The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA molecule. A sequence DL model based on a bidirectional gated recurrent unit (GRU) is implemented. The model is applied to the Stanford COVID-19 mRNA vaccine dataset to predict the mRNA sequences deterioration by predicting five reactivity values for every base in the sequence, namely reactivity values, deterioration rates at high pH, at high temperature, at high pH with Magnesium, and at high temperature with Magnesium. The Stanford COVID-19 mRNA vaccine dataset is split into the training set, validation set, and test set. The bidirectional GRU model minimizes the mean column wise root mean squared error (MCRMSE) of deterioration rates at each base of the mRNA sequence molecule with a value of 0.32086 for the test set which outperformed the winning models with a margin of (0.02112). This study would help other researchers better understand how to forecast mRNA sequence molecule properties to develop a stable COVID-19 vaccine.
Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreWe know that the experiments which conducted by latin square in one location or in one period (season), but there are many cases that need to conduct the same experiments in many locations or in many periods (seasons) to study the interaction between the treatments and locations or between the treatments and periods (seasons) .In this research we present an idea for conduct the experiment in several locations and in many period (seasons) by using LSD , it represent acontribution in the area of design and analysis of experiments ,we had written. we had written (theoretically) the general plans, the mathematical models for these experiments, and finding the derivations of EMS for each component (
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The study aims to build a training program based on the Connectivism Theory to develop e-learning competencies for Islamic education teachers in the Governorate of Dhofar, as well as to identify its effectiveness. The study sample consisted of (30) Islamic education teachers to implement the training program, they were randomly selected. The study used the descriptive approach to determine the electronic competencies and build the training program, and the quasi-experimental approach to determine the effectiveness of the program. The study tools were the cognitive achievement test and the observation card, which were applied before and after. The study found that the effectiveness of the training program
... Show MoreIt has been shown in ionospheric research that calculation of the total electron content (TEC) is an important factor in global navigation system. In this study, TEC calculation was performed over Baghdad city, Iraq, using a combination of two numerical methods called composite Simpson and composite Trapezoidal methods. TEC was calculated using the line integral of the electron density derived from the International reference ionosphere IRI2012 and NeQuick2 models from 70 to 2000 km above the earth surface. The hour of the day and the day number of the year, R12, were chosen as inputs for the calculation techniques to take into account latitudinal, diurnal and seasonal variation of TEC. The results of latitudinal variation of TE
... Show MoreThe present study has three objectives: 1) to investigate the prevalence of complex nominals in economic discourse represented via the selected business news texts, 2) to shed some light on the most common translation errors made by second year students in the Department of Translation in rendering complex nominals into Arabic, and 3) to detect the possible causes behind such translation errors and suggest some translation tips which might sound helpful to the students of translation to find the most suitable translation equivalent. The present study is based on an empirical survey in which a selective analysis of someeconomic texts represented in business news texts is made. A corpus of 159 complex nominals was selected from seven busin
... Show MoreThis research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
... Show MoreThe paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie
... Show MoreAbstract The painful history of slavery has profoundly affected the identities and social interactions of Afro-Caribbean migrants, whose descendants continue to contend with prejudice and socio-economic marginalization. Andrea Levy's semi-autobiographical novel, The Long Song (2010), traces the turbulent history of Jamaica in the nineteenth century through the lens of Miss Kitty, a character based on Levy's great-great-great grandmother, who was born a slave on the plantation Amity in Saint Catherine's parish. The narrative blends the historical with the fictional and depicts various environmental contexts, inscribed meanings, and human exchanges, including the prominence of social situations perceived through race and class tensions ironic
... Show MoreGoal of research is to investigate the impact of the use of effective learning model in the collection of the fourth grade students/Department of physics in the material educational methods and the development of critical thinking .to teach this goal has been formulated hypothesis cefereeten zero subsidiary of the second hypothesis .To investigate the research hypothesis were selected sample of fourth-grade students of the department of physics at the univers
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