Abstract

The objective of this research is to analyze the relationship between the strategic planning for human resources and career path, and I have tested Search the Ministry of  Health and some health centers headquarters in the Karkh district, that is applied in sample Consist of (45) Deputy Director, Head of Depts, Departmental Manager, and health center Manager.

Find interested in studying the two subjects are important and vital, at the level of organizations at the present time, namely the strategic planning of human resources and career path. To achieve the objectives of the research was designed Qusestionnair (31) items to collect  Primary data. and collected t

Beta-irradiation effects on the microstructure of LDPE samples have been investigated
using Positron Annihilation Lifetime Technique (PALT). These effects on the orthopositronium
(o-Ps) Lifetime t3, the free positron annihilation lifetime 2 t , the free-volume
hole size (Vh) and the free volume fraction (fh) were measured as functions of Beta
irradiation - dose up to a total dose of 30.28 kGy.
The results show that the values of t3, Vh and fh increase gradually with increasing Beta
dose up to a total dose of 1.289 kGy, and reach a maximum increment of 17.4%, 32.8% and
5.86%, respectively, while t2 reachs maximum increment of 211.9% at a total dose of 1.59
kGy. Above these doses, the values show nonlinear changes u

The study intends to explore the obstacles that encounter a program of rehabilitating released prisoners as perceived by prisoners themselves in tubas' province. To this end, the researcher used a questionnaire as an instrument which was applied on (150) prisoner had chosen randomly to collect the study data. The findings revealed no significant differences among obstacles the encounter program regarding to the following variables: age, detention period, and number of detention, additionally, the findings found that there is a variance of obstacles mean according to the prisoners themselves, rehabilitation program, and the facility of that program.

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