Evaluation of the SSERC Primary Cluster Programme in Science and Technology: Final Report

No abstract available

Integrating Thermodynamics and Biology for Sustainable Product Lifecycle Design

The linkage between raw resources consumption and economic growth through product manufacture and disposal is creating an untenable pressure on the planet’s natural systems; therefore understanding and embracing the mechanics of the biology and physics of our context could lead to novel approaches in the design of human-built systems/products. Designers are, by active association, responsible for that pressure and much of the impact can be traced back to the early stages of the design process. For designers and engineers the main constraint is accessibility to knowledge of multiple and complex factors in easily digestible form when starting a project. Added to this is the possibility to transcend the realm of products and explore creative solutions throughout the entire life cycle, giving designers the opportunity to propose entire new business models and systems. This paper exposes the search for an intuitive soft modeling tool that considers some of these factors and inspires the innovation of business and systems innovation from a biophysical perspective. The aim of this tool is to enable the exploration of these factors in a playful intuitive way and relate these outcomes to the design of a business model operating within the principles of trophic levels. The first key question to the development of this approach has been: how does it work in nature? Organisms search for their food in other organisms and at the same time are the food of others; biomass and energy are transferred from one level to another, losses occur, higher qualities of energy are created and all is maintained in continuous cycles. The linear human production of goods can be rethought by taking into account this basic principle of thermodynamics and although this is not a technological problem, the relevant constrains need to be integrated for this approach to be feasible. These are from an economics origin: how to achieve a healthy business from a non-linear process? It is proposed that an analogy between natural and human systems: autotrophs = manufacturing, heterotrophs = distributors and consumers, their concentration and size, their possible combinations and their eventual business interpretations, is referred to as Trophic Economics. The envisioned tool will combine the exploration of the complex factors involved in the lifecycle of a product with the suggested Trophic Economics models. The outcome could be sketches of the possible boundaries and structures of new business and products, to be resolved later on the drawing board. In order to measure and keep track of the most relevant decisions, a designer must embrace tools like emergy accounting, MIPS and MI (Wuppertal Institute, 2002) used in related combination, plus indexes of CO2 emissions and relevant economic, social-demographic and ecosystems information about the countries involved in any give proposition of manufacture and use

Measuring the Impact of the ‘Two Hours/Two Periods of Quality Physical Education’ Programme

No abstract available

Production of case studies of the delivery of skills for learning, skills for life and skills for work

This report summarises the main themes to emerge from a study to highlight good practice in delivering practical, applied or vocational learning provision for all pupils

Component Composition in Business and System Modelling

Bespoke development of large business systems can be couched in terms of the composition of components, which are, put simply, chunks of development work. Design, mapping a specification to an implementation, can also be expressed in terms of components: a refinement comprising an abstract component, a concrete component and a mapping between them. Similarly, system extension is the composition of an existing component, the legacy system, with a new component, the extension. This paper overviews work being done on a UK EPSRC funded research project formulating and formalizing techniques for describing, composing and performing integrity checks on components. Although the paper focuses on the specification and development of information systems, the techniques are equally applicable to the modeling and re-engineering of businesses, where no computer system may be involved

A Structural Study of Some (h6-Arene)ML2, First Row, Group VIII, Transition Metal Complexes and Their Derivatives

The structures of five organonickel compounds were determined using x-ray diffraction techniques. This study was conducted to ascertain the relationships between the compound\u27s structures, bonding, and chemical properties. The first structural evidence for discrete complexes containing Ni-SiX3 bonds is (h6-mesitylene)Ni(SiCl3)2 and presented. The compounds (h6-toluene)Ni(SiF3)2, crystallize in space group P21/c with Z = 2. The lattice constants at 23° C are: a = 9.056(2), b = 14.426(1), c = 13. 3 0 3 ( 2) ~, {J = 10 0. 6 9 ( 1 )0 , and a = 11. 3 5 5 ( 3) , b = 11.268(4), c = 14.326(8)~, and {J = 140.97(8)0 for the compounds, respectively. Both structures exhibit short Ni-Si bond distances and planar arenes, with other bond parameters similarly indicating significant Ni-to-SiX3 pi back-bonding. The SiF3 ligands are shown to be much better pi-acids than the SiCl3 groups. The most striking evidence for this is the unprecidented short Ni-SiF3 bond distance of 2.154(3)~ and the predictably short nickel to arene distance of 1.643(3)~ in (h6-toluene)Ni(SiF3)2. The analogous Ni-SiCl3 bond distance in (h6-mesitylene)Ni(SiCl3)2 is 2.194(1)~ while the nickel to arene-plane distance is 1.697(1)~. Analysis of (C0)3Ni(SiCl3)2 revealed a long axial Ni-Si bond distance of 2.286(3)~ in the trigonal bipyramidal complex. The compound crystallizes in space group P21/c with Z = 2, with lattice constants at 25°C of: a= 9.709(8), b = 22.65(2), c = 6.731(5)~, and {J = 75.76(5)0 • The compound (H9C4S)2Ni(C6F5)2, crystallizes in space group P21/c with z = 2, with the Ni residing on a crystallographic center of inversion. The lattice constants at 23°C are: a= 10.698(3), b = 11.246(3), c = 9.561(2)~, and {J = 106.78(2). The Ni-C6F5 bond distance of 2.196(3)A indicates a reasonably strong bonding interaction without any appreciable Ni-to-C6F5 pi back-bonding. The compound [(h5-C5H5)Ni(C6F5)2] [(H5C2)4N] crystallizes with two formula units per unit cell in space group Pl, with lattice constants at 23° C of: a = 14.306(2), b = 0.930\u3c1\u3e, c = l0.599(2\u3eA, a = 96.s1, and ry = 90.61(1)0 • The pi-Cp has a significant non-planar deformation attributable to electronic factors.

Microbial carbon use efficiency: accounting for population, community, and ecosystem-scale controls over the fate of metabolized organic matter

Microbial carbon use efficiency (CUE) is a critical regulator of soil organic matter dynamics and terrestrial carbon fluxes, with strong implications for soil biogeochemistry models. While ecologists increasingly appreciate the importance of CUE, its core concepts remain ambiguous: terminology is inconsistent and confusing, methods capture variable temporal and spatial scales, and the significance of many fundamental drivers remains inconclusive. Here we outline the processes underlying microbial efficiency and propose a conceptual framework that structures the definition of CUE according to increasingly broad temporal and spatial drivers where (1) CUEP reflects population-scale carbon use efficiency of microbes governed by species-specific metabolic and thermodynamic constraints, (2) CUEC defines community-scale microbial efficiency as gross biomass production per unit substrate taken up over short time scales, largely excluding recycling of microbial necromass and exudates, and (3) CUEE reflects the ecosystem-scale efficiency of net microbial biomass production (growth) per unit substrate taken up as iterative breakdown and recycling of microbial products occurs. CUEE integrates all internal and extracellular constraints on CUE and hence embodies an ecosystem perspective that fully captures all drivers of microbial biomass synthesis and decay. These three definitions are distinct yet complementary, capturing the capacity for carbon storage in microbial biomass across different ecological scales. By unifying the existing concepts and terminology underlying microbial efficiency, our framework enhances data interpretation and theoretical advances