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Green Innovation and its Impact in Reinforcing Sustainable Competitive Advantage: An Exploratory Study of Opinions of a Sample of Employees in the Karungi group in Kirkuk
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The development of the world, and in light of the intensity of competition highlighted the need to research and create a sustainable competitive advantage is sustained from an internal source in the company earned by the scarcity and difficulty of imitation by competitors, and this source is green innovation. In order to achieve the objective of the research, which is the diagnosis and analysis of the relationship between green innovation (in products, processes) and sustainable competitive advantage in the group of companies Kronji, was developed a default model of the research reflects the nature of the relationship and influence among its variables, the research adopted the questionnaire as a key tool for collecting data and information , Distributed to a sample of (94) workers tested using some statistical tools of data collected by the adoption of the program (SPSS.V.24). The research came to a number of conclusions, the most important one which is the green innovation , it linked and has a significant impact on sustainable competitive advantage, The biggest impact was on sustainable competitive advantage after green innovation in products, In view of the above, a number of proposals were presented, the most important of which is the need for the company's management to be concerned with green innovation through the establishment of green training courses to identify the importance of many concepts and standards that serve the environmental orientation, because the environmental trend has become a standard of achieving sustainable competitive advantage.  

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Serum Adropin and Apelin as Potential Markers PredictingAcute Heart Failure-associated Renal Dysfunction among Elderly Iraqi Patients
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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for New COVID-19 Cases Using Recurrent Neural Networks and Long-Short Term Memory
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     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470

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Publication Date
Thu May 05 2022
Journal Name
Karbala International Journal Of Modern Science
Nigella sativa Methanol Extract Inhibits PC-3 Cell Line Colonization, Induced Apoptosis, and Modulated LC3-based Autophagy
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Nigella sativa has various pharmacological properties and has been used throughout history for a variety of reasons. However, there is limited data about the effects of N. sativa (NS) on human cancer cells. This study aimed at observing the roles of methanolic extract of N. sativa on apoptosis and autophagy pathway in the Human PC3 (prostate cancer) cell line. The cell viability was checked by MTT assay. Clonogenic assay was performed to demonstrate clonogenicity and Western blot was used to check caspase-3, TIGAR, p53, and LC3 protein expression. The results demonstrated that PC3 cell proliferation was inhibited, caspase-3 and p53 protein expression was induced, and LC3 protein expression was modulated. The clonogenic assay showed that PC3

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Emulsion Liquid Membrane for Pesticides Removal from Aqueous Solution: Emulsion Stability, Extraction Efficiency and Mass Transfer Studies
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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

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Publication Date
Fri Dec 20 2019
Journal Name
Iet Circuits, Devices & Systems
Multi‐bit error control coding with limited correction for high‐performance and energy‐efficient network on chip
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In the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res

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Publication Date
Mon Aug 08 2022
Journal Name
Egyptian Journal Of Chemistry
Synthesis, Characterization, Spectroscopic, Thermal and Biological Studies for New Complexes with N1, N2-bis(3-hydroxyphenyl) Oxalamide
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Publication Date
Sat Jun 02 2018
Journal Name
Agroforestry Systems
Biomass and buffer management practice effects on soil hydraulic properties compared to grain crops for claypan landscapes
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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Relationship between very low birth weight neonates and increased neonatal mortality for age 0 to 7 days
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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

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Publication Date
Wed Mar 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Design and implementation monitoring robotic system based on you only look once model using deep learning technique
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<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

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
Comparing Ionospheric MUF using IRI16 Model with Mid-Latitude Ionosonde Observations and Associated with Strong Geomagnetic Storms
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High frequency (HF) radio wave propagation depends on the ionosphere status which is changed with the time of day, season, and solar activity conditions. In this research, ionosonde observations were used to calculate the values of maximum usable frequency (MUF) the ionospheric F2- layer during strong geomagnetic storms (Dst ≤ -100 nT) which were compared with the predicted MUF for the same layer by using IRI-16 model. Data from years 2015 and 2017, during which five strong geomagnetic storms occurred, were selected from two Japanese ionosonde stations (Kokubunji and Wakkanai) located at the mid-latitude region. The results of the present work do not show a good correlation between the observed and predicted MUF values for F2- laye

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