The nature of interstellar matter has been explained by presenting a model consists of organic and inorganic materials mixture in the wavelength range (9-12) μm.
Laboratory samples of different concentrations of these materials were prepared and examined by using FTIR spectrometer device. Results of spectra for these samples are compared with observation of Trapezium nebula in the same wavelengths range. The best mixture model found to fit with observation is a sample consists of:11.96 % (Diatom silica (98% pure silica)) + 14.35 % (Carbon (C)) +27.63 % (Tryptophan amino acid) + 46.06 % (Tyrosine amino acid), this are done using convolution technique. Interstellar matter could be explained biologically, as the contribution of organic

Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to mea

            Semi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel

The development of technology used in computerized programs is considered on of the most important topics that is responsible for creating tools that can be used in the business environment, the audit profession is one of those professions that received this development. In order for this profession to be more effective, there must be a tool based on sound (correct) scientific basis that can be based upon to enhance the quality of auditing. The research also aims to propose a computerized program to plan the auditing process according to the methods appropriate to the working environment in the audit offices and companies in Iraq. The computerized program was applied to the research sample and the hypothesis of the research has been prov

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

This study deals with air pollution tolerance index (APTI) and anatomical variation in leaves of two species of terrestrial plants Ficus sp. and Conocarpus sp. that have bee commonly the separated along roadsides in many stations within Babylon province. APTI values of both species were less than 10 during study period which represented sensitivity of these plants to air pollution. There are Anatomical responses to pollution in the leaves of both studied species. Main adaptations included increased thickness of parenchyma cell walls with clear dark deposits in sections of Ficus sp. from sections of stations 2 and 4 which represent polluted stations. Conocarpus sp. main adaptation included stomata increased in density and decreased in size w

     This research was conducted to determine the effect of different concentrations of (milkthistle) Silbum marianum   leaves extracts on some plant pathogenic fungi included:      Fusarium oxysporum, Alternaria sp., and Botrytis cinerea.            Results showed the high antifungal activity of milk thistle leaves extract; this was evident at high concentration of extract (80) mg\ml, which completely inhibited the radial growth on solid media (PDA) for pathogens Fusarium oxysporum and Botrytis cinerea. While the spores of pathogen Alternaria sp. was able to  grow in all concentration which used in this study.  &n