This research aims to know the role and impact of participation in the capabilities of human resources programs, and for the purpose of measuring it has been determined the dimensions of these two variables by relying on standards for this purpose, was chosen as the Ministry of Higher Education and Scientific Research / device supervision and scientific calendar as one of the important departments in the ministry and includes a large number of individuals at different organizational levels for the purpose of answering a questionnaire prepared for the purpose of measurement and access to the results and the achievement of the objectives of the research and which ha

Abstract [email protected] Background: Acute Traumatic Stress Disorder (ATSD) might be complicated by Post Traumatic Stress Disorder (PTSD). Psychological First Aid (PFA) said to be helpful to reduce the possibility of reduction of ASD and PTSD symptoms. PFA is simple procedure to deliver help & support to victims, may be by some one close to him, quietly and professionally. Iraq has and is still experiencing, continuous traumatic stresses. ATSD is especially seen in war such as during the Gulf War, Embargo and nowadays under the current American occupation. With the extreme shortage of recourses and the given late priority to psychological problems and intervention have disastrous consequences on the psycho-social wellbeing of peop

In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a prior

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

Infrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector

The dynamic thermomechanical properties, sealing ability, and voids formation of an experimental obturation hydroxyapatite-reinforced polyethylene (HA/PE) composite/carrier system were investigated and compared with those of a commercial system [GuttaCore (GC)]. The HA/PE system was specifically designed using a melt-extrusion process. The viscoelastic properties of HA/PE were determined using a dynamic thermomechanical analyser. Human single-rooted teeth were endodontically instrumented and obturated using HA/PE or GC systems, and then sealing ability was assessed using a fluid filtration system. In addition, micro-computed tomography (μCT) was used to quantify apparent voids within the root-canal space. The data were statistically analys

Purpose: This study aimed to assess the thickness of alveolar bone of maxillary and mandibular incisors from orthodontics perspective. Materials and Method: A total of 73 Cone beam computed tomography for Iraqi patients (47 females and 26 males) were included in this study. The selected images were captured and imported to AutoCAD database software to perform the measurement. To measure alveolar bone thickness, a reference line was drawn through the long axis of each incisor, from the incisal edge to the root apex. Then, labial and lingual/palatal perpendicular lines were drawn to the reference line at 3, 6, and 9mm apically from the cemento-enamel junction (CEJ). Results: The buccal bone is generally thinner than the lingual/palata

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea