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The purpose of this paper is to apply an efficient hybrid computational numerical technique, namely, q-homotopy analysis Sumudu transform method (q-HASTM) and residual power series method (RPSM) for finding the analytical solution of the non-linear time-fractional Hirota–Satsuma coupled KdV (HS-cKdV) equations.

The proposed technique q-HASTM is the graceful amalgamations of q-homotopy analysis method with Sumudu transform via Caputo fractional derivative, whereas RPSM depend on generalized formula of Taylors series along with residual error function.

To illustrate and validate the efficiency of the proposed technique, the authors analyzed the projected non-linear coupled equations in terms of fractional order. Moreover, the physical behavior of the attained solution has been captured in terms of plots and by examining the L₂ and L_∞ error norm for diverse value of fractional order.

The authors implemented two technique, q-HASTM and RPSM to obtain the solution of non-linear time-fractional HS-cKdV equations. The obtained results and comparison between q-HASTM and RPSM, shows that the proposed methods provide the solution of non-linear models in form of a convergent series, without using any restrictive assumption. Also, the proposed algorithm is easy to implement and highly efficient to analyze the behavior of non-linear coupled fractional differential equation arisen in various area of science and engineering.

At this moment, there is substantial anxiety surrounding the fire safety of huge reinforced concrete (RC) constructions. The limitations enforced by test facilities, technology, and high costs have significantly limited both full-scale and scaled-down structural fire experiments. The behavior of an individual structural component can have an impact on the entire structural system when it is connected to it. This paper addresses the development and testing of a self-straining preloading setup that is used to perform thermomechanical action in RC beams and slabs.

Thermomechanical action is a combination of both structural loads and a high-temperature effect. Buildings undergo thermomechanical action when it is exposed to fire. RC beams and slabs are one of the predominant structural members. The conventional method of testing the beams and slabs under high temperatures will be performed by heating the specimens separately under the desired temperature, and then mechanical loading will be performed. This gives the residual strength of the beams and slabs under high temperatures. This method does not show the real-time behavior of the element under fire. In real-time, a fire occurs simultaneously when the structure is subjected to desired loads and this condition is called thermomechanical action. To satisfy this condition, a unique self-training test setup was prepared. The setup is based on the concept of a prestressing condition where the load is applied through the bolts.

To validate the test setup, two RC beams and slabs were used. The test setup was tested in service load range and a temperature of 300 °C. One of the beams and slabs was tested conventionally with four-point bending and point loading on the slab, and another beam and slab were tested using the preloading setup. The results indicate the successful operation of the developed self-strain preloading setup under thermomechanical action.

Gaining insight into the unpredictable reaction of structural systems to fire is crucial for designing resilient structures that can withstand disasters. However, comprehending the instantaneous behavior might be a daunting undertaking as it necessitates extensive testing resources. Therefore, a thorough quantitative and qualitative numerical analysis could effectively evaluate the significance of this research.

The study was performed to validate the thermomechanical load setup for beams and slabs on a single-bay single-storey RC frame with and without slab under various fire possible scenarios. The thermomechanical load setup for RC members is found to be scarce.

The purpose of this study is progressive collapse behavior in buildings. It occurs due to removal/damage of a column by fire, blast or vehicle impact.

The present study investigates the comparative behavior of 3D four-storey moment resisting steel frame using ABAQUS to predict the sensitivity of the structure in progressive collapse because of fire loads. Columns at different levels were given different temperature with reduced material properties and yield strength. Progressive collapse load combination was adopted as per General Service Administration guidelines. Corner, middle, intermediate, multiple corner and multiple intermediate columns were subjected to fire load separately.

The results for displacement, stress, shear force and axial force were captured and discussed.

The study covers linear analysis of steel frame because of different temperature. In linear analysis. columns were subjected to different temperature and their results were studied. Effect of temperature in the structure were captured because of different fire conditions.

The purpose of this study is to investigate the influence of progressive collapse under high temperature for a reinforced concrete (RC) frame. An analytical programme was analysed for a two-bay five-storey RC frame exposed to high temperature at different column locations.

The effects of high temperature protections and locations (i.e. corner, middle and intermediate) on collapse conditions and load distributions were studied for the steady-state linear analysis using finite element software.

The results show that the frame will not collapse suddenly at temperatures up to 400°C. This is attributed to an increase in the deflections of the column, which increases the lateral displacement of adjacent heated columns and governs their buckling. This indicates that the temperature rating in the column against collapse can occur at a range of 500°C-600°C compared to that of individual members. The collapse pattern of RC frames designed as ordinary moment resisting frames, and under ordinary load, combinations is based on GSA guidelines. The results for displacement, stress and axial force were collected and discussed.

The two-bay five-storey frame has been created in finite element software, and linear analysis is used to perform this study with a different temperature.

Progressive collapse because of high temperatures arising from an explosion, vehicle impact or fire is an important issue for structural failure in high-rise buildings.

The present study, using ABAQUS software for the analysis, investigated the progressive collapse of a two-dimensional, three-bay, four-storey steel frame structure from high-temperature stresses.

After structure reaches the temperature results like displacement, stress axial load and shear force are discussed.

Different temperatures were applied to the columns at different heights of a structure framed with various materials. Progressive collapse load combinations were also applied as per general service administration guidelines.

This study covered both steady-state and transient-state conditions of a multistorey-frame building subjected to a rise in temperature in the corner columns and intermediate columns. The columns in the framed structure were subjected to high temperatures at different heights, and the resulting displacements, stresses and axial loads were obtained, analysed and discussed.

This study aims to present systematic analysis of research concerning the intersection of human resource management (HRM) and the integration of artificial intelligence (AI) technologies within a digitalized economy further analyzing the trends in research with specific emphasis on utilization of diverse AI technologies within HRM.

This research is based on bibliometric analyses and content analyses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses review methodology is implemented, using the Scopus database as the primary source which gathered 1,414 articles between 1978 and 2024. This study investigates publishing trends, the most prolific countries, universities, journals, publications and authors in the field. Further, the research trends based on the use of AI in HRM were accomplished through scientific mapping using VOSviewer.

The outcomes demonstrate a rising inclination toward using various AI techniques in HRM which shows increasing influence and growing appeal of the subject. The research uncovers the deployment of diverse technologies, including emerging ones, within the HRM field. It accomplishes this by scrutinizing the connections among various keywords and unearths both contradictions and focal areas of interest within the domain.

The study contributes to the existing body of literature by ascertaining suggestions for further research in the field of HRM integrated with various AI technologies. The integration of these technologies in HR holds a promising and optimistic outlook for the managers, thereby enhancing employee productivity.

A large literature studies why firms self-regulate and “signal green.” However, it has ignored that regulators have enforcement discretion, and may act strategically. We fill this gap. We build a game theoretic model of whether a firm should signal its type through substantial self-regulation. We find self-regulation is a double-edged sword: it can potentially preempt legislation, but it can also lead regulators to demand higher levels of compliance from greener firms if preemption fails. We show how self-regulatory decisions depend upon industry characteristics and political responsiveness to corporate environmental leadership. We have made a number of simplifying assumptions. We assume activist groups cannot challenge regulatory flexibility in court, and that regulatory penalties are fixed and are not collected by the regulator. Firms with low compliance costs confront a tradeoff regarding self-regulation. They can blend in with the rest of the industry, and take few self-regulatory steps. This reduces the risk of regulation somewhat, and preserves their ability to obtain regulatory flexibility should regulation be imposed. Alternatively, they can step up with substantial self-regulation. This better mitigates the risk of regulation, but at the risk of signaling low costs and becoming a target for stringent enforcement should regulation pass. Recent work has found negative market reactions to corporate claims of voluntary emissions reductions, despite the conventional wisdom that it “pays to be green.” We offer a new explanation to scholars and managers: regulatory discretion may undermine the ability of industry self-regulation to profitably preempt mandatory regulatory requirements.

This study investigates what causes businesses to increase their environmental stewardship beyond the governmental standards. This “beyond compliance behavior” is examined by analyzing the influence of organizational slack and institutional pressures in the European paper and paperboard industry. Beyond compliance behavior is measured as the adoption of a sustainable forestry certificate issued by the Forest Stewardship Council (FSC). The longitudinal (10-year period) dataset consists of adoption events per company, their business characteristics and historic socio-economic data per region in the respective European countries. Examination was done by means of an event history analysis using the program “R.” The results show differences between antecedents of compliance and beyond compliance behavior. The authors discuss the results in the light of institutional and stakeholder theories. Due to institutional shifts in environmental demands, adoption of an FSC certificate has become an off-the-shelf compliance answer to legitimacy issues disguised as a progressive environmental stewardship program.

The body has been one of the central tools in analysing connections between sport and postcolonialism in India, given how sport was an essential part of the colonial ‘civilising’ mission, which involved disciplining and controlling Indian bodies. Any discursive understanding of sport and postcolonialism in India must consider how it relates to existing concepts of the body and shapes the experiences of the people involved in it – acknowledging not just the power of colonialism in moulding sporting experiences but also the force of internal hierarchies that exist in Indian society. This chapter explores the experiences of students who studied in higher educational institutions in Kerala under the ‘sports quota’, a system that reserves seats in colleges/universities for high-performing sportspersons in India. Through their interviews, the sustained exclusion of the sporting body in contemporary Indian pedagogy is illustrated here. Specifically, the continuing prevalence of the colonial emphasis on the sporting body, as one whose strength and instrumentality are paramount, as well as its corollary postcolonial position, which treats this sporting body as inferior to the ‘refined mind’ of studious pupils, can be observed. Approaching the sports quota with a decolonising lens would require re-examining the disembodied nature of pedagogy in India’s higher educational institutions, acknowledging sporting students’ lived experiences, and a seamless integration – as opposed to separation/exclusion – of the sportsperson into higher education.