Giardiasis is an infection caused by the protozoan flagellate parasite Giardia spp. in the intestine. G duodenalis, a species complex of diverse genotypes that tend to demonstrate host specificity, is responsible for most veterinary health related infections; production animals, companion animals, and wildlife can all be infected. Abdominal pain and diarrhea, typically accompanied by steatorrhea, are the most common symptoms of Giardiasis. Cysts or antigens in feces are commonly used to diagnose the disease. Treatment regimens vary and are dependent on the indication. Control methods must include hygiene measures. Despite direct evidence of Giardia sp transmission to humans via polluted water supplies, our analysis will focus on some r

This study aims to suggest an alternative to the use of quality agricultural soil in the brick industry (Iraq). The Late Miocene claystone bed in the Injana Formation in central Iraq was targeted through the study of 18 exposed sections that were sampled by using the trench sampling method. The claystones are characterized by quartz (36.4%) followed by calcite (32.8%), quartz (36.4%) feldspar (2.6%), gypsum (1.3%) and dolomite (0.7%), kaolinite (10.5%), illite (7.7%), chlorite (6.7%), palygorskite (6.0%) and montmorillonite (0.7%). New thermal mineral phases were formed at 950°C, including diopside (62.9%), quartz (18.4%), wollastonite (8.28%), akermanite (7.6%), Anorthite (6.25%), Nosean (4.9%), gehlenite (3.75%) and Lazurite (3.1

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

    This study carry’s out the correlation and the effect of two main variables, these variables are Job Satisfaction included six sub: wages - salaries and justice and yield, working  conditions    and services, pattern of supervision and the relationship with the manger, Relationship with colleagues, the content of the work and the variety of tasks, development and  promotion  opportunities available  to  an individual,   and Organizational Performance included  two sub variables:  Efficiency, Effectiveness.  This research was conducted using a questioner as a main tool, This questioner was distributed randomly to a research community composed of

Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

Due to the great evolution in digital commercial cameras, several studies have addressed the using of such cameras in different civil and close-range applications such as 3D models generation. However, previous studies have not discussed a precise relationship between a camera resolution and the accuracy of the models generated based on images of this camera. Therefore the current study aims to evaluate the accuracy of the derived 3D buildings models captured by different resolution cameras. The digital photogrammetric methods were devoted to derive 3D models using the data of various resolution cameras and analyze their accuracies. This investigation involves selecting three different resolution cameras (low, medium and

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri