Diabetic nephropathy (DN) is the foremost cause of end-stage renal disease. Early detection of DN can spare diabetic patients of severe complications. This study aimed to evaluate the diagnostic value of red cell distribution width (RDW) and neutrophil-lymphocyte ratio (NLR) in the detection of DN in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included a total of 130 patients with T2DM, already diagnosed with T2DM. The albumin creatinine ratio (ACR) in urine samples was calculated for each patient, according to which patients were divided into two groups: with evidence of DN when ACR ? 30 mg/g, and those with no evidence of DN when ACR < 30 mg/g. According to multivariate analysis, each of disease duration (OR = 4.43, 95% CI = 1.68-11.68, p = 0.003), HbA1c (OR = 6.4, 95% CI = 2.32-17.65, p < 0.001) and NLR (OR = 13.75, 95% CI = 1.68-11.68, p < 0.001) were independent predictors for DN. Using the receiver operating characteristic (ROC) curve to evaluate the diagnostic value of NLR revealed that the AUC was 0.736 (95% CI = 0.635-0.837), p < 0.001. The sensitivity and specificity of the test at the cut-off value of NLR = 3.35 was 69% and 89%, respectively. These data indicate that NLR is a simple non-expensive test that can be used regularly to investigate diabetic patients for the development of DN. Red cell distribution width (RDW), on the other hand, had no diagnostic value in this regard.
The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but in this paper, the researcher proposed five pile types, one of them is not a traditional, and developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with t
... Show MoreThe investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show MoreDetecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate
... Show MoreThis research discussed and analyzed the formulation of a strategy to manage tax compliance risks, as an applied research in the General commission for Taxes. The questionnaire was used as a research tool to identify the factors that stimulate or retard the research sample from being compliant. The K-means clustering method was also used to enable the classification of the research sample's views into four behaviors, some of these views pose tax-compliance risks. The research concluded that risk management is a continuous process and that all departments of the General commission for Taxes are responsible for its implementation to enable them to deal with the behavior of the taxpayer towards tax compliance. And it recommended
... Show MoreThe importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab
... Show MoreMassive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine
... Show MoreKnowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani
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