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Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This 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 (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic>), chroma (<italic>C</italic>), whiteness (WI), yellowness (YI), and browning index (BI). ANFIS well‐predicted milk fat and moisture content using quadratic and two‐factor interaction models with mean errors of .00858–.01260 and correlation coefficient of .8051–.8205. Stability tests showed <italic>L</italic>* and WI reduced while <italic>a</italic>*, <italic>b</italic>*, Δ<italic>E</italic>, <italic>h</italic>, <italic>C</italic>, YI, and BI increased during the storage. NP milk had 77.21% higher half‐life than CP, as predicted by ANFIS modeling. Findings indicated milk quality characteristics could be estimated based on physical parameters (e.g., color components), contributing to sustainable food production.</p></sec><sec><title>Practical applications

The findings offer practical applications of artificial intelligence (AI) as an innovative monitoring and prediction technique to enhance food quality and sustainability. The proposed methodology makes the real‐time prediction of milk quality feasible by leveraging AI and physical parameters. An adaptive neuro‐fuzzy inference system (ANFIS) accurately predicts moisture and fat contents according to color values, facilitating quality assessment. Stability tests during cold storage provide insights into milk quality changes over time, aiding in determining key parameters in predictive modeling. The proposed approach was found to be applicable to both conventional and non‐thermal pasteurized milk. This study also provides a step‐by‐step protocol, facilitating the implementation of emerging technologies in the food industry.

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Publication Date
Thu May 13 2021
Journal Name
Al-kindy College Medical Journal
Vitamin D deficiency/ insufficiency and some of its related factors in a sample of Iraqi pregnant women and their neonates at Al-Elwiya Maternity Teaching Hospital during 2019
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Background: Vitamin D deficiency/ insufficiency is common in different age groups in both genders especially among pregnant women and neonates where it is associated with several adverse outcomes including preeclampsia and preterm delivery.  

Objectives: To assess the extent of vitamin D deficiency/ insufficiency among mothers and their neonates and some factors related to it and identify some adverse outcomes of the deficiency/ insufficiency on neonates (preterm birth and low birth weight).

Subject and Methods: A cross-sectional study was conducted on 88 Iraqi pregnant women and neonates admitted to “Al-Elwiya teaching hospital for maternity” in Baghdad- Al

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Publication Date
Thu Feb 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Self-Medication Towards Antibiotic Use Among Non- Medical University Staff (Conference Paper )#
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The use of antibiotics without prescription (self-medication) is growing globally and is associated with increased bacterial resistance, ineffective treatment and adverse reactions. This study aimed at assessing the practice of antibiotic self-medication in the Iraqi population. A cross-sectional study design was adopted in this work. The sample was comprised of 303 staff members from the non-medical colleges in Iraq. An online questionnaire was distributed between the 29th of June to the 14th of September 2021 to collect data including socio-demographic characteristics and questions about antibiotic self-medication. Most of the participants had a university degree and a moderate monthly income. The majority (88%) h

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Publication Date
Tue Jan 17 2017
Journal Name
British Journal Of Cancer
Aurora B expression modulates paclitaxel response in non-small cell lung cancer
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Publication Date
Mon Jun 01 2020
Journal Name
Pjmhs Jun
Non-polio Enterovirus Isolation in children with acute Flaccid Paralysis in Iraq
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Aim This study is an overview of NPEV investigated during AFP surveillance programs for the period 2010–2017 in Iraq. Methods Stool samples from 4296 AFP cases and 2933 healthy contacts among children less than 15 years of age were processed for virus isolation as a part of AFP surveillance for the Global Polio Eradication Program in Iraq at National Polio Laboratory. NPEV detection was performed by virus isolation on cell culture according to WHO recommendations. Results The NPEV isolation rate was 14% of total AFP cases and 14.5% of healthy contacts. The infection rate was higher in males than females with a male/female ratio of 1.5: 1. The highest NPEV infection rate was observed among the children aged 1-2 years and decrease significa

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Thu Oct 01 2020
Journal Name
Ieee Transactions On Very Large Scale Integration (vlsi) Systems
Low-Power, Highly Reliable Dynamic Thermal Management by Exploiting Approximate Computing
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With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw

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Publication Date
Fri Jan 01 2016
Journal Name
Applied Numerical Mathematics
Multiple time-dependent coefficient identification thermal problems with a free boundary
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Publication Date
Sun Jan 01 2017
Journal Name
Optics & Laser Technology
Finite element thermal analysis for PMMA/st.st.304 laser direct joining
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This work is concerned with building a three-dimensional (3D) ab-initio models that is capable of predicting the thermal distribution of laser direct joining processes between Polymethylmethacrylate (PMMA) and stainless steel 304(st.st.304). ANSYS® simulation based on finite element analysis (FEA) was implemented for materials joining in two modes; laser transmission joining (LTJ) and conduction joining (CJ). ANSYS® simulator was used to explore the thermal environment of the joints during joining (heating time) and after joining (cooling time). For both modes, the investigation is carried out when the laser spot is at the middle of the joint width, at 15 mm from the commencement point (joint edge) at traveling time of 3.75 s. Process par

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Effect of Laser Surface Modification on the Corrosion Resistance of Dental Alloys in Artificial Saliva Containing Alcoholic Beverages
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The objective of this study is to demonstrate the corrosion behavior of dental alloys Co-Cr-Mo, Ni-Cr-Mo and Ti-Al-V in artificial saliva at pH=4 and 37oC enriched with ethyl alcohol at 8% percentage. The linear and cyclic polarizations were investigated by electrochemical measurements. Laser surface modification was achieved for the three dental alloys to improve corrosion resistance. The results show that corrosion resistance of Co-Cr-Mo and Ni-Cr-Mo alloys only were increased after laser treatment due to the fact that laser radiation has caused a smoother surface, in addition to the decrement in corrosion current densities (icorr) for Co-Cr-Mo and Ni-Cr-Mo alloys and the reverse scan in cyclic polarization became in the wider range of

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
The impact of the use of pulverized black bean and fat in homemade bread mix in the quality and attributes Alkhoznip
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Factory is trotting home favorite of of Aeidid of Iraqi families since he Amta imparted to the taste of the housewife on the method of processing and preparation and the possibility of using some of the ingredients to raise the nutritional value of meat, sesame and other, but how keep Bz'zajh this product Atne storage

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