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"Abdullah, M."
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Engineering statics
\"Engineering statics presents the cutting-edge topics in engineering statics, focusing on practical applications knowledge, with numerous real-world examples, practice problems, and case studies throughout. It covers theory concisely and uses plain language and coverage that can be completed in a one-semester course. It also covers the related concepts required to take the Fundamentals of Engineering (FE) exam. Features: Written in plain language, with numerous realistic step-by-step examples, covers topics required to understand and prepare for the Fundamentals of Engineering (FE) exam, includes practical case studies, concise theory and numerous solved practice problems. Engineering statics is suitable for undergraduate students in civil and mechanical engineering courses, as well as those in Engineering technology and applied courses. Research ambiguities are avoided considering the interests of lower-division students. The authors believe that this text will be very helpful for students to succeed in their degree programs and professional careers\"-- Provided by publisher.
Book
Twenty-two years of dengue outbreaks in Bangladesh: epidemiology, clinical spectrum, serotypes, and future disease risks
Dengue is the most rapidly spreading mosquito-borne disease and has become a major public health threat, particularly for tropical and subtropical countries including Bangladesh. This comprehensive review aims to summarize the overall scenario of dengue, including disease burden, clinical spectrum, seroprevalence, circulating serotypes/genotypes, and spatial distribution since the first recorded outbreak in Bangladesh. Since the first recorded outbreak in 2000, dengue epidemiology has shown the typical epidemic pattern with more frequent and bigger outbreaks and gradual geographic expansion to non-endemic regions in Bangladesh. For instance, highly confined Rohingya refugee camps that provide shelters to nearly 1.2 million forcibly displaced vulnerable Myanmar nationals in Cox’s Bazar district confronted a massive outbreak in 2022. Recent major outbreaks are found to be associated with the emergence of serotype DENV-3, which was undetected for a long time. Consequently, changes in serotypes might be attributed to increased severity in clinical manifestation in recent years. The existing weak surveillance and risk management systems are inadequate to deal with impending dengue risks. The healthcare system, particularly at the district level, is not prepared to manage impending large-scale dengue outbreaks in Bangladesh. Our findings would contribute to the development of strategies for dengue control and management in Bangladesh as well as other similar settings elsewhere in the world.
Journal Article
Fusarium: Molecular Diversity and Intrinsic Drug Resistance
After 1960, the increasing use of antibiotics became a major predisposing condition [4]. Since 1970, prolonged neutropenia due to intensified cytotoxic treatment of hematologic malignancies was the leading risk factor in novel types of fusariosis [5]. Since 1980, Fusarium infections have been seen in severely immunocompromised patients with a 100% mortality rate, e.g., in cases of cerebral involvement [6]. To date, about 36 of the alleged human opportunists carry a name, while 38 are still unnamed and can only be identified by multilocus sequence analysis (MLSA). [...]far, 21 species have been described with proven case reports [16], and more have been published in the literature.
Journal Article
Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production
In the oil and gas industries, predicting and classifying oil and gas production for hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software to predict future oil and gas production and devise optimum field development plans. However, this process costs an immense number of resources and is time consuming. Each reservoir prediction experiment needs tens or hundreds of simulation runs, taking several hours or days to finish. In this paper, we attempt to overcome these issues by creating machine learning and deep learning models to expedite the process of forecasting oil and gas production. The dataset was provided by the leading oil producer, Saudi Aramco. Our approach reduced the time costs to a worst-case of a few minutes. Our study covered eight different ML and DL experiments and achieved its most outstanding R2 scores of 0.96 for XGBoost, 0.97 for ANN, and 0.98 for RNN over the other experiments.
Journal Article
Presence of Middle East respiratory syndrome coronavirus antibodies in Saudi Arabia: a nationwide, cross-sectional, serological study
Scientific evidence suggests that dromedary camels are the intermediary host for the Middle East respiratory syndrome coronavirus (MERS-CoV). However, the actual number of infections in people who have had contact with camels is unknown and most index patients cannot recall any such contact. We aimed to do a nationwide serosurvey in Saudi Arabia to establish the prevalence of MERS-CoV antibodies, both in the general population and in populations of individuals who have maximum exposure to camels.
In the cross-sectional serosurvey, we tested human serum samples obtained from healthy individuals older than 15 years who attended primary health-care centres or participated in a national burden-of-disease study in all 13 provinces of Saudi Arabia. Additionally, we tested serum samples from shepherds and abattoir workers with occupational exposure to camels. Samples were screened by recombinant ELISA and MERS-CoV seropositivity was confirmed by recombinant immunofluorescence and plaque reduction neutralisation tests. We used two-tailed Mann Whitney U exact tests, χ2, and Fisher's exact tests to analyse the data.
Between Dec 1, 2012, and Dec 1, 2013, we obtained individual serum samples from 10 009 individuals. Anti-MERS-CoV antibodies were confirmed in 15 (0·15%; 95% CI 0·09–0·24) of 10 009 people in six of the 13 provinces. The mean age of seropositive individuals was significantly younger than that of patients with reported, laboratory-confirmed, primary Middle Eastern respiratory syndrome (43·5 years [SD 17·3] vs 53·8 years [17·5]; p=0·008). Men had a higher antibody prevalence than did women (11 [0·25%] of 4341 vs two [0·05%] of 4378; p=0·028) and antibody prevalence was significantly higher in central versus coastal provinces (14 [0·26%] of 5479 vs one [0·02%] of 4529; p=0·003). Compared with the general population, seroprevalence of MERS-CoV antibodies was significantly increased by 15 times in shepherds (two [2·3%] of 87, p=0·0004) and by 23 times in slaughterhouse workers (five [3·6%] of 140; p<0·0001).
