Objectives: A cross sectional analytic study was carried out to identify the maternal risk factors which
contribute to occurrence of low birth weight, and to determine the statistical significant differences between low
birth weight and maternal risk factors.
Methodology: A purposive sample of (400) woman was selected from AL-Elwyia Maternity Teaching Hospital
and Fatima Al-Zaharia Maternity and Pediatric Teaching Hospital. Data was collected through the interview of
mothers. Questionnaire format was designed and consisted seven parts, demographic variables, and reproductive
variables , Reproductive health variables, complications during the current pregnancy, the mother newborn
variables nutritional status for the mother , antenatal care services, and the psychosocial status for pregnant
women. Validity and reliability of the questionnaire were determined by conducting a pilot study. Descriptive
and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the most of them their age was ranged between (20-34) years, and
the highest percentage of them were graduated of primary school and less, most of them were housewives
with low socioeconomic status. The result indicated that there were five important variables contributed to the
incidence of low birth weight and these variables were gestational age nutrition status, previous low birth
weight, and psychosocial status for pregnant women during pregnancy and the age of mothers.
Recommendations: it is recommended to emphasize on prenatal care as early as possible and improve health
services rendered to mothers during pregnancy that the nurse must take the role in reducing the incidence of
LBW.
Virtual reality, VR, offers many benefits to technical education, including the delivery of information through multiple active channels, the addressing of different learning styles, and experiential-based learning. This paper presents work performed by the authors to apply VR to engineering education, in three broad project areas: virtual robotic learning, virtual mechatronics laboratory, and a virtual manufacturing platform. The first area provides guided exploration of domains otherwise inaccessible, such as the robotic cell components, robotic kinematics and work envelope. The second promotes mechatronics learning and guidance for new mechatronics engineers when dealing with robots in a safe and interactive manner. And the thir
... Show MoreHybrid architecture of ZnO nanorods/graphene oxide ZnO-NRs@GO synthesized by electrostatic self-assembly methods. The morphological, optical and luminescence characteristics of ZnO-NRs@GO and ZnO-NRs thin films have been described by FESEM, TEM, HRTEM, and AFM, which refers to graphene oxide have been coated ZnO-NRs with five layers. Here we synthesis ZnO-NRs@GO by simple, cheap and environmentally friendly method, which made it favorable for huge -scale preparation in many applications such as photocatalyst. ZnO-NRs@GO was applied as a photocatalyst Rodamin 6 G (R6G) dye from water using 532 nm diode laser-induced photocatalytic process. Overall degradation of R6G/ ZnO-NRs@GO was achieved after 90 minutes of laser irradiation while it ne
... Show MoreThe development that solar energy will have in the next years needs a reliable estimation of available solar energy resources. Several empirical models have been developed to calculate global solar radiation using various parameters such as extraterrestrial radiation, sunshine hours, albedo, maximum temperature, mean temperature, soil temperature, relative humidity, cloudiness, evaporation, total perceptible water, number of rainy days, and altitude and latitude. In present work i) First part has been calculated solar radiation from the daily values of the hours of sun duration using Angstrom model over the Iraq for at July 2017. The second part has been mapping the distribution of so
In the current study, a direct method was used to create a new series of charge-transfer complexes of chemicals. In a good yield, new charge-transfer complexes were produced when different quinones reacted with acetonitrile as solvent in a 1:1 mole ratio with N-phenyl-3,4-selenadiazo benzophenone imine. By using analysis techniques like UV, IR, and 1H, 13C-NMR, every substance was recognized. The analysis's results matched the chemical structures proposed for the synthesized substances. Functional theory of density (DFT)
has been used to analyze the molecular structure of the produced Charge-Transfer Complexes, and the energy gap, HOMO surfaces, and LUMO surfaces have all been created throughout the geometry optimization process ut
The predatory bush crickets Saga ephippigera Fischer Von Waldheim, 1846 is the largest Iraqi orthopterans and one of the most active and successful predators in the Kurdistan region. The nymphs and adults prey on all the stages of various species of insects. Twelve adult specimens were collected from Erbil Province during May 2018 and June 2021. Morphological structures of the adult insects were described and illustrated in details; important taxonomic characteristics of body regions with their appendages were chosen; and the results indicated the importance of morphological characteristics which confirmed the identification of this species correctly.
The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (