Background: Chronic hepatitis B virus (HBV) infection is a common health problem that has a worldwide distribution. Apart from the direct effect of the virus on the liver, there are many extrahepatic manifestations among which the probable effect on bone turnover associated with low bone mineral density (BMD). Objectives: This study aimed to determine the association between treated and untreated chronic HBV infection with BMD. Methods: This is a cross-sectional study which included a total of 48 patients with chronic HBV (28 patients treated with tenofovir-disoproxil-fumarate [TDF] antiviral drug and 20 patients have not yet started treatment). Other age- and sex-matched 30 apparently healthy individuals were recruited to represent the hea

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

Due to the broad range uses of chromium for industrial purposes, besides its carcinogenic effect, an efficient, cost effective removal method should be obtained. In this study, cow bones as a cheap raw material were utilized to produce active carbon (CBAC) by physiochemical activation, which was characterized using: SEM to investigate surface morphology and BET to estimate the specific surface area. The best surface area of CBAC was 595.9 m²/gm which was prepared at 600 ^ᵒC activation temperature and impregnation ratio of 1:1.5. CBAC was used in aqueous chromium ions adsorption. The investigated factors and their ranges are: initial concentration (10-50 mg/L), adsorption time (30-300 min), temperature (20-50

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A comparison between numerical and experimental data, illustrated

The presence of residual antibiotics in water results in the development of antibiotics resistant genes. The available wastewater treatment systems are not capable of removing such antibiotics from sewage. Thus, antibiotics need to be removed before the discharge of wastewater. Adsorption is among the promising techniques for the wastewater treatment to aid the removal of a wide range of organic and inorganic pollutants. The present work is a contribution to the search for an economical method for the removal of low concentrations of amoxicillin (AMX) from water by adsorption on water treatment residue, WTR, taken from a local drinking water facility. The chemical composition and the adsorptive characteristics of the material were first

Atotal of 75 different clinical samples were collected from different hospitals in Baghdad Biochemical and morphological characterization tests showed that forty isolates were identified as Staphylococcus aureus Antibiotic susceptibility tests of all isolates towards ten antibiotics were carried out and results showed that many isolates (97.5 %) were resistant to ?-lactam antibiotic , 70 % were resistant to Tetracyclinee , 62.5% were resistant to co-trimoxazole , 60 % were resistant to ciprofloxacin , 55% were resistant both of chloramphenicol and erythromycin , 52.5% were resistant to gentamicin , 35% were resistant to rifampicin , 10% were resistant to vancomycin . According to the above results the S.aureus I1 which is isolated

A simple all optical fiber sensor based on multimode interference (MMI) for chemical liquids sensing was designed and fabricated. A segment of coreless fiber (CF) was spliced between two single mode fibers to buildup single mode-coreless-single mode (SCS) structure. Broadband source and optical signal analyzer were connected to the ends of SCS structure. De-ionized water, acetone, and n-hexane were used to test the performance of the sensor. Two influence factors on the sensitivity namely the length and the diameter of the CF were investigated. The obtained maximum sensitivity was at n-hexane at 340.89 nm/RIU (at a wavelength resolution of the optical spectrum analyzer of 0.02 nm) when the diameter of the CF reduced from 125 μm to 60 μ

Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM