Objective: Detection the presumptive prevalence of
silent celiac disease in patients with type 1 diabetes
mellitus with determination of which gender more
likely to be affected.
Methods: One hundred twenty asymptomatic patients
[75 male , 45 female] with type 1 diabetes mellitus
with mean age ± SD of 11.25 ± 2.85 year where
included in the study . All subjects were serologically
screened for the presence of anti-tissue transglutaminase
IgA antibodies (anti-tTG antibodies) by Enzyme-
Linked Immunosorbent Assay (ELISA) & total IgA
was also measured for all using radial
immunodiffusion plate . Anti-tissue transglutaminase
IgG was selectively done for patients who were
expressing negative anti-tissue transglutaminase IgA
with low total IgA levels & results were compared
to that obtained from healthy 60 persons with mean
age ± SD for them was 15.25 ± 3.85 year .
Results : Fourteen out of one hundred twenty (11.66
% ) diabetic patients had expressed positivity to antitissue
transglutaminase IgA compared to 1/60 ( 1.66
%) of non diabetic patients who had expressed such
positivity , P value equals to 0.0221 & it is
considered to be statistically significant. Three out of
one hundred twenty (2.5 % ) diabetic patients had
expressed total IgA deficiency whereas all of non
diabetic patients were expressing total IgA within
the normal range , P value equals to 0.55 & it is
considered to be not statistically significant. All of
three diabetic patients with total IgA deficiency were
not showing positivity to anti-tissue transglutaminase
IgG . Six mals & Eight female of those with type 1
diabetes mellitus had expressed positivity to anti-tissue
transglutaminase IgA , P value equals to 0.1426 &
it is considered to be not statistically significant .
Conclusion : There is an increased prevalence of IgA antitissue transglutaminase antibodies ( 11.66 % ) in children & adolescent with type 1 diabetes mellitus in comparison with control group.
The high and low water levels in Tigris River threaten the banks of the river. The study area is located on the main stream of Tigris River at Nu’maniyah City and the length of the considered reach is 5.4 km, especially the region from 400 m upstream Nu’maniyah Bridge and downstream of the bridge up to 1250 mwhich increased the risk ofthe problemthat itheading towardsthe streetand causingdanger tonearbyareas.
The aim of this research is to identify the reason of slope collapse and find proper treatments for erosion problem in the river banks with the least cost. The modeling approach consisted of several steps, the first of which is by using “mini” JET (Jet Erosion Test) d
... Show Moresensor sampling rate (SSR) may be an effective and crucial field in networked control systems. Changing sensor sampling period after designing the networked control system is a critical matter for the stability of the system. In this article, a wireless networked control system with multi-rate sensor sampling is proposed to control the temperature of a multi-zone greenhouse. Here, a behavior based Mamdany fuzzy system is used in three approaches, first is to design the fuzzy temperature controller, second is to design a fuzzy gain selector and third is to design a fuzzy error handler. The main approach of the control system design is to control the input gain of the fuzzy temperature controller depending on the cur
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This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.
A many risk challenge in (settings hospital) are multi- bacteria are antibiotic-resistant. Some type strains that ability adhesion surface-attached bio-film census. Fifteen MRSA isolates were considered as high biofilm producers Moreover all MRSA isolates; M3, M5, M7 and M11 produced biofilms but the thickest biofilm seen M7strain. The MIC values of N. sativa oil against clinical isolates of MRSA were between (0.25, 0.5, 0.75, 1.0) μg/ml While MRSAcin (50, 75, 100, 125) µg\ ml. All biofilms treated with MRSAcin and Nigella sativa developed a presence of live cells after cultured on plate agar with inhibition zone between MIC (18 – 15) and (14- 11)mm respectively.Yet, results showed that MRSA supernatant developed a inhibitory ef
... Show MoreThe ongoing COVID‐19 pandemic caused by SARS‐CoV‐2 is associated with high morbidity and mortality. This zoonotic virus has emerged in Wuhan of China in December 2019 from bats and pangolins probably and continuing the human‐to‐human transmission globally since last two years. As there is no efficient approved treatment, a number of vaccines were developed at an unprecedented speed to counter the pandemic. Moreover, vaccine hesitancy is observed that may be another possible reason for this never ending pandemic. In the meantime, several variants and mutations were identified and causing multiple waves globally. Now the safety and efficacy of these vaccines are debatable and recommended to d
Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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