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| 1 | Genetics of barley tiller and leaf development显示文摘In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960 s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture,focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2 D and 3 D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development,highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance. | Salar Shaaf Gianluca Bretani Abhisek Biswas Irene Maria Fontana Laura Rossini | 2019 | Journal of Integrative Plant Biology2019，61，3： | 3 |
| 2 | Air pollution and the housing market: A neural network approach显示文摘 | Mohamad Shaaf G. Rod Erfani | 1996 | International Advances in Economic Research1996，，4： | 1 |
| 3 | Respiratory tuberculosis in childhood:the diagnosis value of clinical features and special investigations显示文摘 | Beyers N Gie R P | 1995 | Pediatr Infect Dis J1995，14，： | 1 |
| 4 | A fast and easy method to derive highestresolution time-series datasets from drillcores and rock samples 显示文摘 | Shaaf M | 1994 | Sedimentary Geology1994，94，： | 1 |
| 5 | Detection of Left Ventricular Cavity from Cardiac MRI Images Using Faster R-CNN显示文摘The automatic localization of the left ventricle(LV)in short-axis magnetic resonance(MR)images is a required step to process cardiac images using convolutional neural networks for the extraction of a region of interest(ROI).The precise extraction of the LV’s ROI from cardiac MRI images is crucial for detecting heart disorders via cardiac segmentation or registration.Nevertheless,this task appears to be intricate due to the diversities in the size and shape of the LV and the scattering of surrounding tissues across different slices.Thus,this study proposed a region-based convolutional network(Faster R-CNN)for the LV localization from short-axis cardiac MRI images using a region proposal network(RPN)integrated with deep feature classification and regression.Themodel was trained using images with corresponding bounding boxes(labels)around the LV,and various experiments were applied to select the appropriate layers and set the suitable hyper-parameters.The experimental findings showthat the proposed modelwas adequate,with accuracy,precision,recall,and F1 score values of 0.91,0.94,0.95,and 0.95,respectively.This model also allows the cropping of the detected area of LV,which is vital in reducing the computational cost and time during segmentation and classification procedures.Therefore,itwould be an ideal model and clinically applicable for diagnosing cardiac diseases. | Zakarya Farea Shaaf Muhammad Mahadi Abdul Jamil Radzi Ambar Ahmed Abdu Alattab Anwar Ali Yahya Yousef Asiri | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 6 | Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique显示文摘Various data sets showing the prevalence of numerous viral diseases have demonstrated that the transmission is not truly homogeneous.Two examples are the spread of Spanish flu and COVID-19.The aimof this research is to develop a comprehensive nonlinear stochastic model having six cohorts relying on ordinary differential equations via piecewise fractional differential operators.Firstly,the strength number of the deterministic case is carried out.Then,for the stochastic model,we show that there is a critical number RS0 that can predict virus persistence and infection eradication.Because of the peculiarity of this notion,an interesting way to ensure the existence and uniqueness of the global positive solution characterized by the stochastic COVID-19 model is established by creating a sequence of appropriate Lyapunov candidates.Adetailed ergodic stationary distribution for the stochastic COVID-19 model is provided.Our findings demonstrate a piecewise numerical technique to generate simulation studies for these frameworks.The collected outcomes leave no doubt that this conception is a revolutionary doorway that will assist mankind in good perspective nature. | Yu-Ming Chu Sobia Sultana Saima Rashid Mohammed Shaaf Alharthi | 2023 | Computer Modeling in Engineering & Sciences2023，137，12： | 0 |
| 7 | A New Scheme of the ARA Transform for Solving Fractional-Order Waves-Like Equations Involving Variable Coefficients显示文摘The goal of this research is to develop a new,simplified analytical method known as the ARA-residue power series method for obtaining exact-approximate solutions employing Caputo type fractional partial differential equations(PDEs)with variable coefficient.ARA-transform is a robust and highly flexible generalization that unifies several existing transforms.The key concept behind this method is to create approximate series outcomes by implementing the ARA-transform and Taylor’s expansion.The process of finding approximations for dynamical fractional-order PDEs is challenging,but the ARA-residual power series technique magnifies this challenge by articulating the solution in a series pattern and then determining the series coefficients by employing the residual component and the limit at infinity concepts.This approach is effective and useful for solving a massive class of fractional-order PDEs.Five appealing implementations are taken into consideration to demonstrate the effectiveness of the projected technique in creating solitary series findings for the governing equations with variable coefficients.Additionally,several visualizations are drawn for different fractional-order values.Besides that,the estimated findings by the proposed technique are in close agreement with the exact outcomes.Finally,statistical analyses further validate the efficacy,dependability and steady interconnectivity of the suggested ARA-residue power series approach. | Yu-Ming Chu Sobia Sultana Shazia Karim Saima Rashid Mohammed Shaaf Alharthi | 2024 | Computer Modeling in Engineering & Sciences2024，138，1： | 0 |
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