Atherosclerosis is a major complication of diabetes, increasing the risk of cardiovascular related morbidities and mortalities. The hallmark of diabetes is hyperglycemia which duration is best predicted by elevated gl...
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Atherosclerosis is a major complication of diabetes, increasing the risk of cardiovascular related morbidities and mortalities. The hallmark of diabetes is hyperglycemia which duration is best predicted by elevated glycated haemoglobin A1C(Hb A1C) levels. Diabetic complications are usually attributed to oxidative stress associated with glycation of major structural and functional proteins. This non-enzymatic glycation of long lived proteins such as collagen, albumin, fibrinogen, liver enzymes and globulins result in the formation of early and advanced glycation end products(AGEs) associated with the production of myriads of free radicles and oxidants that have detrimental effects leading to diabetic complications. AGEs have been extensively discussed in the literature as etiological factors in the advancement of atherogenic events. Mechanisms described include the effects of glycation on protein structure and function that lead to defective receptor binding, impairment of immune system and enzyme function and alteration of basement membrane structural integrity. Hemoglobin(Hb) is a major circulating protein susceptible to glycation. Glycated Hb, namely Hb A1 C is used as a useful tool in the diagnosis of diabetes progression. Many studies have shown strong positive associations between elevated Hb A1 C levels and existing cardiovascular disease and major risk factors. also, several studies presented Hb A1 C as an independent predictor of cardiovascular risk. In spite of extensive reports on positive associations, limited evidence is available considering the role of glycated Hb in the etiology of atherosclerosis. This editorial highlights potential mechanisms by which glycated hemoglobin may contribute, as a causative factor, to the progression of atherosclerosis in diabetics.
Nowadays,machine learning(ML)algorithms cannot succeed without the availability of an enormous amount of training *** data could contain sensitive information,which needs to be *** inference attacks attempt to find ou...
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Nowadays,machine learning(ML)algorithms cannot succeed without the availability of an enormous amount of training *** data could contain sensitive information,which needs to be *** inference attacks attempt to find out whether a target data point is used to train a certain ML model,which results in security and privacy *** leakage of membership information can vary from one machine-learning algorithm to *** this paper,we conduct an empirical study to explore the performance of membership inference attacks against three different machine learning algorithms,namely,K-nearest neighbors,random forest,support vector machine,and logistic regression using three *** experiments revealed the best machine learning model that can be more immune to privacy ***,we examined the effects of such attacks when varying the dataset *** on our observations for the experimental results,we propose a defense mechanism that is less prone to privacy attacks and demonstrate its effectiveness through an empirical evaluation.
The present researched topic was conceived from a senior design course for Civil Engineering students at CSUN (California State University), Northridge. In this work, experimental trials were performed and compared to...
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The present researched topic was conceived from a senior design course for Civil Engineering students at CSUN (California State University), Northridge. In this work, experimental trials were performed and compared to establish theoretical values of the discharge coefficient. The discharge coefficient is a dimensionless number used to characterize the flow and pressure loss behavior of nozzles and orifices in fluid systems. A group of low-income undergraduate students with diverse backgrounds designed multiple 3D printed orifices where each 3D printed orifice had a specific shape. Utilizing the methods of technical problem solving, the undergraduates found experimental discharge coefficient values for the following orifices: borda, short-tubed, and sharp-edged. Implementing ethics of engineering practice and utilizing university resources, this study is a representation of the collaborative work of minorities and females that want to expand their knowledge within their respective discipline of Civil Engineering.
Twill woven Carbon-Kevlar (CK) fabric was reinforced in epoxy matrix by conventional hand lay-up process. The fabric weight fraction in the composites was kept around 58% and stacking sequence was varied from single t...
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Twill woven Carbon-Kevlar (CK) fabric was reinforced in epoxy matrix by conventional hand lay-up process. The fabric weight fraction in the composites was kept around 58% and stacking sequence was varied from single to five plies. Tensile test was performed and the fracture surface after tensile test was evaluated by scanning electron microscope (SEM). The test result revealed that the tensile properties are strongly dependent on the number of plies. Three point flexural test of the composite was also carried and an increasing trend was observed. Maximum impact energy was recorded for CK3 sample by 202.7 KJ/m2. Thermal stability of the composite was studied via the thermo gravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FT-IR) result show interaction between fiber and matrix material. Finally, CK fabric reinforced epoxy-based composites showed balanced and tailor-able mechanical properties by varying the number of plies, suitable for desired applications in many areas including building, construction, marine, automotive etc.
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