Background: Chronic periodontitis defined as “an infectious inflammatory disease within supporting tissues of the teeth, progressive attachment loss and bone loss". Aggressive periodontitis is rare which in most cases manifest themselves clinically during youth. It characterized by rapid rate of disease progression .Pro-inflammatory chemokines organized inflammatory responses. Granulocyte chemotactic protein 2 is involved in neutrophil gathering and movement. The purpose of the study is to detect serum of Granulocyte Chemotactic Protein 2 and correlate to periodontal condition in patients with chronic periodontitis, Aggressive periodontitis and Healthy Control subjects and measurement the count of neutrophils for the studied groups. S

The density functional B3LYP is used to investigate the effect of decorating the silver (Ag) atom on the sensing capability of an AlN nanotube (AlN-NT) in detecting thiophosgene (TP). There is a weak interaction between the pristine AlN-NT and TP with the sensing response (SR) of approximately 9.4. Decoration of the Ag atom into the structure of AlN-NT causes the adsorption energy of TP to decrease from − 6.2 to − 22.5 kcal/mol. Also, the corresponding SR increases significantly to 100.5. Moreover, the recovery time when TP is desorbed from the surface of the Ag-decorated AlN-NT (Ag@AlN-NT) is short, i.e., 24.9 s. The results show that Ag@AlN-NT can selectively detect TP among other gases, such as N2, O2, CO2, CO, and H2O.

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

Illegal web platforms known as phishing websites adopted high-risk threats to mimic legitimate online platforms in order to steal important data of users, like login credentials and financial information. These forged platforms often involve internet tactics to attract unsuspecting victims through URL manipulation. Many recent machine learning techniques are proposed for detecting web attackers. However, under an increasing number of internet users, they struggle to reveal recent phishing strategies for stealing sensitive information covered by fake websites. This study presents a comprehensive methodology for detecting phishing websites through a proposed hybrid technique (RF_PSO) by involving the Random Forest (RF) classification algorith

The diagnosis of acute appendicitis (AA) sometimes is illusive and the accompanying clinical and laboratory manifestations cannot be used for definitive diagnosis. Objective: This study aimed to evaluate the diagnostic value of neutrophil/lymphocyte ratio (NLR) in detection of AA. Materials and Methods: This is a cross-sectional study that included a total of 80 adult patients with AA and 62 age- and gender-matched patients with abdominal pain due to causes other than AA. Three milliliter of peripheral blood were collected from each participant. The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. Receiver operating characteristic curve was used to assess the diagnostic value of NLR in detection

Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

Many carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve