Parkinson’s disease (PD) consider as a progressive ageing neurodegenerative disease, Parkinson’s consider as a heterogenous disease, with mainly initiate through correlation between genetic and epigenetic by inducing of different factors on some related genes, these factors like (environmental, toxicants, nutrition, heavy metals, pesticides, some drugs) and also(trauma on head ,strokes) in addition to unknown reasons which cause an idiopathic PD .Current study aims to focusing on specific related PD gene called SNCA by single nucleotides polymorphism (rs2619363) as a risk factor for PD initiation disease in PD patients in addition to study the effect of polymorphisms on random Iraqi patients with different gastrointestinal

Ten isolates were collected from different clinical sources from laboratory in medicine century . These isolates were belonging to the genus Salmonella depending on morphological and biochemical tests . The antibiotic scussptibility tests against 10 antibiotics were examined , and it was found that the 60% isolates have multiple resistant to antibiotic ,(70%) of isolates were resistant to ampicillin,(50%) were resistant to augmentin ,(40%) were resistant to ceftriaxone ,(20%) were resistant to cefotaxime and (10%) were resistant to ciprofloxacin and tetracycline while all isolates showed sensitivity to piperacillin, imipenem, amikacin and erythromycin .The ability of Salmonela isolates to produce ?-lactamase enzymes were tested usin

Abstract

The current research is attempt to test the reflection of the lean management on the human resources management practices of two of the most important communication companies operating in Iraq (`Zain & Asia cell), The research aims to Determine the extent of adoption of the lean management approach in the two researched companies, as it improving human resource management practices. The research problem represented in the existence of lack of in some aspects of the application the lean management approach in service sector and neglecting the impact of its tools on the human resource management practices. For this purpose three principle research hypotheses has been formulated, first there is a correlation rel

The present paper describes a static model of malware detection and employs a tri-class prevention policy that operates on the EMBER 2024 Win64 partition. A LightGBM classifier trained on 1,040,000 samples and 804 static PE features achieves AUC-ROC = 0.9979, precision = 98.7%, recall = 97.4%, and F1 = 0.9805 on the temporally-split 240,000-sample test set. An innovative Tri-class Threshold Scheme (BLOCK/SUSPICIOUS/ALLOW) obtained by constrained F2-score optimisation on a separate validation set obtains 97.9% malware detection with 98.1% benign pass rate. Efficient model scoring is verified by mean per-sample model inference latency of 2.30 ms (P99: 2.70 ms) measured on pre-extracted EMBER features, future work is characterized by a complet

Pedagogical stylistics refers to the application of the tools of stylistics in the teaching of the English language as a foreign or a second language.  Teaching and learning poetry is challenging. Thus, pedagogical corpus stylistics (Henceforth, PCS) approach has been introduced to Iraqi undergraduate foreign language learners (EFL) to guide them to analyze poetic language.  The study aims to make students interact with authentic examples of poetic language and answer questions about it. The main objective of the study is to examine whether PCS tools enable the learners to provide linguistic evidence from the poetic texts they are exposed to. This in turn ensures objective poetic analyses. Moreover, it aims to enable EFL Iraqi stu

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin

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,