Background: Very low birth weight (VLBW) neonates constitute approximately 4–7 percent of all live births and their mortality is very high.
Objective: to find out if there is a relationship between Very Low Birth Weight Neonates and increased neonatal mortality for age 0 to 7 days.
Methods: A retrospective study of VLBW neonates admitted to NICU at Ibn Al- Baladi Pediatrics and Maternity hospital over one year (2012)were studied, The study period was from April till August 2013. Exclusion criteria were: (1) neonates weighing less than 700 g and with gestational age less than 24 weeks (abortion) (2) death in the delivery room (3) neonates weighing more than 1500 g. (4) Postnatal age more than 7 days. The outcome measure was in-hos

B aa cc kk gg r oo uu nn dd : Very low birth weight (VLBW) neonates constitute approximately 4–7 percent of all live births and their mortality is very high. O bb j ee cc t i vv ee: to find out if there is a relationship between Very Low Birth Weight Neonates and increased neonatal mortality for age 0 to 7 days. M ee t hh oo dd ss A retrospective study of VLBW neonates admitted to NICU at Ibn Al- Baladi Pediatrics and Maternity hospital over one year (2012)were studied, study period was from April till August 2013. Exclusion criteria were: (1) neonates weighing less than 700 g and with gestational age less than 24 weeks (abortion) (2) death in the delivery room (3) neonates weighing more than 1500 g. (4) Postnatal age more than 7 days.

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

The objective of this experiment was to determine the effects of dietary supplementation with different fat sources on blood parameters of Japanese quail (Coturnix coturnix japonica). Eighty four 7-week old laying quail were randomly assigned to 4 treatment groups (21 birds per group) with 3 replicates for each treatment group and fed for three months on a commercial diet supplemented with 3% of either sunflower oil (T1), flax oil (T2), corn oil (T3) or fish oil (T4). The birds received water and feed ad libitum during the experiment. During the last month of experiment blood samples were collected fortnightly from each bird. The first blood samples collection was used to determine fresh blood parameters, while the second blood samples coll

Anastatica hierochuntica L. is distributed throughout Arabain Peninsula, and elsewhere it is locally called "Kuffe Maryam" .All parts of the plant are used in folk medicine. This study amid to investigate the effect of aqueous extract of anastatica hierochunctica L. on the cancer cell lines AMN-3. Anti cancer activity of aqueous extract of anastatica hierochunctica L. showed anticancer activity against AMN-3 cell line for twelve concentrations (0.04, 0.09, 0.195, 0.39, 0.78, 1.56, 3.125, 6.25, 12.5, 25, 50, 100) mg/mL in comparison with negative control.

Anastatica hierochuntica L. is distributed throughout Arabain Peninsula, and elsewhere it is locally called "Kuffe Maryam" .All parts of the plant are used in folk medicine. This study amid to investigate the effect of aqueous extract of anastatica hierochunctica L. on the cancer cell lines AMN-3. Anti cancer activity of aqueous extract of anastatica hierochunctica L. showed anticancer activity against AMN-3 cell line for twelve concentrations (0.04, 0.09, 0.195, 0.39, 0.78, 1.56, 3.125, 6.25, 12.5, 25, 50, 100) mg/mL in comparison with negative control.

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a