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Electrocatalytic oxidation and determination of morin at a poly(2,5-dimercapto-1,3,4-thiadiazole) modified carbon fiber paper electrode
Voltammetric determination of morin on carbon fiber paper (CFP) electrode modified by electropolymerization of 2,5-dimercapto- 1,3,4-thiadiazole (DMTD) in phosphate buffer solution (PB, pH 9.0) have been studied. This modified electrode showed strong electrocatalytic activity toward the oxidation of morin, a flavonoid at physiological pH (PB, pH 7.0). Morin gave a sensitive anodic peak at 0.245 V (vs. SCE). The parameters influencing the anodic peak of morin such as effect of pH, effect of scan rate and concentration have been optimized. The electrochemical process was found to be irreversible and adsorption-controlled. Under the optimum conditions, the anodic peak current was linear to concentration of morin in the range of 2.5 10-10-2.75 109 M and detection limit was found to be 8.3 10-11 M. The practical application of the modified electrode was successfully demonstrated for the determination of morin in mulberry leaves. 2016 The Electrochemical Society. All rights reserved. -
Implementation of Morphological Gradient Algorithm for Edge Detection
This paper shows the implementation of a morphological gradient in MATLAB and colab platforms to analyze the time consumed on different sizes of grayscale images and structuring elements. A morphological gradient is an edge detecting technique that can be derived from the difference of two morphological operations called dilation and erosion. In order to apply the morphological operations to an image, padding is carried out which involves inserting 0 for dilation operation and 225 for erosion. Padding for the number of rows or columns is based on the size of the structuring element. Further, dilation and erosion are implemented on the image to obtain morphological gradient. Since central processing unit (CPU) implementation follows sequential computing, with the increase in the image size, the time consumption also increases significantly. To analyze the time consumption and to verify the performance across various platforms, the morphological gradient algorithm is implemented in MATLAB and colab. The results demonstrate that colab implementation is ten times faster when constant structuring element with varying image size is used and five times faster when constant image size with varying structuring element size is used than the MATLAB implementation. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Harnessing Machine Learning for Mental Health: A Study on Classifying Depression-Related Social Media Posts
This study is of particular relevance in the way it identifies depression-related content on social media using a machine learning model to classify posts and comments. This dataset, encompassing around 6500 entries from various platforms including Facebook, was rigorously annotated by four proficient English-speaking undergraduate students together with the final label which is established via majority voting. Data Preprocessing, initial cleaning, normalization and TF-IDF feature creation through vectorization for the output of POS tags. The different machine learning models that were trained and tested are Logistic Regression, Random Forest, SVM (Support Vector Machine), Naive Bayes Gradient Boosting Algorithm K-NN (K nearest Neighbors) AdaBoost Decision Tree. Authors evaluated the models and measured their accuracy, precision score, recall rate (also known as sensitivity) in addition to F1-score. Gradient Boost, Random Forest, and SVM were top performers among which Gradient boosting was found to be an overall best one with almost 98.5%. They show that machine learning model can successfully predict the label of social media posts, as a way for accurately identifying depression from text data. This detailed model performance evaluation is useful in understanding what each approach does well and poorly, shedding light into whether they are / would be actually suitable for real-world applications. This study not only developed discriminative classifiers, but also included detailed analysis of their performance which should hopefully guide future work and help in practical implementations for real-time mental health monitoring. Through this work, this study aim to facilitate timely identification of depression-related posts, ultimately supporting mental health awareness and intervention efforts on social media platforms. 2024 IEEE. -
The usage of gold and the investment analysis based on gold rate in India
Gold is one of the main commodities where the customers invest their money comparatively with bank for better interest. In the Indian context people purchase gold for their children's marriages for later period. The investment in gold is better suits for easy conversion into money with quickest possible time from the bank and gold merchants. The appreciation or depreciation of gold based on other investment options like fixed deposit, provident fund, international crude oil price, stock market, mutual fund etc. The comparative analysis of gold with other investment options give an edge to the customer to clearly understand the investment pattern for their hard-earned money expected to give good returns in the future. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Physical ageing in Se-Te-Sb glasses
Bulk Se60-xTe40Sbx glasses in the composition range 0?x?14 were prepared by the melt quenching method. Differential Scanning Calorimetric (DSC) and thermal crystallization studies were performed to understand the thermodynamic property like glass transition and structural transformations. These glasses exhibit sharp endothermic peak at the glass transition (Tg). Disappearance of the endothermic peak at Tg in the rejuvenated samples clearly indicates the ageing effect in these glasses. Addition of Sb to Se-Te increases the connectivity of the structural network which is evidenced from the increase in Tg. A distinct change in the slope of the Tg at x=6, indicates a major change in the way the network is connected. The glass forming ability and the thermal stability also exhibit a maximum at x=6. Tg increases with the ageing time and the corresponding fictive temperature (Tf) calculated from the specific heat curves shows a decreasing trend. The molecular movements along the polymeric Se chains might cause the structural relaxation and the physical ageing. The physical ageing effect has been understood on the basis of the Bond Free Solid Angle (BFSA) model proposed by Kastner. Thermally crystallized samples show the formation of rhombohedral Sb2Te 3, rhombohedral Sb2Se3 and hexagonal Te phases. 2013 Elsevier Ltd. -
An Efficient Deep Learning Model Using Harris-Hawk Optimizer for Prognostication of Mental Health Disorders
Mental health disorders are primarily life style driven disorders, which are mostly unidentifiable by clinical or direct observations, but act as a silent killer for the impacted individuals. Using machine learning (ML), the prediction of mental ailments has taken significant interest in medical informatics community especially when clinical indicators are not there. But, majority studies now focus on usual machine learning methods used to predict mental disorders with few organized health data, this may give wrong signals. To overcome the drawbacks of the conventional ML prediction models, this work presents Deep Learning (DL) trained prediction model for automated feature extraction to realistically predict mental health disorders from the online textual posts of individuals indi cating suicidal and depressive contents. The proposed model encompasses three phases named pre-processing, feature extraction and optimal prediction phase. The developed model utilizes a novel Sparse Auto-Encoder based Optimal Bi-LSTM (SAE-O-Bi-LSTM) model, which integrates Bi-LSTM and Adaptive Harris-Hawk Optimizer (AHHO) for extracting the most relevant mental illness indicating features from the textual content in the dataset. The dataset utilized for training consist of 232074 unique posts from the "SuicideWatch" and "Depression" subreddits of the Reddit platform during December 2009 to Jan 2021 downloaded from Kaggle. In-depth comparative analysis of the testing results is conducted using accuracy, precisions, F1 score, specificity, and Recall and ROC curve. The results depict considerable improvement for our developed approach with an accuracy of 98.8% and precision of 98.7% respectively, which supports the efficacy of our proposed model. The Author(s) 2024. -
Getting Back to Work: Cognitive-Communicative Predictors for Work Re-entry Following Traumatic Brain Injury
Return to work following a Traumatic Brain Injury (TBI) is affected by deficits across the cognitive, psycho-social and physical domains. The specific role of cognitive -communicative abilities influencing work re-entry is understudied. This study aimed at identifying the cognitive-communicative predictors for work re-entry following TBI. Thirty patients with TBI employed pre morbidly were categorized into two groups- 14 employed and 16 unemployed post TBI. Those having sustained mild, moderate or severe head injury and in the post injury period of 648months were recruited and majority belonged to skilled/ professional type of premorbid occupational status. They underwent a detailed assessment of cognition, language and communication using NIMHANS Neuropsychology Battery, Indian adapted versions of Western Aphasia Battery and La Trobe Communication Questionnaire (LCQ) respectively. Patients employed post TBI had better Aphasia Quotient (AQ) and better performance on all the cognitive domains and few domains of LCQ than those who remained unemployed. On step-wise Discriminant Function Analysis (DFA), injury severity and AQ could significantly differentiate between the two groups with an overall accuracy of 80%. Severity of head injury is a significant predictor for employability post TBI and evaluation of language along with cognitive abilities is crucial for patients with TBI for work re-entry. The study highlights the importance of a multi-disciplinary team in the assessment and management of cognitive-communication impairments following a TBI. 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Polymer Nanocomposite Graphene Quantum Dots for High-Efficiency Ultraviolet Photodetector
Influence on photocurrent sensitivity of hydrothermally synthesized electrochemically active graphene quantum dots on conjugated polymer utilized for a novel single-layer device has been performed. Fabrications of high-performance ultraviolet photodetector by depositing the polypyrrole-graphene quantum dots (PPy-GQDs) active layer of the ITO electrode were exposed to an Ultraviolet (UV) source with 265 and 355 nm wavelengths for about 200 s, and we examined the time-dependent photoresponse. The excellent performance of GQDs was exploited as a light absorber, acting as an electron donor to improve the carrier concentration. PGC4 exhibits high photoresponsivity up to the 2.33 A/W at 6 V bias and the photocurrent changes from 2.9 to 18 A. The electrochemical measurement was studied using an electrochemical workstation. The cyclic voltammetry (CV) results show that the hysteresis loop is optically tunable with a UV light source with 265 and 355 nm at 0.1 to 0.5 V/s. The photocurrent response in PPy-GQDs devices may be applicable to optoelectronics devices. 2022 by the authors. -
