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This study aims to reduce the interfacial tension by increasing the better adhesion between different immiscible polymers phases and also to evaluate the mechanical, thermal and thermo-mechanical behavior of the immiscible polymer blends.

The polymer blend composite (PBC) was prepared using a twin-screw extruder followed by injection molding. Two different kinds of PBC with compatibilizer (Ethylene-n-Butylacrylate-Glycidyl methacrylate) of varying compositions like polybutylene terephthalate + poly trimethylene terephthalate and polybutylene terephthalate (30% glass filled) + poly trimethylene terephthalate were prepared and material behavior at various test conditions were studied. The effect of glass fiber reinforcement on polymer blend and the interlocking effect by the compatibilizer between the polymer phases were also assessed.

Mechanical behavior of PBC was estimated by tensile, flexural and angular impact tests. Likewise, the thermal deflection was studied with the help of heat deflection temperature test. Thermo-mechanical behavior likes storage modulus, loss modulus and loss tangent were studied using the dynamic mechanical analysis test. Morphological analysis was characterized using field emission scanning electron microscopy.

This in turn makes the process easy to obtain the PBC having inherent mechanical, thermal and thermo-mechanically stable. And, it also enhances the mechanical properties like tensile, flexural and impact strength. Simultaneously, posse’s excellent heat deflection and thermo-mechanical behavior over a temperature range of 35–140ºC at a constant frequency of 5 Hz.

This study aims to analyze the effect of interrupted rolling on microstructures and mechanical properties of Mg–8Li–xGr composite is investigated.

Graphene reinforced composite was developed by using stir casting route and rolled with different reduction in thickness such as 50, 75 and 90%. Microstructure, hardness and tensile characteristics of the rolled samples were evaluated.

Investigation on microstructures of rolled composite depicts that increase in rolling reduction % resulted in fine elongated grains and decreased aspect ratio. Further, it was also observed that increasing percentage of rolling reduction promotes the dissolution of ß Li phase and as a result the ductility of composite decreases. Interrupted rolled samples showcase higher hardness when compared with as-cast composite. Composite rolled with 90% reduction displays higher yield strength of 219 MPa. Hardening capacity of composites decreases with increase in reduction percentage due to the effective reduction in grain size.

Investigation on the influence of interrupted rolling on microstructures and mechanical properties of Mg graphene composite. The in-depth understanding of this will help to improve its wide spread application.

Neuroeconomics and neurofinance are emerging as intriguing fields of research, despite sharing ambiguity with the concepts of neuroscience. The relationship among the concepts of economics, finance and neuroscience is not explicitly defined in the past literature, which distorts the use of neuroeconomics and neurofinance approaches in real-world practice for financial decision-making. The purpose of this paper is to consolidate the literature in the field of neuroeconomics and neurofinance to set up the research agenda for the upcoming scholarship in the field.

The purpose of this paper is to consolidates the extant literature in the fields of neuroeconomics and neurofinance by conducting an extensive systematic literature review to investigate the current state and define the relationship between economics, finance and neuroscience.

This paper identifies and explains the explicit relationship between different sub-fields of neuroscience with neuroeconomics and neurofinance and providing instances for future research studies.

The exclusive and extensive literature survey in the form of systematic literature review is undertaken for understanding the fields of neuroeconomics and neurofinance and is the key highlight of this paper. Another, interesting fact lies with matching the literature in neuroeconomics and neurofinance with further sub-fields of neuroscience such as neurophysiology, neuroanatomy, molecular neuroscience and cognitive neuroscience.

The purpose of this paper is to study the corrosion behaviour of Al-12Zn-3Mg-2.5Cu alloy by cast, precipitation hardening and non-isothermal step rolling cum cold/cryo rolling (−80 and −196°C) in 3.5 per cent NaCl solution.

Aluminium alloy with high alloying concentration (Zn: 12 per cent, Mg: 3 per cent, Cu: 2.5 per cent) was prepared by squeeze casting method with controlled process parameters. The cast alloy was solution treated at 450°C for 24 h and aged at 120°C with varying time intervals. Initially, the alloy also underwent non-isothermal step rolling from 6 mm to 3 mm at 400-100°C at the step of 100ºC with 15% reduction in thickness. Non-isothermal rolled alloy (3 mm thickness) was the starting material for further rolling at three different temperatures, such as room temperature, −80 and −190°C with 85 per cent reduction. Microstructural evolution during precipitation and thermo-mechanical processing was studied with the help of optical microscopy and electron microscopy. A potentio-dynamic polarization study was performed to evaluate the corrosion behaviour of Al-12Zn-3Mg-2.5Cu alloy processed in different conditions in 3.5 per cent NaCl solution.

There is a distinct evidence that the alloy exhibits varying corrosion resistance by changing its structural features. In fact, the alloy with ultra-fine grained structure exhibits good corrosion resistance than that of alloy in cast. This is attributed to a greater grain boundary region with high dislocation density, and plastic strain adversely affects the corrosion resistance.

The results obtained by this investigation help in understanding the effect of precipitation hardening and non-isothermal step rolling cum cold/cryo rolling (−80 and −196°C) on corrosion behaviour.

The purpose of this paper is to identify whether heuristic and herding biases influence portfolio construction and performance in Greece. The current research determines the situation among investors in Greece, a country with several economic problems for the last decade.

A survey has been conducted covering a group of active private investors. The relationship between private investors' behavior and portfolio construction and performance was tested using a multiple regression.

The authors find that heuristic variable affects private investor's portfolio construction and performance satisfaction level positively. A robustness test on a second group, consisting of professional investors, reveals that heuristic and herding biases affect investment behavior when constructing a portfolio.

The authors recommend investors to select professional's investment portfolio tools in constructing investment portfolios and avoid excessive errors, which occur due to heuristic. The awareness and understanding of heuristic and herding could be helpful for professionals and decision-makers in financial institutions by improving their performance resulting in more efficient markets.

The main contribution of this paper lies in the fact that it is the first study on two major behavioral dimensions that affect the investor's portfolio construction and performance in Greece. The rationale of the current research is that the results are helpful for investors in order to take rational, reliable and profitable decisions.

This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.

For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.

Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.

Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.

This chapter reviews the literature on servitization to understand whether and how mergers and acquisitions (M&As) have been dealt with and what the portrayed consequences are of servitization through M&As. Servitization refers to how manufacturing firms extend and remodel their offerings to focus on value in use rather than product transfer. The rationale of the chapter follows from how business model innovation or business modeling has been predicted as the next M&A wave, while the focus on servitization has been pronounced in research and practice as a means for manufacturing firms to refocus operations during the past decade. The chapter concludes that while the servitization literature is vibrant, the mode of reaching service competence and renewing business is not well explored in the literature. In line with the predicted next M&A wave, servitization through M&As would thereby create an interesting path for future research.

This research work focuses on implementing this methodology in reducing the rejection rate of the turbocharger component problem that occurs during the manufacturing process. Using design, measure, analyze, improve and control (DMAIC) processes, it has been identified that clamping pressure on the component is one factor that affects quality. The impact of clamping pressure is studied to arrive at the ideal clamping pressure in which the rejection rate is the least.

Quality is the keyword in manufacturing where the production of a defect-free component is the most sought out objective. The definition of quality keeps getting refined throughout the years, from making products with no defects to minimizing rejection and scrap in the manufacturing process. Production facilities, to achieve this purpose, have adopted various methods and use of the DMAIC of Six Sigma methodology is one among them.

The study identified the fault causing the defect and suggested the methods to correct the fault. The suggestions would result in reducing the losses arising due to this and similar rejection causes.

With the adoption of DMAIC, it is found that misalignment of top and side clamp pressure is zero. When the side clamp pressure is at 75 PSI, and top clamp pressure is changed from 90 PSI to 95 PSI, the mean of responses is greater than the side clamp pressure of 80 PSI. Therefore, from the three-combination top clamp pressure of 100 PSI and the side clamp pressure of 75 PSI is the optimal condition.

The aim of the present study is to find the tribological properties of newly developed polyester-based hybrid glass-jute fibre reinforced plastic composites loaded with different weight per cent of hybrid filler particles were investigated under a dry sliding medium from room temperature to 75°C.

The study was carried out using a pin-on-disc wear test set-up. The design of experiments was carried out in a controlled way using a central composite design based on response surface methodology to observe the effect of various parameters i.e. sliding velocity, sliding distance, the temperature of counterface and different applied load conditions during dry-sliding.

The maximum wear resistance was found at 9 Wt% loading of filler, 4 ms^-1 sliding velocity, 30 N applied load, 54°C temperature of the counterface and 1,100 m sliding distance condition. Optimum values of hybrid filler loading, sliding velocity, applied load, the temperature of the counterface and sliding distance for the minimum coefficient of friction value and minimum friction force are 9 Wt%, 4 ms⁻¹, 30 N, 54° C, 1,100 m and 12 Wt%, 3 ms⁻¹, 20 N, 59°C and 1,100 m, respectively. The worn surface morphology was studied using scanning electron microscope, for wear dominant mechanisms.

The tribological properties of newly developed polyester-based hybrid glass-jute fibre reinforced plastic composites loaded with different weight % of hybrid filler particles, were investigated under dry sliding medium from room temperature to 75°C has not been attempted yet.