Association between diabetic retinopathy and the neutrophil lymphocyte ratio, platelet lymphocyte ratio, monocyte lymphocyte ratio

BACKGROUND: Diabetic retinopathy is a serious complication of diabetes mellitus and it is considered as a major cause of blindness in working population. Its pathogenesis is complicated and it is related to many factors, but many groups have described the role of inflammatory markers in the development of diabetic retinopathy. AIM OF THE STUDY: The aim of my study is to evaluate the association between Diabetic retinopathy and the Neutrophil Lymphocyte ratio, Monocyte Lymphocyte Ratio and the Platelet Lymphocyte Ratio. METHODS: It is a case control study involving 150 diabetic patients divided into three groups, 50 patients with diabetes without diabetic retinopathy, 50 patients with non proliferative diabetic retinopathy, 50 with proliferative diabetic retinopathy. RESULTS: By using Pearson correlation, age, blood pressure, fasting blood sugar, HbA1c, lipid profile, Total count , NLR, MLR, PLR showed a significant correlation with p value <0.05 at 95%CI. Thus by using both Anova and Pearson correlation there is a significant correlation between the NLR, MLR, PLR and diabetic retinopathy. CONCLUSION: In conclusion, the NLR, MLR, PLR ratios are significantly increased in the setting of diabetic retinopathy and they also correlate well with the severity of diabetic retinopathy these ratios can serve as remarkable markers while evaluating diabetes patients with or without retinopathy and they are of predictive and prognostic value

1,3,4-Oxadiazole Dimers: New and Effective corrosion inhibitors for mild steel in sulphuric acid solution

The corrosion inhibition property of 1,3,4-Oxadiazole dimers have been investigated for mild steel in acidic environment using gravimetric method, Tafel polarization, electrochemical impedance spectroscopy (EIS), scanning electron microscope (SEM), atomic absorption spectroscopy (AAS) and adsorption isotherm. The results revealed that 1,3,4-Oxadiazole dimers had excellent corrosion inhibition property for mild steel in 1M H2SO4 acid media and its inhibitive efficiency was more than 99% even with a low concentration of 1000ppm.The adsorption of the organic compounds on the mild steel surface obeyed Langmuir adsorption  isotherm. IR spectra and SEM proved the adsorption of organic inhibitors and the formation of corrosion products on the mild steel surface.Â

An integrated software quality model and its adaptability within monolithic and virtualized cloud environments

One fundamental problem in current software development life cycles, particularly in distributed and non-deterministic environment, is that software quality assurance and measurements do not start early enough in the development process. Recent research work has been trying to address this problem by using software quality assurance (SQA) measurement frameworks. However, before such frameworks are developed and adopted there is a need to have a clear understanding and to define what is meant by quality. To help this definition process, numerous approaches and quality models have been developed. Many of the early quality models have followed a hierarchical approach with little scope for expansion. More recent models have been developed that follow a 'Define your own' approach. Although an improvement, difficulties arise when comparing quality across projects, due to their tailored nature. The aim of this project is to develop a new generic framework to software quality assurance which addresses the problems of existing approaches. The proposed framework will blend various quality measurement approaches and will provide statistical, probabilistic and subjective measurements for both required and actual quality. Unlike existing techniques, autodidactic mechanisms are incorporated which can be used to measure any software entity type. This however should include the measurements of actual quality using software quality factors that are based on experimental measurements i.e., not only on the subjective view of stakeholders. Moreover the framework should also include the conversion into software measurements of historical reports/data that can be extracted from problem reporting systems such date of problem identification, source of report, critical tendencies of report, cause of problem etc. and other available statistical information. The proposed framework retains the knowledge about software defects and their impact on quality, and has the capacity to add new knowledge dynamically

Food spoilage alert system by deploying deep learning model

Food waste due to rotting is unquestionably an important resource issue that must be addressed as soon as possible in the next age. Recent technological advancements, such as cloud technology, Deep Learning (DL)&nbsp;may aid in the reduction of food waste. To address the rising issue of food spoilage in everyday situations in the most effective way possible, a DL model is built to distinguish between fresh and rotten fruit. The dataset required for this inquiry was obtained from Kaggle. The raw dataset is pre-processed so that it may be used with the DL model. Detection systems, controllers, and transmission elements make up the functional model. These modules interact with the items, such as the fruits, to collect data, which is then processed using a DL technique, such as CNN, and if there is any degradation in the food, an alert message is sent to the registered user

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