Inelastic longitudinal electron scattering form factors to 2+ and 4+ states in 65Cu nucleus has been calculated in the (2p3/2 1f 5/2 2p1/2) shell model space with the F5PVH effective interaction. The harmonic oscillator potential has been applied to calculate the wave functions of radial single-particle matrix elements. Two shell model codes, CP and NUSHELL are used to obtain results. The form factor of inelastic electron scattering to 1/21−, 1/22−, 3/22−, 3/23−, 5/21−, 5/22− and 7/2- states and finding the transition probabilities B (C2) (in units of e2 fm4) for these transitions and B (C4) (in units of e2 fm8) for the transition 7/2-, and comparing them with experimental data. Both the form factors and reduced transition pr

The aim of this work is to study the correlation between the electrons for Li atom in ground state through the calculation of the inter-particle distribution function f (r12) and inter-particle expectation values . By using the f(r12) function for KL shell in both singlet and triplet state .The Fermi hole have been evaluated .In this work the Hartree-Fock wave function (1993) have been used.

Abstract

Objective(s): To determine the interventional program effectiveness on nurses' practices concerning diet instructions for orthopedic patients treated by internal fixation devices.

Methodology: A quantitative approach using prexperimental design is conducted to determine the effectiveness of an interventional program on nurses’ practices regarding orthopedic patients diet instruction and teaching after internal fixation implemented. The study has started from 1^st of April 2022 and ended on 15^th of December, 2022. The conduction of the study in Misan governorate  / Al-Zaharawy surgical hospital. A non-probability, purpo

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Introduction: Implant stability is usually measured with resonance frequency analysis (RFA) and damping capacity assessment (DCA). This study aimed to measure primary and secondary stabilities using 3 devices that are based on these methods, namely; RFA (Osstell^®) and DCA (Periotest^® and AnyCheck^®) to assess the correlations of the measurements obtained by these devices and the correlations between implant stability and insertion torque. Material and Methods: This observational prospective study included 35 dental implants. The implant stability was measured using the 3 devices. Mann–Whitney U

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai