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.

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

In this work, the precursor [2-(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylimino)acetic acid] was synthesised from 4-aminoantipyrine and glyoxylic acid, this precursor has been used in the synthesis of new multidentate ligand [2-((E)-3-(2-hydroxyphenylimino)-1,5-dimethyl-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylimino)acetic acid][H2L] type (N2O2). The ligand was refluxed in ethanol with metal ions [VO(II), Mn(II), Co(II) and Ni(II)] salts to give complexes of general molecular formula:[M(H2L)2(X)(Y)].B, where: M=VO(II), X=0, Y=OSO3-2, B=2H2O; M=Mn(II),Co(II) ,X=Cl, Y=Cl, B=0; M=Ni(II), X=H2O, Y=Cl, B=Cl. These complexes were characterised by atomic absorpition(A.A), F.T-I.R., (U.V-Vis)spectroscopies (1H,13C NMR for ligand only), alon

In this study, a novel application of lab-scale dual chambered air-cathode microbial fuel cell (MFC) has been developed for simultaneous bio-treatment of real pharmaceutical wastewater and renewable electricity generation. The microbial fuel cell (MFC) was provided with zeolite-packed anodic compartment and a cation exchange membrane (CEM) to separate the anode and cathode. The performance of the proposed MFC was evaluated in terms of COD removal and power generation based on the activity of the bacterial consortium in the biofilm mobilized on zeolite bearer. The MFC was fueled with real pharmaceutical wastewater having an initial COD concentration equal to 800 mg/L and inoculated with anaerobic aged sludge. Results demo

Abstract

Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through eviden