The Nuclear structure of 110-116Cd isotopes was studied theoretically in the framework of the interacting boson model of IBM-l and IBM-2. The properties of the lowest mixed symmetry states such as the 1+, 2+ and 3+ levels produced by the IBM-2 model in the vibrational-limit U(5) of Cd - isotopes are studied in details. This analysis shows that the character of mixed symmetry of 2+ is shared between and states in 110-114Cd – isotopes, the large shar goes to s, while in isotope, the state is declared as a mixed symmetry state without sharing. This identification is confirmed by the percentage of F-spin contribution. The electromagnetic properties of E2 and Ml operators were investigated and the results were analyzed. Various values of eB in the IBM-l and fixed e?= 0.104 eb and e?=0.093 e.b in the IBM-2 are used to generate the B(E2) and Q(2+). Fixed values of g? =0.31?N and g? =-0.31?N were adopted to generate the B(Ml) and ?(E2/ Ml) mixing ratios. The small values of ?(E2/Ml) which obtained for transition from MS- states to those of full symmetry support the conclusion that there may be a strong Ml transition between these states.
In this study, the stable isotop 18O and 2H has been used to investigate the interaction of surface water (SW), and groundwater (GW) in Al-Taji district/ Northern Baghdad for two seasons (March and August 2022). 16 Samples were collected from water resources in the Al-Taji district (Tigris channel, Tigris River, and groundwater), in each season water samples from 8 Tigris channel, 5 drilled wells, and 3 Tigris River were taken for the analysis of the isotopes 18O and 2H. The average analysis results of 18O and 2H in the Tigris channel, Tigris River, and groundwater were found to be -3.435‰ and -18.6094‰, -2.07167‰ and -17.81‰, -4.125‰ and -34.707‰ respectively. The results, generally, show a comparable range of isotope c
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreIsotope tracer methods were used to determine flow paths, recharge areas, and relative age for groundwater in the Ameriyat Al- Falluja Al-Anbar governorate. The isotope of surface water and groundwater in the Ameriyat Al- Falluja area was assessed using a stable isotope technique. Data stable isotope parameters (2H and 18O) for three surface water and five groundwater samples were detected. The comparison of hydrogen and oxygen isotope compositions between groundwater and Euphrates River water demonstrated that the composition of the hydrogen and oxygen isotopes from Euphrates River matched that of the local meteoric water. This indicated that rainfall is the primary source of the river wate
... Show MoreProjects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo
The tremendous benefits of using cellular phones, which began to increase and unprecedented spread worldwide last decade, were accompanied by harmful effects on the environment due to the increase in electromagnetic radiation (EMR) which be emitted from mobile phone towers. This effect on humans, animals, and plants, which is considered a form of environmental pollution, was sensed by developed countries and Environmental protection organizations. These countries have established restrictions and enacted laws to reduce their negative impact on living beings. The field survey included six major hospitals and 38 schools were distributed over the central neighbourhoods in Al-Najaf city. The results showed that power density (PD) measurement
... Show MoreThe inelastic C2 form factors and the charge density distribution (CDD) for 58,60,62Ni and 64,66,68Zn nuclei has been investigated by employing the Skyrme-Hartree-Fock method with (Sk35-Skzs*) parametrization. The inelastic C2 form factor is calculated by using the shape of Tassie and Bohr-Mottelson models with appropriate proton and neutron effective charges to account for the core-polarization effects contribution. The comparison of the predicted theoretical values was conducted with the available measured data for C2 and CDD form factors and showed very good agreement.
Photobiomodulation (PBM) is a form of the use of visible red and Near-infrared (NIR) light at low power, where a laser light photon is absorbed at the electronic level, without heat production. PBM can be applied in wide range of treatment to help the wound, inflammation, edema, and pain reduction. However, there is a lack of scientific documentation regarding its actual effects. Objectives: This study assesses the impact of PBM on the release of M1-related cytokine in monocyte cells with particular emphasis on interleukin-1β (IL-1β) and Tumour Necrosis Factor α (TNF-α). Methods: Tamm-Horsfall Protein 1 (THP-1) macrophages M1 cells have been exposed to the light from the diode laser of 850nmat different doses (0, 0.6, 1.2 and 3.
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
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