Novel Urinary Biomarkers and Chronic Kidney Disease After Coronary Angiography: A Prospective Case-Controlled Study

BACKGROUND: Novel urinary biomarkers may have potential for early detection of acute kidney injury. AIM: The aim of the study was to test two urinary biomarkers: Kidney injury molecule-1(KIM-1) and liver-type fatty acid binding protein (L-FABP) as markers of kidney injury following coronary angiography. METHODS: This is a prospective non-randomized controlled trial, performed in two large teaching hospitals. Patients were recruited from the catheter lab or form nephrology outpatient clinics. In group (A), 100 patients with AKI on top of CKD after coronary angiography and Group B: Thirty-one patients with stable CKD as a control. KIM-1 and L-FABP were measured at base line and after 3 months. RESULTS: In group (A), 100 patients who had acute on top of CKD after coronary angiography, stage progression occurred in 15 patients in group (A) compared to two patients in group (B) (p = 0.28). The median change in eGFR after 3 months was not statistically significant between both groups (p = 0.8). Median baseline urinary liver-type fatty acid binding protein was higher in Group A compared to Group B (3.7 μg/g vs. 1.82μg/g). The change in L-FABP from baseline to 3 months was significant between both groups (p < 0.001). The median urinary concentrations of KIM-1 and L-FABP were higher at the end of the follow-up compared to base line values in both groups, (p < 0.000). CONCLUSION: Urinary L-FABP correlates with kidney function decline in patients with acute on top of CKD after coronary angiography. Urinary levels of KIM-1 and L-FABP at 3 months increase significantly compared to baseline in patients with progressive CKD

New 1.5V CMOS current feedback operational amplifier

Abstract-a novel CMOS low-voltage current feedback operational amplifier (CFOA) is presented. The proposed CFOA based on a new positive second-generation current conveyor (CCII+). The new circuit allows almost a rail-to-rail input and output operation; also, it reduces the offset voltage and provides high driving current capabilities. The CFOA is operating at supply voltages of ±0.75 V with a total standby current of 338 µA. The circuit exhibits better than 10 MHz bandwidth and ±1mA current drive capability. PSpice simulation results are given using 0.35µm technology for the proposed CFOA

Testing the WEAP Hydrologic Model for Awash Basin, Ethiopia “Soil Moisture Module with Watershed Demand Approach”

The research is financed by the Egyptian Government through the Nile Sector bilateral cooperation project Abstract Currently, there are several hydrological simulation models in use worldwide. Prior to adoption of a model to a specific basin, its feasibility and practicality should be tested. This study highlights on the application of Water Evaluation and Planning system (WEAP) model for hydrologic simulation of Awash river basin in Ethiopia. A monthly time step hydrologic model was developed using the soil moisture rainfall-runoff method incorporated in WEAP with an aim to check the suitability of the model for Awash river basin. For this purpose five selected flow gauge stations located at the upper, middle and lower Awash basin were used as control stations. The model is configured taking into account the effects of development and hence the water abstractions, storage, loss rate, etc. are estimated using the data provided through various kinds of research and survey in Ethiopia. Standard methods are also used to prepare the hydro-metrological and landuse input data for each sub-catchment. Based on data availability, the time period 1986-2005 was selected for the hydrologic simulation. The observed data were split for calibration (1986–1995) and validation (1996–2005) purposes. Initially, the model was set up using the default model parameters. Then, manual calibration is performed to reproduce the observed streamflow. The model-simulated values are compared with those obtained from observations using standard statistical tests on monthly and monthly average basis. From the performance test results, it is observed that the coefficient of determination (R2) and the Index of Agreement (IA) show a good fit. Furthermore, the Nash-Sutcliffe Efficiency (NSE) and the Percent Bias (PBIAS) calibration and validation results show good performance for Upper Awash stations and satisfactory results for the middle and lower Awash control stations. As a conclusion, the main modelling constraints were discussed and possible solutions were also suggested in order to improve the performance of water resources simulation models for the Awash basin. Keywords: Awash Basin, Hydrologic Simulation, Calibration, Validation, Model Performance, WEAP DOI: 10.7176/CER/12-3-07 Publication date:March 31st 202

The Impact of Shear Reinforcement Amount and Arrangement on the Shear Capacity of Shallow RC Beams: An Experimental Study

