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Anchored ferrocene based heterogeneous electrocatalyst for the synthesis of benzimidazoles
A facile and sustainable electrochemical synthetic strategy for phenyl benzimidazoles has been developed using a ferrocene-based electrocatalyst anchored on Toray carbon paper (TCP) coated with conducting polymeric film. The developed electrode was used for the electrochemical dehydrogenative cyclization reaction of o-phenylene diamine and benzaldehyde using lithium perchlorate/acetonitrile as electrolyte. The surface characteristic properties of the developed electrode were characterized by FESEM, Optical profilometer and X-ray photoelectron spectroscopy. Electron transfer mechanism of the anchored ferrocene-based electrocatalyst was thoroughly studied. To determine the efficacy of the catalyst, the electron transfer coefficient (0.5) and apparent rate constant 41.4 s?1 were determined. The cyclic voltammetry studies reveal that the electrochemical oxidation peak for the synthesis of benzimidazole occurs at 0.48 V. The formation of the product was confirmed by Gas chromatography and Nuclear Magnetic Resonance spectroscopy. A comparison chart is presented for the green metrics and sustainability of the present strategy with other electrochemical approach. 2022 Elsevier Ltd -
Sampling and Categorization of Households for Research in Urban India
Conventional sampling methodologies for citizens/households in urban research in India are constrained due to the lack of readily available, reliable sampling frames. Voter lists, for example, are riddled with errors and, as such may not be able to provide a robust sampling frame from which a representative sample can be drawn. The JanaBrown Citizenship Index project consortium (Janaagraha, India; Brown University, USA) has conceptualized a unique research design that provides an alternative way on how to identify, categorize and sample households (and citizens within) in a city in a representative and meaningful way. The consortium consists of the Janaagraha Centre for Citizenship and Democracy, based in India, and the Brown Center for Contemporary South Asia, part of Brown University, USA. The methodology was designed to enable systematic data collection from citizens and households on aspects of citizenship, infrastructure and service delivery across different demographic sections of society. The article describes how (a) data on communities that are in the minority, such as Muslims, scheduled castes (SC) and scheduled tribes (ST), were used to categorize Polling Parts to allow for stratified random sampling using these strata, (b) geospatial tools such as QGIS and Google Earth were used to create base maps aligning to the established Polling Part unit, (c) the resulting maps were used to create listings of buildings, (d) how housing type categorizations were created (based on the structure/construction material/amenities, etc.) and comprised part of the building listing process, and (e) how the listings were used for sampling and to create population weights where necessary. This article describes these methodological approaches in the context of the project while highlighting advantages and challenges in application to urban research in India more generally. 2022 Lokniti, Centre For The Study Of Developing Societies. -
Emission line star catalogues post- Gaia DR3: A validation of Gaia DR3 data using the LAMOST OBA emission catalogue
Aims.Gaia Data Release 3 (DR3) and further releases have the potential to identify and categorise new emission-line stars in the Galaxy. We perform a comprehensive validation of astrophysical parameters from Gaia DR3 with the spectroscopically estimated emission-line star parameters from the LAMOST OBA emission catalogue. Method. We compare different astrophysical parameters provided by Gaia DR3 with those estimated using LAMOST spectra. By using a larger sample of emission-line stars, we performed a global polynomial and piece-wise linear fit to update the empirical relation to convert the Gaia DR3 pseudo-equivalent width to the observed equivalent width, after removing the weak emitters from the analysis. Results. We find that the emission-line source classifications given by DR3 is in reasonable agreement with the classification from the LAMOST OBA emission catalogue. The astrophysical parameters estimated by the esphs module from Gaia DR3 provides a better estimate when compared to gspphot and gspspec. A second degree polynomial relation is provided along with piece-wise linear fit parameters for the equivalent width conversion. We notice that the LAMOST stars with weak H? emission are not identified to be in emission from BP/RP spectra. This suggests that emission-line sources identified by Gaia DR3 are incomplete. In addition, Gaia DR3 provides valuable information about the binary and variable nature of a sample of emission-line stars. 2022 EDP Sciences. All rights reserved. -
A Bose horn antenna radio telescope (BHARAT) design for 21 cm hydrogen line experiments for radio astronomy teaching
We have designed a low-cost radio telescope system named the Bose Horn Antenna Radio Telescope (BHARAT) to detect the 21 cm hydrogen line emission from our Galaxy. The system is being used at the Radio Physics Laboratory (RPL) (Radio Physics Lab, IUCAA NCRA-TIFR, , ), Inter-University Centre for Astronomy and Astrophysics (IUCAA), India, for laboratory sessions and training students and teachers. It is also a part of the laboratory curriculum at several universities and colleges. Here, we present the design of a highly efficient, easy to build, and cost-effective dual-mode conical horn used as a radio telescope and describe the calibration procedure. We also present some model observation data acquired using the telescope for facilitating easy incorporation of this experiment in the laboratory curriculum of undergraduate or post-graduate programs. We have named the antenna after Acharya (teacher or an influential mentor) Jagadish Chandra Bose, honoring a pioneer in radio-wave science and an outstanding teacher, who inspired several world renowned scientists. 2022 Author(s). -
Drill hole surface characterisation of hybrid FRP laminates through statistical analysis
As it is known that the hybrid Fibre Reinforced Polymer (FRP) composite laminate is a recently evolved class of structural material. Hence, the present work deals with secondary processing ability like hole drilling on hard to machine FRP laminate. The influence of drilling attributes on the delamination factor and surface roughness contours are studied for a high thickness hybrid (carbon/glass FRP) laminates. Here, the experimentation was performed utilising Taguchis L27 design of experiments array. Later, on post-drilling, the predominant and optimum variables were studied through taguchi and variance analysis to highlight their contribution on the response functions. Taguchi results indicate that the combination of the 90?tungsten carbide tool, speed of 800 rpm, and rate of feed 50 mm/min gives the best performance concerning the delamination. Also, it was observed that the combination of the 118?tungsten carbide tool, cutting speed of 900 rpm and the rate of feed 60 mm/min give the best performance concerning surface roughness. Whereas, as per ANOVA, the highest percentage contribution factor was concerned to a tool material followed by other factors and analysed data lie with the confidence level of 95%. The work also indicates that tungsten carbide tool yield better results compared to high-speed steel tool. Further, fibre morphology has been studied, which indicates optimal structure with minimal damage. 2020 Engineers Australia. -
The Un-Human Beings: The Denial of Muslim Migrants Bodies in India and Poland
This essay traces the political and legal discourses around migrants and refugees in two distinct conditions: the postcolonial and the postsocialist of India and Poland, respectively. The two countries have recently turned to nationalist right-wing politics with an increasingly hostile focus on foreign Others, particularly Muslims. In the context of increased global surveillance and criminalization of Muslims, we show how the bodies of Muslim migrants are dehumanized and constructed as threats, denying their humanity in the process. We do this through the two cases of Ayub and Ameer, two Muslim men navigating their illegality in two different contexts in India and Poland. This essay is a contribution to the literature on postcolonial and postsocialist theories and critical debates about the possibilities of dialogue between postsocialist and postcolonial geographies. The examples we use demonstrate that the postcolonial and postsocialist nation-states respond to global phenomena such as migration and Islamophobia in ways that have discernible traces of their histories and are constituted distinctively from the western metropoles. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
The Challenges of Blockchain Technology Adoption in the Agro-based Industries
Blockchain is one of the latest innovations in information technology, bringing a digital revolution to many industries by increasing transparency. But this technology needs to be explored a lot as of now. Agriculture supply chain management distributes agro-based products like vegetables, fruits, pulses, and cereals. This research is conducted to identify the agro-based industries' adoption of blockchain in their supply chain for achieving sustainability. The next step towards sustainable agriculture is primarily seen as blockchain-enabled agriculture. By making supply chains transparent, technology can follow products from the point of manufacture and prevent waste and inefficiency. A structured literature review helped determine the barriers to blockchain adoption in agro-based industries. This research is unique as no survey-based research on blockchain in the agriculture supply chain using structural equation modeling has been found. The seven proposed hypotheses support the blockchain challenges for adoption in agro-based industries. The findings of this study suggest that the blockchain can bring transparency and traceability and will remove the agro-industry inefficiencies. 2022 International Journal of Mathematical, Engineering and Management Sciences. All rights reserved. -
Barbell-shaped giant radio galaxy with ? 100 kpc kink in the jet
We present for the first time a study of peculiar giant radio galaxy (GRG) J223301+131502 using deep multi-frequency radio observations from GMRT (323, 612, and 1300 MHz) and LOFAR (144 MHz) along with optical spectroscopic observations with the WHT 4.2m optical telescope. Our observations have firmly established its redshift of 0.09956 and unveiled its exceptional jet structure extending more than ? 200 kpc leading to a peculiar kink structure of ? 100 kpc. We measure the overall size of this GRG to be ? 1.83 Mpc; it exhibits lobes without any prominent hotspots and closely resembles a barbell. Our deep low-frequency radio maps clearly reveal the steep-spectrum diffuse emission from the lobes of the GRG. The magnetic field strength of ? 5 ?G and spectral ages between about 110 to 200 mega years for the radio lobes were estimated using radio data from LOFAR 144 MHz observations and GMRT 323 and 612 MHz observations. We discuss the possible causes leading to the formation of the observed kink feature for the GRG, which include precession of the jet axis, development of instabilities and magnetic reconnection. Despite its enormous size, the Barbell GRG is found to be residing in a low-mass (M200 ? 1014 M) galaxy cluster. This GRG with two-sided large-scale jets with a kink and diffuse outer lobes residing in a cluster environment, provides an opportunity to explore the structure and growth of GRGs in different environments. 2022 EDP Sciences. All rights reserved. -
Dependence between Sugar Industry Specific Factors and Sugar Companies Share Prices: Evidence from India
We assess the effects of sugar industry-specific macroeconomic factors on share prices of sugar companies in India using quantile regression approach from January 2001 to December 2017. We detect grounds to affirm the dependence between sugar industry specific macroeconomic factors and sugar companies share prices. The results indicate that the change in sugarcane cultivation area has both positive and negative effect on the share prices of sugar companies. Further, it shows that the impact of sugar production on share prices of sugar companies varies across the different quantiles except an insignificant effect on two companies for all quantiles. Moreover, most of the companies share prices are highly and positively influenced by sugar import. The study pointed out that the risk of sugar industry specific macroeconomic factors noticed in the sugar companies share prices is heterogenous. Indian Institute of Finance Vol. XXXVI No. 4, December 2022. -
Modeling of Real Time Traffic Flow Monitoring System Using Deep Learning and Unmanned Aerial Vehicles
Recently, intelligent video surveillance technologies using unmanned aerial vehicles (UAVs) have been considerably increased in the transportation sector. Real time collection of traffic videos by the use of UAVs finds useful to monitor the traffic flow and road conditions. Since traffic jams have become common in urban areas, it is needed to design artificial intelligence (AI) based recognition techniques to attain effective traffic flow monitoring. Besides, the traffic flow monitoring system can assist the traffic managers to start efficient dispersal actions. Therefore, this study designs a real time traffic flow monitoring system using deep learning (DL) and UAVs, called RTTFM-DL. The proposed RTTFM-DL technique aims to detect vehicles, count vehicles, estimate speed and determine traffic flow. In addition, an efficient vehicle detection model is proposed by the use of Faster Regional Convolutional Neural Network (Faster RCNN) with Residual Network (ResNet). Also, a detection line based vehicle counting approach is designed, which is based on overlap ratio. Finally, traffic flow monitoring takes place based on the estimated vehicle count and vehicle speed. In order to guarantee the effectual performance of the RTTFM-DL technique, a series of experimental analyses take place and the results are examined under varying aspects. The experimental outcomes highlighted the betterment of the RTTFM-DL technique over the recent techniques. The RTTFM-DL technique has gained improved outcomes with a higher accuracy of 0.975. 2022 River Publishers. -
Integrated Effect of Flow Field Misalignment and Gas Diffusion Layer Compression/Intrusion on High Temperature - Polymer Electrolyte Membrane Fuel Cell Performance
Misalignment in the flow field plates of High-Temperature Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) due to manufacturing tolerances, assembly process, or unavoidable vibration during the cell operation is contemplated its performance and durability. This study investigates the effect of flow field plate misalignment and its concomitant impact with varying the clamping pressures on HT-PEMFC operation. The study considers six degrees of cathode flow field misalignment, varying from 0% to 100% with respect to the anode flow field. Clamping pressures ranging from 1 to 2 MPa are applied to the various cases of misalignment to study their effect on GDL deformation and intrusion into the channels. The structural analysis shows that as the misalignment increases from 0 to 100%, the GDL compression increases from 26.72% to 37.75% for 1 MPa, 40.07% to 56.63% for 1.5 MPa, and 53.43% to 75.51% for 2 MPa, owing to the increase in compression approximately by 41% from their base cases and it is also crucial to note that GDL compression exaggerates at higher clamping pressures. The misalignment results in the sagging of Membrane Electrode Assembly (MEA), and the amplitude of wave nature is proportional to the degree of misalignment and clamping pressure, indicating the misalignment is the sole factor for structural changes. As a result, considerable variance in current distribution and average value is observed, i.e., at operating voltage 0.5 V, the current density drops from 4472.7 to 4264.4, 4420.7 to 4211.8, and 4374.1 to 4161.3 A m?2 from cases 1 to 6 for clamping pressures 1, 1.5, and 2 MPa, respectively, resulting in a 4.7% loss in performance. According to the observations, a misalignment of 60% is tolerable, with minimal performance loss and negligible non-uniformity in cell distributions. 2022 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Spectral characteristics of the black hole binary 4U 1957+115: a multi mission perspective
We report spectral analysis of the persistent black hole X-ray binary, 4U 1957+115, using AstroSat, Swift, and NuSTAR observations carried out between 2016 and 2019. Modelling with a disc emission, thermal Comptonization, and blurred reflection components revealed that the source was in the high-soft state with the disc flux ?87 per cent of the total and high-energy photon index ?2.6. There is an evidence that either the inner disc radius varied by ?25 per cent or the colour hardening factor changed by ?12 per cent. The values of the inner disc radius imply that for a non-spinning black hole, the black hole mass is < 7 M ? and the source is located > 30 kpc away. On the other hand, a rapidly spinning black hole would be consistent with the more plausible black hole mass of < 10 M ? and a source distance of ?10 kpc. Fixing the distance to 10 kpc and using a relativistic accretion disc model, constrained the black hole mass to 6 M? and inclination angle to 72. A positive correlation is detected between the accretion rate and inner radii or equivalently between the accretion rate and colour factor. 2022 The Author(s). -
A STUDY OF AN UNDIRECTED GRAPH ON A FINITE SUBSET OF NATURAL NUMBERS
Let Gn = (V, E) be an undirected simple graph, whose vertex set comprises of the natural numbers which are less than n but not relatively prime to n and two distinct vertices u, v ? V are adjacent if and only if gcd(u, v) > 1. Connectedness, completeness, minimum degree, maximum degree, independence number, domination number and Eulerian property of the graph Gn are studied in this paper. 2022, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
IoT enabled lung cancer detection and routing algorithm using CBSOA-based ShCNN
The Internet of Things (IoT) has tremendously spread worldwide, and it influenced the world through easy connectivity, interoperability, and interconnectivity using IoT devices. Numerous techniques have been developed using IoT-enabled health care systems for cancer detection, but some limitations exist in transmitting the health data to the cloud. The limitations can be accomplished using the proposed chronological-based social optimization algorithm (CBSOA) that effectively transmits the patient's health data using IoT network, thereby detecting lung cancer in an effective way. Initially, nodes in the IoT network are simulated such that patient's health data are collected, and for transmission of such data, routing is performed in order to transmit the health data from source to destination through a gateway based on cloud service using CBSOA. The fitness is newly modeled by assuming the factors like energy, distance, trust, delay, and link quality. Finally, lung cancer detection is carried out at the destination point. At the destination point, the acquired input data is fed to preprocessing phase to make the data acceptable for further mechanism using data normalization. Once the feature selection is done using Canberra distance, then the lung cancer detection is performed using shepard convolutional neural network (ShCNN). The process of routing as well as training of ShCNN is performed using the CBSOA algorithm, which is devised by the inclusion of the chronological concept into the social optimization algorithm. The proposed approach has achieved a maximum accuracy of 0.940, maximum sensitivity of 0.941, maximum specificity of 0.928, and minimum energy of 0.452. 2022 John Wiley & Sons Ltd. -
Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs
In todays information technology (IT) world, the multi-hop wireless sensor networks (MHWSNs) are considered the building block for the Internet of Things (IoT) enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service (QoS) in a stipulated time slot to end-user over the Internet. Smart city (SC) is an example of one such application which can automate a group of civil services like automatic control of traffic lights, weather prediction, surveillance, etc., in our daily life. These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput, energy efficiency, and end-to-end delay, wherein low latency is considered a challenging issue in next-generation networks (NGN). This paper introduces a single and parallels stable server queuing model with a multi-class of packets and native and coded packet flow to illustrate the simple chain topology and complex multiway relay (MWR) node with specific neighbor topology. Further, for improving data transmission capacity in MHWSNs, an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node. Finally, the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets. The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results. 2023 Tech Science Press. All rights reserved. -
Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach
Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid. References 22, tables 2, figures 17. E. Parimalasundar, R. Senthil Kumar, V.S. Chandrika, K. Suresh. -
Impact of helpful reviews on customer purchase intention with special reference to mobile phone reviews
Technological advances in the digital space have provided renewed impetus to businesses. Costly, labor-intensive marketing campaigns have been replaced by digital marketing. However, along with benefits, the increasing sophistication and exponential growth of e-commerce businesses have also introduced new challenges. The large number of similar product offerings and the high volume of reviews have created a technology-induced hurdle for consumers that can impair their thought processes. Often, users will only scan the top few reviews to arrive at a decision. In the current setup, older reviews that accumulate votes over time are found at the top of the helpful review list, in contrast to fresh entrants. The current study proposes placing reviews in appropriate positions in the helpful review list using statistical and scientifically derived helpfulness scores. The study utilized a sample of consumer goods (specifically, mobile phones) and re-ranked reviews based on their expected score. Amazon.in provided the initial review dataset. Random Forest and gradient-boosting regression techniques were used to predict review helpfulness. An Elaboration Likelihood Model was used to explore the impact of central and peripheral cues on review helpfulness. The gradient-boosting regression was the best-performing method of predicting review helpfulness, and the reviews were re-ranked. The re-ranked reviews were tested for helpfulness vis-a-vis the initial ranking of reviews using the survey method. The result indicated that the proposed re-ranking of reviews was more helpful to end users and helped mitigate uncertainty in decisions. The study utilized the Information Acceptance Model to assess the influence of electronic word of mouth on purchase intention. 2023 Conscientia Beam. All Rights Reserved. -
Examining the Relationship between Academic Expectations and Suicidal Ideation among College Students in India Using the Interpersonal Theory of Suicide
Objective: As the second most populous country in the world, India accounts for over 20% of the global suicide deaths. Notably, young adults make up 38% of those who die by suicide in India. Yet, the literature on factors associated with suicide within this age group in India is limited. The Interpersonal Theory of Suicide (IPTS) posits thwarted belongingness and perceived burdensomeness as constructs that heighten the risk for suicide. Testing mechanisms that may mediate the relationship between common stressors for young adults in India, such as academic expectations, and suicidal ideation are important to better understand factors contributing to suicide risk within this country. Method: Indian college students (N = 432, M age = 19.41, 73.1% male) completed questionnaires on academic expectations, thwarted belongingness, perceived burdensomeness, collectivism, and suicidal ideation. Results: Current suicidal ideation was endorsed at a rate of 38%. Academic expectancy from the self, perceived burdensomeness, and thwarted belongingness was significantly associated with suicidal ideation. The only significantly mediated pathway was academic expectancy from others to suicidal ideation through perceived burdensomeness. Collectivism was not a significant moderator in the model. Discussion: The sample endorsed high rates of suicidal ideation, highlighting the need for culturally appropriate interventions. Thwarted belongingness, perceived burdensomeness, and academic expectations from oneself may be relevant treatment targets for reducing suicidal ideation among college students in India.HIGHLIGHTS Over one-third of Indian university students endorsed suicidal ideation. Suicidal ideation related to ones own more than others academic expectations. Results offer support for the Interpersonal Theory of Suicide within this context. 2022 International Academy for Suicide Research. -
Machine LearningEnabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data
Abstract: An increasingly large dataset of pharmaceuticsdisciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robustdata on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset (http://www.models.life.ku.dk/Tablets) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. Highlights: We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation Model extension from lab-scale to pilot-scale successfully demonstrated Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s). -
Mediating role of self-concept on character strengths and well-being among adolescents with specific learning disorder in India
Background: Adolescents with Specific Learning Disorder (SLD) are at higher risk of academic underachievement, stigmatization, and mental health issues. However, the complete elimination of disorder-related deficits and external challenges is an impracticable solution for enhancing their well-being. Aim: The study adopts a strength-based approach to understand the role of an innate factor, i.e., self-concept, in the association between character strengths and well-being of adolescents with SLD. Methods: A correlational research design following a mediation analysis was adopted to examine the association between the study variables on a sample of 115 adolescents with SLD from India. Results: Self-concept functioned as a partial mediator between the life-satisfaction construct of well-being and six character strengths: Appreciation of beauty and excellence, Perseverance, Judgment, Leadership, Perspective, and Zest. Gender differences were identified with regard to the study variables. Conclusions and implications: Self-concept of adolescents with SLD could partly contribute to enhanced character strengths awareness to protect well-being. Further, the crucial role of internal factors like self-concept and character strengths in improving the well-being of this population was highlighted. Thereby encouraging future research on SLD to adopt approaches that focus on innate strengths rather than deficits and external sources of well-being. 2022 Elsevier Ltd