The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were

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

Wearable sensors are a revolutionary tool in agriculture because they collect accurate data on plant environmental conditions that affect plant growth in real-time. Moreover, this technology is crucial in increasing agricultural sustainability and productivity by improving irrigation strategies and water resource management. This review examines the role of wearable sensors in measuring plant water content, leaf and air humidity, stem flow, plant and air temperature, light, and soil moisture sensors. Wearable sensors are designed to monitor various plant physiological parameters in real-time. These data, obtained through wearable sensors, provide information on plant water use and physiology, making our agricultural choices more informed an

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % we

New complexes have been prepared from the new ligand [N1,N5-bis(3-hydroxyphenyl)-2- oxopentanediamide] derived from 2-Oxoglutaric acid and 3-aminophenol. Accordingly its binudear Mn(II),Co(II),Ni(II),Pd(II) and VO(II) complexes were prepared.. These compounds have been characterized by FT-IR, UV-Vis,Mass, 1H-NMR spectra, TGA curve, Chloride containing ,Molar conductance and atomic absorption. The characterization results gave binuclear complexes and pentadentate coordination and tetrahedral geometry for each Cobalt, Nickel, Manganese and Copper complexes otherwise Palladium complex gave a square planar geometry and Vanadium complex gave a square pyramidal geometry and the ligand is tetradentate. The biological activities for the new compoun

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