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jkmc-966
Pancreatic Stone Protein/ regenerating Protein (PSP/reg) as a Biochemical Marker for prediction of Microvascular Complications of Type 2 Diabetes Mellitus
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Background: Type 2 diabetes mellitus (T2DM) characterized by insulin resistance (IR) and progressive decline in functional beta (β) cell mass partially due to increased β cell apoptosis rate. Pancreatic stone protein /regenerating protein (PSP/reg) is produced mainly by the pancreas and elevated drastically during pancreatic disorder. Beta cells are experiencing apoptosis that stimulate the expression of PSP/reg gene in surviving neighboring cells, and that PSP/reg protein is subsequently secreted from these cells which could play a role in their regeneration.

Objectives: To analyze serum levels of PSP/reg protein in T2DM patients and evaluate its correlation with the microvascular complications of the disease.

Subjects and Methods: One hundred fifty participants (64 males, 86 females; aged 40–70 years) include T2DM patients with and without microvascular complications as well as healthy controls were enrolled in this study. Biochemical parameters like random blood glucose (RBG), glycated hemoglobin (HbA1c), lipid profile, urea and creatinine (Cr) were measured. Serum values of PSP/reg protein were measured by enzyme- linked immunosorbent assay (ELISA).

Results: Serum levels of PSP/reg protein were found significantly elevated in T2DM patients with microvascular complications compared with those of controls (p<0.001) and T2DM patients without microvascular complications (p< 0.001).PSP/reg protein is correlated with type 2 DM duration (p<0.001), RBG (p<0.001), and HbA1c (p<0.001). The area under the curve (AUC) for the presence of microvascular complications was 0.973.

Conclusion: PSP/reg protein may be used as biochemical marker to predict microvascular complications of T2DM.

 

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
User (K-Means) for clustering in Data Mining with application
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  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Optimized Kalman filters for sensorless vector control induction motor drives
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<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t

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Publication Date
Sun Feb 08 2026
Journal Name
International Journal Of Engineering &amp; Technology
An integrated multi layers approach for detecting unknown malware behaviours
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Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel

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Publication Date
Fri May 13 2022
Journal Name
Electronics
Fuzzy Luenberger Observer Design for Nonlinear Flexible Joint Robot Manipulator
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The process of controlling a Flexible Joint Robot Manipulator (FJRM) requires additional sensors for measuring the state variables of flexible joints. Therefore, taking the elasticity into account adds a lot of complexity as all the additional sensors must be taken into account during the control process. This paper proposes a nonlinear observer that controls FJRM, without requiring equipment sensors for measuring the states. The nonlinear state equations are derived in detail for the FJRM where nonlinearity, of order three, is considered. The Takagi–Sugeno Fuzzy Model (T-SFM) technique is applied to linearize the FJRM system. The Luenberger observer is designed to estimate the unmeasured states using error correction. The develop

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Publication Date
Fri Mar 31 2023
Journal Name
Iraqi Geological Journal
Glass Wastes Sorption Efficiency for Removing Cadmium from Aqueous Solutions
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This research aims to test the ability of glass waste powder to adsorb cadmium from aqueous solutions. The glass wastes were collected from the Glass Manufacturing Factory in Ramadi. The effect of concentration and reaction time on sorption was tested through a series of laboratory experiments. Four Cd concentrations (20, 40, 60, and 80) as each concentration was tested ten times for 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 min. Solid (glass wastes) to liquid was 2g to 30ml was fixed in each experiment where the total volume of the solution was 30ml. The pH, total dissolved salts and electrical conductivity were measured at 30ºC. The equilibrium concentration was determined at 25 minutes, thereafter it was noted that the sorption

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Building 1D Mechanical Earth Model for Zubair Oilfield in Iraq
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Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Wed Sep 13 2023
Journal Name
Aip Conference Proceedings
Results for the (b,t)-blocking sets in PG(2,8)
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Publication Date
Fri Apr 04 2025
Journal Name
لارك
Difficulties in Forming Compound Sentences in Spanish for Arabic Speakers
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A sentence is a key part of Spanish grammar and serves as the fundamental unit in constructing discourse. However, foreign language learners, particularly Arabic speakers, may face complex aspects that hinder their understanding and correct use of sentences. Additionally, there are at least two linguistic approaches that describe the use of compound sentences: one considers the sentence as the basic unit for discourse analysis, while other studies, starting with Van Dijk (2003), emphasize the importance of understanding both the partial and holistic structure of discourse. Therefore, we consider the significance of reviewing the linguistic differences between the native language and Spanish as a potential cause of misunderstanding a

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