This study investigates the impact of shear reinforcement amount and arrangement on the shear capacity of shallow/wide RC beams. Seven specimens of shallow/wide beams with different ultimate shear reinforcement stress (μ.Fys), longitudinal spacing to depth ratio (S/d), and transversal spacing to depth ratio (S’/d) were tested under a monotonic three-point bending test. All the specimens were designed to fail at shearing. The results showed that the shear reinforcement was fully functioning until it yielded; also, the amount of shear reinforcement had the major impact on the shear capacity; in addition, the transverse spacing had more influence on the shear capacity than the longitudinal spacing. The measured shear capacities were compared to six design codes, in which the results ranged from 95% to 110%, with the Japanese code (JSCE) being the closest to the experimental results. Two AI-based predicting equations, “Genetic Programming” (GP) and “Evolutionary Polynomial Regression” (EPR), were also compared to the experimental, with accuracies of 78% and 86% of the measured capacities, respectively. Initial stiffness, final stiffness, dissipated energy, and ductility were all discussed for the seven specimens, with ultimate shear reinforcement stress being the most impactful on the total shear capacity of the wide beams. Doi: 10.28991/CEJ-2023-09-12-013 Full Text: PD

The Impact of Aspect Ratio, Characteristic Strength and Compression Rebars on the Shear Capacity of Shallow RC Beams

This paper investigates the impact of the aspect ratio, the characteristics strength of the concrete, and the compression steel ratio on the shear capacity of wide-shallow beams. An experimental program consists of seven specimens, including a control specimen, all tested under a three-point load test. Three specimens were considered for each parameter (the control specimen was included in all three variables). The experimental results were compared to the theoretical values of six different codes of practice; they were also analyzed to determine the ductility, stiffness, and dissipated energy of each specimen. The results indicated that the shear reinforcement was fully functioning until it yielded, with a minimum contribution of 55% of the total shear capacity of the specimens. The aspect ratio and the characteristic strength had a notable impact on the shear capacity of the specimens, while the compression steel ratio had a minor effect on the shear capacity, but it improved the stiffness and the ductility of the beams. Theoretical concrete shear strengths from design codes ranged between 77 and 163% of the experimental values; EN-1992 was the closest code to the experimental results. A comparison between the experimental results and predicted values using GP and EPR methods from previous research showed accuracies of 72% and 81%, respectively. Doi: 10.28991/CEJ-2023-09-09-012 Full Text: PD

Adenosine A2A Receptor Blockade Prevents Rotenone-Induced Motor Impairment in a Rat Model of Parkinsonism

Pharmacological studies implicate the blockade of adenosine receptorsas an effective strategy for reducing Parkinson’s disease (PD) symptoms. The objective of this study is to elucidate the possible protective effects of ZM241385 and 8-cyclopentyl-1, 3-dipropylxanthine, two selective A2A and A1 receptor antagonists, on a rotenone rat model of PD. Rats were split into four groups: vehicle control (1 ml/kg/48 h), rotenone (1.5 mg/kg/48 h, s.c.), ZM241385 (3.3 mg/kg/day, i.p) and 8-cyclopentyl-1, 3-dipropylxanthine (5 mg/kg/day, i.p). After that, animals were subjected to behavioral (stride length and grid walking) and biochemical (measuring concentration of dopamine levels using high performance liquid chromatography, HPLC). In the rotenone group, rats displayed a reduced motor activity and disturbed movement coordination in the behavioral tests and a decreased dopamine concentration as foundby HPLC. The effect of rotenone was partially prevented in the ZM241385 group, but not with 8-cyclopentyl-1,3-dipropylxanthine administration. The administration of ZM241385 improved motor function and movement coordination (partial increase of stride length and partial decrease in the number of foot slips) and an increase in dopamine concentration in the rotenone-injected rats. However, the 8-cyclopentyl-1,3-dipropylxanthine and rotenone groups were not significantly different. These results indicate that selective A2A receptor blockade by ZM241385, but not A1 receptor blockadeby 8-cyclopentyl-1,3-dipropylxanthine, may treat PD motor symptoms. This reinforces the potential use of A2A receptor antagonists as a treatment strategy for PD patients

A Predictive Model for Student Performance in Classrooms using Student Interactions with an eTextbook

With the rise of online eTextbooks and Massive Open Online Courses (MOOCs), a huge amount of data has been collected related to students’ learning. With the careful analysis of this data, educators can gain useful insights into their students’ performance and their behavior in learning a particular topic. This paper proposes a new model for predicting student performance based on an analysis of how students interact with an interactive online eTextbook. By being able to predict students’ performance early in the course, educators can easily identify students at risk and provide a suitable intervention. We considered two main issues: the prediction of good/bad performance and the prediction of the final exam grade. To build the proposed model, we evaluated the most popular classification and regression algorithms. Random Forest Regression and Multiple Linear Regression have been applied in Regression. While Logistic Regression, decision tree, Random Forest Classifier, K Nearest Neighbors, and Support Vector Machine have been applied in classification. Based on the findings of the experiments, the algorithm with the best result overall in classification was Random Forest Classifier with an accuracy equal to 91.7%, while in the regression it was Random Forest Regression with an R2 equal to 0.977