Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact t

In this work, we calculate and analyze the photon emission from quark and anti-quark interaction during annihilation process using simple model depending on phenomenology of quantum chromodynamic theory (QCD). The parameters, which include the running strength coupling, temperature of the system and the critical temperature, carry information regarding photon emission and have a significant impact on the photons yield. The emission of photon from strange interaction with anti-strange is large sensitive to decreases or increases there running strength coupling. The photons emission increases with decreases running strength coupling and vice versa. We introduce the influence of critical temperature on the  photon emission  rate in o

This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement.

Consequently, HS

The study in duded isolation and identification of microbial isolates from oral cavity to 10 volunteers, diagnosed within the three groups: Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus spp. and Candida albicans . The sensitivity test of all isolates bacteria Streptococcus spp. , S. aureus and S. epidermidis showed high resistance to Ampicillin(100)%,followed Methicillin (88.88)% and Amoxicillin / clavulanic acid(77.77)%, while the resistance for each of Vancomycin and Amoxicillin were (66.66)%, and the resistance to Erythromycin and Pencillin (55.55)% to each of them. The results showed less resistance to Trimethoprim (22.22)% and Cefalotine (11.11)% of all bacteria isolate. Investigation of the pre

Background: Anemia of chronic disease (ACD) occurs in the presence of chronic infection, inflammatory conditions or neoplastic conditions despite of adequate iron and vitamins storage. Gingivitis is the inflammation of the gingiva, periodontitis is the inflammation in the periodontium that extend deeper with loss of connective tissue attachment and supporting bone. The main pathogenesis of periodontal diseases and ACD is immune activation. Aims of study: Determine and compare the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL)). Evaluate the hematocrit (Hct) level, red blood cells (RBCs) count and white blood cells (WBCs) c

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Objective: This study evaluated the effect of immediate dentin sealing on the marginal adaptation of lithium disilicate overlays with three different types of resin-luting agents: preheated composite, dual-cure adhesive resin, and flowable composite. Materials and Methods: Forty-eight maxillary first premolars of similar size were prepared with a butt joint preparation design. The teeth were separated into two primary groups, each with twenty-four teeth: Group DDS: Delay dentin sealing (non-IDS) teeth were not treated. Group IDS: dentin sealing was applied immediately after teeth preparation. Each group was subsequently separated into three separate subgroups. Subgroups (DDS+Phc, IDS+Phc): cemented with preheated composite (Enamel plus HRi,