Treated effluent wastewater is considered an alternative water resource which can provide an important contribution for using it in different purposes, so, the wastewater quality is very important for knowing its suitability for different uses before discharging it into fresh water ecosystems. The wastewater quality index (WWQI) may be considered as a useful and effective tool to assess wastewater quality by indicating one value representing the overall characteristic of the wastewater. It could be used to indicate the suitability of wastewater for different uses in water quality management and decision making. The present study was conducted to evaluate the Al-Diwaniyah sewage treatment plant (STP) effluent quality based on wastewater quality index (WWQI) for disposal according to Iraqi limitations. Wastewater samples were collected from Al-Diwaniyah STP during 2012-2016 and tested for a comprehensive analysis of physical and chemical analysis. The parameters included Total suspended solids (TSS), Nitrate (NO3), Biological oxygen demand (BOD5), and Chemical oxygen demand (COD). The determination of the WWQI was done using the weighted arithmetic method. The results showed that the effluent BOD5, COD and TSS concentrations were not in the Iraqi standards for effluent disposal. The WWQI of this effluent classified its quality within ranged from poor to very poor according to Iraqi standards (IQS) and very poor to very polluted under the world health standards (WHO), that could cause environmental pollution in the receiving river. The permanent solution is through the proper operation using scientific methods and training the operational staff using technical methods and then future solution, advanced treatment in the plant, by completing both the solutions above will lead to upgrade the effluent quality to achieve the required water standards.
The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t
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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
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The drive of this exploration is to investigate the mucoadhesive assets of A. indica (Azadirachta indica) fruit mucilage by incorporating it into mucoadhesive microspheres with Acyclovir (AVR) as a model drug. The study was performed to check the impact of the mucilage proportion on particle size and swelling index. Nine batches of AVR mucoadhesive microspheres were made with varying proportions of Polyacrylic acid 934P and A. indica fruit mucilage (AIFM). A central composite design with design expert software to check the impact of dependent variables (A. indica mucilage and Polyacrylic acid 934 P levels) on particle size and swelling index as a response. As part of congeniality studies, the batches w
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This study is concerned with the effect of Deep Cryogenic Treatment (DCT) at liquid nitrogen temperature (-196 o C) on the mechanical properties and performance of low carbon steel (A858). The tests specimens were divided in to two groups, the first group was subjected to the conventional heat treatment of normalizing, and the second group was also normalized then subjected to (DCT). The results have shown that after (DCT), the Hardness, Tensile properties and the impact energy absorbed were all slightly increased. However the fatigue test showed some positive improvement in fatigue limit by 20(N/mm2 ), and the volume wear rates at different loads were significantly decreased after (DCT). The changes in microstructure due to (DCT) were c
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CuInSe2(CIS) thin films have been prepared by use vacuum thermal evaporation technique, of thickness750 nm with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant) by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can make to control it are wide applications as an optoelectronic devices and photovoltaic applications.
CuInSe2 (CIS)thin films have been prepared by use vacuum thermal evaporation technique, of 750 nm thickness, with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant)by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can made to control it is wide applications as an optoelectronic devices and photovoltaic applications.
Background: Polymer surfaces usually present problems in bonding and finishing due to their low hydrophilicity. The aim of this study is to investigate the effect of plasma treatment with the use of two types of gases (oxygen and argon) on surface roughness, and chemical surface properties of acrylic resin denture base polymer material. Materials and Methods: Three heat cured acrylic resin specimens of (2*8*30 mm) dimensions were prepared for each test carried out in this study. Two tests were conducted, surface roughness test and chemical surface analysis test. Results: Application of plasma treatment increased surface roughness for both oxygen and argon plasma treated acrylic resin specimen groups compared with control untreated group,
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