Fostering active network management through SMEs’practises

Managing the electricity network through ‘smart grid’ systems is a key strategy to address challenges of energy security, low carbon transitions and the replacement of ageing infrastructure networks in the UK. Small and medium enterprises (SMEs) have a significant role in shaping patterns of energy consumption. Understanding how their activities interrelate with changes in electricity systems is critical for active network management. A significant challenge for the transformation of electricity systems involves comprehending the complexity that stems from the variety of commercial activities and diversity of social and organizational practises among SMEs that interact with material infrastructures. We engage with SMEs to consider how smart grid interventions ‘fit’ into everyday operational activities. Drawing on analysis of empirical data on electricity use, smart metre data, surveys, interviews and ‘energy tours’ with SMEs to understand lighting, space heating and cooling, refrigeration and IT use, this paper argues for experimenting with the use of practise theory as a framework for bringing together technical and social aspects of energy use in SMEs. This approach reveals that material circumstances and temporal factors shape current energy demand among SMEs, with ‘connectedness’ an emergent factor

A Survey of Resource Management Challenges in Multi-cloud Environment: Taxonomy and Empirical Analysis

Cloud computing has seen a great deal of interest by researchers and industrial firms since its first coined. Different perspectives and research problems, such as energy efficiency, security and threats, to name but a few, have been dealt with and addressed from cloud computing perspective. However, cloud computing environment still encounters a major challenge of how to allocate and manage computational resources efficiently. Furthermore, due to the different architectures and cloud computing networks and models used (i.e., federated clouds, VM migrations, cloud brokerage), the complexity of resource management in the cloud has been increased dramatically. Cloud providers and service consumers have the cloud brokers working as the intermediaries between them, and the confusion among the cloud computing parties (consumers, brokers, data centres and service providers) on who is responsible for managing the request of cloud resources is a key issue. In a traditional scenario, upon renting the various cloud resources from the providers, the cloud brokers engage in subletting and managing these resources to the service consumers. However, providers’ usually deal with many brokers, and vice versa, and any dispute of any kind between the providers and the brokers will lead to service unavailability, in which the consumer is the only victim. Therefore, managing cloud resources and services still needs a lot of attention and effort. This paper expresses the survey on the systems of the cloud brokerage resource management issues in multi-cloud environments

Developments in the Safety Science Domain and in Safety Management From the 1970s Till the 1979 Near Disaster at Three Mile Island

Objective: What has been the influence of general management schools and safety research into causes of accidents and disasters on managing safety from 1970 till 1979? Method: The study was limited to original articles and documents, written in English or Dutch from the period under concern. For the Netherlands, the professional journal De Veiligheid (Safety) has been consulted. Results and conclusions: Dominant management approaches started with 1) the classical management starting from the 19th century, with scientific management from the start of the 20st century as a main component. During the interwar period 2) behavioural management started, based on behaviourism, followed by 3) quantitative management from the Second World War onwards. After the war 4) modern management became important. A company was seen as an open system, interacting with an external environment with external stakeholders. These schools management were not exclusive, but have existed in the period together. Early 20th century, the U.S. 'Safety First' movement was the starting point of this knowledge development on managing safety, with cost reduction and production efficiency as key drivers. Psychological models and metaphors explained accidents from ‘unsafe acts’. And safety was managed with training and selection of reckless workers, all in line with scientific management. Supported by behavioural management, this approach remained dominant for many years, even long after World War II. Influenced by quantitative management, potential and actual disasters after the war led to two approaches; loss prevention (up-scaling process industry) and reliability engineering (inherently dangerous processes in the aerospace and nuclear industries). The distinction between process safety and occupational safety became clear after the war, and the two developed into relatively independent domains. In occupational safety in the 1970s human errors thought to be symptoms of mismanagement. The term ‘safety management’ was introduced in scientific safety literature as well as concepts as loose, and tightly coupled processes, organizational culture, incubation of a disaster and mechanisms blinding organizations for portents of disaster scenarios. Loss prevention remained technically oriented. Till 1979 there was no clear relation with safety management. Reliability engineering, based on systems theory did have that relation with the MORT technique as a management audit. The Netherlands mainly followed Anglo-Saxon developments. Late 1970s, following international safety symposia in The Hague and Delft, independent research started in The Netherland

Advances in Rule-based Modeling: Compartments, Energy, and Hybrid Simulation, with Application to Sepsis and Cell Signaling

Biological systems are commonly modeled as reaction networks, which describe the system at the resolution of biochemical species. Cellular systems, however, are governed by events at a finer scale: local interactions among macromolecular domains. The multi-domain structure of macromolecules, combined with the local nature of interactions, can lead to a combinatorial explosion that pushes reaction network methods to their limits. As an alternative, rule-based models (RBMs) describe the domain-based structure and local interactions found in biological systems. Molecular complexes are represented by graphs: functional domains as vertices, macromolecules as groupings of vertices, and molecular bonding as edges. Reaction rules, which describe classes of reactions, govern local modifications to molecular graphs, such as binding, post-translational modification, and degradation. RBMs can be transformed to equivalent reaction networks and simulated by differential or stochastic methods, or simulated directly with a network-free approach that avoids the problem of combinatorial complexity. Although RBMs and network-free methods resolve many problems in systems modeling, challenges remain. I address three challenges here: (i) managing model complexity due to cooperative interactions, (ii) representing biochemical systems in the compartmental setting of cells and organisms, and (iii) reducing the memory burden of large-scale network-free simulations. First, I present a general theory of energy-based modeling within the BioNetGen framework. Free energy is computed under a pattern-based formalism, and contextual variations within reaction classes are enumerated automatically. Next, I extend the BioNetGen language to permit description of compartmentalized biochemical systems, with treatment of volumes, surfaces and transport. Finally, a hybrid particle/population method is developed to reduce memory requirements of network-free simulations. All methods are implemented and available as part of BioNetGen. The remainder of this work presents an application to sepsis and inflammation. A multi-organ model of peritoneal infection and systemic inflammation is constructed and calibrated to experiment. Extra-corporeal blood purification, a potential treatment for sepsis, is explored in silico. Model simulations demonstrate that removal of blood cytokines and chemokines is a sufficient mechanism for improved survival in sepsis. However, differences between model predictions and the latest experimental data suggest directions for further exploration