Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydrophobicity, which can be modified by using unsaturated resin and silicon carbide nanoparticles (SiC-NPs). The obtained results show a remarkable increase and improvement in the mechanical properties of the artificial stone composite in the samples containing modified NGO with SiC-NPs. These samples have less porosity, smoother, more polished surface and, high bending and compressive strength. The addition of these materials to the artificial stone has increased durability and reduced costs and has caused water repellency, and prevented the penetration of harmful ions such as chloride, etc.
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show MoreBackground: Preeclampsia is a pregnancy-specific, multisystem condition characterized by the onset of de novo hypertension and proteinuria occurring in previously normotensive women after the twentieth week of pregnancy. Pregnancy is associated with a physiological adaptation that leads to changes in the hematological system including platelet parameters.
Objectives: Is to compare platelet count, and platelet indices, namely mean platelet volume platelet distribution width and platelet count to mean platelet volume MPV ratio in preeclamptic patients with normal pregnant women.
Patients &a
... Show MoreThe question about the existence of correlation between the parameters A and m of the Paris function is re-examined theoretically for brittle material such as alumina ceramic (Al2O3) with different grain size. Investigation about existence of the exponential function which fit a good approximation to the majority of experimental data of crack velocity versus stress intensity factor diagram. The rate theory of crack growth was applied for data of alumina ceramics samples in region I and making use of the values of the exponential function parameters the crack growth rate theory parameters were estimated.
The inhibitive action of Phenyl Thiourea (PTU) on the corrosion of mild steel in strong Hydrochloric acid, HCl, has been investigated by weight loss and potentiostatic polarization. The effect of PTU concentration, HCl concentration, and temperature on corrosion rate of mild steel were verified using 2 levels factorial design and surface response analysis through weight loss approach, while the electrochemical measurements were used to study the behavior of mild steel in 5-7N HCl at temperatures 30, 40 and 50 °C, in absence and presence of PTU. It was verified that all variables and their interaction were statistically significant. The adsorption of (PTU) is found to obey the Langmuir adsorption isotherm. The effect of temperature on th
... Show MoreFabrication and investigation of the properties of CdSe/ZnS core/shell for the luminescent solar concentrates (LSC) application is presented. An increase of the efficiency of a silicon solar cell was obtained by applying the LSC. The increase was a result of the optical properties of the semiconductor nanoparticles CdSe/ZnS core/shell that were deposited over the top surface of the silicon solar cell facing the illumination source (Halogen lamp). The gravity force was invested for the film deposition process.The optical properties of these nanoparticles were studied. The absorption spectra for the CdSe/ZnS core-shell were 270-600nm, i.e., located within the spectral response area of the examined solar cell. The energy gap values for CdSe
... Show MoreA Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and
... Show MoreBackground: Data on SARS-CoV-2 from developing countries is not entirely accurate, demanding incorporating digital epidemiology data on the pandemic.
Objectives: To reconcile non-Bayesian models and artificial intelligence connected with digital and classical (non-digital) epidemiological data on SARS-CoV-2 pandemic in Iraq.
Results: Baghdad and Sulaymaniyah represented statistical outliers in connection with daily cases and recoveries, and daily deaths, respectively. Multivariate tests and neural networks detected a predictor effect of deaths, recoveries, and daily cases on web searches concerning two search terms, "كورونا" and "Coronavirus" (Pillai's Trace val
In this paper, we proposed a hybrid control methodology using improved artificial potential field with modify cat swarm algorithm to path planning of decoupled multi-mobile robot in dynamic environment. The proposed method consists of two phase: in the first phase, Artificial Potential Field method (APF) is used to generate path for each one of robots and avoided static obstacles in environment, and improved this method to solve the local minimum problem by using A* algorithm with B-Spline curve while in the second phase, modify Cat Swarm Algorithm (CSA) is used to control collision that occurs among robots or between robot with movable obstacles by using two behaviour modes: seek mode and track mode. Experimental results show that the p
... Show MoreThis paper focuses on Load distribution factors for horizontally curved composite concrete-steel girder bridges. The finite-element analysis software“SAP2000” is used to examine the key parameters that can influence the distribution factors for horizontally curved composite steel
girders. A parametric study is conducted to study the load distribution characteristics of such bridge system due to dead loading and AASHTO truck loading using finite elements method. The key parameters considered in this study are: span-to-radius of curvature ratio, span length, number of girders, girders spacing, number of lanes, and truck loading conditions. The results have shown that the curvature is the most critical factor which plays an important
Meerkat Clan Algorithm (MCA) that is a swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. Meerkat has some behaviour. Sentry, foraging, and baby-sitter are the behaviour used to build this algorithm through dividing the solution sets into two sets, all the operations are performed on the foraging set. The sentry presents the best solution. The Flexible Job Shop Scheduling Problem (FJSSP) is vital in the two fields of generation administration and combinatorial advancement. In any case, it is very hard to accomplish an ideal answer for this problem with customary streamlining approaches attributable to the high computational unpredictability. Most
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