The relationship of hyperuricemia to kidney disease, diabetes, hypertension and the risk of cardiovascular diseases remain controversial. The aim of this study is to evaluate the use of uric acid (UA) levels to find the higher risk of cardiovascular disease (CVD) in patients with end stage renal disease that have diabetic nephropathy (DN), nephropathy with hypertension (NH) and patients with both diabetic nephropathy with hypertension (DNH). This study deals with 115 patients with end-stage renal disease under hemodialysis sub-grouped into 35 patients with (DN), 40 patients with (NH), and 40 patients with (DNH). Some biochemical parameters were determined in the serum of all participants such as HbA1c, fasting blood glucose (FBG), UA, urea, serum creatinine, total serum protein, calcium, phosphate, albumin, and globin levels. The present study revealed a significant increase (P<0.05) in HbA1c, FBG, urea and creatinine in DN and DNH patients compared to NH group. However, non-significant difference was found in total serum protein, serum albumin, globulin, calcium, and phosphate levels between the groups. A positive correlation was found between UA level with FBG, HbA1c and creatinine in DN and DNH groups in comparison to NH group. Levels of UA can be considered as a reliable marker, which is less expensive and helps clinicians in controlling the progression to microvascular complications. The early detection of any complication and adopting the appropriate treatment to reduce the risk of CVD can reduce morbidity and mortality.
Warfarin dosing is challenging due to a multitude of factors affecting its pharmacokinetics (PK) and pharmacodynamics (PD). A novel personalised dosing algorithm predicated on a warfarin PK/PD model and incorporating CYP2C9 and VKORC1 genotype information has been developed for children. The present prospective, observational study aimed to compare the model with conventional weight-based dosing. The study involved two groups of children post-cardiac surgery: Group 1 were warfarin naïve, in whom loading and maintenance doses were estimated using the model over a 6-month duration and compared to historical case-matched controls. Group 2 were already established on maintenance therapy a
This aim research of this discussion impact of investment in human capital dimensions (training, education, knowledge management, skills development) and its components (knowledge, skills, abilities, value) with the Office of the Inspector General's staff - Ministry of Culture in Iraq, has depended questionnaire as a tool in the collection data and information ,subjected to a measure of validity and reliability, and distributed to a sample of (63) individuals were distributed in positions (director, director of the Division of employees) have been analyzed data search using ready-statistical software (SPSS) the used hypothesis testing and correlati
... Show MoreR. Vasuki [1] proved fixed point theorems for expansive mappings in Menger spaces. R. Gujetiya and et al [2] presented an extension of the main result of Vasuki, for four expansive mappings in Menger space. In this article, an important lemma is given to prove that the iteration sequence is Cauchy under suitable condition in Menger probabilistic G-metric space (shortly, MPGM-space). And then, used to obtain three common fixed point theorems for expansive type mappings.
<p>In this paper, we prove there exists a coupled fixed point for a set- valued contraction mapping defined on X× X , where X is incomplete ordered G-metric. Also, we prove the existence of a unique fixed point for single valued mapping with respect to implicit condition defined on a complete G- metric.</p>
The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
... Show MoreInvestment Bases directly and closely to an environment characterized by political, social and economic stability, and through a range of policies and institutions and economic laws that affect investor confidence and convince him directing investments to country without the other, where inter conditions and circumstances affecting the trends of capital and settle in, and political situation of the country and what is characterized of stability or disorder as well as economic conditions that are affected by what is distinguishes the country from geographic and demographic characteristics are reflected on availability of production elements and country's infrastructure.
... Show MoreThe main aim of this research is to introduce financing cost optimization and different financing alternatives. There are many studies about financing cost optimization. All previous studies considering the cost of financing have many shortcomings, some considered only one source of financing as a credit line without taking into account different financing alternatives. Having only one funding alternative powers, restricts contractors and leads to a very specific financing model. Although it is beneficial for the contractor to use a long-term loan to minimize interest charges and prevent a substantial withdrawal from his credit line, none of the existing financial-based planning models have considered long-term loans in
... Show MoreIn general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o
... Show MoreThe study includes the phytoplankton compositions in Alaaras Lake , in summer 2008 and winter , spring , summer 2009. Samples were collected from three selected sites at north , middle and south of lake. A total of 74 taxa of phytoplankton were identified . The diatoms were the dominated by 44 taxa represented 82.8% of the total indentified species, followed by green algae ( Chlorophyta ) of 20 taxa (8.5%), and blue green algae (Cyanophyta of 7 taxa (7.2%). Tow species were recorded of Pyrrophyta and one species of Euglenophyta .The seasonal variation for Diatoms density showed tow peaks during Autumn and summer. Few species were dominated during the most studied period such as Cocconeis placentula var. euglypta, Synedra fasciculata and
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