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Analysis and Forecasting of Area Under Cultivation of Rice in India: Univariate Time Series Approach
This study uses three distinct models to analyse a univariate time series of data: Holt's exponential smoothing model, the autoregressive integrated moving average (ARIMA) model, and the neural network autoregression (NNAR) model. The effectiveness of each model is assessed using in-sample forecasts and accuracy metrics, including mean absolute percentage error, mean absolute square error, and root mean square log error. The area under cultivation in India for the following 5years is predicted using the model whose fitted values are most like the observed values. This is determined by performing a residual analysis. The time series data used for the study was initially found to be non-stationary. It is then transformed into stationary data using differencing before the models can be used for analysis and prediction. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Influence of perceived equity, job enrichment, and burnout among educators in Indian private universities on job satisfaction and the desire to quit
The desire to quit converts into actual attrition if left unaddressed. Additionally, employees job satisfaction strongly influences their desire to stay or leave. Several individual and organizational factors affect job satisfaction levels, all of which must be thoroughly analyzed to curb both the desire to quit and attrition. The current study tests a model associating perceived equity, job enrichment, and burnout with job satisfaction and the desire to quit of educators employed in private universities in India. Data were collected from 272 university faculty members using five scales, namely, job enrichment, perceived equity, employee burnout, job satisfaction, and intention to leave, and were analyzed using AMOS 17. The initial fitness results failed to support the hypothesized framework, but a revised framework yielded a good fit for the data. Results show that perceived equity has a positive influence on job satisfaction (Hypothesis 2), job enrichment positively affects job satisfaction (Hypothesis 3), burnout negatively influences job satisfaction (Hypothesis 4), and job satisfaction negatively affects the desire to leave (Hypothesis 1). Perceived equity, burnout, and job satisfaction were found to mediate the association between job enrichment and the desire to leave. The results indicate that private universities must focus on job satisfaction to reduce employees desire to quit, thereby reducing the attrition level, which is currently a severe problem with both financial and non-financial consequences to universities. From the results, it can be seen that job enrichment has acted as a mediator to influence employees job satisfaction. Future research can explore HR practices contributing to high job enrichment, and this study would have considerable practical implications. Copyright 2022 Annamalai. -
Pedagogical exploration for generation z students: Experiments using student-developed video case studies, gamification, student-developed case simulation and a movie reflection exercise in an organizational behaviour course
This paper will focus on three experiments performed while teaching undergraduate and graduate students using innovative pedagogy. In all three studies, the purpose was to understand how effective these pedagogical tools were in generating enthusiasm and engaging the students in the learning process. In study 1, teams developed and presented video case studies on the organizational behaviour themes studied in the course, applying them to practical scenarios. Later, the facilitators conducted a modified gamification quiz based on the video case studies, and the quiz results were considered to be the actual assessment of the students learning process. In study 2, student teams were asked to brain-storm and develop case simulations based on actual incidents encountered by those students who had work experience. In study 3, the undergraduate students were shown the classic movie 12 Angry Men as a means of learning about team decision-making processes. They reflected on and discussed the movie in relation to theory. Feedback collected at the end of each study conveyed that students experienced high levels of enthusiasm and engagement with positive learning outcomes. 2020 NeilsonJournals Publishing. -
Embracing intelligent machines: Aqualitative study to explore thetransformational trends inthe workplace
Purpose: With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines. Design/methodology/approach: We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected. Findings: This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies. Originality/value: This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation. 2024, Sumathi Annamalai and Aditi Vasunandan. -
Social isolation and loneliness among Generation Z employees: can emotional intelligence help mitigate?
The paper tested a moderated mediation model with social isolation, loneliness, emotional intelligence, and quality of life among Generation Z (Gen Z) employees. Approximately 568 Gen Z employees participated in this study. We used WHOQOL-BREF for measuring quality of life, Schuttes emotional intelligence test, UCLA loneliness scale and social isolation scale from Choi and Noh. We applied the PROCESS macro (model 7) by Hayes for a moderated mediation analysis, using emotional intelligence as a moderating variable and loneliness as a mediating variable between social isolation and quality of life. The results indicate that emotional intelligence moderates the mediating effect of loneliness on social isolation and quality of life and supports hypothesis 2. First, the indirect impact of social isolation on quality of life varies as a function of emotional intelligence moderating the path. Second, both social isolation and loneliness are negative and significant predictors of quality of life. Loneliness is not an individual problem anymore but a public health issue around the world. Individuals who are lonely experience both mental and physical health issues. Strong measures are needed to combat loneliness, and the current research results confirm that emotional intelligence-based interventions will help individuals fight loneliness. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Development of a Supported Education Program for Students with Severe Mental Disorders in India
Background: The onset of severe mental disorders (SMDs) is during adolescence or young adulthood, which affects the well-being and the educational aspirations of the students. Models of supported education practiced in the West are not culturally suitable for Indian students or the Indian education system. This study aimed to develop a Supported Education Program (SEP) for students with SMDs to help them with academic reintegration in an Indian context. Methods and Material: To develop the SEP, a realist review was done, followed by an in-depth interview with eight mental health professionals (MHP) and nine lecturers, using a validated interview script. After each interview, interim analysis and modifications were done to improve the rigor of the interview. After all interviews, the SEP was circulated for a second round of iteration for consensual validation by four mental health experts. The outcome of the entire process was the final version of SEP for students with SMDs. Results: The final SEP had two broad themes and 18 subthemes from the qualitative thematic analysis: theme 1 included issues and strategies relevant to the client or caregivers, and theme 2 was pertinent to the education system. Conclusion: The SEP developed and validated for people with SMDs has distinctive components: one for the individual and caregiver and the other for the educational system. 2020 Indian Psychiatric Society - South Zonal Branch. -
The Impact of Supportive Factors on the Academic Reintegration of Students with Mental Illness: A Qualitative Study
Introduction: Returning to college following a psychiatric illness can be overwhelming for students as academic reintegration is a significant undertaking. Psychological distress can negatively impact a student's performance and levels of academic achievement. A better understandingof the factors that facilitateacademicreintegration would helpmental health professionals, educators, and family members support students more effectively. Methods and Materials: The study followed an explorative research design and utilized a purposivesampling technique. The Institute's(National Institute of Mental Health and Neurosciences, NIMHANS) Ethics Committee evaluated and approved this study, while four (4) mental health experts validated the interview schedule. Theprimary researcher (ASR) audio-recorded, transcribed and coded fourteen (14) in-depth interviews.The study supervisors (AJ and TK) verified this procedure.Themes and sub-themes were derivedfrom the codes,and thenthematic analysis was conducted. Results: Fivesupportive factors (themes and sub-themes) were derived: 1. Family:Educational qualification of the members, Family accommodations (travelling to the city where the student is studying for additional support).Academic assistance, Freedom to select their educational course; 2.Support from friends and peers: Academic support, Emotional support (caregiving,home visits, sharing problems with them), Logistic support (physically accompanying the student to and from class, providing transport); 3.Support from Teachers and Collegeadministration: Additional academic support from teachers, Reasonable classroom accommodations; 4.SupportfromMental health professionals (MHPs):Providing Pharmacological or Psychosocial Interventions, Follow up,andcontinuous guidance (handholding); 5. Individual factors (students' strengths): High degree of motivation or interest in studies, strong academic record, and healthy coping mechanisms. Conclusion: Students with mental illnesses require additional support with academic reintegration. As a result, assisting students in successfully returning to academics is frequently a collaborative effort involving family, peers, mental health professionals, teachers, and college administration. 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Understanding the role of acid sites of Zinc Aluminophosphate catalysts in eco-friendly synthesis of carbamates
Aluminophosphate and metal incorporated aluminophosphates have been synthesized at ice-cold temperature by simple co-precipitation method in the absence of a templating agent. Surface and bulk properties of synthesized materials were studied by different characterization techniques. The materials were found to be X-ray amorphous. N2 adsorption-desorption studies exhibited the existence of microporous structure and uniform narrow slit type of pores on the materials. The catalytic activity of the synthesized material was tested in phosgene free synthesis of carbamates from corresponding amines and dimethyl carbonate (DMC) through a greener route. Metal incorporated Aluminophosphates indicated excellent catalytic activity compared to pure aluminophosphates. Zinc aluminophosphate catalyst exhibited 83% carbamate yield with 100% selectivity towards the formation of carbamate. The excellent catalytic activity of Zinc aluminophosphate with 94% amine conversion is attributed to its surface properties mainly moderate acid strength. The incorporated metal plays a vital role in the structural and textural properties of aluminophosphates. A systematic study was conducted to correlate the catalytic activity and surface properties of metal aluminophosphates. Reaction conditions were optimized to obtain a better yield through phosgene free eco-friendly routes using different amines. The catalyst was found to be recyclable for 5 cycles in the desired reaction without a reduction in conversion and selectivity. 2021. All Rights Reserved. -
Linear and non-linear analyses of double-diffusive-Chandrasekhar convection coupled with cross-diffusion in micropolar fluid over saturated porous medium
Purpose: The problem aims to find the effects of coupled cross-diffusion in micropolar fluid oversaturated porous medium, subjected to Double-Diffusive Chandrasekhar convection. Design/methodology/approach: Normal mode and perturbation technique have been employed to determine the critical Rayleigh number. Non-linear analysis is carried out by deriving the Lorenz equations using truncated Fourier series representation. Heat and Mass transport are quantified by Nusselt and Sherwood numbers, respectively. Findings: Analysis related to the effects of various parameters is plotted, and the results for the same are interpreted. It is observed from the results that the Dufour parameter and Soret parameter have an opposite influence on the system of cross-diffusion. Originality/value: The effect of the magnetic field on the onset of double-diffusive convection in a porous medium coupled with cross-diffusion in a micropolar fluid is studied for the first time. 2020, Emerald Publishing Limited. -
Linear and non-linear analyses of double diffusive chandrasekhar convection with heat and concentration source in micropolar fluid with saturated porous media under gravity modulation
In this paper, linear and non-linear analysis of Double-Diffusive convection in the presence of magnetic field and gravity modulation with heat and concentration source in a micropolar fluid is studied by assuming the strength of heat and concentration source same. The expression for Rayleigh number and correction Rayleigh number are obtained using regular perturbation method. The effects of parameters on heat and mass transport is investigated using non-linear analysis by deriving eighth order Lorenz equation. It is found that coupling parameter and Chandrasekhar number stabilizes the system. Whereas internal Rayleigh number and Darcy number destabilizes the system. 2020 International Association of Engineers. -
Efficacy of digital MBCT-PD in preventing postpartum depression and enhancing work motivation: A study protocol
Background: Postpartum depression (PPD) is a significant challenge for women transitioning back to work. While preventive measures are essential, the effectiveness of Mindfulness-Based Cognitive Therapy (MBCT) in this context remains underexplored. This study will assess the efficacy of a digital MBCT program (MBCT-PD) in preventing PPD, enhancing well-being, and motivating work resumption after childbirth. Methods: A randomized controlled trial (RCT) with repeated measures will evaluate MBCT-PD, a digitally delivered intervention designed to promote mindfulness and emotional resilience. Eighty consenting pregnant women aged 18+, between 16 and 32 weeks gestation, residing in urban India will be recruited and randomized to either the MBCT-PD group or an enhanced treatment-as-usual (TAU) control group, which includes additional prenatal wellness resources. The intervention will span eight weeks, with assessments at baseline, post-intervention (T1), and six weeks postpartum (T2). Primary outcomes are depression (Edinburgh Postnatal Depression Scale), well-being (Pregnancy Experience Scale-Brief), and work motivation (Multidimensional Work Motivation Scale). Secondary outcome is mindfulness level (Three Facet Mindfulness Questionnaire-Short Form). Descriptive statistics, repeated measures ANOVA, and regression analyses will determine the effect of MBCT-PD on these outcomes. Expected Results: We anticipate that the MBCT-PD group will show reduced PPD symptoms, improved well-being, and greater motivation to resume work than the control group, consistent with previous findings on mindfulness-based interventions. Conclusion: The findings from this study are expected to support the efficacy of MBCT-PD as a cost-effective, scalable intervention for enhancing postpartum mental health and work reintegration, with potential applications in maternal mental health practices and policies worldwide. Trial Registration: Clinical Trial Registry of India. CTRI/2024/03/064,831 2025 -
Efficacy of in-person versus digital mental health interventions for postpartum depression: meta-analysis of randomized controlled trials
Aim: This meta-analysis aimed to compare the efficacy of in-person and digital mental health interventions in addressing Postpartum Depression. Methods: Following PRISMA guidelines, the protocol for this meta-analysis was registered at the Open Science Framework (Retrieved from osf.io/wy3s4). This meta analysis included Randomized Controlled Trials (RCTs) conducted between 2013 and 2023. A comprehensive literature search identified 35 eligible RCTs from various electronic databases. Inclusion criteria focused on pregnant women over 18 years old, encompassing antenatal depression and up to two years postpartum. Diagnostic interviews or Edinburgh Postnatal Depression Scale (EPDS) were used to establish PPD. Digital interventions included telephonic, app-based, or internet-based approaches, while in-person interventions involved face-to-face sessions. Results: The meta-analysis revealed a moderate overall effect size of ?0.69, indicating that psychological interventions are effective for PPD. Digital interventions (g = ?0.86) exhibited a higher mean effect size than in-person interventions (g = ?0.55). Both types of interventions displayed substantial heterogeneity (digital: I2 = 99%, in-person: I2 = 92%), suggesting variability in intervention content, delivery methods, and participant characteristics. Conclusion: Digital mental health interventions show promise in addressing PPD symptoms, with a potentially greater effect size compared to in-person interventions. However, the high heterogeneity observed in both modalities underscores the need for further research to identify key drivers of success and tailor interventions to diverse populations. Additionally, the choice between digital and in-person interventions should consider individual needs and preferences. Ongoing research should further investigate and optimise intervention modalities to better serve pregnant women at risk of PPD. 2024 Society for Reproductive & Infant Psychology. -
Modeling of the LiouvilleGreen method to approximate the mechanical waves in functionally graded and piezo material with a comparative study
The present research article studies and compares the surface waves transmission through the functionally graded piezoelectric material (FGPM) club between the piezomagnetic (PM) layer -and half-space, and for a comparative study, lower half-space is assumed to be piezoelectric material. The transmission of mechanical waves in a smart structure is analyzed by following the elastic wave theory of magneto-electro-elasticity. The Liouville-Green (LG) approximation technique is used to solve the differential equation in the FGPM stratum, where exponential variation is assumed in material gradients. It is noticed that the material gradients depend considerably on the angular frequency, which should be a crucial factor in regulating the dispersion characteristics of functionally graded materials (FGM) waveguides. In closed determinant form, the dispersion relation has been obtained for FGPM plate for electrically open and short cases. The profound effect of parameters, such as material gradient, a width of the layer on phase velocity, coupled electromechanical factor, and angular velocity, is observed and delineated graphically. Different parametric plots are sub-plotted into a single figure to increase the readability of the graphs. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Examining the consumption of oil on total factor productivity and CO2 emissions: an analysis of highly oil-consuming countries
Purpose: This study aims to examine the impact of oil consumption on carbon dioxide (CO2) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from 1995 to 2019. Design/methodology/approach: For this purpose, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied. Findings: FMOLS and DOLS models reveal that oil consumption, human capital, population, trade openness and nonrenewable energy have a significant positive effect on CO2 emissions. While information and communication technology (ICT), as proxied by mobile and natural resources, has a significant negative effect on CO2 emissions. In the case of TFP, oil consumption, ICT and natural resources have a significant positive effect on the TFP. On the other hand, trade openness, population, human capital and nonrenewable energy have a significant negative effect on TFP. The results of this study can help to provide policy recommendations to reduce CO2 emissions in studied highly oil-consuming countries of the world. Originality/value: Due to the threat to sustainable development, climate change has become a major topic for debate around the world. The influence of oil consumption on CO2 emission and TFP is less known in the available literature. Another significance of this study is that many researchers considered aggregate energy consumption to study this relationship, but the authors have studied the effect of energy consumption, particularly from oil in the top oil-consuming countries, which is a significant shortcoming of the present research. 2023, Emerald Publishing Limited. -
The Association between Accounting determined and market determined measures of risk: Evidences from Indian Pharmaceutical Industry.
Volume : 3, Issue : 12, pp- 35-44, ISSN: 2249-7307 -
Multi-stage fuzzy swarm intelligence for automatic hepatic lesion segmentation from CT scans
Segmentation of liver and hepatic lesions using computed tomography (CT) is a critical and challenging task for doctors to accurately identify liver abnormalities and to reduce the risk of liver surgery. This study proposed a novel dynamic approach to improve the fuzzy c-means (FCM) clustering algorithm for automatic localization and segmentation of liver and hepatic lesions from CT scans. More specifically, we developed a powerful optimization approach in terms of accuracy, speed, and optimal convergence based on fast-FCM, chaos theory, and bio-inspired ant lion optimizer (ALO), named (CALOFCM), for automatic liver and hepatic lesion segmentation. We employed ALO to guide the FCM to determine the optimal cluster centroids for segmentation processes. We used chaos theory to improve the performance of ALO in terms of convergence speed and local minima avoidance. In addition, chaos theory-based ALO prevented the FCM from getting stuck in local minima and increased computational performance, thus increasing stability, reducing sensitivity in the iterative process, and allowing the best centroids to be used by FCM. We validated the proposed approach on a group of patients with abdominal liver CT images, and the results showed good detection and segmentation performance compared with other popular techniques. This new hybrid approach allowed for the clinical diagnosis of hepatic lesions earlier and more systematically, thereby helping medical experts in their decision-making. 2020 Elsevier B.V. -
A compression system for Unicode files using an enhanced Lzw method
Data compression plays a vital and pivotal role in the process of computing as it helps in space reduction occupied by a file as well as to reduce the time taken to access the file.This work relates to a method for compressing and decompressing a UTF-8 encoded stream of data pertaining to Lempel-Ziv-welch (LZW) method. It is worth to use an exclusive-purpose LZW compression scheme as many applications are utilizing Unicode text. The system of the present work comprises a compression module, configured to compress the Unicode data by creating the dictionary entries in Unicode format. This is accomplished with adaptive characteristic data compression tables built upon the data to be compressed reflecting the characteristics of the most recent input data. The decompression module is configured to decompress the compressed file with the help of unique Unicode character table obtained from the compression module and the encoded output. We can have remarkable gain in compression, wherein the knowledge that we gather from the source is used to explore the decompression process. Universiti Putra Malaysia Press. -
Epileptic seizure detection using EEG signals and multilayer perceptron learning algorithm
Purpose: Epileptic is a neurological chronic disorder that causes unprovoked, recurrent seizure. A seizure is a sudden rush of electrical activity in the brain. The central nervous system characterized by the loss of consciousness and convulsions. Epileptic is caused by abnormal electrical discharge that lead to uncountable movements, loss of consciousness and convulsions. 50-80 million people in the world are affected by this disorder. Now a days children and adults are affected the most and it has been medically treated. Sometimes it may lead to death and serious injuries. In this technology world the computerized detection is an enhanced solution to protect epileptic patients from dangers at the time of this seizure. Method: Perceptron learning algorithm is a supervised learning of binary classifiers and also it is a simple prototype of a biological neuron in artificial neural network. EEG is extensively documented for the diagnosing and assessing brain activates and related disorders. In this paper EEG signals are taken as dataset for epilepsy detection. The data is been represented based on three domains namely frequency, time and time-frequency applied by the chebysev filter for processing the signals. Result: Help the patients from dangers at the time of the seizure. Conclusion: The neurological diseases can be divided into two loss of consciousness and convulsions. In this technology world the seizure can be detected by computerized way like EEG and so on. This paper proposes an epileptic seizure detection using EEG (Electroencephalogram) and perceptron learning algorithm. 2020, IJSTR. -
Heavy metal stress influence the andrographolide content, phytochemicals and antioxidant activity of Andrographis paniculata
Heavy metals (HM) are toxic components present in the earth's crust that can have a negative impact on plants as well as animals. Andrographis paniculata or 'King of bitters' belonging to the family Acanthaceae, is a medicinal herb traditionally used in the treatment of fever, common cold etc. In the present study, the effect of heavy metals (copper, tin and cobalt) on the andrographolide content, biochemical parameters like chlorophyll, carotenoid, protein, Total phenolic content (TPC), Total flavonoid content (TFC) and antioxidant activity in A. paniculata were analysed. Saplings of A. paniculata were treated at 50 and 100 mM concentrations, three different times at a time interval of 7 days. Andrographolide production was found to increase in copper and cobalt treated saplings when compared with the control. From the results, maximum andrographolide concentration was found in the saplings treated with 50 mM copper (8.51 mg/gm of DW) and 50 mM tin (8.10 mg/gm of DW) respectively. 50 mM cobalt treated plants have shown the highest concentration of TPC (17.21 mg/g of extract) and TFC (6.97 mg/gm of extract). Notable variations in other biochemical parameters like total chlorophyll, carotenoid content and antioxidant activities were observed in all treatments compared with the control. Antony & Nagella (2021). This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/). -
Effect of heavy metals on the andrographolide content, phytochemicals and antioxidant activity of Andrographis paniculata
Andrographis paniculata is a medicinal plant that has several medicinal properties and has been traditionally used in different medicinal preparations. The present study deals with the influence of heavy metals (lead, mercury and silver) on andrographolide, phytochemicals and antioxidant activity in Andrographis paniculata. Two months old saplings were subjected to heavy metal stress of two different concentrations (0.2 mM and 0.4 mM) for three different times at 3 day time interval. The results showed that the saplings treated with heavy metals showed increased concentration of andrographolide content. The saplings treated with 0.4 mM silver showed the highest increase in the andrographolide content (24.58 2.85 mg/g of DW) compared with control (9.41 1.26 mg/g of DW) and other treatments. Variations in the biochemical parameters like total phenolic content, total flavonoid content, etc. were also prominent with all the treated samples when compared to that of control. 2020 Chemical Publishing Co.. All rights reserved.