Herbal remedies are used in induction of lactation. In view of that .Borage Officinalis was employed to ensure an abundant milk supply or rectify milk insufficiency .However, this remedy has not been scientifically tested .The animals were treated with the aqueous extract of Borage Officinalis flowers at a daily concentration of 100 mg / kg body weight /ml for each rat through Oro-gastric tube for 14 days. Animals were subdivided into subgroups according to their physiological status. Mammary glands of these animals were processed for histological, histochemical and immunohistochemical studies. Parameters indicated that the aqueous extract of Borage Officinalis flowers induced lactogenesis in the mammmary glands of virgin and pregnant rats

The self-evident truth existing in today's business environment is the continuity of change and its continuity and turmoil, also its increase over time as it is more abundant, abundant, wide and complex than ever before, and it is the dominant feature in the business environment, as different organizations and operating units can find themselves shifting from the top to the bottom. And then it requires its departments to strive to adapt to these rapid and turbulent shifts and changes by bringing about a series of organizational and adaptive changes that are not limited to one organizational aspect only but rather include all organizational components. Accordingly, this research came to determine the readiness of public organizations to chan

The high bounce activity according to the fosbery way is regarded as of the difficult sports concerning its way of training and perfection due to hard technique of its performance on one hand and because it depends on the player’s ability to overcome body weight resistance against the gravity. In addition to the strong ability to control the body posture when leaving the land and flying over the barrier. This activity needs to high plosion power at the moment of bouncing and this plosion depends on the period of bouncing, so the two researchers aimed to use a mechanical bouncing platform and an electronic one through several training by one foot and both feet in different directions and positions in order to reduce the time of bouncing an

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete