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Flat Unglazed Transpired Solar Collector: Performance Probability Prediction Approach Using Monte Carlo Simulation Technique
Engineering applications including food processing, wastewater treatment, home heating, commercial heating, and institutional heating successfully use unglazed transpired solar collectors (UTCs). Trapping of solar energy is the prime goal of developing an unglazed transpired solar collector. The UTC is usually developed in and around the walls of the building and absorbs the solar energy to heat the air. One of the key challenges faced by the UTC designer is the prediction of performance and its warranty under uncertain operating conditions of flow variables. Some of the flow features are the velocity distribution, plate temperature, exit temperature and perforation location. The objective of the present study was to establish correlations among these flow features and demonstrate a method of predicting the performance of the UTC. Hence, a correlation matrix was generated from the dataset prepared after solving the airflow over a perforated flat UTC. Further, both strong and weak correlations of flow features were captured through Pearsons correlation coefficient. A comparison between the outcomes from a linear regression model and that of computational simulation was showcased. The performance probability for the UTC was interlinked with correlation matrix data. The Monte Carlo simulation was used to predict the performance from random values of the flow parameters. The study showed that the difference between the free stream value of temperature and the value of temperature inside the UTCs chamber varied between 15 and 20 C. The probability of achieving system efficiency greater than 35% was 55.2%. This has raised the hope of recommending the UTC for drying and heating where the required temperature differential is within 20 C. 2022 by the authors. -
Early diagnosis of COVID-19 patients using deep learning-based deep forest model
Coronavirus disease-19 (COVID-19) has rapidly spread all over the world. It is found that the low sensitivity of reverse transcription-polymerase chain reaction (RT-PCR) examinations during the early stage of COVID-19 disease. Thus, efficient models are desirable for early-stage testing of COVID-19 infected patients. Chest X-ray (CXR) images of COVID-19 infected patients have shown some bilateral changes. In this paper, deep transfer learning and a deep forest-based model are proposed to diagnose COVID-19 infection from CXR images. Initially, features of X-ray images are extracted using the well-known deep transfer learning model (i.e., ResNet101), which does not require tuning many parameters compared to the deep convolutional neural network (CNN). After that, the deep forest model is utilised to predict COVID-19 infected patients. The deep forest is based upon ensemble learning and requires a small number of hyper-parameters. Additionally, the proposed model is trained on a multi-class dataset that contains four different classes as COVID-19 (+), pneumonia, tuberculosis, and healthy patients. The comparisons are drawn among the proposed deep transfer learning and deep forest-based models, the competitive models. The obtained results show that the proposed model effectively diagnoses COVID-19 infection with an accuracy of 99.4%. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indi-cator of diabetic retinopathy. With that in mind, the purpose of this work is to cre-ate an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine (SVM)-based classification to separate normal and abnormal fundus images at the first level. The input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix (GLCM). Furthermore, the presence of Exudate and Diabetic Retinopathy (DR) in fundus images is detected using the Adaptive Neuro Fuzzy Inference System (ANFIS) classifier at the second level of classification. Exudate detection, blood vessel extraction, and Optic Disc (OD) detection are all processed to achieve suitable results. Furthermore, the second level processing comprises Morphological Component Analysis (MCA) based image enhancement and object segmentation processes, as well as feature extraction for training the ANFIS clas-sifier, to reliably diagnose DR. Furthermore, the findings reveal that the proposed model surpasses existing models in terms of accuracy, time efficiency, and precision rate with the lowest possible error rate. 2023, Tech Science Press. All rights reserved. -
FAMILY OF CONGRUENCES FOR (2, ?)?REGULAR BIPARTITION TRIPLES
Though congruences have their limitations, they have significant importance in the field of number theory and helps in proving many interesting results. Thus, this article has adopted the technique and properties of congruences to identify and prove a set of congruent properties for integer partition. The partition of a positive integer is a way of expressing the number as a sum of positive integers. One such partitions known as regular bipartition triple are discussed in this article. New congruences modulo even integers and modulo prime (p ? 5) powers are derived for (2, ?)?regular bipartition triples. Also infinite families of congruences modulo 2 for some (2, ?)?regular bipartition triples are derived. The theorems stated in this article are proved using the q?series notation and some of the prominent results such as Eulers pentagonal number theorem and Jacobis triple product identities. There are certain lemmas which are derived using these results that help in proving the major results of this article. 2022, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
Ganga and Yamuna Rivers: Through the Lens of the National Green Tribunal
Despite the country's extensive environmental jurisprudence and many historic rulings in which the courts have rescued worsening environmental situations, river (Ganga and Yamuna) water does not match the mandated minimum "bathing quality." Rivers like the Ganga and Yamuna, which flow through numerous states and towns, would be in a different situation. Without strict monitoring and enforcement of the measures, no action plan can work. Punishment of defaulters can serve as deterrence while also instilling fear in other non-compliant enterprises. In comparison to environmental legislation, the NGT Act allows for substantially harsher fines and penalties. River rejuvenation plans must be carefully monitored to ensure that they do not suffer the same fate. Making action plans will not improve river water quality unless they are implemented with sincerity and consistency, as well as continuous monitoring and severe enforcement. 2022 Technoscience Publications. All rights reserved. -
Evidence and Predictors of Resilience among Young Adults Exposed to Traumatic Events of the Armed Conflict in Kashmir
No study to date exists regarding resilience in the context of armed conflict in Kashmir, India. Therefore, this study intended to understand the factors that predict resilience among young adults affected by the violence of the protracted conflict in Kashmir. The data were collected from 656 students, who experienced stress, related to the conflict. Findings showed that more than a quarter of the respondents (35.8%) were exposed, from 7 to 10, less than a quarter (16.6%) of participants reported 26, and almost half of the respondents (47.6%) were exposed to 11 or more stressful events related to the conflict in Kashmir. Multiple hierarchical regression analysis was used to examine the role of conflict exposure, social support, and demographic variables in predicting resilience. The results of the final regression model revealed that exposure to armed conflict, social support, level of education, monthly family income and gender, emerged as significant predictors of resilience. The study recommends the formulation of programs to sensitize people living in the areas affected by the armed conflicts, regarding the importance of social support and resilience, to help them withstand various adverse life experiences. 2021 Taylor & Francis Group, LLC. -
Potassium tert-Butoxide-Mediated Synthesis of 2-Aminoquinolines from Alkylnitriles and 2-Aminobenzaldehyde Derivatives
KOtBu mediates the reaction between 2-amino arylcarbaldehydes and benzyl/alkyl cyanides toward the expeditious formation of 2-aminoquinolines under transition-metal-free conditions. The described transformation proceeds through in-situ generated enimine intermediate from benzyl/alkyl cyanides under KOtBu-mediated reaction conditions. The substituted 2-aminoquinolines were realized in excellent yields at room temperature and shorter reaction time. The designed process exhibits operational simplicity and broad functional group tolerance in delivering the products of high significance. 2022 Wiley-VCH GmbH. -
Gaussian MutationSpider Monkey Optimization (GM-SMO) Model for Remote Sensing Scene Classification
Scene classification aims to classify various objects and land use classes such as farms, highways, rivers, and airplanes in the remote sensing images. In recent times, the Convolutional Neural Network (CNN) based models have been widely applied in scene classification, due to their efficiency in feature representation. The CNN based models have the limitation of overfitting problems, due to the generation of more features in the convolutional layer and imbalanced data problems. This study proposed Gaussian MutationSpider Monkey Optimization (GM-SMO) model for feature selection to solve overfitting and imbalanced data problems in scene classification. The Gaussian mutation changes the position of the solution after exploration to increase the exploitation in feature selection. The GM-SMO model maintains better tradeoff between exploration and exploitation to select relevant features for superior classification. The GM-SMO model selects unique features to overcome overfitting and imbalanced data problems. In this manuscript, the Generative Adversarial Network (GAN) is used for generating the augmented images, and the AlexNet and Visual Geometry Group (VGG) 19 models are applied to extract the features from the augmented images. Then, the GM-SMO model selects unique features, which are given to the Long Short-Term Memory (LSTM) network for classification. In the resulting phase, the GM-SMO model achieves 99.46% of accuracy, where the existing transformer-CNN has achieved only 98.76% on the UCM dataset. 2022 by the authors. -
Extraction, characterization, and fabrication of cellulose biopolymer sheets from Pistia stratiotes as a biodegradative coating material: an unique strategy for the conversion of invasive weeds into value-added products
This study explores the possibility of using Water lettuce (Pistia stratiotes) as a cost-effective substrate for the commercial extraction of cellulose biopolymer using a wide variety of physicochemical treatment methods to compare their efficiency in cellulose extraction. The extraction of cellulose from water lettuce, although promising due to their high cellulose content, was less explored as per the available literature. In this study, functional properties like bulk density-packed density, hydrated density, water retention capacity, oil retention capacity, emulsifying activity and setting volume of the extracted cellulose were studied. The cellulose content from water lettuce was found to be 38.94 0.10% by anthrone method. Preliminary confirmation of cellulose biopolymer was done using the study of functional groups using Fourier Transform Infrared (FT-IR) analysis. Further characterization studies like Scanning Electron Microscopy (SEM), X- Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to understand the molecular architecture and purity of the cellulose extracted. Fabrication of cellulose sheets was carried out using starch as the plasticizer. Biodegradation studies were conducted in garden soil for four weeks and a high degradation rate of 78.22 0.71% was observed in the fourth week of soil burial. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Biocontrol of Aedes aegypti using Talaromyces islandicus Synthesized Silver Nanoparticles
Aedes aegypti is the vector that spreads the dengue virus, causing dengue fever and dengue hemorrhagic fever. With more than half the worlds population at the risk of acquiring this infection, controlling the Aedes mosquitoes is the only path to limit the spread of the fatal disease. The emergence of insect resistance in mosquitoes raised the need for developing novel insecticides. Present research is focused on using fungus (Talaromyces islandicus) as the biosystem in the synthesis of nanoparticles. Myco-synthesized silver nanoparticles were characterized using UV-visible spectrometry that exhibited a peak at 429 nm. The XRD spectral peaks were in the range of 27.83, 32.27, 38.23and 65.01. The FTIR spectrum showed peaks corresponding to O-H, N-O, S=O, etc. representing the silver nanoparticles. SEM and EDAX represent the formation of silver ions that are spherical in shape with a size range of 23 to 26 nm. The antioxidant activity of silver nanoparticles and the extract of Talaromyces islandicus were assessed by DPPH assay, reducing power assay and hydrogen peroxide assay. The nanoparticles studied for its bio efficacy against the larval stages of Aedes aegypti indicated the LC50 value of 352.03, 389.86, 397.72 and 443.50 when tested against first, second, third and fourth instar larvae. respectively. The LC50 value of 540.41 was determined against the pupae of Aedes. The predatory efficiency of P. reticulata indicated the positive feeding behaviour of the fish when exposed to the silver nanoparticles. The cell toxicity assay was conducted against C6/36 insect cell lines and the cell viability inhibition was calculated. A toxic free, environmentally acceptable approach for controlling the mosquito vector by utilizing fungal nanoparticles was assessed and their efficacy in vector control was analyzed in this study. 2022 Chemical Publishing Co.. All rights reserved. -
A Compact Super Wideband Antenna with Controllable Dual Notch Band Capability
In this paper, a novel super wideband (SWB) antenna with dual band notch capability is designed and analyzed for wide band applications. The proposed antenna consists of a pentagonal shaped radiator, beveled-shaped partial ground plane with slot and U-shaped parasitic strips. The beveled-shaped defected ground structure with rectangular slot helps to realize wideband characteristics from 2.4 to 28.2 GHz. Independent control of the notch band's center frequency and bandwidth is achieved by using U-shaped parasitic strips. This key feature is achieved in the WiMAX (3.3 to 3.7 GHz) and WLAN (5.1 to 5.9 GHz) bands. Furthermore, it exhibits a stable radiation pattern and offers acceptable gain over the entire operating bandwidth with sharp decrease in gain at the notches. The percentage bandwidth of 169% is achieved with a bandwidth dimension ratio (BDR) of 6986. Group delay is less than 1 ns in the entire operating bandwidth except at the notch bands. The measured reflection and radiation characteristics of fabricated SWB antenna are in good agreement with the simulation results. The proposed antenna has the advantage of simple design and compact size with an overall dimension of 18 x 21 x 1.6 mm3. The performance of the proposed antenna is superior compared to reported antenna designs in terms of controllable sharp notches and size for the bandwidth achieved. 2022 IAMOT -
Effect of substrate temperature on the properties of spray deposited Ga2O3 thin films, for solar blind UV detector applications
In this work, Ga2O3 thin films were deposited on glass substrates by chemical spray pyrolysis technique at three different substrate temperatures 350 C, 400 C, and 450 C. The structural, optical, morphological and electrical characteristics of the deposited sample thin films were investigated. From the studies, it is understood that by tuning substrate temperature, we can extensively change the properties of the film. Optimum temperature for coating Ga2O3 thin films was understood and the work was extended to demonstrate a simple deep UV detector, working in photoconductive mode. The fabricated device exhibit medium response to UV light at 254 nm. The present work report the fabrication of solar blind UV detector based on Ga2O3 thin film, grown using low cost, easily scalable spray deposition technique. 2022 Elsevier B.V. -
A continuous protocol for the epoxidation of olefins, monocyclic terpenes, and Alpha Beta Unsaturated Carbonyl Synthons using eco-friendly Flow Reactor Conditions
Herein, we report a simple synthetic protocol for selective epoxidation of olefins, monocyclic terpenes, and chalcones using a continuous semi-batch process in good to excellent yields. Mainly, industrial semi-batch epoxidation is an extremely risky process that includes very high safety measures to avoid the accumulation of peroxide species in the reactor during the process, which leads to accidents. To avoid the same, we have established a constant flow reactor protocol for the epoxidation of fore mentioned key synthons using a cyanamide-potassium carbonate catalytic system which helps to reduce the accumulation of the peroxide species, and also yields moderate to high yields of the desired products. The developed methodology was successfully utilized for the epoxidation of a range of aliphatic to aromatic olefins to generate corresponding epoxides. All the products and their structures were examined using 1HNMR, and 13NMR spectroscopy. More importantly, this proposed protocol is recyclable and reproducible where in using similar research conditions. 2022 The Authors -
Comparative Study on the Experimental Results on Low-Velocity Impact Characteristics of GLARE Laminates with Simulation Results from LS Dyna
Fiber reinforcement with metallic face sheets is one of the recently implemented materials for distinctive applications in automotive and aerospace sectors. While the reinforcement enhances the sustenance property of the laminate, the face sheets provide resistance to impact force. In most automotive sectors, drop weight analysis at varying velocity ranges is performed to evaluate the damage characteristics of the vehicle body. The present work is aimed at studying the influence of low-velocity impact (LVI) on Glass Laminate Aluminum-Reinforced Epoxy (GLARE) laminate. Three distinct thicknesses of Al-2024 T3 aluminum alloy (0.2, 0.3 and 0.4mm) were chosen as the face sheet and E-glass fiber was used as intermediate layers. Epoxy resin LY556 with a HY951 hardener was used to fabricate the GLARE structure and the overall thickness was maintained at 2.0mm for all the cases. Energy absorbed by GLARE laminates for different energy was determined using Drop weight Impact test experimentally and analytically. The laminate and the dart were modeled by ANSYS ACP tool and the simulation was performed using LS Dyna software. It was evident that laminate can sustain impact at a velocity of 3.13m/s and beyond which leads to surface delamination. The simulation results were in close agreement with the experimental values for the absorbed energy, with less than 10% error. 2022, The Institution of Engineers (India). -
A novel security framework for healthcare data through IOT sensors
The Internet of Things (IoT) has played a crucial role in the distribution of health records and poses security issues to the patient-specific health information needed for remote hospital attention. The majority of publicly accessible security mechanisms for health information do not concentrate on the flow of information from IoT different sensors installed upon the person's blood through networking devices to primary health care centers. In this paper, we investigated the potential risks of unprotected transmission data, particularly among IoT sensor systems and network gateways. The study encourages the transmission of health insurance data to hospitals remotely. The proposed health care information model would encode immediately so that the sensing element before even being transferred to cryptographic techniques. To use a laboratory configuration with two-stage cryptography at the IoT sensor and two-stage decoding at the physician's surgery receptor, the prototype system was validated. The test results for a complete safety system for IoT - based on the transmission of healthcare data seem good. The study opens up new avenues for information security on IoT devices. 2022 The Authors -
Coping with Public and Private Face-to-Face and Cyber Victimization among Adolescents in Six Countries: Roles of Severity and Country
This study investigated the role of medium (face-to-face, cyber) and publicity (public, private) in adolescents perceptions of severity and coping strategies (i.e., avoidant, ignoring, helplessness, social support seeking, retaliation) for victimization, while accounting for gender and cultural values. There were 3432 adolescents (ages 1115, 49% girls) in this study; they were from China, Cyprus, the Czech Republic, India, Japan, and the United States. Adolescents completed questionnaires on individualism and collectivism, and ratings of coping strategies and severity for public face-to-face victimization, private face-to-face victimization, public cyber victimization, and private cyber victimization. Findings revealed similarities in adolescents coping strategies based on perceptions of severity, publicity, and medium for some coping strategies (i.e., social support seeking, retaliation) but differential associations for other coping strategies (i.e., avoidance, helplessness, ignoring). The results of this study are important for prevention and intervention efforts because they underscore the importance of teaching effective coping strategies to adolescents, and to consider how perceptions of severity, publicity, and medium might influence the implementation of these coping strategies. 2022 by the authors. -
Effect of heavy metals on germination, biochemical, and L-DOPA content in Mucuna pruriens (L.) DC.
Mucuna pruriens (L.) DC. is a medicinal plant with a wide range of pharmacological properties that have been used in various medicinal preparations for centuries. M. pruriens is a rich source of levodopa (L-DOPA), mainly used to treat Parkinsons disease. The present study investigates the impact of heavy metals such as cadmium (Cd), mercury (Hg), and lead (Pb) on the growth parameters and biochemical characteristics, including the L-DOPA content of M. pruriens. The seeds of M. pruriens were treated with different concentrations of Cd (0250 ppm), Hg (0250 ppm), and Pb (02000 ppm) for 21 days. On exposure to heavy metals, the germination %, the vegetative growth, and the biochemical characteristics such as the protein, carbohydrate, chlorophyll, total phenol, flavonoid, and proline content varied significantly in the heavy metal-treated plants when compared to control. It was also observed that the L-DOPA content increased with increased metal concentration and then decreased further with higher concentration of metals. The metal accumulation increased with the increase in the metal concentration. The seeds treated with 1000 ppm of Pb showed the highest L-DOPA content compared with control and other treatments. 2022 Banadka and Nagella. -
An energy efficient approach of deep learning based soft sensor for air quality management
Monitoring environmental pollution is emerging as a recent study area especially in urban and highly polluted industrial areas. This field deploys many chemical analysis models and data driven models through soft sensors. But bio indicators are a more feasible, cost effective and precise monitoring model, which are rarely explored. This paper is based on growth monitoring of Cryptogams, a bio indicator which is capable of directly reflecting the pollution levels in the region of growth. A novel enhanced and energy efficient deformable active contour model is introduced to trace the development of transplanted Cryptogams at various sites with diverse pollution levels. The vegetative development of Cryptogams is monitored for duration of two weeks. The proposed energy efficient contour tracing model proves its superiority in precise tracing of the Cryptogam development, thus aiding in accurate pollution monitoring. The VGG 16 architecture built using deep convolutional neural network by constructing stacks of filters. VGG 16 architecture showed high performance when compared with other existing models. The accuracy is compared with the Ant colony optimization using GVF. 2022 The Authors -
Solution Focused vs Problem Focused Questions on Affect and Processing Speed among Individuals with Depression
The present study investigated the effect of solution-focused and problem-focused questions on affect and processing speed in a sample of 60 individuals diagnosed with depression. Participants were equally and randomly assigned to the solution focused question group, problem focused question group, and delayed experimental group. The Beck depression inventory-II was used to assess the severity of depressive symptoms of the participants. The positive and negative affect schedule was used to measure affect. Symbol search and coding were used to measure the processing speed. Solution-focused questions significantly reduced negative affect and improved coding compared to problem-focused questions. Even though there was no significant interaction between the groups in positive affect and symbol search test performance, solution-focused questions caused simple effects in both. Findings imply the scope of solution-focused questions as psychological first aid in intervening depression. Possible long-term effects of solution-focused questions on individuals with depression were discussed. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Does Gender and Family Income Impact Stock Trading of B-School Students? Findings from a Stock Simulation Exercise
Educators across the globe utilize online stock market simulation games to introduce students to trading in the stock market. The primary objective of the simulation exercise is to expose students to the practical application of financial theories on fundamental analysis, stock selection, building an optimal portfolio, monitoring the risk-return characteristics and continuously improving the portfolio based on changing realities. This article utilizes the trading data from a simulation exercise conducted by a leading B-school in India. The exercise was conducted as part of Security Analysis and Portfolio Management (SAPM) course offered by the B-school. The objective of the article is to understand the role of gender and family income in the trading patterns of students in the simulation exercise. The article covers 163 students who were part of the simulation exercise in 2019. The results indicate that male students trade more aggressively than female students, both in terms of number of trades and the number of companies traded. However, the female students reported higher stock trading performance, measured in stock returns. This is observed to be true at all the quartiles, with the largest magnitude of the difference in the mid-quartiles. The study also indicates that the students from wealthier families perform better than those from poorer backgrounds. However, family income is an insignificant differentiating factor. Further, regression analysis indicates that gender is a significant determinant of stock returns. Based on these findings, the authors argue that gender has a significant role in the stock trading performance of B-schoolers. The article contributes to the field of behavioural finance, especially on the literature of gender and performance in financial markets. 2022 Management Development Institute.