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Reliability study plays a significant role in supporting the operation of any machinery working in a dynamic and harsh environment. This quality is inherently uncertain and a stochastic variable of any system. This study will be beneficial for designing an appropriate maintenance schedule, reducing unplanned production downtime and reducing maintenance cost of electrical motor operated particularly in dynamic and harsh environmental industries.

This study focused on the effects of operating conditions (OCs) on the operational reliability and remaining useful life (RUL) of machinery. A probabilistic graphical method called Bayesian network (BN) was used for studying the effect of OCs on the system performance. The developed methodology has been demonstrated by analyzing the operational reliability and predicting the RUL of electrical motors operated in a heavy mining machinery.

The failure probabilities estimated from the historical data of the motor system are failure likelihood, and OCs are the evidence in the developed BN model. It has been observed that the performance and RUL of the motor are significantly influenced by OCs and maintenance. A threshold value of reliability at which the motor system requires maintenance or replacement has been proposed to guide management in decision making.

The Bayesian approach for studying the covariate of motor reliability and RUL estimation is a novel approach. This study will be beneficial for designing an appropriate maintenance schedule, reducing unplanned production downtime and reducing maintenance cost of electrical motor operated particularly in dynamic and harsh environmental industries.

This study aims to explore how operational resilience can be achieved within supply ecosystems in the delicate yet harsh natural environments of the Arctic.

An in-depth, multiple qualitative case study of offshore supply operations in Arctic oil and gas field projects is conducted. Data from semi-structured interviews, personal observations and archival materials are analysed through institutional work and logics approaches.

The findings suggest that achieving social-ecological resilience depends on the interaction between social and natural (irreversible) systems, which are shaped and influenced by various institutional dynamics. Different resilience solutions were detected.

This study develops a comprehensive understanding of how social-ecological resilience emerges in supply ecosystems through institutional dynamics. The study’s empirical basis is limited to offshore oil and gas projects in the Arctic. However, due to anticipated future growth of Arctic economic activities, other types of supply ecosystems may benefit from the study’s results.

This research contributes with empirical knowledge about how social-ecological resilience is created through institutional interaction within supply ecosystems to prevent disruptions of both social and ecological ecosystems under the harsh natural conditions of the Arctic.

One of the most innovative materials available today is polyester resin, which finds application in a wide range of industries, including consumer products, automotive, aircraft, marine, construction, sports and renewable energy, due to its impressive mechanical properties and low cost. In recent years, significant progress has been achieved in the development of polyester resin composites. This paper aims to provide an overview of the recent advances in the field of polyester resin composites.

The review introduces the properties of polyester resins and the fabrication techniques used to prepare polyester resin composites. It provides an overview of the reinforcement materials such as fibers and nanoparticles that are commonly used to enhance the properties of the composites. Recent advances in the use of fillers such as nanocellulose, graphene and carbon nanotubes are also discussed. This work highlights the latest developments in the functionalization of polyester resin composites, which aims to improve the properties of the composite materials for specific applications in diverse fields such as aerospace, biomedical and energy. It highlights how collaborations worldwide, business and academia are working together to advance polyester resin composite technologies.

The study emphasizes how urgent it is to adopt sustainable practices, which, in turn, is driving research into polyester resins that are recycled and biobased to create a circular economy. Constant advancements open up new possibilities for application development and improve performance, such as nanotechnology and smart materials. Furthermore, businesses are being revolutionized by sophisticated production processes like 3Dimensional printing and Internet of Things integration, which enable mass customization and real-time monitoring. These partnerships advance the sector and encourage the use of polyester resin composites in environmentally friendly applications. The remarkable mechanical, thermal and chemical capabilities of polyester resin composites are highlighted, showcasing their importance in a range of applications.

The study is a major step toward a sustainable tomorrow since it highlights the potential of polyester resin composites to build a more durable and environmentally friendly future. This review paper summarizes the recent advances in the development of polyester resin composites, highlighting their potential for advancing technologies in various fields. The knowledge gained from this review paper will undoubtedly aid researchers in designing novel polyester resin composite materials with tailored properties for specific applications.

Without precedent, green bonds confront, for the first time since their emergence, a twofold crisis context, namely the Covid-19-Russian–Ukrainian crisis period. In this context, this paper aims to investigate the connectedness between the two pioneering bond market classes that are conventional and treasury, with the green bonds market.

In their forecasting target, authors use a Support Vector Regression model on daily S&P 500 Green, Conventional and Treasury Bond Indexes for a year from 2012 to 2022.

Authors argue that conventional bonds could better explain and predict green bonds than treasury bonds for the three studied sub-periods (pre-crisis period, Covid-19 crisis and Covid-19-Russian–Ukrainian crisis period). Furthermore, conventional and treasury bonds lose their forecasting power in crisis framework due to enhancements in market connectedness relationships. This effect makes spillovers in bond markets more sensitive to crisis and less predictable. Furthermore, this research paper indicates that even if the indicators of the COVID-19 crisis have stagnated and the markets have adapted to this rather harsh economic framework, the forecast errors persist higher than in the pre-crisis phase due to the Russian–Ukrainian crisis effect not yet addressed by the literature.

This study has several implications for the field of green bond forecasting. It not only illuminates the market participants to the best market forecasters, but it also contributes to the literature by proposing an unadvanced investigation of green bonds forecasting in Crisis periods that could help market participants and market policymakers to anticipate market evolutions and adapt their strategies to period specificities.

In response to the navigation challenges faced by coal mine tunnel inspection robots in semistructured underground intersection environments, many current studies rely on structured map-based planning algorithms and trajectory tracking techniques. However, this approach is highly dependent on the accuracy of the global map, which can lead to deviations from the predetermined route or collisions with obstacles. To improve the environmental adaptability and navigation precision of the robot, this paper aims to propose an adaptive navigation system based on a two-dimensional (2D) LiDAR.

Leveraging the geometric features of coal mine tunnel environments, the clustering and fitting algorithms are used to construct a geometric model within the navigation system. This not only reduces the complexity of the navigation system but also optimizes local positioning. By constructing a local potential field, there is no need for path-fitting planning, thus enhancing the robot’s adaptability in intersection environments. The feasibility of the algorithm principles is validated through MATLAB and robot operating system simulations in this paper.

The experiments demonstrate that this method enables autonomous driving and optimized positioning capabilities in harsh environments, with high real-time performance and environmental adaptability, achieving a positioning error rate of less than 3%.

This paper presents an adaptive navigation system for a coal mine tunnel inspection robot using a 2D LiDAR sensor. The system improves robot attitude estimation and motion control accuracy to ensure safe and reliable navigation, especially at tunnel intersections.

This study aims to describe the conversion of rice straw (RS) as an agricultural plant waste to high-performance cationic flocculant for kaolin clay suspension in wastewater treatment as an alternative to synthetic ones.

This was done by grafting rice straw after pretreatment with acrylamide (Aam) using microwave irradiation technique without using an initiator in an open vessel container for wastewater treatment. Radiation time, monomer and rice straw pulp concentration as well as microwave power were scrutinized to examine their impact on maximizing the graft yield %. Application of the resultant copolymers as flocculants for kaolin clay suspension was willful by studying the foremost influences inducing the flocculation process, for instance, flocculent dose, pH, stirring speed and extent of grafting.

It is seen from the obtained results that both FTIR, SEM, X-Ray diffraction, Thermo gravimetric analysis and Zeta potential confirmed the formation of the cationic amide group onto the graft copolymer chain in comparison with the ungrafted one; the microwave initiation method proved to be a very efficient tool concerning maximizing the graft yield % with no harsh chemicals used for initiating grafting; the flocculation efficiency of the prepared copolymers augmented by increasing the flocculant dose, pH and stirring speed to a maximum value signified at 2.0 g, 6.0 and 75 r/min, respectively, then decreased thereafter while increased by increasing the extent of grafting within the range studied; the flocculant reserved high flocculation efficiency even after five cycles of flocculation/regeneration; preliminary bridging mechanism demonstrating the attraction between the kaolin anionic suspended particles and cationic poly (Aam)-rice straw graft copolymer has been predicted.

The novelty addressed here is undertaken by preparing a very efficient cationic flocculant using rice straw waste with different degrees of grafting for the treatment of wastewater using this kind of microwave irradiation approach as an eco-friendly tool. As far as the authors are aware, no thorough investigation has been done in the literature until now dealing with the above-mentioned preparation process.

Touch mode capacitive pressure sensors (TMCPS) offer superior sensitivity and linearity in comparison to normal mode CPS and have therefore seen substantial improvements in modeling and construction. This study aims to develop a sensor that is highly robust, with near-linear output characteristics, increased sensitivity and superior overload protection, making it an ideal choice for deployment in harsh industrial environments.

The proposed sensor design uses a substrate with a multi-step notch, introducing a new quadruple TMCPS and uses a small deflection model for mathematical analysis. Addition of a multi-step notch to traditional touch mode capacitive sensors results in quadruple touch regions which further enhances its operational range performance.

The simulation of diaphragm deflection in response to pressure is carried out by using COMSOL Multiphysics, whereas MATLAB is used for analytical simulations pertaining to variations in capacitance and capacitive sensitivity. Comparing with earlier models, there is a noticeable enhancement in capacitance, experiencing a fivefold increase. The achieved value stands at 50.1 pF, reflecting improved sensitivity for applied pressure ranging from 0 to 2 MPa.

In existing literature to improve the performance of the single TMCPS, a double-sided TMCPS has been developed. To enhance sensor performance, a substrate with a multi-step notch is proposed. The notch creates four touch regions with varying gap depths, resulting in increased capacitance and capacitive sensitivity.

During the COVID-19 pandemic, immigrants faced new challenges that increased their precarity which often perpetuated existing social and health-related inequities. This compounded inadequate access to healthcare, harsh working conditions, marginalization due to legal status and fear of deportation, all of which were worsened during the height of the pandemic. This article aims to examine how existing social factors that marginalize immigrant populations were affected by the COVID-19 pandemic based on a study with immigrant farmworkers in Apopka, Florida.

The author analyzes how they were affected by stress both before and during the pandemic, and how these factors affected their mental health.

The author concludes that im/migrants’ often precarious status negatively affects their experiences with mental health, and that this was heightened during the COVID-19 pandemic. Despite the long-term nature of precarity for this vulnerable population, this study captures these issues as they were experienced during the COVID-19 pandemic.

This research contributes to emerging scholarship concerning social factors and mental health during the pandemic by examining the experiences of one of the most marginal populations in the United States.

Examining dominance in influencing leadership perceptions for men and women has received significant scholarly attention. The studies typically show that dominance is beneficial for men in attaining leadership positions but not for women. However, the studies were predominantly conducted more than two decades ago. Given the developments in gender research, this study extends the dominance line of inquiry by probing the impact of dominance need on leader emergence for men versus women in self-managed work teams. Furthermore, this study aims to examine if team dominance needs dispersion posits as a boundary condition for the combined impact of dominance needs and gender on leader emergence.

The authors conducted a longitudinal study that lasted one semester and involved 44 ad hoc self-managed work teams.

This study found that dominance needs facilitated leader emergence regardless of gender, and team dominance needs dispersion. Furthermore, men with high dominance needs were likelier to emerge as leaders than women with high dominance needs in high dominance needs dispersion teams. By contrast, women low in dominance needs received a harsher penalty in their leadership emergence than men low in dominance needs in low dominance needs dispersion teams

These results depart from the usual findings regarding the backlash effects that dominant women face and paint a rosy picture regarding the use of dominance in shaping leader emergence. However, the findings support the notion in gender stereotypes research that women are judged more critically than men in ascending to leadership positions.

Evaluating and exploiting an opportunity is an iterative process, and one of the triggers for the re-evaluation is the feedback received from stakeholders. Most of the time, the feedback comes in the form of harsh comments, criticisms and rejections, which can cause shame. There is also a lack of studies on the impact of shame on the decision-making ability of the entrepreneur, which is addressed through this study.

The study uses an experimental design, which is considered the “gold standard” in establishing causality. By manipulating the emotions of 107 entrepreneurs and making them assess a hypothetical opportunity, the study finds conclusive evidence for the proposed hypotheses.

Using the appraisal tendency framework, the authors show that shame makes an entrepreneur assess an opportunity as lower in desirability and feasibility. Shame also makes an entrepreneur give more significant weight to feasibility (over desirability) when deciding on entrepreneurial action.

The study provides strong empirical evidence that shame is an important emotion and influences the decision-making ability of the entrepreneur. The study reveals that important stakeholders assessing entrepreneurs need to be careful about how they provide feedback. Since the emotion it can elicit has a bearing on the subsequent decisions made by the entrepreneur.