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IEEE 802.15.4 is a new standard uniquely designed for low‐rate wireless sensor networks (WSNs). It targets low data rate, low power consumption and low‐cost wireless networking, and offers device level wireless connectivity. The purpose of this paper is to propose a traffic adaptive power control algorithm for beacon relayed distributed WSNs.

A general coordinated sleeping algorithm and the traffic adaptive algorithm are combined in an IEEE 802.15.4 MAC protocol to achieve high‐energy efficiency and high performance at the same time.

By observing the sporadic traffic and beacon relaying characteristics of WSNs, the paper proposes a traffic‐adaptive IEEE 802.15.4 MAC with a coordinated sleeping algorithm. Based on various performance studies, it was found that the proposed algorithm can significantly improve power consumptions in wireless sensor networks.

The paper is of value in proposing a traffic adaptive power control algorithm showing highly efficient power consumptions in low‐traffic conditions as well as with an acceptable degree of adaptation to high‐traffic conditions. In delay performance, it shows longer delay performance compared with other schemes because of the beacon relay procedure while the proposed algorithm reduces the power consumptions dramatically.

This paper aims to propose an alternative strategy for preparing, recovering and conserving cultural built heritage (CBH) in the context of natural disasters. It presents the idea that disaster preparedness is integral to CBH protection and conservation.

Building upon a review of existing scholarship on CBH, resilience and disaster management, a conceptual model is proposed to assist key stakeholders preparing for the recovery of CBH after natural disasters. It is argued that the protection and recovery of CBH in the wake of natural disasters require a holistic approach and that the theoretical framework of resilience thinking can support such an approach.

The paper discusses how the process of adaptive cycles has a role to play in the development of a holistic understanding of the conservation process. It proposes an adaptive cycle model that is supported by four critical factors: reordering, conserving, shifting and transforming.

Through exploration of systems thinking and resilience theory, the research presented in this paper explores a new approach to the conceptualisation of CBH. The paper presents the first stage of a research project that aims to develop strategies that can support the protection and recovery of CBH in the wake of natural disasters. The proposed model represents a holistic approach for reconceptualising CBH and may, as such, have potential implications that extend from the field of post-disaster recovery into the domain of CBH conservation and protection.

This paper presents some linear adaptive non‐nested multigrid methods which are applied to linear elastic problems discretized with triangular and tetrahedral finite elements using unstructured and Delaunay mesh generators. The Zienkiewicz‐Zhu error estimator and a h‐refinement procedure are used to obtain the non‐nested meshes used by the multigrid methods. We solve problems with a specified percentage error in the energy norm using the optimal performance of multigrid methods.

The Hermite collocation method of discretization can be used to determine highly accurate solutions to the steady‐state one‐dimensional convection‐diffusion equation (which can be used to model the transport of contaminants dissolved in groundwater). This accuracy is dependent upon sufficient refinement of the finite‐element mesh as well as applying upstream or downstream weighting to the convective term through the determination of collocation locations which meet specified constraints. Owing to an increase in computational intensity of the application of the method of collocation associated with increases in the mesh refinement, minimal mesh refinement is sought. Very often this optimization problem is the one where the feasible region is not connected and as such requires a specialized optimization search technique. This paper aims to focus on this method.

An original hybrid method that utilizes a specialized adaptive genetic algorithm followed by a hill‐climbing approach is used to search for the optimal mesh refinement for a number of models differentiated by their velocity fields. The adaptive genetic algorithm is used to determine a mesh refinement that is close to a locally optimal mesh refinement. Following the adaptive genetic algorithm, a hill‐climbing approach is used to determine a local optimal feasible mesh refinement.

In all cases the optimal mesh refinements determined with this hybrid method are equally optimal to, or a significant improvement over, mesh refinements determined through direct search methods.

Further extensions of this work could include the application of the mesh refinement technique presented in this paper to non‐steady‐state problems with time‐dependent coefficients with multi‐dimensional velocity fields.

The present work applies an original hybrid optimization technique to obtain highly accurate solutions using the method of Hermite collocation with minimal mesh refinement.

To explain how an innovative practice-based approach to teacher preparation called the Adaptive Cycles of Teaching utilizes video reflection as part of multiple cycles of teaching across high impact literacy practices.

The faculty research team adopted a design-based research approach to develop and test the ACT model through iterations of design, implementation, analysis, and redesign. The chapter outlines the curriculum and findings from the initial iteration of design.

Teacher candidates experiencing the ACT model developed a strong knowledge of core literacy practices and were able to implement them with children. They continued to need additional scaffolding with respect to the quality of their instructional discourse and the gradual release of responsibility.

Continued research on the ACT model will allow us to refine the ways in which video use can enable preservice teachers to reflect and analyze their teaching and learning.

The paper aims to provide methodological support for hybrid project management, in which the discipline of predictive methodologies combines with the flexibility of adaptive ones. Specifically, the paper explores the extent complexity and volatility dimensions of organisational problems inform choices of PM methodologies both theoretically and in current practice, as a first step towards better methodological support for hybridisation.

The paper takes a mixed method approach, including both secondary research and primary research with practitioners. Primary research consists of a small scale survey (n = 31) followed by semi-structured interviews, with findings triangulated against secondary evidence.

The paper provides empirical insights on how complexity and volatility of organisational problems can inform hybrid project management practices. Specifically, it suggests a mapping between volatility and complexity dimensions and predictive and adaptive risk controls as a first step towards the systematisation of hybrid combinations in projects.

Due to the small participant sample, the research results may lack generalisability.

The paper includes implications for the development of methodological support for setting up hybrid projects in practice.

The paper addresses a gap acknowledged both in the literature and by practitioners.

Resilience in agri-food supply chains (AFSCs) is an area of significant importance due to growing supply chain volatility. While the majority of research exploring supply chain resilience has originated from a supply chain management perspective, many other disciplines (such as environmental systems science and the social sciences) have also explored the topic. As complex social, economic and environmental constructs, the priority of resilience in AFSCs goes far beyond the company specific focus of supply chain management works and would conceivably benefit from including more diverse academic disciplines. However, this is hindered by inconsistencies in terminology and the conceptual components of resilience across different disciplines. The purpose of this study is to use a systematic literature review to identify which multidisciplinary aspects of resilience are applicable to AFSCs and to generate a novel AFSC resilience framework.

This paper uses a structured and multidisciplinary review of 137 articles in the resilience literature followed by critical analysis and synthesis of findings to generate new knowledge in the form of a novel AFSC resilience framework.

Findings indicate that the complexity of AFSCs and subsequent exposure to almost constant external interference means that disruptions cannot be seen as a one-off event; thus, resilience must concern the ability to not only maintain core function but also adapt to changing conditions.

A number of resilience elements can be used to enhance resilience, but their selection and implementation must be carefully matched to relevant phases of disruption and assessed on their broader supply chain impacts. In particular, the focus must be on overall impact on the ability of the supply chain as a whole to provide food security rather than to boost individual company performance.

The research novelty lies in the utilisation of wider understandings of resilience from various research fields to propose a rigorous and food-specific resilience framework with end consumer food security as its main focus.

The purpose of this paper is to develop an original six-phase model describing entrepreneurial learning in the transition of place-based enterprises toward a sustainable exploitation of natural common resources (commons).

The six-phase model proposed by this study explains the learning processes involving place-based enterprises through two important existing theories: adaptive co-management and Lachmann’s evolutionary, embedded theory of entrepreneurship. The proposed model integrates these two theories on the basis of a longitudinal case study on the fishing enterprises in an Italian marine protected area (MPA).

In the case study, the success factors identified by the adaptive co-management literature proved important in enabling an embedded entrepreneurial learning process consistent with Lachmann’s view. The case analysis allowed the authors to cluster these learning processes around six phases. Further, even if traditional fishing is not knowledge-intensive, this case shows the transition to a sustainable business model required intense efforts of educated institutional work and scientific research. Interestingly, the key learning processes were enabled by the emergence of a larger, networked social entity (a network form of organization) including the community of fishermen, the MPA management and a network of scientists studying the marine area ecosystem.

This study is explorative and relies on a single case study. Despite this limitation, it opens up new research paths in the fields of entrepreneurship, institutional work, network organizations and adaptive management of the commons.

This study is strongly interdisciplinary; it proposes an original model based on a theoretical view that is highly innovative for organization and management studies; and addresses a relevant but overlooked issue with important societal implications.

Historically black colleges and universities (HBCUs) are facing changes in the twenty-first century driven in part by a change in the societal demands on the educational system. Organizational adaptation to changing environment is discussed in the business and management literature, which now includes organizational adaptation in higher education (Brown, 2012; Cameron, 1984; Drew, 2010; Rogers, 2013; Sporn, 1999). The focus of this research is organizational adaptation in four HBCUs. Although HBCUs have long histories and just over 100 of them currently exist, the researchers have focused on four of these institutions and the factors that have enabled them to adapt to change. These changes are forcing colleges and universities to reexamine their organizational strategy to adapt to changes in the educational environment.

The purpose of this research was to examine enabling factors of four HBCUs to adapt to the changing environment. Drawing from historical and archival material, the researcher examined four HBCUs – Bluefield State College, Bowie State University, Hampton University, and Spelman College, and how each adapted to the changing environment. A multiple case study designed was selected to understand the adaptation phenomenon within and across institutions. A review of the literature on organizational adaptation and change, along with a case study analysis of four HBCUs identified the factors that enhanced their adaptive strategies and ability to adapt successfully to the changing environment. The four factors were leadership, culture, structure, and business strategy that influenced each university's ability to adapt successfully to change. Chaffee's (1984, 1985) adaptive and interpretative strategy models and Miles and Snow's (1978) adaptive cycle provided the lens to examine adaptation in these institutions. In this study, leadership, culture, structure, and business strategy were observed as factors that enhanced each school's adaptation to the changing environment.

Chaffee's (1984, 1985) adaptation models and Miles and Snow's (1978) theoretical framework were employed to evaluate adaptation in these organizations. Each of these institutions faced organizational challenges that required an adaptive response. The quality of the adaptive response enabled each organization to adapt to its changing environment, and these changes involved long-range planning for these organizations and not merely short-term gains. The adaptive responses were hinged on the presence of four factors: leadership, culture, structure, and business strategy. Leadership and culture were the most prominent factors that supported organizational change.

This paper aims to speed up finite element analyses of structures with a highly nonlinear material response subjected to many loading cycles.

An approach where large time increments are taken in an adaptive fashion is presented. The size of the large time increments typically spans several loading cycles and is based on Taylor series expansions of the response combined with error control.

The suggested adaptive algorithm is simple compared with some well‐known alternatives in the literature. It also has the inherent convergence property that it reduces to the classical time incrementation in the case where the estimated error is too large.

The algorithm is suitable for (restricted to) a special class of problems where the material response versus a representative time sequence are smooth curves. The simplicity of the method results in a robust algorithm.

Similar algorithms have been presented earlier in the literature but the present work introduces some enhancements, e.g. accounting for general internal variables also in the error estimate. In addition, the present work considers a more complex constitutive model compared with earlier work within the research field.