With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

In her poetry, Carol Ann Duffy looks into the concerns of the disregarded and humiliated people. Approaching facts fearlessly and disclosing realities in a way highly characteristic of her, she establishes the world newly and reframes it honestly. This research shows how Duffy reframes the world in her own peculiar terms, starting with her own creative use of the language, in particular, when the forms of things of the world are distorted, thus our perception of things will be reframed too.
As regards relations among people, the research elucidates how Duffy’s strained characters abandon real life and reframe an eccentric way of living, while respecting faith, wherein Duffy notices that religious rituals confine the intellect, she r

Hydro cracking of heavy oil is used in refinery to produce invaluable products. In this research, a model of hydro cracking reactor has been used to study the behavior of heavy oil in hydro cracking under the conditions recommended by literature in terms lumping of feed and products. The lumping scheme is based on five lumps include: heavy oil, vacuum oil, distillates, naphtha and gases. The first order kinetics was assumed for the conversion in the model and the system is modeled as an isothermal tubular reactor. MATLAB 6.1 was used to solve the model for a five lump scheme for different values of feed velocity, and temperature.

The research discussed the possibility of adsorption of Brilliant Blue Dye (BBD) from wastewater using 13X zeolite adsorbent, which is considered a byproduct of the production process of potassium carbonate from Iraqi potash raw materials. The 13X zeolite adsorbent was prepared and characterized by X-ray diffraction that showed a clear match with the standard 13X zeolite. The crystallinity rate was 82.15% and the crystal zeolite size was 5.29 nm. The surface area and pore volume of the obtained 13X zeolite were estimated. The prepared 13X zeolite showed the ability to remove BBD contaminant from wastewater at concentrations 5 to 50 ppm and the removal reached 96.60% at the lower pollutant concentration. Adsorption measurements versus tim

The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd+2, Nickel Ni+2, and Vanadium V+5) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir model with correlation coefficients (R2)

The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd⁺², Nickel Ni⁺², and Vanadium V⁺⁵) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L^-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir mo

The removal of turbidity from produced water by chemical coagulation/flocculation method using locally available coagulants was investigated. Aluminum sulfate (alum) is selected as a primary coagulant, while calcium hydroxide (lime) is used as a coagulant aid. The performance of these coagulants was studied through jar test by comparing turbidity removal at different coagulant/ coagulants aid ratio, coagulant dose, water pH, and sedimentation time. In addition, an attempt has been made to examine the relationship between turbidity (NTU) and total suspended solids (mg/L) on the same samples of produced water. The best conditions for turbidity removal can be obtained at 75% alum+25% lime coagulant at coagulant dose of 80 m

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi