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The purpose of this paper is to focus on the use of a nickel‐titanium (nitinol) shape memory alloy (SMA) wire (capable of showing strains of up to 8 per cent) as the active element that drives a flexible and lightweight micropositioning actuator. The purpose of this paper is to finely control the wire contraction, and as a result, the deflection of the actuator, with micrometric accuracies.

Different experimental platforms are built, all of them using the same nitinol wire as the active element. In all cases a current is applied to the wire to heat it up using the Joule effect, and in doing so cause the wire to transform from the martensite into the austenite. This phase transition has a non‐linear and hysteretic nature, so, finely controling wire's position requires a non trivial control strategy. A neural network used to compensate the hysteretic behaviour of the wire combined with proportional‐integral with antiwindup control strategy is implemented. Control experiments are carried out on a light robot gripper and on a single‐fingered experimental device.

It is found that the single‐fingered device could be used to better analyze the behaviour of the gripper. It is also found that the accuracy obtainable strongly depended on the position sensor used for the feedback, ranging from 3 μm for an linear variable differential transformer sensor to 30 μm for strain gauges mounted on the “fingers” of the grip.

This paper shows the viability of using SMA‐based actuators for lightweight applications, controllable with micrometric accuracies, without the need to place an extraordinarily large burden on the control system.

Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme for robot manipulators in a universal unmodeled method, avoiding complicated modeling processes.

An augmented neural network (NN) constituted of radial basis function neural networks (RBFNNs) and additional sigmoid-jump activation function (SJF) neurons is introduced to approximate complicated dynamics of the system: the RBFNNs estimate the continuous dynamic term and SJF neurons handle the discontinuous friction torques. Moreover, the control algorithm is designed based on Barrier Lyapunov Function (BLF) to constrain output error.

Lyapunov stability analysis demonstrates the exponential stability of the closed-loop system and guarantees the tracking errors within predefined boundaries. The introduction of SJFs alleviates the limitation of RBFNNs on discontinuous function approximation. Owing to the fast learning speed of RBFNNs and jump response of SJFs, this modified NN approximator can reconstruct the system model accurately at a low compute cost, and thereby better tracking performance can be obtained. Experiments conducted on a manipulator verify the improvement and superiority of the proposed scheme in tracking performance and uncertainty compensation compared to a standard NN control scheme.

An enhanced NN approximator constituted of RBFNN and additional SJF neurons is presented which can compensate the continuous dynamic and discontinuous friction simultaneously. This control algorithm has potential usages in high-performance robots with unknown dynamic and variable friction. Furthermore, it is the first time to combine the augmented NN approximator with BLF. After more exact model compensation, a smaller tracking error is realized and a more stringent constraint of output error can be implemented. The proposed control scheme is applicable to some constraint occasion like an exoskeleton and surgical robot.

Pandemic along with causing disruption in economy and health of the communities, has also exposed the vulnerabilities of the people and the government. Innumerable research papers reported that this is leading to an increase in psychological issues like depression, OCD, anxiety, etc.,. However, our past experiences with pandemics has shown that the survival of communities depends on the level of adaptability and change management. This study aims to observe the influence of the disruption in emotional health measured in terms of Level of Adaptability and Level of Resistance to Change as a result of Lockdown.

(1) Assess the level of disruption in the emotional health (in terms of Level of Adaptability and Level of Resistance to Change) of the people due to this Lockdown. (2)Impact of this disruption on physical health.

This is a cross-sectional survey of the urban Indian population. The sampling method used was the snow-ball sampling. Adaptability and Resistance to change have been considered as the measure of a person's emotional health and then correlated to their physical health.

The study hypothesized that people underwent emotional disruption and that affected their physical health negatively. But our findings showed that people were happy and used this time to improve their lives and relationships. The study found age having a significant association with both adaptability and resistance to change. There was inverse correlation between Resistance to change and physical health. And the level of Adaptability was considerably high in participants who were greater than 30 years and participants who were Self-employed or salaried.

The disruption in the lives of people due to Lockdown has given ample time for families to reconnect and relationships to improve. People have had time to introspect and hence have adapted well to the impending crisis.

Introduction – In recent years, there has been a growing interest in innovation, not only in developed countries but also in developing countries. However, there has been limited literature for the developing countries.

Purpose – The literature on national innovation systems (NIS) mainly consists of case studies or qualitative researches aiming to explain the patterns of innovation, while the quantitative analysis are limited in explaining the innovation capability and efficiency of innovation. This study is unique in a sense that it compares the innovation efficiencies of the EECA countries. This chapter aims to measure the efficiency of NIS via data envelopment analysis (DEA) method.

Methodology – DEA is used to consider a sample of 18 Eastern European and Central Asian (EECA) countries and Turkey. One of the main issues is to determine the input and output variables because the available data for some of these countries were limited. Therefore, research and development expenditure (% of GDP), government expenditure on education, total (% of GDP), imports of goods and services (% of GDP) and foreign direct investment, net inflows (% of GDP) were determined as input variables. Output variables were as follows; patent applications both residents and non-residents, high-technology exports (% of manufactured exports) and scientific and technical journal articles.

Findings – Based on the key findings it can be noted that Kazakhstan, Turkey, Latvia and Uzbekistan are more efficient in innovation performance compared to other EECA countries. Throughout the results of the DEA, these countries may develop new policies about their innovation systems to reach out the higher performance.

The purpose of this study is to capture the journey of the first female leader in sports management in her country in the south-east Asian region for their National Sport and the values and behaviors enabling her to achieve it.

The study uses a mixed-methods case study design, quantitative and qualitative outcome measures, to assess the career progression of the first female executive director of a national sporting organization in her country, namely, BWN and her involvement in a two-week intensive sports management, leadership and development program.

A professional and courageous approach to identify and implement honest and evidence-based solutions were key for BWN’s success. BWN complemented professionalism with soft skills, clear communication and an outcome-based approach to challenging situations, successfully influencing change within her national sporting organization. This female leader is an inspiring role model for other women and her professionalism her most influential value driving innovation in sports management and organizational change. The positive impact she had in her community highlights the significant contributions female leaders can have within the sports leadership context, given the opportunity and scope to do so.

For the first time in her country, the unsolicited and unprecedented evidence-based approach, professionalism and proactivity assisted BWN with her colleagues accepting her as the first woman on the executive board of her national sporting body of one of the most celebrated national sports. Breaking the mold with unexpected (positive) behavior might be the secret to further breakthroughs for women in sports management.

Introduction: Human resource management (HRM) is going through a transformation phase due to the pandemic. The COVID-19 crisis compelled the employees to work virtually. To mitigate the effects of COVID-19, several organisations heavily invested in artificial intelligence (AI) in the realm of HRM.

Purpose: With limited studies on the paradigm shift in HRM post-pandemic and the role of AI, the study investigates and proposes a conceptual framework for the paradigm shift in HRM practices post-COVID-19 pandemic and the significance of AI. Furthermore, the study investigates the outcomes of the use of AI in HRM for organisations and employees.

Methodology: A comprehensive review of the literature based on the guidelines of Tranfield, Denyer, and Smart (2003) and Crossan and Apaydin (2010) has been followed. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes involved.

Findings: COVID-19-related economic disruption has led to a paradigm shift in HRM practices. AI-enabled HRM practices are now centred around remote and contingent workforce management, mindfulness, social capital, increasing employee engagement, reskilling and upskilling towards new competencies, etc. AI is making remote work seamless through smooth recruitment and selection process, onboarding, career and development, tracking and managing the performance, facilitating learning, and talent management. Post-pandemic, AI-powered tools based on data mining (DM), predictive analytics, big data analytics, natural language processing (NLP), intelligent robots, machine learning (ML), virtual (VR)/augmented reality (AR), etc., have paved the way for managing the HRM practices effectively, thereby leading to enhanced organisational performance, employee well-being, automation, and reduced cost.

Internationalisation became an important component of science parks (SPs) practices. In recent years, they have started to include, among the portfolio of their services, the support and fostering of their tenant firms’ internationalisation, such as soft-landing programmes and international immersion experiences for start-ups. Thus, the main aim of this chapter is to analyse these internationalisation practices in the light of the network and internationalisation theories. Based on an exploratory multiple case study the authors conducted in three Brazilian SPs located in the South of Brazil (Rio Grande do Sul State) – Tecnopuc in Porto Alegre, Tecnosinos in São Leopoldo and Feevale Techpark in Campo Bom. The authors provide evidences on how cohesive internal and external ties, networks as well as the level of specialisation are the key drivers of the internationalisation process of SPs and their tenant firms.

The purpose of this paper is to explore the relationship between changes in the business cycle (as indicated by the incidence and duration of unemployment) and the incidence of suicide.

A theoretical utility model with savings and consumption is used, while time series micro‐level suicide data and probit analysis is used to empirically test the implications of the model.

With declining economic activity and the corresponding increase in unemployment the propensity to commit suicide rises among men for numerable reasons. The authors hypothesize that there is a negative impact with respect to the decline in economic activity and as the intensity increases with respect to the declining business cycle, female's suicides will tend to accelerate.

One of the primary limitations of this study is the amount of control variables to which the authors had access. There are many factors that would influence an individual when determining whether or not to take their own life. Religious convictions, the presence of children, income, educational attainment, occupational attainment, pre‐unemployment income, and how long one had been married or divorced (or unmarried) are all variables that could influence the likelihood of a suicide. The center of disease control (CDC) public use files, however, do not include these variables; thus, the authors were unable to control for their impact.

The authors believe that these findings merit greater public awareness and increases in various forms of public and private support for recently unemployed individuals, being particularly attentive to the effect of higher than normal rates and durations of unemployment and the differences based on gender. These findings also establish another sound rationale for public policies to encourage the increase of personal savings during times of employment to make weathering periods of unemployment easier.

In times of increased incidence and duration of unemployment, the tendency of legislators and other public policy makers presumably would be to establish programs targeted to address the population with the highest rates of unemployment‐related suicide – White males. It can be argued, however, that since the increased incidence and duration of unemployment have a greater effect on increasing the rate of suicide in women, public policies and programs targeting the specific needs and issues of those unemployed women with an increased risk of suicide would be more cost‐effective, preventing or reducing those incremental suicides and mitigating their negative economic, social, and familial impacts.

Previous studies used descriptive statistics, contingency tables, and the traditional statistical regression techniques in their empirical analysis; this study deviates from the norm by the use of probit analysis. Using the probit technique allowed the authors to focus their analysis on the probabilities of suicide with regard not just to the business cycle itself but also to the intensity of the business cycle.

This paper aims to study the moderating effect of customer type (business customers versus private customers) on the link between two forms of openness (cross-industry networks and customer integration) and two front-end innovation outcomes (a creative idea and a product definition), in the context of radical innovations.

An agreement was established with the Statistical Office of the Basque Government. This agreement enabled us to access a reliable list of innovative companies in the region that constituted our sample frame. Questionnaires were collected by phone. The response rate was 41.6%, which led to a sample size of 189 firms. Structural equation modeling was used to analyze the data.

The study reveals that idea creativity is explained by different external drivers in business-to-business (B2B) and business-to-customer (B2C) settings. In B2B settings, customer integration is found to have no effect on idea creativity. For product definition, however, both the external drivers, namely, cross-industry networks and customer integration, matter, although the latter is more salient.

In the search for creative ideas, managers of firms that serve business customers should focus on cross-industry networks, while those that serve private customers should concentrate on customer integration.

Most previous quantitative studies on the front end have focused on internal drivers, and some of them use a mix of B2B and B2C data, which could lead to misleading conclusions.