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| 1 | 感应磁场和变热导率对二级流体驻点流动的影响显示文摘本文研究变热导率和感应磁场冲击作用下具有线性拉伸特性的二级流体驻点输运问题。通过适当的变换,将非线性粒子微分方程组转化为常微分方程组。用最优同伦分析方法对所得方程进行求解。通过图解研究相关参数对表面摩擦系数、温度、感应磁场、速度和局部努塞尔数的影响。利用MATLAB软件中内置的bvp4c技术对得到的级数解进行收敛和残差处理。结果表明:随着磁场参数的增大,表面摩擦系数也随拉伸比的增大而增大。为验证结果的有效性,我们与文献进行对比,发现本研究与现有文献结果非常一致。 | A.A.KHAN S.ILYAS T.ABBAS R.ELLAHI | 2021 | Journal of Central South University2021，28，11： | 1 |
| 2 | Biochar Application Improves the Drought Tolerance in Maize Seedlings显示文摘Application of biochar to agricultural soils is mostly used to improve soil fertility.Experimental treatments were comprised of two factors:i)drought at two level,i.e.,80%and 40%water holding capacity(WHC)which was maintained on gravimetric basis ii)three levels of biochar i.e.,control,2 t ha^(-1) and 4 t ha^(-1) added to soil.Experimentation was done to examine potential of biochar application to enhance the growth attributes,water relations,photosynthetic pigments and antioxidants activities in maize(Zea mays L.)seedlings.Results of study revealed that biochar application increased the growth qualities(total seedlings biomass,dry weight of shoot and root,shoot length and root length).In addition;contents of photosynthetic pigments(chlorophyll a,b,a+b and a/b),water relation(relative water contents,turgor potential,osmotic potential and water potential)were improved significantly due to addition of biochar.Addition of 4 t ha^(-1) biochar led to significant rise activity of enzymatic antioxidant catalase(CAT),superoxide dismutase(SOD)and peroxidase(POD)in leaf of maize seedling sunder drought as well as well watered circumstances.However,biochar applied at the rate 4 t ha^(-1) improved the all the physiological and biochemical attributes in maize seedlings under drought.From the results it was concluded that biochar application is an efficient way to alleviate adverse effect of drought stress on maize.In drought prone areas,long term impacts of biochar on production of maize and properties of soil could be recommended as upcoming shove. | A.Sattar A.Sher M.Ijaz M.Irfan M.Butt T.Abbas S.Hussain A.Abbas M.S.Ullah M.A.Cheema | 2019 | Phyton-International Journal of Experimental Botany2019，88，4： | 0 |
| 3 | Magnetohydrodynamics hemodynamics hybrid nanofluid flow through inclined stenotic artery显示文摘The present study aims to perform computational simulations of twodimensional(2D)hemodynamics of unsteady blood flow via an inclined overlapping stenosed artery employing the Casson fluid model to discuss the hemorheological properties in the arterial region.A uniform magnetic field is applied to the blood flow in the radial direction as the magneto-hemodynamics effect is considered.The entropy generation is discussed using the second law of thermodynamics.The influence of different shape parameters is explored,which are assumed to have varied shapes(spherical,brick,cylindrical,platelet,and blade).The Crank-Nicolson scheme solves the equations and boundary conditions governing the flow.For a given critical height of the stenosis,the key hemodynamic variables such as velocity,wall shear stress(WSS),temperature,flow rate,and heat transfer coefficient are computed. | B.K.SHARMA R.GANDHI T.ABBAS M.M.BHATTI | 2023 | Applied Mathematics and Mechanics(English Edition)2023，44，3： | 0 |
| 4 | Machine learning enabled identification and real-time prediction of living plants’ stress using terahertz waves显示文摘Considering the ongoing climate transformations, the appropriate and reliable phenotyping information of plant leaves is quite significant for early detection of disease, yield improvement. In real-life digital agricultural environment, the real-time prediction and identification of living plants leaves has immensely grown in recent years. Hence, cost-effective and automated and timely detection of plans species is vital for sustainable agriculture. This paper presents a novel, non-invasive method aiming to establish a feasible, and viable technique for the precise identification and observation of altering behaviour of plants species at cellular level for four consecutive days by integrating machine learning (ML) and THz with a swissto12 materials characterization kit (MCK) in the frequency range of 0.75 to 1.1 THz. For this purpose, measurements observations data of seven various living plants leaves were determined and incorporate three different ML algorithms such as random forest (RF), support vector machine, (SVM), and K-nearest neighbour (KNN). The results demonstrated that RF exhibited higher accuracy of 98.87% followed by KNN and SVM with an accuracy of 94.64% and 89.67%, respectively, for precise detection of different leaves by observing their morphological features. In addition, RF outperformed other classifiers for determination of water-stressed leaves and having an accuracy of 99.42%. It is envisioned that proposed study can be proven beneficial and vital in digital agriculture technology for the timely detection of plants species to significantly help in mitigate yield and economic losses and improve crops quality. | Adnan Zahid Kia Dashtipour Hasan T.Abbas Ismail Ben Mabrouk Muath Al-Hasan Aifeng Ren Muhammad A.Imran Akram Alomainy Qammer H.Abbasi | 2022 | Defence Technology(防务技术)2022，18，8： | 0 |
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