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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. -
Effects of reduced graphene oxide on nonlinear absorption and optical limiting properties of spin coated aluminium doped zinc oxide thin films
In this work, we investigate the nonlinear absorption and optical limiting properties of reduced graphene oxide (rGO) incorporated aluminum doped zinc oxide (AZO) composite thin films by open aperture z-scan technique using Q-switched Nd:YAG laser at 532 nm. The structural and spectral properties were also systemically analyzed. The composite thin films were synthesized by spin coating technique with online infrared curing facility. Studies on nonlinear optical responses of the investigated samples proved a substantial enhancement in the nonlinear absorption coefficient of AZO:rGO composites compared to AZO thin film. The nonlinear absorption is attributed to the two photon absorption with reverse saturable absorption. The strong nonlinear absorption and nonlinear scattering effects result in the optical limiting property of the composite material. The AZO:rGO thin film exhibits lower optical limiting threshold value (32 MW/cm2) as compared to AZO (59 MW/cm2). Hence it is an excellent optical limiter which explores applications in the field of optoelectronics as protecting material for sensitive photonic devices. 2021 -
Effects of Rough Boundaries on RayleighBenard Convection in Nanofluids
A linear stability analysis of RayleighBenard convection in a Newtonian nanofluid is carried out using most general boundary conditions. A single-phase description of nanofluids is adopted in the study. The nanofluids used for the study are wateralumina and watercopper nanofluids in order to analyze how a choice between them can be made. The values of thermophysical quantities of nanofluids are calculated using the mixture theory and phenomenological-laws. The paper applies the Maclaurin series in solving the boundary-eigenvalue-problem through a simple and innovative approach. A single-term Galerkin technique is adopted to obtain the guess value of the critical Rayleigh number and the wave number. Further, improved values of the Rayleigh number and the wave number are obtained using the solution of a system of three linear-algebraic equations. A detailed discussion is made on the effect of rough-boundaries and Robin-boundary conditions for temperature on the onset of convection. A comparative study between the results of two nanofluids is made and the destabilizing effect of nanoparticles in the Newtonian carrier-fluid on the onset of convection is studied. Copyright 2023 by ASME. -
EFFECTS OF SINUSOIDAL AND NON-SINUSOIDAL TEMPERATURE MODULATION IN A TRIPLE DIFFUSIVE CONVECTION
The Triple Diffusive convection with time-dependent sinusoidal (cosine) and non-sinusoidal (square and triangular) temperature modulation is studied using linear and non-linear analysis. The expression for Rayleigh number and correction Rayleigh number is obtained by using perturbation method which gives the prospect to control the convection. Effects of various parameters of the problem are individually studied for two cases of temperature modulation namely, (i) in-phase and (ii)out-of-phase. Ginzburg-Landau equation using multi-scale method is derived to study the effects of temperature modulation on heat and mass transfer. It is observed that both solutal Rayleigh numbers stabilizes or destabilizes the system depending on the values of the frequency of modulation. 2021 I??k University, Department of Mathematics. All Rights Reserved. -
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Effects of suction-injection-combination (SIC) on the onset of Rayleigh-Benard magnetoconvection in a micropolar fluid
The effects of suction-injection-combination (SIC) and magnetic field on the linear stability analysis of Rayleigh-Benard convection in a horizontal layer of an Boussinesq micropolar fluid is studied using a Rayleigh-Ritz techinque. The eigenvalues are obtained for free-free, rigid-free and rigid-rigid velocity boundary combinations with isothermal and adiabatic temperature conditions on the spin-vanishing boundaries. The eigenvalues are also obtained for lower rigid isothermal and upper free adiabatic boundaries with vanishing spin. The influence of various micropolar fluid parameters on the onset of convection has been analysed. It is found that the effect of Prandtl number on the stability of the system is dependent on the SIC being pro-gravity or anti-gravity. A similar Pe-sensitivity is found in respect of the critical wave number. It is observed that the micropolar fluid layer heated from below is more stable compared to the classical fluid layer. 2003 Elsevier Science Ltd. All rights reserved. -
Effects of supply chain integration on firm's performance: A study on micro, small and medium enterprises in India /
Uncertain Supply Chain Management, Vol.8, Issue 1, pp.231-240, ISSN No: 2291-6830. -
Effects of supply chain integration on firms performance: a study on micro, small and medium enterprises in India
The cooperation in the supply chain assumes an adequate job for enhancing an organisation's performance and increasing competitive advantage. Supply Chain Integration (SCI) affects organisational performance. This paper studies the impact of the integration of supply chain procedures and practices on organisational performance and explores the effect of SCI on organisational performance at Micro, Small and Medium Enterprises (MSMEs) in Madurai District, Tamilnadu, India. A questionnaire is developed with validated measurement scales from previous studies and empirical data are collected through a survey questionnaire from 250 randomly selected MSMEs. This research provides sound recommendations to MSMEs in Madurai District, Tamilnadu, India, and maybe used for different industries and decision making policies. Finally, the study will contribute to the scientific field by providing some future studies. 2020 by the authors; licensee Growing Science, Canada. -
Effects of the Doctrine of Discovery: A Strive to build Sustainable and Peaceful Communities in North East India
The article analyses the Doctrine of Discovery which advocates racial superiority and colonisation of indigenous lands. Indigenous people of North East India continually strives for sustainable and peaceful situation. A strong relational bond between the ethnic tribes and the environment is fundamental for self-determination, sustainability and peace. Consequently, humans bond with land stirs a readiness to sacrifice their lives for their motherland juxtaposed in the precarious context of international boundaries and past colonial annexations. The colonial-influenced literature has moulded their ethnic identity. This further leads to an upsurge of emic historical and anthropological perspective writings, framing their history, interaction with the environment, the rise of ethnic consciousness and identity politics. There is a continuous struggle to free themselves from the colonial enslavement of the Doctrine of Discovery that has ultimately encroached on their land and culture. The Electrochemical Society -
Effects of variable thermal properties on thermoelastic waves induced by sinusoidal heat source in half space medium
Aim of the present study is to characterize the effects of changing thermal conductivity on the propagation of thermoelastic waves in the half space medium when it is exposed to a periodic heat source. Closed form solutions of all significant physical fields such as conductive temperature, stress and displacement are evaluated in their dimensionless form in the Laplace transform domain. Impact of changing thermal conductivity parameter is exhibited on all field variables with the help of quantitative outcomes in time-domain. Following this pattern, the effects of time parameter is also observed on the field quantities. 2022 -
Effects of Variable Viscosity and Internal Heat Generation on RayleighBard Convection in Newtonian Dielectric Liquid
The onset of RayleighBard convection of variable-viscosity Newtonian dielectric liquid confined between two parallel plates is subject to free-free isothermal boundary condition. The combined and individual effects of temperature-dependent and electric-field-dependent variable-viscosity along with the internal heat generation are studied using the higher order Galerkin technique. This theoretical study shows that even a mild temperature-dependent variable-viscosity destabilizes the system and the electric-field-dependent variable-viscosity stabilizes the system both in the absence/presence of heat source/sink. 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Effects of variable viscosity and rotation modulation on ferroconvection
We theoretically explore the dynamics of a ferrofluid with temperature and magnetic field-dependent viscosity, which is in a RayleighBard situation and is subjected to rotation. The problem considers both sinusoidal and non-sinusoidal time-periodic variations of rotation to study the onset and post-onset regimes of RayleighBard ferroconvection. We perform a weakly nonlinear stability analysis using a truncated Fourier series representation and arrive at the third-order Lorenz system for ferrofluid convection with variable viscosity. By using the linearized form of the Lorenz system for ferrofluid convection with variable viscosity, we arrive at the critical Rayleigh number to study the onset of rotating ferroconvection. The heat transport is quantified in terms of the time-averaged Nusselt number and the effects of various parameters on it are studied. The effect of modulated rotation is found to have a stabilizing effect on the onset of ferroconvection while that of variable viscosity has a destabilizing effect. The effects of magnetorheological and thermorheological effects are antagonistic in nature. It is found that the square waveform modulation facilitates maximum heat transport in the system due to advanced onset of ferroconvection. 2021, Akadiai Kiad Budapest, Hungary. -
EFFECTS OF VIRTUAL PRIVATE SOCIAL NETWORKING IN ACADEMIC PERFORMANCE OF STUDENTS
A virtual private social network (VPSN) is generated automatically amongst peers using a social media app to build ties. One of the most significant repercussions of students' excessive usage of social networking sites is a decline in their academic performance. In a study of medical students, social media and the internet were shown to harm students' academic performance and classroom attentiveness. An increasing number of studies link the use of social media to poorer academic performance, such as fewer students doing their assignments and lower test scores. Students who receive specialised training in deep learning will have the superior cognitive abilities needed to succeed in today's more cognitively demanding workplaces. It teaches children to be critical thinkers, productive members of society, and active participants in a democratic society. As a perceptron used in image recognition and processing, a convolutional neural network (CNN) processes pixel data from social networks. A CNN uses multiplayer perception to lessen the processing needs of pupils. Humans and neurons make up the VPSN-CNN network, which the article explains. Neurons generate dendrites and axons to receive and transmit signals, while humans engage with long-reaching telecommunication equipment or biological communication systems. These will help remember, learn, unlearn, and relearn what has already been learned. In courses where social networking sites were utilised in addition to traditional teaching methods, most students reported feeling more socially engaged and more positive about their educational experiences. Students' and instructors' concerns regarding the educational usage of social media are addressed with recommendations for further study and practice in better performance and accuracy for student's data secure and comparison with existing methods. 2023 Little Lion Scientific. All rights reserved. -
Effects of Yoga and Combined Yoga with Neuro-Linguistic Programming on Psychological Management in Mothers of Adolescents: A Randomized Controlled Trial
Adolescent parenting presents significant challenges for mothers, often leading to elevated levels of stress and anxiety that can adversely affect their well-being and parenting effectiveness. This study aims to evaluate the efficacy of yoga alone and in combination with Neuro-Linguistic Programming (NLP) in managing stress and anxiety among mothers of adolescent children. In this randomized controlled trial, 90 participants aged 35-55 years (mean age 44.564.58 years), each with at least one child aged 13-19 years, were randomly assigned to one of three groups: control, yoga, or yoga with NLP. Interventions were conducted over 12 weeks, with outcome measures assessed pre- and post-intervention by trained research assistants blinded to group allocation. The Depression, Anxiety, and Stress Scale (DASS-21), and Pittsburgh Sleep Quality Index (PSQI), were utilized to evaluate outcomes. Both intervention groups demonstrated significant reductions in depression, anxiety, and stress levels compared to the control group. The yoga with NLP group exhibited superior improvements across all primary outcomes, with statistically significant differences noted in depression (mean difference =7.1, p<0.001), anxiety (mean difference =5.1, p<0.001) and stress levels (mean difference =5.5, p<0.001). Additionally, sleep quality improved significantly in both intervention groups, with the yoga with NLP group showing greater benefits. This study provides evidence that yoga, particularly in combination with NLP, is an effective non-pharmacological approach for reducing stress and anxiety and improving sleep quality among mothers of adolescents. These findings support the integration of mind-body practices into mental health care, highlighting the potential synergistic benefits of combining physical and cognitive interventions. Future research should explore long-term effects and the mechanisms underlying these improvements. 2024 Montenegrin Sports Academy. All rights reserved. -
Effectual Energy Optimization Stratagems for Wireless Sensor Network Collections Through Fuzzy-Based Inadequate Clustering
Wireless Sensor Networks (WSNs) are crucial in the burgeoning Internet of Things (IoT) landscape, serving as a backbone technology that enables myriad applications across various industries. Originating as a simple methodology, WSNs have evolved significantly, propelled by rapid advancements in sensor technology and hardware capabilities. These networks play a pivotal role in collecting and transmitting data, which is essential for the infrastructure of most IoT systems. WSNs operate by deploying sensor nodes across diverse locations to gather environmental data. This scalability and adaptability of WSNs were demonstrated in studies where network coverage was expanded to include 100 and 200 nodes. Notably, the implementation of the innovative FLECH (Fuzzy Logic Energy-efficient Clustering Hierarchy) protocol significantly enhanced energy efficiency, reducing consumption by 12.69% in networks with 100 nodes and by 36.85% in those with 200 nodes, compared to the traditional LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol. This work innovatively combines fuzzy logic and Particle Swarm Optimization (PSO) for efficient Cluster Head selection in Wireless Sensor Networks. The evaluation of these protocols involved numerous simulations and communication tests to ascertain the First Node Die (FND) pointindicative of when a network begins to lose efficacy due to energy depletion. Results indicated that the LEACH protocol reached the FND point faster than FLECH, suggesting that FLECH may offer better longevity and durability for IoT applications, aligning with the needs for sustainable and efficient operation in expanding technological ecosystems. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. -
Efficacy of a peer-delivered group psychological intervention to reduce psychological distress among university students in India: a randomised controlled trial using an active control condition; [Eficacia de una intervenci psicolica grupal realizada por pares para la reducci del malestar psicologico en estudiantes universitarios en India: ensayo clico aleatorizado empleando una condici de control activo]
Background: Brief psychological interventions in low-and-middle-income-countries (LMICs) have been typically tested against usual or enhanced usual care (EUC). This design precludes understanding of the role of non-specific factors in influencing outcomes. Objective: This study evaluated an adapted version of WHOs Problem Management Plus (gPM+), titled Coping with COVID, against an active control condition to reduce anxiety and depression during the COVID-19 pandemic. Methods: In this two-arm, single-blind, randomised controlled trial, young adults aged 1824 years who screened positive for COVID-19 related psychological distress in Bengaluru (India) were randomly allocated to either Coping with COVID (n = 91) or non-directive Supportive Counselling (SC; n = 92) groups. Coping with COVID was a 6-sesion, group-based programme that taught coping strategies for stress. SC was a 6-sesion, group-based programme that offered non-directive support. The primary outcomes were anxiety and depression as measured by the Hospital Anxiety and Depression Scales (HADS) assessed at baseline, post-intervention, 2-months (primary outcome timepoint), and 6-months after treatment. Secondary outcomes included generalised worry, positive wellbeing, pandemic-related stress, and suicidal ideation. Results: Between October 2021 and December 2022, 183 participants were enrolled into the trial. Relative to SC, Coping with COVID did not lead to significant reductions in anxiety (mean difference 0.24 [95% CI, ?1.01,1.48], p>.05), or depression (mean difference.03 [95% CI, ?1.19, 1.26], p>.05). Similarly, there were no significant differences between conditions for all secondary outcomes. Conclusions: The findings suggest that the benefits of strategies that comprise transdiagnostic scalable psychological interventions may not surpass non-specific factors in driving symptom reduction. Clinical implications: There is a need to further evaluate the role of non-specific factors in scalable psychological programmes because focusing on these may have implications for ease of training and implementation. Trial registration:Australian New Zealand Clinical Trials Registry identifier: ACTRN12621001064897. 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Efficacy of AI for Three-Dimensional Point Cloud Semantic Segmentation of Heritage Data for XR Environments
In heritage documentation, three-dimensional (3D) models created using Scan-to-BIM processes are essential for interpreting and presenting historic structures. Point cloud data derived from 3D laser scanning and photogrammetry facilitate realistic digital models used for immersive experiences. For this, raw point clouds, which are unstructured, are processed, semantically classified, and segmented to create parametric architectural objects in modeling platforms. Three-Dimensional Point Cloud Semantic Segmentation (3DPCSS) refers to segmenting point clouds into classes like walls, columns, etc. Automating 3DPCSS using Artificial Intelligence (AI) has gained importance in current research activities because of its versatility and efficiency over manual segmentation. However, implementing it solely with AI presents various operational and conceptual challenges, particularly for XR models in digital heritage. Automated segmentation often fails to capture the unique characteristics and intricate geometries, leading to misrepresentations or oversimplifications. Selecting an appropriate algorithmic framework for automating 3DPCSS is essential to address this gap. This paper aims to understand the efficacy of AI algorithms in recent research for 3DPCSS, particularly those tailored for 3D modeling. A study of Dwarakadesh Haveli, Ahmedabad, India, highlights the workflow and challenges of integrating point clouds into 3D models. The findings indicate the need for a detailed approach tailored to the projects specific characteristics, emphasizing the importance of systematic algorithm ensemble experimentation to refine segmentation, leading to the development of 3D parametric objects. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
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Efficacy of Art Based Interventions for Emotional Problems among Children Affected by Earthquake in Nepal
The earthquake of April 2015 left Nepal in a vulnerable state. Children represent an estimated 3.2 million of the 8 million people affected by the earthquake. The aim of the study was to examine the role of art in dealing with the long-term impact of earthquake on emotional problems in children in Nepal. A purposive sampling was adopted to select 454 children studying in 4th and 5th standard from four schools in Kathmandu Metropolitan City. Children completed the Level of Exposure Scale while the parents provided information about the emotional and behavioural difficulties of children using the Nepali version of Strengths and Difficulties Questionnaire (SDQ/ 4-17). The influence of gender, severity of exposure, socio-economic status and type of family in relation to emotional problems were also examined in the selected group. The results of Phase 1 show that conduct, hyperactivity-inattention and peer problems were higher in boys while girls had higher pro-social behaviour. Children belonging to lower socio-economic status were found to be at risk for emotional problems. Gender and exposure were also identified as predictors of emotional problems in children. For the second phase of the study, those children with high emotional problems (N=60) were selected for an art-based intervention consisting of nine sessions. Both the treatment (N=30) and control group (N=30) completed the pre- and post- treatment measure of SDQ. The results show that the children in the treatment group reported lower levels of emotional problems, hyperactivity-inattention and peer problems compared to the control group (Cohen's d: 0.50-0.80). In the final phase of the study, 12 children from the treatment group were interviewed to identify the elements of art that contributed to a change in the emotional problems. A thematic vii analysis revealed six global themes: a new schema, an expression space, drawing the trauma, reappraisal of trauma narrative, protective factors and future benefits. The responses of the children show that the inherent properties such as regulation and social connection promoted by an engagement in arts needs to be adopted as an effective mode of trauma care. The findings also point to the possibility of using art-based therapy to overcome stigma which hinder the mental health professionals when implementing evidence-based treatments in the country. -
Efficacy of Artificial Neural Networks (ANN) as a Tool for Predictive Analytics
Predictive analytics could also be defined as the application of statistical techniques and mathematical modeling to anticipate the future performance and expected return on investments. Predictive analytics examines the most recent and the historical data to see if the same pattern is likely to reoccur or not. This gives an opportunity to businessmen and financial investors to make an appropriate decision about their investments and expected returns. Ever since the development of ANN technique, researchers have tried to create a number of predictive models using ANN. The chapter is focused on defining predictive analytics and the tools used in predictive analytics, with a special orientation on Artificial Neural Networks. The objective of the chapter is to establish ANN as an effective technique for making appropriate predictions and thereby contributing toward the decision-making in various spheres using the outcomes from various researches. The chapter also aims to explain the step-by-step process of ANN in outcome prediction with the help of example. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.