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The purpose of this study is a numerical simulation and an analytical analysis about the low-velocity impact on a functionally graded porous plate with porosity distribution in the thickness direction. In this article, polymethyl methacrylate is used for matrix, and single-walled carbon nanotube (CNTs) (10,10) with consideration agglomeration sizes and lumping of CNT inside the agglomerations is applied for reinforcement.

In analytical formulation, the non-linear Hertz contact law is applied for interaction between projectile and plate surface. High-order shear deformation plate theory is developed, and energy of the system for impactor and plate is written. The governing equations are derived using Ritz method and Lagrange equations and are solved using the fourth-order Runge–Kutta method. Also, ABAQUS finite element model of functionally graded porous plate with all edges simply supported and reinforced by CNT under low-velocity impact is simulated and is compared with those is achieved in the present analytical approach.

In parametric studies, the influence of porosity distribution patterns include uniform, non-uniform symmetric and non-uniform asymmetric on the histories of contact force and impactor displacement of simply supported plate reinforced by CNT are presented. Eventually, the effects of porosity coefficient, impactor initial velocity, impactor radius and CNTs lumping inside agglomerations for non-uniform symmetric distribution patterns are discussed in impact event in detail.

In this paper, the effect of combination of polymethyl methacrylate and CNTs with consideration agglomeration sizes and lumping of CNTs inside the agglomerations in the form of a functionally graded porous plate is studied in the problem of low-velocity impact analysis.

The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context.

A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes.

The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology.

This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM).

This study aims to propose a numerical modeling procedure for response analysis of elastic body floating in water and submitted to regular waves. An equivalent simplified mechanical single-degree-of-freedom system allowing to reproduce the heave movements is first developed, then the obtained lumped characteristics are used for elastic analysis of the floating body in heave motion.

First, a two-dimensional numerical model of a rigid floating body in a wave tank is implemented under DualSPHysics, an open source computational fluid dynamics (CFD) code based on smoothed particle hydrodynamics method. Then, the obtained results are exploited to derive an equivalent mechanical mass-spring-damper model. Finally, estimated equivalent characteristics are used in a structural finite element modeling of the considered body assuming elastic behavior.

Obtained results concerning the floating body displacements are represented and validated using existing experimental data in the literature. Wave forces acting on the body are also evaluated. It was found that for regular waves, it is possible to replace the complex CFD refined model by an equivalent simplified mechanical system which makes easy the use of structural finite element analysis.

The originality of this work lies in the proposed procedure to evaluate the mechanical properties of the equivalent elastic system. This allows to couple two different software tools and to take advantages of their features.

The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).

Industrial motor drive systems (IMDS) are currently expected to perform beyond the desired operating conditions to meet the demand. The PoF of the subsystem affects its reliability under such harsh operating circumstances. It is crucial to estimate reliability by integrating PoF, which helps in understanding its impact and to develop a fault-tolerant design, particularly in such an integrated drive system. An integrated PoF extended reliability method for industrial drive system is proposed to address this issue. In research, the numerical failure rate of each component of industrial drive is obtained first with the help of the MIL-HDBK-217 military handbook. Furthermore, the mathematically deduced proposed approach is modeled in the GoldSim Monte Carlo reliability workbench.

From the results, for a 15% rise in integrated PoF, the reliability and availability of the entire IMDS dropped by 23%, resulting in an impact on mean time to failure (MTTF).

The integrated PoF of the motor and motor controller affects industrial drive reliability, which falls to 0.18 with the least MTTF (2.27 years); whose overall reliability of industrial drive drops to 0.06 if it is additionally integrated with communication protocol.

Although healthcare and healthy living are integral to the Sustainable Development Goals (SDGs) for 2030, the coronavirus epidemic has dealt a devastating blow to these efforts. As governments and policymakers were compelled to shift their focus to lockdowns, sustenance, procurement, and distribution of vaccines, the momentum for health initiatives slowed, and the already fragile health systems of emerging markets were subjected to additional shocks. However, in many underserved regions of the globe, the introduction of technology has greatly facilitated the distribution and adoption of healthcare services.

This chapter highlights mini-cases from four emerging nations: Bangladesh, Nigeria, Vietnam, and the Philippines. Although the countries are emerging, each one of them are in a distinct stage of development and face a unique set of healthcare-related challenges. The chapter showcases how four different organizations based in these countries leveraged the use of technology to take healthcare services to underserved populations. In doing so, they addressed the key challenges of imparting healthcare: geographic accessibility, availability, financial accessibility, and acceptability.

This chapter concludes with a discussion of the implications of expanding healthcare industries leading to increased healthcare waste. To prevent mass population exposure to hazardous substances, the emergence of intelligent healthcare waste collection and disposal systems will be an absolute necessity. Hence, with the development of healthcare services, governments and policymakers need to mechanize smart waste management systems to safeguard humans, animals, and the environment.

This paper aims to study the impact of pyro-electricity, moisture and temperature diffusivity on the energy distribution of plane waves at the free surface of an orthotropic piezo-hygro-thermo-elastic medium.

This study presents the novel creation of governing equations for an anisotropic piezothermoelastic medium with moisture impact, which is a significant contribution of this paper.

In addition to providing numerical data for the amplitude ratios and energy ratios of reflected waves, this study identifies five different kinds of coupled reflected plane waves, namely, quasi-longitudinal P wave, quasi-thermal wave, quasi-transverse wave, quasi-moisture wave and electric potential wave.

The graphical analysis examines the impact of various factors, such as the angle of incidence, moisture and temperature diffusivity, pyro-electricity and frequency, on energy distribution.

This paper's results significantly impact the development of more efficient piezoelectric materials and their applications in geophysics.

The authors of the submitted document initiated and produced it collectively, with equal contributions from all members.

In this study, the effects of strain rate on the bending strength of full-scale wide-flange steel beams have been examined at elevated temperatures. Both full-scale loaded heating tests under steady-state conditions and in-plane numerical analysis using a beam element have been employed.

The load–deformation relationships in 385 N/mm²-class steel beam specimens was examined using steady-state tests at two loading rate values (0.05 and 1.00 kN/s) and at two constant member temperatures (600 and 700 °C). Furthermore, the stress–strain relationships considering the strain rate effects were proposed based on tensile coupon test results under various strain rate values. The in-plane elastoplastic numerical analysis was conducted considering the strain rate effect.

The experimental test results of the full-scale steel beam specimens confirmed that the bending strength increased with increase in strain rate. In addition, the analytical results agreed relatively well with the test results, and both strain and strain rate behaviours of a heated steel member, which were difficult to evaluate from the test results, could be quantified numerically.

The novelty of this study is the quantification of the strain rate effect on the bending strength of steel beams at elevated temperatures. The results clarify that the load–deformation relationship of steel beams could be evaluated by using in-plane analysis using the tensile coupon test results. The numerical simulation method can increase the accuracy of evaluation of the actual behaviour of steel members in case of fire.

Traceability of food is of paramount importance to the increasingly sustainability-conscious consumers. Several tracking and tracing systems have been developed in the AgriFood sector in order to prove to the consumers the origins and processing of food products. Critical challenges in realizing food's traceability include cooperating with multiple actors on common data sharing standards and data models.

This research applies a design science approach to showcase traceability that includes preharvest activities and conditions in a case study. The authors demonstrate how existing data sharing standards can be applied in combination with new data models suitable for capturing transparency information about plant production.

Together with existing studies on farm-to-fork transparency, our results demonstrate how to realize transparency from field to fork and enable producers to show a complete bill of sustainability.

The existing standards and data models address transparency challenges in AgriFood chains from the moment of harvest up to retail (farm-to-fork) relatively well, but not what happens before harvest. In order to address sustainability concerns, there is a need to collect data about production activities related to product quality and sustainability before harvesting and share it downstream the supply chain. The ability to gather data on sustainability practices such as reducing pesticide, herbicide, fertilizer and water use are crucial requirements for producers to market their produce as quality and sustainable products.

This study examines whether education in developing countries directly impacts their foreign income from the top export sector.

As most developing countries follow developed nations to shape their development, this study assumes developing countries as education-follower and developed countries as education-leader countries. Considering selected countries from the South Asian Regional Cooperation (SAARC) and African countries as follower countries and Group of Seven (G7) as leader countries, this study employs Dumitrescu-Hurlin Granger non-causality tests.

This study finds that education-follower countries' achievements do not directly impact foreign earnings from their leading export sectors. However, findings also confirm that leader countries have a bidirectional causal relationship between tertiary education and earnings from high technology exports.

To the best of the authors' knowledge, this is the first study urging research-intensive education with comparative advantages in international trade. Using educational attainment on export earnings from the leading sector, findings support dependency theory in education is still existed.

This study deals with the main issues concerning the interplay between homeownership and labour market outcomes, namely (1) the relation between homeownership and labour market outcomes, at both the individual level and the aggregate level, and (2) the relation between homeownership and human capital.

This paper is both theoretical and empirical. A search and matching model of the labour market is developed to explain the strong relation between mortgage markets and wages. A regional panel analysis in Italy is used to verify the interplay between homeownership and wages.

Homeownership is not, by itself, a condition for receiving higher wages, but rather higher wages increase the probability to become a homeowner, since they positively affect the probability of acquiring a mortgage from the bank. Eventually, wages cause homeownership, but the reverse may not be true.

The paper focuses on the labour market, while the housing market model is restricted to the mortgage market.

The positive effect of homeownership on wages is hard to theoretically formalise and is not empirically proven. Before investigating a (potential) bidirectional relationship between homeownership and labour market outcomes, therefore, the related literature should assume a new theoretical link between homeowners and wages.

The result that “homeownership is not, by itself, a condition for receiving higher wages” has positive implications for human and social development. If homeownership could lead to better labour market outcomes, indeed, socio-economic inequalities would increase in the society, because homeownership would be the starting point of a “lucky” circle that increases the well-being of people who are already wealthy.

First, this study clearly explains why the microeconomic result that homeowners are more likely to be employed than tenants is consistent – at the aggregate level – with a negative relation between homeownership and better labour market outcomes. Second, the related literature has largely ignored the social implications of the topic. A potential bidirectional relation between homeownership and (better) labour market outcomes, indeed, could imply an increase in the well-being of people who are already wealthy.