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The purpose of this paper is to explore a new possibility of providing high-temperature stable lead-free interconnections for low-temperature co-fired ceramics (LTCC) hotplate. For gas-sensing application, a temperature range of 200°C-400°C is usually required by the sensing film to detect different gases which imply the requirement of thermally stable interconnects. To observe the effect of parameters influencing power of the device, electro-thermal simulation of LTCC hotplate is also presented. Simulated LTCC hotplate is fabricated using the LTCC technology.

The proposed task is to fabricate LTCC hotplate with interconnects through vertical access. Dedicated via-holes generated on the LTCC hotplate are used to provide the interconnections. These interconnections are based on adherence and bonding mechanism between LTCC and thick film. COMSOL software is used for finite element method (FEM) simulation of the LTCC hotplate structure.

Thermal reliability of these interconnections is tested by continuous operation of hotplate at 350°C for 175 h and cycling durability test performed at 500°C. Additionally, vibration test is also carried out for the hotplate with no damage observed in the interconnections. An optimized firing profile to reproduce these interconnections along with the experimental flowchart is presented.

Research activity includes design and fabrication of LTCC hotplate with metal to thick-film based interconnections through vertical access. Research work on interconnections based on adherence of LTCC and thick film is limited.

A new way of providing lead-free and reliable interconnections will be useful for gas sensor fabricated on LTCC substrate. The FEM results are useful for optimizing the design for developing low-power LTCC hotplate.

Adherence and bonding mechanism between LTCC and thick film can be used to provide interconnections for LTCC devices. Methodology for providing such interconnections is discussed.

Over the years, India has witnessed irregular FDI inflows. Therefore, this study aims to explore the asymmetric impact of per capita income, final consumption expenditure, globalization index and exchange rate on FDI inflows in India.

Using the nonlinear autoregressive distributed lag bounds framework and unknown structural break, the study investigates the impacts of selected macroeconomic variables in driving FDI inflows in India during the study period (1979-2016).

The outcomes of the study confirm the asymmetric relationship between FDI inflows and its determinants during the study period. The results have confirmed that the improvement in per capita income, private consumption expenditure, globalization index and currency value appreciation play a crucial role in increasing FDI inflows in India. In contrast, the downside movements in the volume of consumption expenditure, globalization index and depreciation of the currency value in relation to the trade partners result in reducing the volume of FDI inflows in the long run.

For determining FDI inflows, previous studies have considered the overall impact of its potential determinants, which may provide partial information about the phenomenon. The adopted nonlinear approach highlights that both the types of fluctuations (i.e. upside and downside) in the independent variables may affect FDI inflows differently and substantially. The nonlinear association between FDI and selected determinants may be vital in formulating a long-term policy.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

The paper underpins an advanced domestic manufacturing that comes with some advanced employment specialization status of individual industries as the key determinant of foreign direct investment (FDI) and considers how FDI in the food processing industry in India relates to this focal point.

This paper investigates how inward FDI inflows relate to domestic investment and revival in the industry using Auto Regressive Distributed lags (ARDL) model over the period 2000–2017. The model allows for different specifications to study whether FDI is responsible for the revival or the prior revival induces the FDI.

The results show the lack of proper advanced specialized employment status of the food processing industry. FDI in food processing is mainly guided by exports and imports opportunities and FDI plays no role in the revival of advanced growth in the industry. This finding explains why FDI in the industry is predominantly service sector oriented.

The paper underlines (1) the proper conceptualization of human capital as an important determinant of FDI; (2) reinterpretation of Kaldor's technical progress function that uncovers how employment dynamics embedded in intermediate goods specializations play a key role in supporting a higher pace of investment (and FDI); (3) labor costs' importance should involve not only the wage rate but also the advantages that a specialized employment base and (4) FDI in manufacturing demands a greater policy focus on developing domestic bases of intermediate goods specializations.

The purpose of this paper is to understand the factors determining the incidence and extent of indebtedness among agricultural households in rural India.

This study is based on a nationally representative survey carried out under the 70th Round of the National Sampling Survey Office (NSSO) across rural India. Data on household characteristics, farming characteristics, indebtedness and extent of outstanding credit have been extracted from the comprehensive survey data. Four research hypotheses have been formulated and tested using simple statistical techniques. Further, using the Heckman Selection Model, the study assesses the factors determining the agrarian indebtedness among households in rural India.

The results from the descriptive analysis show that there is a significant difference in socio-economic and farm characteristics of indebted and non-indebted households. Further, the level of indebtedness differs across sources of the loan, landholding sizes and geographical locations among agricultural households. The results of regression analysis clearly indicate that household characteristics, farm characteristics and sources of loan determine both the incidence and extent of indebtedness among agricultural households.

The main limitation of the study is that only the data giving information regarding the amount of outstanding loans have been collected, and there is no information regarding the amount of credit availed, the purpose and the due date of payment. Further, there is scope to improve the robustness of the empirical model by adding and modifying explanatory variables.

There are only a limited number of empirical studies providing an understanding of the factors determining the indebtedness of agricultural households in rural India. Hence, this study is a good value addition to the existing literature.

The purpose of this study is to examine the effectiveness of two intervention strategies – identifying the global letter of Navon letters and verbally describing a face – in improving face recognition abilities of adolescents with autism spectrum disorder (ASD).

A total of 15 adolescents with ASD and 15 typically developing (TD) adolescents participated in this study, which consisted of three experimental conditions: verbalization, Navon and control. Participants were presented with a target face for a short period of time, then completed a task specific to the condition in a counterbalanced order, followed by a face recognition task.

The results of this study showed no significant interaction effects between groups and conditions, either in accuracy or reaction time. However, TD adolescents performed better than ASD adolescents in terms of accuracy. In addition, the verbalization condition resulted in better performance with slower response times compared to the control condition.

These findings suggest that verbalization may be a useful strategy to enhance face recognition abilities in ASD and TD individuals.

Unions and organizations interests are often seen to be in competition. However, union-voice hypothesis suggests that unions can provide a distinctive mechanism to lower organizational costs by reducing exit behavior, absence from work and conflict levels at work. This study aims to look at union participation as a form of voice which is affected by a number of antecedents and in turn has an effect upon the workers performance (i.e. worker behavior effectiveness [WBE]) in an organization.

The study draws on data from 340 permanent labors working in 19 manufacturing units across different regions of India to explore both the antecedents and outcomes of union participation. Hypotheses are tested using mediation analysis.

Results indicate statistically significant relationships between union participation, its antecedents and WBE, with union participation partially influencing the relationship between the constructs.

Uniqueness of the study lies in its findings which report positive relationship among union participation, its antecedents and behavior effectiveness. Contrary to the traditional belief that unions are detrimental to the health of any organization, the study suggests that workers decision to join and participate in unions should be viewed positively because only if a person is willing to stay with the organization, he/she seeks to resolve the issues/problems through collective mechanism of union participation and which in turn leads to enhanced performance, reduced absenteeism at the workplace.

Application environments of wireless sensor networks (WSNs) include heterogeneous nodes with different packet sizes, transmission abilities and tolerable delay times. This study aims to design a reasonable network topology and transmission timing for these heterogeneous nodes to improve the quality of service (QoS) of networks.

In this paper, the authors treat node urgency and data packets as the basis of network clustering and to extend the network lifetime. The flow, energy consumption and residual energy of a node are included in the cluster head election. We also propose a delay evaluation function.

All the nodes in the network are guaranteed to transmit to the sink nodes efficiently by planning the transmission order in each cluster.

The simulation results show that the proposed method can balance node urgency and data packets path planning, which not only extends the lifetime of the network but also decreases network delay and improves the overall efficiency.

This study aims to examine the perception of military people regarding the use of a network of various intelligent objects, the Internet of Things (IoT), in the future battlespace.

A research model that analyzes military acceptance of the IoT is proposed. The model is created by integrating the technology acceptance model and diffusion of innovation theory. Then an empirical study is conducted through a survey, and the proposed hypotheses are tested. The findings are obtained thanks to the structural equation model (SEM), which clearly reveals the overall dependency relationship among independent and dependent variables even when a dependent variable is an independent variable in another relationship.

The study clearly reveals the significant factors effecting the attitude toward the use of IoT in the military. It also uncovers potential barriers to the adoption of IoT in the military domain. Especially, risk factor seems to have no significant impact on the acceptance of IoT, and also, there seems to be a positive relationship between risk and trust contrary to an expected negative relationship.

To the best of the authors’ knowledge, this study is the first research analyzing the acceptance of IoT in the military domain through hypotheses in a SEM.