Phlebotomus papatasi sand fly is the main vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Iraq. The aim of this study was to assess and predict the effects of climate change on the distribution of the cutaneous leishmaniasis (CL) cases and the main vector presently and in the future. Data of the CL cases were collected for the period (2000-2018) in addition to sand fly (SF) abundance. Geographic information system, R studio and MaxEnt (Maximum entropy niche model) software were used for analysis and predict effect of (elevation, population, Bio1-19, and Bio28-35) on CL cases distribution and SF occurrence. HadGEM2-ES model with two climate change scenarios, RCP 4.5 and RCP 8.5 were used for future projections 2050. The results showed th

Abstract:

The achievement of economic and social welfare for individual is the main target to all policies that adopted by all countries worldwide either were economic, social, political or others. The obtaining of education by individuals and especially the higher education is one of the most important determinates in achieving the wellbeing and lasted economic development. This is because via the higher education new fields can be opened in front of individuals in order to get adequate jobs associated with their scientific specialization. This is allowing educated individuals gain higher income that can reduce the gap of income inequality.

Thus, this paper aims to analysis the n

In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.

The optimum conditions for the production of neutral protease from local strain Aspergillus niger var carbonarius by solid – state fermentation system (Wheat bran) moisted with 0.2 M phosphate buffer (PH7.0) . the hydration ratio was 1:5 (V:W) . the concentration of inoculum was 1×106 spores per 10 gram of solid materials , initial P H 6.5 and 96 hours of incubation period at 30? C .the enzyme activity was 1300 unit / ml and specific activity was 1550 unit / mg protein .

Background: Wound healing is a complex dynamical interaction between various cell types, the extracellular matrix, cytokines, and growth factors. osteoponetin is a substance that acts as an anti-inflammatory. Aims of study: The study was designed to identify the role of local exogenous applications of osteopontin on wound healing (in cheek skin). Materials and methods: Thirty adult male albino rats weighting an average of (250-300gm) used in this study, incisional wounds were made in the skin of the cheek of rat and they were divided into the following groups: A-Control group: 15 rats treated with 1µ l of normal saline B-Experimental groups: 15 rats treated with topical application of 1µl osteopontin. The scarification of animals we

The construction sector consumes large amounts of energy during the lifetime of a building. This consumption starts with manufacturing and transferring building materials to the sites and demolishing this building after a long time of occupying it. The topic of energy conservation and finding the solution inside the building spaces become an important and urgent necessity. It is known that the roof is exposed to a high amount of thermal loads compared to other elements in a building envelope, so this needs some solutions and treatments to control the flow of the heat through them. These solutions and treatments may be achieved by using nanomaterials. Recently, nanomaterials have high properties, so that this made them go

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen