Background: Plantar heel pain is a clinical syndrome characterized by pain and tenderness beneath the heel which is typically worse in the morning and improves after the first few steps in the day. It is a common and frequently disabling clinical complaint that may be caused by a broad spectrum of osseous or soft tissue disorders^.

Objective: To evaluate the effectiveness of an operation of multiple drilling of calcaneum for resistant plantar heel pain syndrome.

Methods: During the period from November 2012 to August 2016, 17 patients (17heels) were enrolled in a cohort clinical study at the orthopedic unit in AL-Sheikh Zayed and Al-Wassity Hospitals.

Research deals the crises of the global recession of the facets of different and calls for the need to think out of the ordinary theory and find the arguments of the theory to accommodate the evolution of life, globalization and technological change and the standard of living of individuals and the size of the disparity in income distribution is not on the national level, but also at the global level as well, without paying attention to the potential resistance for thought the usual classical, Where the greater the returns of factors of production, the consumption will increase, and that the marginal propensity to consume may rise and the rise at rates greater with slices of low-income (the mouths of the poor) wi

Experimental measurements of viscosity and thermal conductivity of single layer of graphene . based DI-water nanofluid are performed as a function of  concentrations (0.1-1wt%) and temperatures between (5 to 35ºC). The result reveals that the thermal conductivity of GNPs nanofluids was increased with increasing the nanoparticle weight fraction concentration and temperature, while the maximum enhancement was about 22% for concentration of 1 wt.% at
35ºC. These experimental results were compared with some theoretical models and a good agreement between Nan’s model and the experimental results was observed. The viscosity of the graphene nanofluid displays Newtonian and Non-Newtonian behaviors with respect to nanoparticles concen

Abstract

The study aims to identify the common fears of preschool children and their relationship to the approaches to parental treatment in South Al Batinah Governorate from their mother’s point of view. Total of (466) mothers were selected as the study sample. The researcher used the scale of common fear and the scale of parental treatment approaches. The results of the study have shown that the most common fear among the study sample was (the fear of darkness) in the first level with a rate of 75.03%, and in the second level came the item (my child is afraid to sleep alone) by 72.74%, in the third level came to the item (fear of seeing insects) with a rate of 67.59%, and the last one was (the fear of rain) w

The synthesis, characterization and mesomorphic properties of two new series of triazine-core based liquid crystals have been investigated. The amino triazine derivatives were characterized by elemental analysis, Fourier transforms infrared (FTIR), 1HNMR and mass spectroscopy. The liquid crystalline properties of these compounds were examined by differential scanning calorimetry (DSC) and polarizing optical microscopy (POM). DSC and POM confirmed nematic (N) and columnar mesophase textures of the materials. The formation of mesomorphic properties was found to be dependent on the number of methylene unit in alkoxy side chains.

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni