in the South Asian countries and their adverse consequences on plants,and upcoming challenges towards a sustainable production.

关键词： Climate change South Asia plant growth abiotic stress food security

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The Influence of Elimination of Roving Frame on Ring Spun Cotton Yarn Characteristics

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World Journal of Engineering and Technology 2023年第1期11卷 10-19页

作者： Md. Ikramul Islam Sadikur Rahman Mohammad Mohsin ul hoque Department of Textile Engineering National Institute of Textile Engineering and Research Dhaka Bangladesh

Generally, ring spun yarns are manufactured from roving which is produced by roving frame. In this paper, an experiment has been done producing ring spun cotton yarn directly from finisher drawn sliver eliminating the roving frame. Total 3 types of yarn with the various linear density of 8 Ne, 10 Ne & 12 Ne were produced using a roving frame and without using a roving frame. In the next step, physical and mechanical properties of those yarns including unevenness, imperfections, hairiness & tenacity were investigated. The result showed that ring spun cotton yarns produced from sliver exhibited inferior physical and mechanical properties compared with samples from the conventional ring spinning system.

关键词： Roving Frame Linear Density Physical and Mechanical Properties Ring Spun Yarn Cotton Yarn

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Prediction of Strength Properties of Soft Soil Considering Simple Soil Parameters

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Open Journal of Civil Engineering 2023年第3期13卷 479-496页

作者： Md. Janibul hoque Md. Bayezid Ahnaf Rafi Sharan Mozaher ul Kabir Tahsin Tareque Department of Civil and Environment Engineering Islamic University of Technology Gazipur Bangladesh

Cohesion is an important soil strength parameter for the overall structure and quality of building foundations as well as slope stability. For a civil engineering project, cohesion (c) can be determined directly from mainly unconfined compression tests, direct shear tests, and triaxial tests of soil. However, it’s quite challenging to collect soil samples as there are time and cost constraints, as well as a diversity of soil deposits. Hence, this research aims to demonstrate a simplified method in order to determine the strength parameter of cohesive soil. Here, we propose an alternative solution adopting statistical correlations and machine learning techniques to establish correlations between the liquid limit, plastic limit, moisture content and %fine of soil with the strength parameter. In laboratory testing, these parameters can be obtained easily and these tests are relatively simple, quick to perform and also comparatively inexpensive. Hence, several test results were used from 100 boreholes which were soft soil or silty clay-type soil. Using the collected in-situ and lab test results of soil samples, a Multiple Linear Regression (MLR), Random Forest Regression (RFR) and Machine Learning (ML) model will be developed to establish a relationship between cohesion and the available test results. In order to assess the performances of both models, several performance indicators like: correlation coefficient (R2), mean squared error (MSE), root mean square error (RMSE), and mean average error (MAE) will be used. These correlation coefficients will be used to demonstrate the prediction capacity and accuracy of both models. It should be noted that this approach will substitute the conventional testing required for strength parameters, which is both expensive and time-consuming.

关键词： Cohesion MLR RFR ML MSE RMSE MAE

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