An efficient scheme for the evaluation of coding performance of high speed links incorporating joint error behaviour based on Monte Carlo Method

While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting

Forms of participatory democracy: an analytical framework based on the experiences of Bolivia, brazil and Colombia

Based on the experiences of Colombia, Brazil and Bolivia, the paper proposes a general analytical framework for participatory mechanisms. The analysis is oriented to detect the incentives in each system and theethics and behavior sustaining them. It investigates about the sustainability of participatory democracy, in the face of tensions with representative democracy. The article presents a theoretical framework built from theseexperiences of institutional design and political practice, and confronts it against the theoretical conceptualizationsof participatory democracy in Bobbio, Sartori, Elster and Nino, among others. In this context, different waysin which those schemes can be inserted in the political systems become apparent, along with the variables thatresult from combining elements of direct, representative and participatory democracy”

Adaptive project planning and management based on best practices - COBRA system

Planning a project with proper considerations of all necessary factors and managing a project to ensure its successful implementation will face a lot of challenges. Initial stage in planning a project for bidding a project is costly, time consuming and usually with poor accuracy on cost and effort predictions. On the other hand, detailed information for previous projects may be buried in piles of archived documents which can be increasingly difficult to learn from the previous experiences. Project portfolio has been brought into this field aiming to improve the information sharing and management among different projects. However, the amount of information that could be shared is still limited to generic information. This paper, we report a recently developed software system COBRA to automatically generate a project plan with effort estimation of time and cost based on data collected from previous completed projects. To maximise the data sharing and management among different projects, we proposed a method of using product based planning from PRINCE2 methodology. (Automated Project Information Sharing and Management System -�COBRA) Keywords: project management, product based planning, best practice, PRINCE2

An evaluation of a Bayesian method of dose escalation based on bivariate binary responses

Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.

Phylogeny of Pelargonium (Geraniaceae) based on DNA sequences from three genomes

Phylogenetic hypotheses for the largely South African genus Pelargonium L'Hér. (Geraniaceae) were derived based on DNA sequence data from nuclear, chloroplast and mitochondrial encoded regions. The datasets were unequally represented and comprised cpDNA trnL-F sequences for 152 taxa, nrDNA ITS sequences for 55 taxa, and mtDNA nad1 b/c exons for 51 taxa. Phylogenetic hypotheses derived from the separate three datasets were overall congruent. A single hypothesis synthesising the information in the three datasets was constructed following a total evidence approach and implementing dataset specific stepmatrices in order to correct for substitution biases. Pelargonium was found to consist of five main clades, some with contrasting evolutionary patterns with respect to biogeographic distributions, dispersal capacity, pollination biology and karyological diversification. The five main clades are structured in two (subgeneric) clades that correlate with chromosome size. One of these clades includes a "winter rainfall clade" containing more than 70% of all currently described Pelargonium species, and all restricted to the South African Cape winter rainfall region. Apart from (woody) shrubs and small herbaceous rosette subshrubs, this clade comprises a large "xerophytic" clade including geophytes, stem and leaf succulents, harbouring in total almost half of the genus. This clade is considered to be the result of in situ proliferation, possibly in response to late-Miocene and Pliocene aridification events. Nested within it is a radiation comprising c. 80 species from the geophytic Pelargonium section Hoarea, all characterised by the possession of (a series of) tunicate tubers.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

e-learning in project management using simulation models: a case study based on the replication of an experiment

Current e-learning systems are increasing their importance in higher education. However, the state of the art of e-learning applications, besides the state of the practice, does not achieve the level of interactivity that current learning theories advocate. In this paper, the possibility of enhancing e-learning systems to achieve deep learning has been studied by replicating an experiment in which students had to learn basic software engineering principles. One group learned these principles using a static approach, while the other group learned the same principles using a system-dynamics-based approach, which provided interactivity and feedback. The results show that, quantitatively, the latter group achieved a better understanding of the principles; furthermore, qualitatively, they enjoyed the learning experience

Redox-active polymers based on nonbridged metal−metal bonds. Electrochemical formation of [Os(bpy)(CO)(L)]n(bpy = 2,2‘-bipyridine; L = CO, MeCN) and of their reduced forms: a spectroelectrochemical study

IR, UV-vis, and EPR spectroelectrochemistry at variable temperatures and in different solvents were applied to investigate in situ the formation of electroactive molecular chains with a nonbridged Os-Os backbone, in particular, the polymer [Os-0(bpy)(CO)(2)](n), (bpy = 2,2'-bipyridine), from a mononuclear Os(II) carbonyl precursor, [Os-II(bpy)(CO)(2)Cl-2]. The one-electron-reduced form, [Os-II(bpy(.-))(CO)(2)Cl-2](-), has been characterized spectroscopically at low temperatures. This radical anion is the key intermediate in the electrochemical propagation process responsible for the metal-metal bond formation. Unambiguous spectroscopic evidence has been gained also for the formation of [{Os-0(bpy(.-))(CO)(2)}(-)](n), the electron-rich electrocatalyst of CO2 reduction. The polymer species are fairly well soluble in butyronitrile, which is important for their potential utilization in nanoscience, for example, as conducting molecular wires. We have also shown that complete solubility is accomplished for the monocarbonyl-acetonitrile derivative of the polymer, [Os-0(bpy)(CO)(MeCN)(2)Cl](n).

Evidence-based psychological therapies: from bench to bedside

Patients with mental health difficulties do not always receive appropriate and recommended psychological treatment for their difficulties, and clinicians are not always appropriately trained to deliver them. This paper considers why this might be the case and provides an overview of the Charlie Waller Institute, a not-for-profit organisation funded by the NHS, University of Reading, and the Charlie Waller Memorial Trust. The Institute seeks to address this problem by training clinicians in wide variety of evidence-based therapies and assessing the impact of this training on clinician knowledge and skill.

Policy ‘framing’ and evidence-based planning: ‘epistemic communities’ in the multi-jurisdictional environment of an enlarged Europe

The following paper builds on ongoing discussions over the spatial and territorial turns in planning, as it relates to the dynamics of evidence-based planning and knowledge production in the policy process. It brings this knowledge perspective to the organizational and institutional dynamics of transformational challenges implicit in the recent enlargement of the EU. Thus it explores the development of new spatial ideas and planning approaches, and their potential to shape or ‘frame’ spatial policy through the formulation of new institutional arrangements and the de-institutionalization of others. That is, how knowledge is created, contested, mobilized and controlled across governance architectures or territorial knowledge channels. In so doing, the paper elaborates and discusses a theoretical framework through which the interplay of knowledge and policymaking can be conceptualized and analyzed.

Identifying key knowledge needs for evidence-based conservation of wild insect pollinators: a collaborative cross-sectoral exercise

In response to evidence of insect pollinator declines, organisations in many sectors, including the food and farming industry, are investing in pollinator conservation. They are keen to ensure that their efforts use the best available science. We convened a group of 32 ‘conservation practitioners’ with an active interest in pollinators and 16 insect pollinator scientists. The conservation practitioners include representatives from UK industry (including retail), environmental non-government organisations and nature conservation agencies. We collaboratively developed a long list of 246 knowledge needs relating to conservation of wild insect pollinators in the UK. We refined and selected the most important knowledge needs, through a three-stage process of voting and scoring, including discussions of each need at a workshop. We present the top 35 knowledge needs as scored by conservation practitioners or scientists. We find general agreement in priorities identified by these two groups. The priority knowledge needs will structure ongoing work to make science accessible to practitioners, and help to guide future science policy and funding. Understanding the economic benefits of crop pollination, basic pollinator ecology and impacts of pesticides on wild pollinators emerge strongly as priorities, as well as a need to monitor floral resources in the landscape.

Punishing the foreigner: implicit discrimination in the Premier League based on oppositional identity

We present the first empirical study to reveal the presence of implicit discrimination in a non-experimental setting. By using a large dataset of in-match data in the English Premier League, we show that white referees award significantly more yellow cards against non-white players of oppositional identity. We argue that this is the result of implicit discrimination by showing that this discriminatory behaviour: (i) increases in how rushed the referee is before making a decision, and (ii) it increases in the level of ambiguity of the decision. The variation in (i) and (ii) cannot be explained by any form of conscious discrimination such as taste-based or statistical discrimination. Moreover, we show that oppositional identity players do not differ in their behaviour from other players along several dimensions related to aggressiveness and style of play providing further evidence that this is not statistical discrimination.

Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.