STUDY OF THERMAL STABILITY OF SOLAR POND INTEGRATED WITH SOLAR COLLECTOR

In this study, heat supply to LCZ of a salinity gradient solar pond was evaluated. The dimensions of the rectangular solar pond are 45 cm height, 90 cm length and volume of 0.18225 m3. The main aim is to evaluate the heat storage capacity of the solar pond and to increase its heat storage capacity by using flat plate collectors for a period of 10 days. An in-pond heat exchanger covering the bottom wall area of the pond was installed, and its performance was compared with the traditional in-pond without heat exchangers. Temperature at the LCZ was observed as 48ºC with the bottom heat exchanger and 42.5ºC without exchanger. This indicates an increase in the solar pond efficiency of 12.94 % .The difference between the amount of heat energy stored is 14.44 kJ. The results demonstrate that efficiency of solar pond increases with bottom heat exchanger, when compared to the efficiency of solar pond without bottom heat exchanger

Eye Disease Prediction Among Corporate Employees using Machine Learning Techniques

In the IT sector, employees use systems for more than 6 hs, so they are affected by many health problems. Mostly In the IT sector, employees are affected with eye diseases like eye strain, eye pain, burning sensation, double vision, blurring of vision, and frequent watering. The major goal of this research is to identify the different types of eye problems encountered, the symptoms present, and the population afflicted by eye diseases in order to accurately forecast outcomes using a Machine learning techniques for real-time data sets.Additional Notes: Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved

Managing The Tomato Leaf Disease Detection Accuracy Using Computer Vision Based Deep Neural Network

Development of leaf disease in the agricultural sector would decrease crop yield output. Thus, leaf disease identification can be achieved in an automatic way to increase the yield in the agriculture sector. However, most of the disease recognition system works with poor disease recognition due to varying patterns of leaf disease which impair detection accuracy. In this article, we are managing this issue by designing a computer vision model that assists in building a system that involves real-time image detection, feature extraction and image classification. The findings are given by the classifier, whether the leaf is diseased or not. In this paper we use Deep Neural Network (DNN) for real-time image classification. The experimental findings on tomato plant indicate that classification rates have increased with the proposed system relative to other current methods

The Influence Of Maternal Infections On Congenital Heart Defect

ABSTRACT Congenital heart defects (CHDs) contribute significantly to heightened infant mortality rates. This review explores the intricate link between maternal infections and CHDs, emphasizing diverse factors influencing fetal development, such as bacterial, fungal, protozoan and viral agents. These infections pose reproductive health risks, potentially leading to complications like prematurity, stillbirth and heart defect to the fetus. The TORCH acronym (Toxoplasma, Other infections, Rubella, Cytomegalovirus, Herpes simplex) identifies infectious teratogens related to congenital issues, emphasizing vertical transmission through the placenta or ascending from the vagina. Rubella and Cytomegalovirus play a significant role in heart defects, particularly when maternal infections amplify CHD risk during pregnancy. Specific scrutiny is placed on Rubella and Cytomegalovirus for their impact on pregnancy outcomes and potential links to congenital heart defects, with preventive strategies discussed, including vaccination and antiviral therapy. The timing and severity of these infections are pivotal in determining their impact on fetal heart development. Environmental exposures and maternal nutrition are critical factors influencing fetal development. Maternal undernutrition in low- and middle-income countries associates with adverse pregnancy outcomes, including congenital heart defects. Emphasizing the importance of maintaining a nutritious maternal diet, rich in essential nutrients, is crucial for improved fetal health and successful pregnancy outcomes. This review offers insights into preventive measures and underscores the need for continued research to enhance prenatal care strategies

Analytics in Microfluidic Systems

Viefhues M. Analytics in Microfluidic Systems. In: Advances in Biochemical Engineering/Biotechnology. Berlin ; Heidelberg: Springer ; 2020.Microfluidic analysis proved to be very sufficient in supporting biotechnological studies. This is due to the wide range of new analysis methods that provide further insight into biotechnological questions but also to intrinsic advantages of the systems themselves. To name two of them, only very small sample amounts are needed, and the analytics are very fast. In this overview paper, microfluidic analysis methods are introduced with a special focus on electric analysis methods. The aim of this work is to shed light on the special advantages of miniaturized electrical analysis in microfluidics; the main theoretical aspects of the methods are given together with the potential scientific insight that can be gained by the respective methods