The economic development and intense competition may make economic units neglected the social aspect as a service workers and the environment, the community and focus on the economic side and achieve profitability only, which puts it in a position of accountability of trade unions and bodies, environment, health, civil society organizations and the focus of many studies accounting in order to clarify social activities and disclosed in the financial statements, increasing pressure from multiple parties calling for governments to issue laws and regulations oblige economic units to disclose complete and accurate information in a timely manner for all social activities and be subj

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

Background: The autism spectrum disorder (ASD) describes a wide range of symptoms, including difficulty with social interaction and communication skills. Controversial thinking about oral health of children with ASD, in general may have a lower hygiene level than healthy individuals, low caries rate and high body weight in comparison to healthy children. This study was conducted to assess the oral health status in relation to nutritional status among institutionalized autistic children and adolescents. Materials and methods: From 12 institutes in Baghdad, the study group contained 364 child and adolescent with ASD (Male= 294, Female=70), while control group included 441 normal child and adolescent (Male=357, Female=84) from primary and seco

Groundwater is an important source of fresh water especially in countries having a decrease in or no surface water; therefore itis essential to assess the quality of groundwater and find the possibility of its use in different purposes (domestic; agricultural; animal; and other purposes). In this paper samples from 66 wells lying in different places in Baghdad city were used to determine 13 water parameters, to find the quality of groundwater and evaluate the possibility of using it for human, animal and irrigation by calculating WQI, SAR, RSC and Na% and TDS indicators. WQI results showed that the groundwater in all wells are not qualified for human use, while SAR and RSC indicated that most samples are suitable for irrigation use, and

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

A study was carried out to determine the concentrations of trace metals in vegetables and fruits, which are locally available in the markets of Baghdad-samples of fourteen varieties of vegetables and fruits, belonging to Beta vulgaris, Brassica rapa, Daucus carota, Allium cepa, Eurica sativa, Malva silvestris, Coriandrum Sativum, Trigonella Foenum craecum, Anethum graveolens, Barassica oleracea, Phaseolus vulgaris, citrus reticulata, Py rus malus, and Punica granatum. Analysis for Cd,Pb, Mn, Fe, Co, Ni, Cu and Zn were determined by flame atomic absorption sp ectrophotometry. The results indicated that the Malva silvestris recorded the highest concentrations of Cd and Mn while Allium cepa showed the highest concentrations of Pb and Cu. But E

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to