The Impact of Molar Proportion of Sodium Hydroxide and Water Amount on the Compressive Strength of Slag/Metakaolin (Waste Materials) Geopolymer Mortar

This investigation aimed to improve great early geopolymer mortar strengths under various parameters with various binder proportions to reduce the use of cement since the OPC production process leads to high emissions of CO2. Hence, to solve this problem, alternative materials were used. In this research, metakaolin (MK) and ground-granulated blast-furnace slag (GGBFS) waste materials were utilized and mixed together with the sodium hydroxide and alkaline activator sodium silicate (NaOH and Na2SiO3). The performance of the various mixtures was assessed via compressive strength testing based on British standards. The compressive strength was found to be highly affected by molar proportion and water amount. The optimum strength was 77.8 MPa for a mix design of 95% GGBFS +5% MK and a 2.5 mass proportion between Na2SiO3 and NaOH (12 Molar), together with a 0.2 water/binder proportion

DETERMINATION CADMIUM, LEAD AND ZINC IN HUMAN HAIR BY USING FLAME ATOMIC ABSORPTION SPECTROMETRY (FAAS)

The heavy metals mean serious hazard in environmental pollution. Some of them are vital for many organisms in a low concentration, however the others ought to be poisonous at low concentrations, too. This paper gives an example for the correlation of the attention in human hair and in the environment of different heavy metals. Human hair (n=50) Volunteers (35 males and 15 females) of different age groups between 1 to 57 years samples were collected in Al – Ajailat, Libya. Hair samples were analyzed for heavy metals (Cd, Pb and Zn) by Flame Atomic Absorption Spectrophotometric technique (FAAS). The results showed that the samples concentrations ranged between 0.0001 and 0.3840 mg.kg−1 for cadmium, followed by zinc between 68.99 mg kg−1 and 225mg. kg−1while lead was between 0.632 mg kg−1 and 7.708mg. Kg−1. The results indicated that metal concentrations in male samples varied based on age, such that age group 33-43 years had the highest zinc concentration (206.2±11.6 mg/kg), and age group 1-10 years had the highest Cd (0.384±0.01 mg/kg) and Pb (1.929±0.05 mg/kg) concentrations. while, the cadmium and lead contents in children’s hair samples of both sexes was higher than compared to the values available in some countries. The difference between male and female concentration could be due to individual differences in exposure to heavy metal load as a result of habitual or environmental factors

A newly developed integrative bio-inspired artificial intelligence model for wind speed prediction

Accurate wind speed (WS) modelling is crucial for optimal utilization of wind energy. NumericalWeather Prediction (NWP) techniques, generally used for WS modelling are not only less cost-effective but also poor in predicting in shorter time horizon. Novel WS prediction models based on the multivariate empirical mode decomposition (MEMD), random forest (RF) and Kernel Ridge Regression (KRR) were constructed in this paper better accuracy in WS prediction. Particle swarm optimization algorithm (PSO) was employed to optimize the parameters of the hybridized MEMD model with RF (MEMD-PSO-RF) and KRR (MEMD-PSO-KRR) models. Obtained results were compared to those of the standalone RF and KRR models. The proposed methodology is applied for monthly WS prediction at meteorological stations of Iraq, Baghdad (Station1) and Mosul (Station2) for the period 1977-2013. Results showed higher accuracy of MEMD-PSO-RF model in predicting WS at both stations with a correlation coefficient (r) of 0.972 and r D 0.971 during testing phase at Station1 and Station2, respectively. The MEMD-PSO-KRR was found as the second most accurate model followed by Standalone RF and KRR, but all showed a competitive performance to the MEMD-PSO-RF model. The outcomes of this work indicated that the MEMD-PSO-RF model has a remarkable performance in predicting WS and can be considered for practical applications

Experimental and theoretical analysis of energy efficiency in a flat plate solar collector using monolayer graphene nanofluids

Flat‐plate solar collectors are one of the cleanest and most efficient heating systems available. Studies on the presence of covalently functionalized graphene (Gr) suspended in distilled water as operating fluids inside an indoor flat‐plate solar collector (FPSC) were experimentally and theoretically performed. These examinations were conducted under different testing conditions namely 0.025%‐wt., 0.05%‐wt., 0.075%‐wt., and 0.1%‐wt., 0.5, 1, and 1.5 kg/min, 30, 40, and 50 °C, and 500, 750, and 1000 W/m2. Various techniques were used to characterize the functionalized nanofluids’ stability and morphological properties namely UV/Vis spectrophotometry, EDX analysis with a Scanning Electron Microscope (SEM), zeta potential, and nanoparticle size. The results showed that the collected heat improved as the percentage of GrNPs and the fluid mass flow rates increased, although it decreased as the reduced temperature coefficient increased, whereas the maximum increase in collector efficiency at higher concentration was 13% and 12.5% compared with distilled water at 0.025 kg/s. Finally, a new correlation was developed for the base fluid and nanofluids’ thermal efficiency as a function of dropped temperature parameter and weight concentration with 2.758% and 4.232% maximum deviations

Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm

Flood prediction and control are among the major tools for decision makers and water resources planners to avoid flood disasters. The Muskingum model is one of the most widely used methods for flood routing prediction. The Muskingum model contains four parameters that must be determined for accurate flood routing. In this context, an optimization process that self-searches for the optimal values of these four parameters might improve the traditional Muskingum model. In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. Data for the three different case studies from the USA and the UK were utilized to examine the suitability of the proposed HBSA for flood routing. Comparative analyses based on the sum of squared deviations (SSD), sum of absolute deviations (SAD), error of peak discharge, and error of time to peak showed that the proposed HBSA based on the Muskingum model achieved excellent flood routing accuracy compared to that of other methods while requiring less computational time

Quantitative Whole Body Biodistribution of Fluorescent-Labeled Agents by Non-Invasive Tomographic Imaging

When small molecules or proteins are injected into live animals, their physical and chemical properties will significantly affect pharmacokinetics, tissue penetration, and the ultimate routes of metabolism and clearance. Fluorescence molecular tomography (FMT) offers the ability to non-invasively image and quantify temporal changes in fluorescence throughout the major organ systems of living animals, in a manner analogous to traditional approaches with radiolabeled agents. This approach is best used with biotherapeutics (therapeutic antibodies, or other large proteins) or large-scaffold drug-delivery vectors, that are minimally affected by low-level fluorophore conjugation. Application to small molecule drugs should take into account the significant impact of fluorophore labeling on size and physicochemical properties, however, the presents studies show that this technique is readily applied to small molecule agents developed for far-red (FR) or near infrared (NIR) imaging. Quantification by non-invasive FMT correlated well with both fluorescence from tissue homogenates as well as with planar (2D) fluorescence reflectance imaging of excised intact organs (r2 = 0.996 and 0.969, respectively). Dynamic FMT imaging (multiple times from 0 to 24 h) performed in live mice after the injection of four different FR/NIR-labeled agents, including immunoglobulin, 20–50 nm nanoparticles, a large vascular imaging agent, and a small molecule integrin antagonist, showed clear differences in the percentage of injected dose per gram of tissue (%ID/g) in liver, kidney, and bladder signal. Nanoparticles and IgG1 favored liver over kidney signal, the small molecule integrin-binding agent favored rapid kidney and bladder clearance, and the vascular agent, showed both liver and kidney clearance. Further assessment of the volume of distribution of these agents by fluorescent volume added information regarding their biodistribution and highlighted the relatively poor extravasation into tissue by IgG1. These studies demonstrate the ability of quantitative FMT imaging of FR/NIR agents to non-invasively visualize and quantify the biodistribution of different agents over time

Prevalence of coronary artery disease and its risk factors in Majmaah City, Kingdom of Saudi Arabia

ObjectiveThis study was carried out with an aim to outline the prevalence of coronary artery diseases, its risk of one region of the Saudi Arabia.MethodsA retrospective observational study conducted across five secondary medical centers located in the city of Majmaah. Hospital medical records and ministry of health records were screened over a 6-month period for data on patients admitted for Coronary artery disease (CAD). Data collected included sociodemographic characteristics, medical profile, and laboratory findings.ResultsA total of 327 participants were included in this study with a median age of 64 and the majority being male participants (59.8%). The majority were married, held a primary school degree and earned a salary for living. A large number (82.9%) were hypertensive and diabetic (66.7%) and one-fourth had a previous MI (25.1%). A large number (73.7%) had heart failure with a mean ejection fraction of 44% (SD = 13). The causes of heart failure were mainly ischemic (56.3%) and hypertensive (28.1%). Readmission rates at 30 and 90 days then at 6 and 12 months were 22, 53.8, 68.8, and 75.8%, respectively. The mortality rates at the same time intervals were 5.5, 8.9, 14.1, and 22.9%, respectively. Predictors of readmission are age, CCI, and NYHA class.ConclusionCoronary artery disease is the leading cause of heart failure. End stage CAD can have similar results in terms of readmission and mortality as heart failure. Future research should target patients in different stages of the condition and monitor their comorbidities which may impact the study findings