Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease that affects 43.7 per 100,000 people worldwide, most commonly presenting in childbearing years. SLE pregnancies are complicated by cardiovascular events in up to 7.8% of cases, which translates to a 3.2- to 31.5-fold increase in severe maternal morbidity and a seven-fold increase in maternal mortality, compared to the general obstetric population. The highest risk is reported in cases with concurrent lupus nephritis or antiphospholipid syndrome [1]. These complications are not surprisingly seen; they are the end result of endothelial dysfunction, immune aberration, and placental dysfunction that precedes clinical decompensation by weeks [2,3].The current approach in management is reactive, while SLE needs proactive care. We suggest a structured three-phase approach to managing cardiovascular risk in pregnancy with SLE, from pre-conception through delivery and post-partum
Rapid and continuous developments and changes in the modern business environment in all areas of economic, environmental, social, technology and communications push economic units to search for modern methods and methodologies to produce products at low cost as well as produce products that meet the wishes of customers in terms of quality and environment to maintain their market position, and accounting for the costs of the flow of materials is one of the most prominent environmental management accounting techniques capable of providing information to help produce
Abstract:
The aim of this research is to highlight the importance of reducing the cost of a flight ticket by using information technology and the Internet, in the process of purchasing tickets for electronic flights, and to shift from the traditional method of purchasing and payment operations to the electronic method, to reduce the financial and non-financial risks associated with the traditional purchase process, as well as saving the cost Time, effort and money for the customer, and the researcher used the deductive approach in linking the variables (Internet of Things technology and reducing the costs of air tickets) wi
... Show MoreThe role of relaxation program for reducing anxiety of patients in dental clinic
The aim of this study was to evaluate the risk factors that influence the perforation, regardless of the presence of H. pylori infection, in a sample of Iraqi patients with peptic ulcers, admitted to Al-Kindy Teaching Hospital. A total of 90 patients who had perforated peptic ulcer participated in this study. The diagnosis was based on history, clinical examination, laboratory and radiological investigations and was confirmed intraoperatively. A number of probable risk factors for perforation were investigated. Eighty participants were males and 10 were females (male to female ratio 8:1). About 42.2% of patients were in their fifth decade of life. Forty-nine (54.4%) patients were asymptomatic be
Smoking and central obesity have both been linked to periodontitis, but their combined relationship with periodontal disease may be influenced by demographic and behavioral factors. This cross-sectional study analyzed records of 420 adult dental patients attending the College of Dentistry at the University of Baghdad. Data included demographic characteristics, smoking status, periodontal clinical findings, body mass index (BMI), and waist-to-height ratio (WHtR). Periodontitis was defined according to the 2018 classification framework, and logistic regression models were used to examine the associations of smoking and obesity-related indicators with periodontitis. The overall prevalence of periodontitis was 36.4%. Participants with p
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
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