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The purpose of this study is to numerically model the rigid pavement resting on two-parameter soil and to examine its modal parameters.

This study is carried out using a one-dimensional beam element with three rotational and three translational degrees of freedom based on the finite element method. MATLAB programming is used to perform the free vibration analysis of the rigid pavement.

Cyclic frequency and their corresponding mode shapes were determined. It has been investigated how cyclic frequency changes as a result of variations in the thickness, span length of pavement, shear modulus, modulus of subgrade, different boundary conditions and element discretization. Thickness of the pavement and span length has greater effect on the cyclic frequency. Maximum increase of 29.7% is found on increasing the thickness, whereas the cyclic frequency decreases by 63.49% on increasing span length of pavement.

The pavement's free vibration is the sole subject of the current investigation. This study limits for the preliminary design phase of rigid pavements, where a complete three-dimensional finite element analysis is unnecessary. The current approach can be extended to future research using a different method, such as finite element grilling technique, mesh-free technique on reinforced concrete pavements or jointed concrete pavements.

The finite element approach adopted in this paper involves six degrees of freedom for each node. Furthermore, to the best of the authors’ knowledge, no prior study has done seven separate parametric investigations on the modal analysis of rigid pavement resting on two-parameter soil.

In this study, a finite element model of a box-girder bridge along with the railway sub-track system is developed to predict the static behavior due to different combinations of the Indian railway system and free vibration responses resulting in different natural frequencies and their corresponding mode shapes.

The modeling and evaluation of the bridge and sub-track system were performed using non-closed form finite element method (FEM)-based ANSYS software.

From the analysis, the worst possible cases of deformation and stress due to different static load combinations were determined in the static analysis, while different natural frequencies were determined in the free vibrational analysis that can be used for further analysis because of the dynamic effect of the train vehicle.

The scope of the current investigation is confined to the structure's static and free vibration analysis. However, this study will help the designers obtain relevant information for further analysis of the dynamic behavior of the bridge model.

In static analysis, the maximum deformation of the bridge deck was found to be 10.70E-03m due to load combination 5, whereas the maximum natural frequency for free vibration analysis is found to be 4.7626 Hz.

This study aims to attempt to make an aluminum-based composite using reinforcement such as graphite and fly ash. Pollution is an enhanced serious issue of concern for global. Industries play a major role in disturbing the balance of the environment system. Composite is made by using the stir casting technique. The waste that is generated by the industries if left untreated or left to be rotten at some place may prove fatal to invite various types of diseases. Proper treatment of these wastes is the need of the hour, the best way to get rid of such kinds of hazardous wastes is to use them by recycling.

Stir casting technique was used to make a composite. Graphite and fly ash were mixed with equal amounts of 2.5% to 15% in aluminum. The microstructure of composite formed after composite was noticed. After seeing the microstructure it was understood that reinforcement particles are very well-mixed in aluminum.

When graphite was mixed with 3.75% and 3.75% fly ash in aluminum, the strength of the composite came to about 171.12 MPa. As a result, the strength of the composite increased by about 16.10% with respect to the base material. In the same way, when 3.75% graphite and 3.75% fly ash were added to aluminum, the hardness of the composite increased by about 26.60%.

In this work, graphite and fly ash have been used to develop green metal matrix composite to support the green revolution as promoted/suggested by United Nations, thus reducing the environmental pollution. The addition of graphite and fly ash to aluminum reduced toughness. The thermal expansion of the composite has also been observed to know whether the composite made is worth using in higher temperatures.

Introduction: The pandemic era has given rise to emerging VUCA factors, characterised by volatility, uncertainty, complexity, and ambiguity. Navigating the impact of these challenges is essential for adapting and thriving in a post-pandemic world; therefore, it is important to identify VUCA factors.

Purpose: The purpose of this study is to identify and analyse the VUCA factors that emerged during the COVID-19 pandemic, focusing on sectors such as hospitality, tourism, education, construction, manufacturing, Information Technology, healthcare, and automobiles.

Need for the Study: Analysing emerging VUCA factors is crucial for businesses to prepare for unforeseen events. While VUCA factors were previously studied during significant events like the Greater Recession, BREXIT, and demonetisation, the pandemic has presented unprecedented challenges, making the identification of emerging VUCA components crucial.

Methodology: The methodology involves reviewing articles and research papers to understand the pandemic’s impact on various sectors. The findings provide insights into prominent VUCA factors and their implications for businesses, contributing to existing knowledge.

Findings: This research uncovers the challenges organisations encountered in the pandemic’s VUCA environment, offering insights into uncertainties and strategies for survival. It highlights the importance of adaptability, resilience, and innovation in overcoming VUCA’s negative impacts and establishing a new business paradigm.

Practical Implications: This chapter is essential in providing valuable insights for organisations, policymakers, and businesses on crisis preparedness, emphasising the significance of agility, robust contingency planning, and sector-specific considerations. Reviewing operations and implementing backup plans, businesses can develop effective strategies for long-term resilience and success in the face of unforeseen disruptions.

This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods.

The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis.

In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods.

Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers.

Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer’s experience.

Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies.