raisin on mice in comparison with negative (phosphate buffer saline (PBS) and positive Mitomycin-C (MMC) controls. Moreover, the effect on fertility hormones (follicles stimulation hormone/FSH, lutenising hormone/LH) was also measured. The effect of the extracted samples were measured by employing cytogenetic analysis which included (the mitotic index (MI), chromosomal aberrations (CAs) and micronucleus (MN)) parameters. Results showed that significant increase in MI and significant reduction in both CAs and MN percentage were seen after treatment with both alcoholic and water extracts of the two raisins and alcoholic extracts was more effective than water extracts. On the other hand both the gold and black raisin enhanced the levels of the

Incorporating the LiDAR sensor in the most recent Apple devices represents a substantial development in 3D mapping technology. Meanwhile, Apple's Lidar is still a new sensor. Therefore, this article reviews the potential uses of the Apple Lidar sensor in various fields, including engineering and construction, focusing on indoor and outdoor as-built 3D mapping and cultural heritage conservation. The affordable cost and shorter observation times compared to traditional surveying and other remote sensing techniques make the Apple Lidar an attractive choice among scholars and professionals. This article highlights the need for continued research on the Apple LiDAR sensor technology while discussing its specifications and limitations. A

Objectives: The study aims to evaluate the application of monitoring indicators for maternal, newborn and
child health through the evaluation of impact and coverage health indicators and to evaluate the usefulness of the
application of these indicators at sub primary health care centers in Baghdad City.
Methodology: A descriptive comparative design, which is using the evaluation approach, has been steered at
Sub Primary Health Centers of Baghdad City in order to evaluate the application; impact and coverage, and the
usefulness of monitoring indicators for maternal, newborn and child health from December 4th 2017 to April 29th
2018. A multistage, "non-probability" convenient, sample is selected for the present study. A t

Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

The research was carried out in lathhouse on one-year-old apple seedlings of the Ibrahimi variety in the Karma-Fallujah region for the 2021 growing season to study the effect of methods of adding nano-fertilizer and humic acid on seedling growth. A two-factor experiment was designed according to a randomized complete block design, with three replicates and two seedlings per experimental unit, so the number of seedlings was 54. The first factor includes NPK nanofertilizer at three levels (0- and 2-ml L-1 foliar spray and 5 ml L-1 soil application). The second factor is humic acid at three levels (0 and 5 g of seedlings - 1 foliar spray and 10 g of seedlings - 1 soil application). The results of the study show that the NPK nano-fertil

Conducted Althilelat chemical models of crude oil back to the reservoir Fertile from the fields of Baghdad and Kut and models of crude oil back to the reservoir ??????? of Haklbe Tikrit and Baghdad were calculated their properties Alvezaúah Kalkthaqh and weight, quality and degree of August j (API) and know the quality Nfothma that was light or heavy and make the comparison between Alinvtin also conducted chemical analyzes of the two models of Almia associated with each of the oil above Almkmnin and measured Ktvthma and Zojithma and concentrations of some dissolved salts in them and clarify the relationship between the oil reservoir and water associated with oil fields...

In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be