A new bio-electrochemical system was proposed for simultaneous removal of organic matters and salinity from actual domestic wastewater and synthetically prepared saline water, respectively. The performance of a three-chambered microbial osmotic fuel cell (MOFC) provided with forward osmosis (FO) membrane and cation exchange membrane (CEM) was evaluated with respect to the chemical oxygen demand (COD) removal from wastewater, electricity generation, and desalination of saline water. The MOFC wasinoculated with activated sludge and fueled with actual domestic wastewater. Results revealed that maximum removal efficiency of COD from wastewater, TDS removal efficiency from saline water, power density, and current density were

The study seeks to examine the level of personal efficacy and its relation to mental alertness among university students. Besides, the statistically significant differences in regard of students' gender, and the correlation between male and female. To do this, the researcher adopted two scales: one to measure the personal efficacy which was made up by (abed al-jabaar, 2010) included (26) items, and the other to measure the mental alertness that designed by (abed Allah, 2012) included (36) items. A total of (120) student were selected randomly from three-different colleges at the Al-Mustansiriyah University for the academic year 2016-2017. The findings revealed there are no significant differences among students in regard of the personal

A solar cell was manufactured from local materials and was dyed using dyes extracted from different organic plants. The solar cell glass slides were coated with a nano-porous layer of Titanium Oxide and infused with two types of acids, Nitric acid and Acetic acid. The organic dyes were extracted from Pomegranate, Hibiscus, Blackberry and Blue Flowers. They were then tested and a comparison was made for the amount of voltage they generate when exposed to sunlight. Hibiscus sabdariffa extract had the best performance parameters; also Different plants give different levels of voltage.

The study aims to identify the Traumatic Symptoms (physiological, emotional, and cognitive) of earthquakes among the targeted sample; it also aims to identify the significant differences between psychological, emotional, and cognitive traumatic symptoms of earthquakes according to the gender and age of participants. The study additionally seeks to identify thepsychological positive-negative reactions associated with earthquakes according to gender and age of the participants. To measure the traumatic symptoms of earthquakes, a 4-point Likert scale questionnaire with (20) items (questions) accompanied with a 4-point Likert scale questionnaire with (18) items (questions) were used to measure the Psychological positive-n

Background: Osteoarthritis (OA) is a degenerative joint disease. It is one of the major causes of disability in developed and developing countries. Human leukocyte antigen (HLA) as part of immune system has a role in the disease process.Objectives: To investigate whether there is an association between HLA class II-DRB and OA.Methods: A case control study with 26 patients with osteoarthritis and 22 apparently healthy obese control persons matching in ethnicity were enrolled in this study during the period between October 2012 till March 2013. Direct interview was done with each patient and HLA typing was done by molecular method using Sequence Specific Primer (PCR-SSP) method using One Lambda Kit-USA. Results: The results showed that fem

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi