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This paper aims to examine the influence of radiative nanoparticles on incompressible electrically conducting upper convected Maxwell fluid (rate type fluid) flow over a convectively heated exponential stretching sheet with suction/injection in the presence of heat source taking chemical reaction into account. Also, a comparison of the flow behavior of Newtonian and Maxwell fluid containing nanoparticles under the effect of different thermophysical parameters is elaborated. Velocity, temperature and nanoparticle volume fractions are assumed to have exponential distribution at boundary. Buongiorno model is considered for nanofluid transport.

The equations, which govern the flow, are reduced to ordinary differential equations using suitable transformation. The transformed equations are solved using a robust homotopy analysis method. The convergence of the homotopy series solution is explicitly discussed. The present results are compared with the results reported in the literature and are found to be in good agreement.

It is observed from the present study that larger relaxation time leads to slower recovery, which results in a decrease in velocity, whereas temperature and nanoparticle volume fraction is increased. Maxwell nanofluid has lower velocity with higher temperature and nanoparticle volume fraction when compared with Newtonian counterpart. Also, the presence of magnetic field leads to decrease the velocity of the nanofluid and enhances the skin coefficient friction. The existence of thermal radiation and heat source enhance the temperature. Further, the presence of chemical reaction leads to decrease in nanoparticle volume fraction. Higher value of Deborah number results in lower the rate of heat and mass transfer.

The novelty of present work lies in understanding the impact of fluid elasticity and radiative nanoparticles on the flow over convectively heated exponentially boundary surface in the presence of a magnetic field using homotopy analysis method. The current results may help in designing electronic and industrial applicants. The present outputs have not been considered elsewhere.

Looks at the 2000 Employment Research Unit Annual Conference held at the University of Cardiff in Wales on 6/7 September 2000. Spotlights the 76 or so presentations within and shows that these are in many, differing, areas across management research from: retail finance; precarious jobs and decisions; methodological lessons from feminism; call centre experience and disability discrimination. These and all points east and west are covered and laid out in a simple, abstract style, including, where applicable, references, endnotes and bibliography in an easy‐to‐follow manner. Summarizes each paper and also gives conclusions where needed, in a comfortable modern format.

In magnetostatics, topology optimization (TO) addresses the problem of finding the distributions of both current densities and ferromagnetic materials to comply with fixed magnetic specifications. The purpose of this paper is to develop TO in order to design Hall-effect Thrusters (HETs).

In fact, TO problems are known to be large-scale optimization problems. The authors therefore adopt the adjoint method to reduce the computation time required to obtain the gradient information. In this paper, they illustrate the continuous variant of the adjoint method in the context of magnetostatics TO. Herein, the authors propose an implementation of the adjoint method then use it within a gradient-based optimization solver fmincon-MATLAB to solve a HET TO design problem.

By comparison with finite difference method, the authors validate the accuracy of the suggested implementation of the adjoint method. Then, they solve a large-scale HET TO design problem. The resultant design of TO is distinctly original and not intuitive.

In this paper, the authors introduce TO as a tool that has allowed them to explore new and innovative design of a HET. However, although the design presented is original, its manufacture is not feasible. Thus, a discussion section has been included at the end of paper to suggest a possible way to concretize topological solutions.

TO helps to explore more original design possibilities. In this paper, the authors present an implementation of the adjoint method that makes it possible to solve efficiently and in less central processing unit time large-scale TO design problem.

An easy implementation of the adjoint method is presented in magnetostatics TO. This implementation was first validated by comparison with the finite difference method and then used to solve a large-scale design problem. The result of the TO design problem is distinctly original and non-intuitive.

This paper proposes a new conception of school systems arising out of the collision of three forces: (1) a longstanding press to rationalize the technical work of schools in the service of educational excellence; (2) a growing democratic press to equitably engage community members in the process of defining educational excellence; which together are (3) heightening legacy uncertainties that pervade educational organizations. It then draws on paradox theory to explore how leaders might navigate the growing uncertainties that are central to the work of organizing for excellence and equity.

Integrating scholarship related to organizational institutionalism, paradox theory, learning sciences, social justice leadership and educational system building, this paper examines the changing organization of schools, the growing uncertainty facing educators and the implications for leaders and preparation programs.

This paper introduces two perspectives on how to navigate the growing uncertainty facing educators and educational leaders: one that centers on mitigating uncertainty, the other that prioritizes leveraging uncertainty. Both perspectives have affordances and limitations when considering the twin goals of educational excellence and equitable involvement in decision-making, and leaders should thus view uncertainty as a paradox—an interdependent, persistent, contradiction—that can never be fully resolved, but can be managed. A paradox perspective makes visible the complex work of effectively moving between mitigating and leveraging uncertainty, especially in a field where the latter garners more support and legitimacy.

This paper synthesizes recent educational and organizational scholarship to develop a new conception of educational organizations and a corresponding approach to educational leadership capable of navigating the growing complexity and uncertainty that pervades school systems.

The purpose of this study is to examine dilemmas in a district–university partnership that used network improvement communities (NIC) as a levers for systems change after COVID-19.

We draw on observations and in-depth, semi-structured interviews to understand the benefits and limitations of using network improvement communities embedded within a longstanding district–university partnership to address problems of practice.

Five dilemmas that emerged: (1) the need to continue the pilot roll-out of the NIC while still communicating a vision of the long-term, large-scale vision of NIC work, (2) center collaborative inquiry while still moving at a fast enough pace for participants to see progress, (3) include those most involved in the work while still having efficient decision making processes, (4) respect the knowledge and agency of participants while still supporting rigorous and impactful change and (5) honor the work the district is already engaged in while still extending beyond existing initiatives.

We conclude that the work of leading network improvement communities as part of a district–university partnership is complex. We add to the emerging research on NIC hub leadership by highlighting the dilemmas that must be managed in this work.

Improvement science (IS) has become a popular approach to organizing school–university partnerships because of IS’s potential to increase schools' capacity for sustainable improvement. However, little research has directly examined whether and how specific elements of IS support school improvement, particularly during and post-COVID-19 when improvement was particularly challenging.

We draw on a longitudinal case study of a school-university partnership supporting a group of schools using IS to guide school improvement with data collected in Fall 2019–Spring 2022 including interviews and meeting observations. We compare how educators engaged with three IS elements: plan-do-study-act (PDSA) continuous improvement (CI) cycles, networked learning and driver diagrams. We qualitatively examine participants' perspectives of these elements through the lens of contingency theory, analyzing which elements were more or less successful at empowering schools to continue their improvement efforts throughout the pandemic.

IS processes are varied in their resilience to complexity. Schools mostly abandoned some elements during tumultuous periods (PDSA cycles) while others were successfully adapted to sustain improvement work (driver diagrams). Findings also discuss the perceived impact of university partners in school improvement work, primarily as coaches.

These findings are uniquely positioned to examine whether and how IS elements enabled sustained school improvement amidst the complexities generated by COVID-19. By focusing on strengths and limitations of three common elements, we offer valuable guidance to school–university partnerships about the conditions under which these elements might support sustained school improvement and how these elements might need to be adapted.

This chapter addresses evidence-informed teaching in the English context. The chapter makes the case for considering England as having elements of both high and low social cohesion, with an increasingly narrow role for Local Authorities (districts) alongside the growth of more powerful but smaller Multi-Academy Trusts. Within the context of a highly regulated accountability regime, this places England in the hierarchist, with elements of fatalist, quadrant of the cohesion/regulation matrix. England has a well-developed infrastructure for supporting research use, including the Education Endowment Foundation (EEF), a very well-resourced charity acting as the What Works Centre for school education. Despite this, use of research evidence amongst teachers is low, and this has changed little since the mid-2010s. The chapter draws on institutional theory to explain this finding. The following explanations are provided: a lack of resources, coupled with a strong, politicised accountability system and a hollowed out middle tier to support schools, contributing to a lack of prioritisation amongst school leaders. However, England's well-developed infrastructure has enabled the EEF to play a significant and evidence-led role in supporting schools in the context of the COVID-19 pandemic. The chapter concludes by suggesting a series of suggestions to improve use of research in England. These include alignment of policy with research evidence; support for school leaders; work to explicitly link research to the evidence forms and supporting research brokerage.

Continuous fiber-reinforced thermoplastic composites are a class of materials highly valuable for structural applications and modeling of heat transfer within them is critical to the design of their processing methods. However, the fiber reinforcement leads to highly anisotropic thermal conduction. Among a variety of methods to account for anisotropic thermal conductivity, continuum models with effective media approximation thermal conductivity are computationally efficient and require minimal data to begin modeling a specific composite material. The purpose of this study is to evalute the utility of these models.

In this work, six potential effective media approximation models are evaluated against experimental heating data. Thick (>25 mm) glass fiber-reinforced polyethylene terephthalate glycol (PET-G) specimens with 40% fiber volume fraction were heated with embedded resistance heating to produce validation and testing data sets. A two-dimensional finite-difference solver was implemented using each of the six effective media approximation models. The accuracy of each model is compared.

The model developed by Cheng and Vachon was found to predict the experimental results most accurately. Fit statistics were similar in the testing and validation data sets. This model is recommended for simulation of transient heating in continuous fiber-reinforced thermoplastic composites with low-to-moderate fiber volume fractions.

There are a wide variety of mathematical models for effective media approximation thermal conductivity, though very few have been applied to continuous fiber-reinforced thermoplastic composites. This work shows that the simplest methods based on rules of mixtures are well outperformed by more modern and complex models, and should be incorporated for accurate prediction of heating during thermal processing of fiber-reinforced thermoplastic composites.

The objective of this chapter is to provide an understanding of the meaning and measurements of food security.

This chapter consolidates and examines the evolution of the many definitions of food security since 1975 and describes the four dimensions of global food security. We examine the relationship between global food crisis and food security, and the significance of Brazil, Russia, India, China, and South Africa as emerging markets.

Achieving food security will be determined by the world as a group helping developing countries in creating proper infrastructures, providing better income opportunities, and reducing financial constraints.

Governments, international agencies, private firms, and the world’s population need to be involved in food security from seed to plate.