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Effect of laparoscopic sleeve gastrectomy on blood sugar and blood pressure
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Background: Surgery is one and may be the most effective method to treat obesity. In the last decade, Laparoscopic Sleeve Gastrectomy is perceived to be less invasive, technically simple, less morbid and more popular form of bariatric surgery.

Objectives: This study aims to assess the effect of Laparoscopic Sleeve Gastrectomy on Fasting Blood Glucose Levels and Blood Pressure.

 Methods: A prospective controlled study in which 50 obese patients were involved, 36 of patients have hypertension and type 2 diabetes mellitus , 7 patients have type 2 diabetes mellitus only, and 7 patients don’t have hypertension or type 2 diabetes. All patients were submitted to Laparoscopic Sleeve Gastrectomy at Al-Kindy Teaching Hospital between October 2014 and October 2016.

Results: Forty five of patients were females, while five were males . Mean age was 34 years, mean height 159 cm mean pre Laparoscopic Sleeve Gastrectomy weight was 121kg. Mean post- Laparoscopic Sleeve Gastrectomy weight was 82kg. Mean weight loss outcome at 1 year follow-up is 32.23% of total body weight. . Preoperative initial mean value of fasting blood glucose was 157.4 mg/dL and the declining occurred at 12 months after Laparoscopic Sleeve Gastrectomy was 97 mg/dL . The hypertension remission rates 1 year after Laparoscopic Sleeve Gastrectomy ranges up to 54% of total number of patients and 75% of those with Hypertension.

Conclusions: Laparoscopic Sleeve Gastrectomy has an effect in improving Fasting Blood Glucose Levels and Blood Pressure.

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Publication Date
Tue Jan 10 2017
Journal Name
International Journal Of Dynamics And Control
On local approximation-based adaptive control with applications to robotic manipulators and biped robots
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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Zinc Element Traces to Inhibit Scale Formation on Cooling Tower and Air Cooler Systems
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Calcium carbonate is predominantly present in aqueous systems, which is
commonly used in industrial processes. It has inverse solubility characteristics
resulting in the deposition of scale on heat transfer surface. This paper focuses on
developing methods for inhibition of calcium carbonate scale formation in cooling
tower and air cooler system where scaling can cause serious problems, ZnCl 2 and ZnI
2 has been investigated as scale inhibitor on AISI 316 and 304. ZnCl 2 were more
effective than ZnI 2 in both systems, and AISI 316 show more receptivity to the
chlorides salt compared to AISI 304. The inhibitors were more effective in cooling
tower than air cooler system. AISI 316 show more constant inhibition effic

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Pathological And Immunological Study On Infection With Escherichia Coli In ale BALB/c mice
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Publication Date
Thu Dec 31 2020
Journal Name
International Journal On Governmental Financial Management
The Shift towards the Results-Oriented Budget and Its Impact on Government Performance Information
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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sun Mar 01 2020
Journal Name
Agronomy Journal
Long‐term perennial management and cropping effects on soil microbial biomass for claypan watersheds
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Sustainable vegetative management plays a significant role in improving soil quality in degraded agricultural landscapes by enhancing soil microbial biomass. This study investigated the effects of grass buffers (GBs), biomass crops (BCs), grass waterways (GWWs), and agroforestry buffers (ABs) on soil microbial biomass and soil organic C (SOC) compared with continuous corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation (row crop [RC]) on claypan soils. The RC, AB, GB, GWW, and BC treatments were established in 1991, 1997, 1997, 1997, and 2012, respectively, and are located at Greenley Memorial Research Center in Missouri. Soil samples were collected in May 2018 from the 0‐ to

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