In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after

Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pres

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Background. Temporomandibular dysfunction syndrome (TMD) is a common disease among dental patients. It occurs as a consequence of malfunction of the tempromandibular and/or surrounding facial muscles. LED red light therapy is not been well established, and it is important to find out the role of this technique in the treatment of temporomandibular disorders. Aim of the Study. To evaluate the efficacy of the LED red light in the treatment of the tempromandibular dysfunction syndrome. Material and Methods. Fifty students of the College of Dentistry/University of Baghdad with myofacial pain associated with Tempromandibular Disorder volunteered to participa

Background. Temporomandibular dysfunction syndrome (TMD) is a common disease among dental patients. It occurs as a consequence of malfunction of the tempromandibular and/or surrounding facial muscles. LED red light therapy is not been well established, and it is important to find out the role of this technique in the treatment of temporomandibular disorders. Aim of the Study. To evaluate the efficacy of the LED red light in the treatment of the tempromandibular dysfunction syndrome. Material and Methods. Fifty students of the College of Dentistry/University of Baghdad with myofacial pain associated with Tempromandibular Disorder volunteered to participa

Background: Uncontrolled hyperphosphatemia is the main difficulty facing staff treating patients with end-stage renal disease on hemodialysis. Sevelamer and calcium-containing phosphate binders have been associated with cost burden and tissue calcification, respectively. Therefore, the current trial was targeted to investigate the efficacy of a new phosphate binder, ferric citrate, in a sample of Iraqi patients with end-stage renal disease on hemodialysis. Keywords: Ferric citrate, Hemodialysis Phosphate binder

A fully automatic electrothermal atomic emission spectrometry (ETA-AES) is described. This system is based on an echelle monochromator modified for wave¬length modulation which is completely controlled by microcomputer . The advantages of the system in atomic spectrometry have been discussed . Aspects of the analytical performances such as calibration ? dection limit, precision , and recovery for copper are considered . This system is applied for routine determination of copper in commercial powdered mill? by slurr>' atomization versus aqueous atomization techniques.