Recent advances in the development, design and mechanism of negative electrodes for asymmetric supercapacitor applications
Continuous technical advancements in a variety of industries, such as portable electronics, transportation, green energy, are frequently hampered by the inadequacy of energy-storage technologies. Asymmetric supercapacitors can expand their operating voltage window past the thermodynamic breakdown voltage of electrolytes by utilizing two distinct electrode materials, providing a workaround for the symmetric supercapacitors energy storage constraints. This evaluation offers a thorough understanding of this area. To comprehend the extensive research done in this field, we first examine the fundamental energy-storage mechanisms and performance evaluation standards for asymmetric supercapacitors. The most recent developments in the design and manufacture of electrode materials as well as the general structure of asymmetric supercapacitors. We have also discussed a number of significant scientific issues and offer our opinions on how to improve the electrochemical properties of future asymmetric energy storage devices. First, methods for designing high-performance electrode materials for supercapacitors must be developed; next, controllably built supercapacitor types must be attained (such as symmetric capacitors including double-layer and pseudocapacitors, asymmetric capacitors, and Li-ion capacitors). This review is timely because of the rapid expansion of research in this area. It summarizes recent developments in the study and creation of high-performance electrode materials with high supercapacitors. A number of crucial topics for enhancing the energy density of supercapacitors are examined, along with some reciprocal correlations between the main impacting parameters. Difficulties and prospects in this fascinating field are also covered. This offers a fundamental understanding of supercapacitors and serves as a crucial design rule for enhanced next-generation supercapacitors that will be used in both industrial and consumer applications. In this context, we extensively reviewed the classification of supercapacitor, EDLC (activated carbon, carbon aerogel, carbon nanotube), Pseudocapacitors, conducting polymers, metal oxides, hybrid materials, composite hybrids, rechargeable batteries, asymmetric devices and its design, aqueous solid state, fiber based asymmetric device, graphene based asymmetric device, terminologies used during the electrode selection, positive and negative electrodes in asymmetric device, material used for fabrication of negative electrodes, electrochemical performance of various devices which are fabricated by different electrode materials. Performance of material for various asymmetric device applications, conclusions outlook, recent developments in asymmetric devices. The current review may offer a thorough understanding and future prospects for developing negative electrodes to enhance asymmetric supercapacitor performance. 2023 Taylor & Francis Group, LLC. -
An Intelligent System to Forecast COVID-19 Pandemic using Hybrid Neural Network
A current outbreak known as COVID-19 has been discovered from the coronavirus was informed by WHO. COVID-19 is a universal pandemic that has brought out the best and the worst of humanity. Due to an increase in the cases daily, COVID-19 is creating a menace to public health and establishes a disruption of the social and economic development of the countries. The problem is the hospitals are not able to provide proper facilities and treatments on time due to the lack of facilities in India. The purpose of this project to build an efficient hybrid deep learning model for forecasting the COVID-19 pandemic with multiple features that are responsible for the spread of COVID-19 in the top five states in India. In particular, a hybrid model that incorporates Auto-Regressive Integrated Moving Average and Long-term Short Memory is been used to forecast confirmed cases. The linear and non-linear dependencies in the dataset is been dealt with by an ARIMA-LSTM hybrid model. As a result, when compared to the outcomes of ARIMA, LSTM models independently, the hybrid model was giving better results and was performing well in forecasting COVID-19 cases. Through this, the policymakers will get prior information on COVID-19 cases in states which will help the government and healthcare departments to take prominent measures to prevent it. 2021 IEEE. -
District Level Analytical Study of Infant Malnutrition in Madhya Pradesh
One of the main causes for Indias high infant mortality rate is malnutrition. It can be addressed using three broad groups of conditions: stunting, wasting, and underweight. Other factors such as sanitation, poverty, breastfeeding also contribute to the prevalence of malnutrition. Understanding the contribution of these factors and thus, eliminating them, to reduce malnutrition, is the purpose of this study. In this chapter, the district-level data obtained through NFHS-4 is used for analytical study for infant malnutrition, in Madhya Pradesh. Hierarchical Agglomerative clustering is used to group the districts based on the factors such as exclusively breastfeeding, inoculation, breastfeeding within one hour, no inoculation. The proposed model presents the effect of each factor, on infant malnutrition. It will help decision-makers and the government to shortlist the most appropriate districts contributing to malnutrition and to take curative action to reduce the rate of infant malnutrition. It is a generic model which can be utilized by other states to study infant malnutrition. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Effects of Processing Parameters on Microstructure Evolution of Al-7Si-Mg Alloy by Cooling Slope Casting
This work investigates the effects of pouring temperature, slope length, and slope temperature in cooling slope casting on the formation of globular microstructure of Al-7Si-Mg alloy. The remnant alloy on the slope during casting was quenched and characterized at different stages of flow to evaluate the microstructure features developed in cooling slope casting. The primary ?-Al dendritic phase found in conventional cast alloy was transformed into globular shape in slope-processed cast alloy. Finer and more homogenous primary ?-Al phase was formed at lower pouring temperature (625C). The effect of slope length on microstructure of Al-7Si-Mg alloy was significant at high pouring temperatures (640 and 660C) but was not visible at low pouring temperature (625C). The microstructure of alloy became coarser with increasing slope temperature. 2015, ASM International. -
An updated review on advancement in fermentative production strategies for biobutanol using Clostridium spp.
A significant concern of our fuel-dependent era is the unceasing exhaustion of petroleum fuel supplies. In parallel to this, environmental issues such as the greenhouse effect, change in global climate, and increasing global temperature must be addressed on a priority basis. Biobutanol, which has fuel characteristics comparable to gasoline, has attracted global attention as a viable green fuel alternative among the many biofuel alternatives. Renewable biomass could be used for the sustainable production of biobutanol by the acetone-butanol-ethanol (ABE) pathway. Non-extinguishable resources, such as algal and lignocellulosic biomass, and starch are some of the most commonly used feedstock for fermentative production of biobutanol, and each has its particular set of advantages. Clostridium, a gram-positive endospore-forming bacterium that can produce a range of compounds, along with n-butanol is traditionally known for its biobutanol production capabilities. Clostridium fermentation produces biobased n-butanol through ABE fermentation. However, low butanol titer, a lack of suitable feedstock, and product inhibition are the primary difficulties in biobutanol synthesis. Critical issues that are essential for sustainable production of biobutanol include (i) developing high butanol titer producing strains utilizing genetic and metabolic engineering approaches, (ii) renewable biomass that could be used for biobutanol production at a larger scale, and (iii) addressing the limits of traditional batch fermentation by integrated bioprocessing technologies with effective product recovery procedures that have increased the efficiency of biobutanol synthesis. Our paper reviews the current progress in all three aspects of butanol production and presents recent data on current practices in fermentative biobutanol production technology. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Sensitivity and tolerance analysis of 2D Profilometer for TMT primary mirror segments
The primary mirror (M1) of Thirty Meter Telescope (TMT) consists of 492 segments of which, 86 are ground and polished by India-TMT. These segments are off-Axis and aspheric in nature and one of the effective methods to polish such segments is through Stressed Mirror Polishing (SMP). During SMP, consistent in-situ metrology of the surface is needed to achieve the required profile. A 2D Profilometer (2DP) will be used by India-TMT for the low frequency profile metrology. The 2DP is a contact-Approach metrology, consisting of probes positioned in a spiral pattern, measuring the sag of segment surface. Initial section of this paper deals with the sensitivity and tolerance analysis of the 2DP. This is followed by the study on position and rotational errors of the 2DP as a whole. Simulation of these analysis is carried out initially on a sphere and then on different segments of the TMT, in order to study the induced measurement errors. COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. -
Development and Efficacy of Parenting Skill Training for Mothers of Adolescents in Kerala
The primary objective of this research is to develop and assess the effectiveness of an intervention program tailored for mothers of adolescents in Kerala to strengthen their parenting skills. The digital age and unique socio-cultural context present new challenges in child-rearing, and existing parenting programs fall short of addressing these evolving issues. The study employed a mixed-method framework with specific objectives to fill this research gap. The research unfolded in three phases. The initial stage encompassed comprehensive interviews with ten mothers and their adolescents, utilizing a constructionist model for thematic analysis. It unveiled five main and 22 sub-themes, shedding light on mothers' and adolescents' needs and challenges in Kerala. The second phase focused on designing an intervention module specifically suited to address the needs and challenges identified in the qualitative phase. The study used a pre-test, post-test, and experimental design with a control group for the third phase. The researcher used the Alabama Parenting Questionnaire, the Family Environmental Scale, and the Parental Satisfaction Scale to measure the efficacy of the training. The results presented significant improvements in parenting practices in the experimental group, particularly in positive parenting and mothers' involvement with their children. Corporal punishment and inconsistent discipline decreased, while family environment and parenting satisfaction increased. This study contributes substantially to the mental health field by offering an evidence-based program to assist mothers in navigating parenting challenges during adolescence. This intervention aims to improve family dynamics and adolescent well-being. It is a valuable resource for trainers seeking to facilitate behavioral changes within the target groups. -
Multifunctional biosensor activities in food technology, microbes and toxins A systematic mini review
Biosensors have its significant applications in various fields, its use in food processing, food safety and food technology has helped to enhance the overall health of the society as it can successfully determine the presence and concentration of different microorganisms including Escheichia coli, Vibrio cholera, Clostridium spp. etc., and also determination of various toxins present in food like acrylamides, benzene, ethylbenzene, toluene, xylene, nitrosamines, Benzo[a]pyrene (BaP) which are carcinogenic. The preface of biosensors has assisted food industries for monitoring and verification of raw materials, food processing, and composition of the food and assessment of product freshness. Symbolic biosensors have been developed in recent years and yet there is much immediate need for the development of more reliable, cost-effective, sensitive and novel biosensors for rapid detection and identification of food borne pathogens and toxins. Extensive review recapitulates overall food-pathogen testing research market trends, as well as commercialization of biosensors for the food safety industry as legislation creates novel standards for microbial monitoring. Furthermore, the world's concern about the food safety and human's healthcare, the one and only biosensor's exclusive demand is nothing but an alternative in real time diagnosis of diseases causing pathogens. 2022 Elsevier Ltd -
Effective and Meaningful Student Engagement Through Service Learning
A paradigm shift is underway in education, challenging traditional teaching methods and calling for a more engaging and purposeful approach. It is necessary to explore how service learning empowers students to address real-world issues, fostering critical thinking, creativity, collaboration, and communication skills essential for the 21st century. Effective and Meaningful Student Engagement Through Service Learning is a comprehensive exploration of the transformative power of service learning in contemporary education. Within this text, seasoned researchers and practitioners delve into the intricacies of student engagement, emphasizing the importance of active involvement in the learning process. This book opens with a reflection on education, where traditional practices give way to innovative pedagogies. This includes a new pedagogical approach that not only imparts knowledge but also cultivates socially responsible citizens. The book provides a rich tapestry of theoretical foundations, curriculum development strategies, and innovative pedagogical approaches that move beyond passive learning. From evaluating the impact of service learning to incorporating technology and measuring learning outcomes, each chapter offers theoretical frameworks, practical experiments, and real-life examples for educators, administrators, and policymakers. The book addresses the challenges and barriers to achieving meaningful student engagement, proposing practical solutions and recommendations. It emphasizes the role of service learning in building reciprocal relationships with communities and fostering inclusivity. Case studies and best practices from diverse educational settings showcase the effectiveness of different approaches to student engagement. The diverse audience within and beyond the education sector, including students, faculty members, parents, policymakers, NGOs, and community organizations, will find within the pages of this book valuable insights and tools to create more effective and meaningful learning experiences. The book covers a broad spectrum of topics, from the institutionalization of service learning to motivations for sustainable engagement, making it an indispensable resource for anyone passionate about shaping the future of education. 2024 by IGI Global. All rights reserved. -
Disclosure of University Social Responsibility A Review of Select Higher Educational Institutions
This paper explores the disclosure of university social responsibility by higher educational institutions. Based on the disclosure of information on institutional websites, 39 universities were selected for the study. The data, which was assessed on the criteria used by regulatory authorities for grading institutions, revealed that while 12 institutions performed above average in most of the criteria, 17 were in the medium range, and 10 performed below average. The study proposes that disclosure of social responsibility activities with adequate evidence from institutional websites can attract more viewers and prospective students. 2023 Tata Institute of Social Sciences. All rights reserved.