The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the R0 value from time to time, hoping that the virus will vanish one day.
The aim of the research is to measure the efficiency of the companies in the industrial sector listed in the Iraqi Stock Exchange , by directing these companies to their resources (inputs) towards achieving the greatest possible returns (outputs) or reduce those resources while maintaining the level of returns to achieve the efficiency of these companies, therefore, in order to achieve the objectives of the research, it was used (Demerjian.et.al) model to measure the efficiency of companies and the factors influencing them. The researchers had got a number of conclusions , in which the most important of them is that 66.6% of the companies in the research sample do no
... Show MoreFlexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy
... Show MoreThe root lesion nematode, Pratylenchus neglectus, is one of the most damaging nematodes to affect wheat worldwide. The nematode is widely distributed in Montana, primarily affecting winter wheat within the state. Managing the nematode primarily involves rotation to resistant and moderately resistant crops (peas, lentils, and barley). A nematode survey was conducted across the state nearly 10 years after an initial survey, to reassess the nematode threat and assess the impact of changing trends in crop rotations. To assess the broad applicability of rotation crops to control P. neglectus across Montana, greenhouse trials were conducted to challenge rotational crops using eight populations of P. neglectus collected from geographicall
... Show MoreThe preparation of the title compound, C26H25N, was achieved by the condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 molar ratio. There are two crystallographically independent molecules in the asymmetric unit. The two cyclohexyl rings adopt an
Coronavirus 2019 (COVID-19) pandemic led to a massive global socio-economic tragedy that has impacted the ecosystem. This paper aims to contextualize urban and rural environmental situations during the COVID-19 pandemic in the Middle East and North Africa (MENA) Region.
An online survey was conducted, 6770 participants were included in the final analysis, and 64% were females. The majority of the participants were urban citizens (74%). Over 50% of the urban residents significantly (
In current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi
... Show MoreA seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus
... Show MoreAuthentic materials are the most important tools that the teacher could use in class in order to make teaching go smoothly and effectively in transmitting the necessary knowledge to all students. This research has investigated experimentally the effect of using authentic materials in teaching English as a foreign Language, because a number of studies point out that the use of authentic materials is regarded a useful means to motivate learners, arouse their interest and expose them to the real language they will face in real life situations.
It is hypothesis that there is no statistical significance difference between the experimental group who taught English as a foreign language by using the authentic materials with those
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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