Seroprevalence of MERS-CoV antibodies was significantly higher in camel-exposed individuals than in the general population. By simple multiplication, a projected 44 951 (95% CI 26 971–71 922) individuals older than 15 years might be seropositive for MERS-CoV in Saudi Arabia. These individuals might be the source of infection for patients with confirmed MERS who had no previous exposure to camels.
European Union, German Centre for Infection Research, Federal Ministry of Education and Research, German Research Council, and Ministry of Health of Saudi Arabia.
Journal Article
Magnesium and Human Health: Perspectives and Research Directions
Magnesium is the fourth most abundant cation in the body. It has several functions in the human body including its role as a cofactor for more than 300 enzymatic reactions. Several studies have shown that hypomagnesemia is a common electrolyte derangement in clinical setting especially in patients admitted to intensive care unit where it has been found to be associated with increase mortality and hospital stay. Hypomagnesemia can be caused by a wide range of inherited and acquired diseases. It can also be a side effect of several medications. Many studies have reported that reduced levels of magnesium are associated with a wide range of chronic diseases. Magnesium can play important therapeutic and preventive role in several conditions such as diabetes, osteoporosis, bronchial asthma, preeclampsia, migraine, and cardiovascular diseases. This review is aimed at comprehensively collating the current available published evidence and clinical correlates of magnesium disorders.
Journal Article
Clinicopathological characterization of non-guttata corneal endothelial dystrophy in Saudi patients with idiopathic endothelial failure
Corneal endothelial cell dysfunction is a common cause of corneal decompensation in elderly. We describe a non-guttata corneal endothelial dystrophy with correlation of the clinical features to the histopathological and ultrastructural characteristics in a cohort of Saudi patients. A retrospective study of all consecutive cases of primary corneal decompensation in phakic eyes due to endothelial attenuation, in the absence of guttata is conducted. Patients were treated by either penetrating keratoplasty (PKP) or Descemet’s Stripping Automated Endothelial Keratoplasty (DSAEK) as a primary procedure between 2002 and 2016. Clinical and demographic data were obtained through chart review and the histopathological data were collected by reviewing Descemet’s membrane (DM) in the corneal tissue samples of the affected eyes. We included 17 eyes from 17 patients (10 females and 7 males), with a mean age of 67.17 ± 8.98 years. All patients were phakic, and decreased vision was the patients’ main complaint at presentation. The pre-operative endothelial cell count was obtained in 3 eyes with a mean of 531.7 ± 309.5/mm
2
. Histopathology of the 17 corneal specimens showed thick multi-laminated DM and attenuated endothelium. The success rate of the primary procedure was 70%. The cornea of the other eye remained clear in 12/17 patients. This is a type of corneal endothelial cell dysfunction with a late onset of presentation, spontaneous corneal decompensation in phakic eyes or a rapid onset of decompensation following uncomplicated surgery. It seems to be asymmetrically bilateral among our Saudi patients. Fellow eyes are at the same risk of decompensation. DM lacks the presence of guttata clinically and histopathologically.
Journal Article
Statistical modelling and forecasting of HIV and anti-retroviral therapy cases by time-series and machine learning models
HIV (Human Immunodeficiency Virus) is a virus that causes the immune system to be damaged, thereby reducing the body’s ability to defend against infections and illnesses. In the absence of proper treatment, HIV can culminate into AIDS (Acquired Immunodeficiency Syndrome). The first-line approach to HIV infection consists of antiretroviral therapy (ART), a combination of drugs that restrict virus replication. Effective prediction of infectious diseases is particularly vital for timely interventions and allocation of resources for disease management and prevention. This study focuses on identifying effective time series forecasting models for HIV and anti-retroviral therapy (ART) cases in Pakistan. The study utilized monthly reported HIV and ART cases data from the National AIDS Control Program, sourced from the Pakistan Bureau of Statistics, spanning the period from 2016 to 2021. Various time series models including ARIMA (Auto-regressive integrated moving average), exponential smoothing (Brown, Holt, Winter), neural network auto-regressive model (NNAR), and ETS (Exponential Smoothing State space) models were applied to analyze and forecast the monthly patterns of HIV and ART cases. Descriptive and time series analyses were conducted using the R programming language. The models were evaluated based on their ability to accurately capture and predict the fluctuations in HIV and ART cases over time. The average monthly cases for HIV and ART were found to be 36,405 ± 12,740 and 28,287 ± 12,485, respectively. Among the models evaluated, the NNAR (1,1,2) forecasting model emerged as the most accurate for both HIV and ART cases. It outperformed other competing models based on well-known accuracy measures such as RMSE, MAE, and MAPE. According to the selected NNAR(1,1,2) model, the study predicts a monthly increase of 4.98% in HIV cases and 16.32% in ART cases. The results proposed the non-linear approach of NNAR model to predict the AIDS and ART cases which help policymakers and healthcare professionals involved in disease management and prevention strategies in Pakistan to improve the policies and their implementation.
Journal Article