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Red Cell Distribution Width and Neutrophil-Lymphocyte Ratio as Markers for Diabetic Nephropathy
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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.

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Publication Date
Tue Aug 23 2022
Journal Name
Frontiers In Energy Research
Evaluation of T-Shaped Fins With a Novel Layout for Improved Melting in a Triple-Tube Heat Storage System
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The effects of T-shaped fins on the improvement of phase change materials (PCM) melting are numerically investigated in vertical triple-tube storage containment. The PCM is held in the middle pipe of a triple-pipe heat exchanger while the heat transfer fluid flows through the internal and external pipes. The dimension effects of the T-shaped fins on the melting process of the PCM are investigated to determine the optimum case. Results indicate that while using T-shaped fins improves the melting performance of the PCM, the improvement potential is mainly governed by the fin’s body rather than the head. Hence, the proposed T-shaped fin did not noticeably improve melting at the bottom of the PCM domain; additionally, a flat fin is ad

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Effect Of Talent Management To Achieve Organizational sac seed Research in The General Company for Dairy Products in Baghdad
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The research aims at identifying the extent to which the top management in the organization is interested in managing the talents of its employees, through which it can face the competing organizations, as well as the great challenges faced by all organizations in recent years. The task of attracting and maintaining talented human resources is one of the biggest challenges facing Organizations 
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Publication Date
Fri Jan 21 2022
Journal Name
Environmental Science And Pollution Research
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Optimization of Fenton process for removal of chemical oxygen demand (COD) from hospital wastewater using response surface methodology (RSM)
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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Asphaltene Precipitation Investigation Using a Screening Techniques for Crude Oil Sample from the Nahr-Umr Formation/Halfaya Oil Field
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Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A Developed Colorimetric Assay Using Unmodified Gold Nanoparticles for the Identification of Acinetobacter baumannii Isolates from Different Clinical Samples
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  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Photochemistry And Photobiology A: Chemistry
Facile assembly of CoS/Ag2MoO4 nanohybrids for visible light-promoted Z-type-induced synergistically improved photocatalytic degradation of antibiotics
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