Functional Complexity: The source of value in biodiversity.

Biodiversity may be seen as a scientific measure of the complexity of a biological system, implying an information basis. Complexity cannot be directly valued, so economists have tried to define the services it provides, though often just valuing the services of 'key' species. Here we provide a new definition of biodiversity as a measure of functional information, arguing that complexity embodies meaningful information as Gregory Bateson defined it. We argue that functional information content (FIC) is the potentially valuable component of total (algorithmic) information content (AIC), as it alone determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. Establishing substitutability is an essential foundation for valuation. From it, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and the production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science. © 2012 Elsevier B.V.

Optimizing the balance between false positive and false negative error probabilities of confirmatory methods for the detection of veterinary drug residues

GC-MS data on veterinary drug residues in bovine urine are used for controlling the illegal practice of fattening cattle. According to current detection criteria, peak patterns of preferably four ions should agree within 10 or 20% from a corresponding standard pattern. These criteria are rigid, rather arbitrary and do not match daily practice. A new model, based on multivariate modeling of log peak abundance ratios, provides a theoretical basis for the identification of analytes and optimizes the balance between the avoidance of false positives and false negatives. The performance of the model is demonstrated on data provided by five laboratories, each supplying GC-MS measurements on the detection of clenbuterol, dienestrol and 19 beta-nortestosterone in urine. The proposed model shows a better performance than confirmation by using the current criteria and provides a statistical basis for inspection criteria in terms of error probabilities.

Irresponsible Lending?: A Case Study of a U.K. Credit Industry Reform Initiative

There are major concerns about the level of personal borrowing, particularly sourced from credit cards. This paper charts the progress of an initiative to create a Responsible Lending Index (RLI) for the credit industry. The RLI proposed to voluntarily benchmark lending standards and promote best practice within the credit industry by involving suppliers of credit, customer representatives and regulators. However, despite initial support from some banks, consumer bodies and the Chair of the Treasury Select Committee, it failed to gain sufficient support from financial institutions in its original format. The primary reasons for this were related to the complexity of building such a robust index and the banks trade body’s fear of exposing its members to public scrutiny. A revised alternative, the Responsible Lending Initiative, was proposed which took into account these concerns. However, the Association of Payment Clearing Service (APACS), the trade body of the credit industry, then effectively destroyed the proposal. This article describes an attempt to address the challenges in the credit card industry with the initiation of the RLI, reflected in stakeholder discourse and in the context of a wider concern expressed by the involved stakeholders in terms of the need for greater responsibility in the banking industry’s lending practices.

Thermal conductivities of ionic liquids over the temperature range from 293 K to 353 K

The thermal conductivities of 11 ionic liquids were determined, over the temperature range from 293 K to 353 K, at atmospheric pressure, using an apparatus based on the transient hot-wire method. For each of the ionic liquids studied, the thermal conductivities were found to be between (0.1 and 0.2) W.m(-1).K-1, with a slight decrease observed on increasing temperature. The uncertainty is estimated to be less than +/- 0.002 W.m(-1).K-1. In all cases, a linear equation was found to give a good fit to the data. The effects of water content and chloride content on the thermal conductivities of some of the ionic liquids were investigated. In each case, the thermal conductivities of the water + ionic liquid and chloride + ionic liquid binary mixtures were found to be less than the weighted average of the pure component thermal conductivities. This effect was adequately modeled using the Jamieson correlation. Chloride contamination at typical postsynthesis levels was found to have no significant effect on the thermal conductivities of the ionic liquid studied.

How Prepared are UK Medical Graduates for Practice? Final report from a programme of research commissioned by the General Medical Council

This programme of research aimed to understand the extent to which current UK medical graduates are prepared for practice. Commissioned by the General Medical Council, we conducted: (1) A Rapid Review of the literature between 2009 and 2013; (2) narrative interviews with a range of stakeholders; and (3) longitudinal audio-diaries with Foundation Year 1 doctors. The Rapid Review (RR) resulted in data from 81 manuscripts being extracted and mapped against a coding framework (including outcomes from Tomorrow's Doctors (2009) (TD09)). A narrative synthesis of the data was undertaken. Narrative interviews were conducted with 185 participants from 8 stakeholder groups: F1 trainees, newly registered trainee doctors, clinical educators, undergraduate and postgraduate deans and foundation programme directors, other healthcare professionals, employers, policy and government and patient and public representatives. Longitudinal audio-diaries were recorded by 26 F1 trainees over 4 months. The data were analysed thematically and mapped against TD09. Together these data shed light onto how preparedness for practice is conceptualised, measured, how prepared UK medical graduates are for practice, the effectiveness of transition interventions and the currently debated issue of bringing full registration forward to align with medical students’ graduation. Preparedness for practice was conceptualised as both a long- and short-term venture that included personal readiness as well as knowledge, skills and attitudes. It has mainly been researched using self-report measures of generalised incidents that have been shown to be problematic. In terms of transition interventions: assistantships were found to be valuable and efficacious for proactive students as team members, shadowing is effective when undertaken close to employment/setting of F1 post and induction is generally effective but of inconsistent quality. The August transition was highlighted in our interview and audio-diary data where F1s felt unprepared, particularly for the step-change in responsibility, workload, degree of multitasking and understanding where to go for help. Evidence of preparedness for specific tasks, skills and knowledge was contradictory: trainees are well prepared for some practical procedures but not others, reasonably well prepared for history taking and full physical examinations, but mostly unprepared for adopting an holistic understanding of the patient, involving patients in their care, safe and legal prescribing, diagnosing and managing complex clinical conditions and providing immediate care in medical emergencies. Evidence for preparedness for interactional and interpersonal aspects of practice was inconsistent with some studies in the RR suggesting graduates were prepared for team working and communicating with colleagues and patients, but other studies contradicting this. Interview and audio-diary data highlights concerns around F1s preparedness for communicating with angry or upset patients and relatives, breaking bad news, communicating with the wider team (including interprofessionally) and handover communication. There was some evidence in the RR to suggest that graduates were unprepared for dealing with error and safety incidents and lack an understanding of how the clinical environment works. Interview and audio-diary data backs this up, adding that F1s are also unprepared for understanding financial aspects of healthcare. In terms of being personally prepared, RR, interview and audio diary evidence is mixed around graduates’ preparedness for identifying their own limitations, but all data points to graduates’ difficulties in the domain of time management. In terms of personal and situational demographic factors, the RR found that gender did not typically predict perceptions of preparedness, but graduates from more recent cohorts, graduate entry students, graduates from problem based learning courses, UK educated graduates and graduates with an integrated degree reported feeling better prepared. The longitudinal audio-diaries provided insights into the preparedness journey for F1s. There seems to be a general development in the direction of trainees feeling more confident and competent as they gain more experience. However, these developments were not necessarily linear as challenging circumstances (e.g. new specialty, new colleagues, lack of staffing) sometimes made them feel unprepared for situations where they had previously indicated preparedness.

Search for the Return of Activity in Active Asteroid 176P/LINEAR

We present the results of a search for the reactivation of active asteroid 176P/LINEAR during its 2011 perihelion passage using deep optical observations obtained before, during, and after that perihelion passage. Deep composite images of 176P constructed from data obtained between 2011 June and 2011 December show no visible signs of activity, while photometric measurements of the object during this period also show no significant brightness enhancements similar to that observed for 176P between 2005 November and 2005 December when it was previously observed to be active. An azimuthal search for dust emission likewise reveals no evidence for directed emission (i.e., a tail, as was previously observed for 176P), while a one-dimensional surface brightness profile analysis shows no indication of a spherically symmetric coma at any time in 2011. We conclude that 176P did not in fact exhibit activity in 2011, at least not on the level on which it exhibited activity in 2005, and suggest that this could be due to the devolatization or mantling of the active site responsible for its activity in 2005.

Impact of offshore wind power forecast error in a carbon constraint electricity market

This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

System level DSP synthesis using voltage overscaling, unequal error protection & adaptive quality tuning

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration system level interactions and ensuring that under any change of operating conditions only the "lesscrucial" computations, that contribute less to block/system output quality, are affected. The design methodology applied to a DCT/IDCT system shows large power benefits (up to 69%) at reasonable image quality while tolerating errors induced by varying operating conditions (VOS, process variations, channel noise). Interestingly, the proposed IDCT scheme conceals channel noise at scaled voltages. ©2009 IEEE.

An optimal algorithm for low power multiplierless FIR filter design using chebychev criterion

In this paper, we propose a novel finite impulse response (FIR) filter design methodology that reduces the number of operations with a motivation to reduce power consumption and enhance performance. The novelty of our approach lies in the generation of filter coefficients such that they conform to a given low-power architecture, while meeting the given filter specifications. The proposed algorithm is formulated as a mixed integer linear programming problem that minimizes chebychev error and synthesizes coefficients which consist of pre-specified alphabets. The new modified coefficients can be used for low-power VLSI implementation of vector scaling operations such as FIR filtering using computation sharing multiplier (CSHM). Simulations in 0.25um technology show that CSHM FIR filter architecture can result in 55% power and 34% speed improvement compared to carry save multiplier (CSAM) based filters.