Data visualization during the early stages of drug discovery

Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

Real estate research needs of the plan sponsor community:what do the plan sponsor real estate investment managers want to know?

This article reports the results of a web-based survey of real estate portfolio managers in the pension fund industry. The study focused on ascertaining the real estate research interests of the respondents as well as whether or not research funding should be allocated to various research topics. Performance measures of real estate assets and portfolios, microeconomic factors affecting real estate and the role of real estate in a mixed-asset portfolio were the top three real estate research interests. There was some variation by the type and size of fund providing evidence that segmentation is important within the money management industry. Respondents were also queried on more focused research subtopics and additional questions in the survey focused on satisfaction with existing real estate benchmarks, and perceptions of the usefulness of published research. Findings should be used to guide research practitioners and academics as to the most important research interests of plan sponsor real estate investment managers.

Journey making group workshops as a research tool

Problem-structuring group workshops can be used in organizations as a consulting tool and as a research tool. One example of the latter is using a problem-structuring method (PSM) to help a group tackle an organizational issue; meanwhile, researchers collect the participants' initial views, discussion of divergent views, the negotiated agreement, and the reasoning for outcomes emerging. Technology can help by supporting participants in freely sharing their opinions and by logging data for post-workshop analyses. For example, computers let participants share views anonymously and without being influenced by others (as well as logging those views), and video-cameras can record discussions and intra-group dynamics. This paper evaluates whether technology-supported Journey Making workshops can be effective research tools that can capture quality research data when compared against theoretical performance benchmarks and other qualitative research tools. © 2006 Operational Research Society Ltd. All rights reserved.

Can you tell your clunis from your cubitus? A benchmark for functional imaging

Advances in functional brain imaging have allowed the development of new investigative techniques with clinical application—ranging from presurgical mapping of eloquent cortex to identifying cortical regions involved in religious experiences. Similarly a variety of methods are available to referring physicians, ranging from metabolic measures such as functional magnetic resonance imaging and positron emission tomography to measurements based on electrical activity such as electroencephalography and magnetoencephalography. However, there are no universal benchmarks by which to judge between these methods. In this study we attempt to develop a standard for functional localisation, based on the known functional organisation of somatosensory cortex. Studies have shown spatially distinct sites of brain activity in response to stimulation of various body parts. Generally these studies have focused on areas with large cortical representations, such as the index finger and face. We tested the limits of magnetoencephalography source localisation by stimulation of body parts, namely the clunis and the cubitus, that map to proximal and relatively poorly represented regions of somatosensory cortex.

Sustainability practices and indicators in food retail logistics:findings from an exploratory study

The aim of this paper is to provide an overview and an analysis of recent developments and changes in the implementation of sustainability practices by food retailers. It also aims to explore whether the sustainability measurement criteria and indicators identified in the literature can be applied in practice. A literature review identified the current trends, developments and the proposed sustainability objectives, criteria and indicators. Via case study research, we collected empirical data from four retailers. This involved both qualitative and quantitative data drawn from questionnaires and in-depth interviews with logistics directors from four retailers' distribution centres. The empirical data collected from the interviews indicate similarities in some of the characteristics of distribution centres, as well as differences. However, it was difficult to make cross-company comparisons due to the absence of benchmarks or assessments of the relative importance of each sustainability criterion and indicator. This research focused only on two sustainability objectives. Further research on other sustainability objectives is therefore required. Lessons learnt from the four case studies can be taken into consideration when developing future sustainability performance rating scales. The paper provides an in-depth analysis of sustainability in the food chain, with emphasis on food retailing. Its value lies in presenting an attempt to test in practice how a number of sustainability objectives, criteria and indicators are applied in logistics-related processes, identifying the gaps and reporting the potential difficulties.

Causality in crude oil prices

Economic media inform on prices of three well established crude oil benchmarks: Brent, WTI and Dubai Fateh. The relevance of these is however declining with their low output - motivating investigation of the pricing dynamics. We apply Granger causality tests to study the price dependencies of 32 crude oils. The aim is to establish what crudes are setting the prices and what crudes are just following the general market trends. The investigation is performed globally as well as for different quality, geographical and organisational segments. The results indicate that crude oil price analysts should follow at least four different crudes that are good price indicators. WTI and Brent still lead the market, but they are not the only crude prices worth paying attention to. In particular, Russian Urals drives global prices in a significant way, and Iran Seri Kerir is a significant price setter within OPEC. Dubai Fateh does not display any significant influence as a price setter, which confirms the lack of dominant benchmark within the segment of medium quality crudes.

World knowledge competitiveness index 2008

The 2008 edition of the WKCI compares 145 regions across 19 knowledge economy benchmarks (full data for all indicators across each of the 19 benchmarks is contained in the accompanying Excel spreadsheets). This represents an increase of twenty regions compared to the last edition in 2005: nine from Europe, eight from North America, and three from Asia Pacific. These new regions were selected on the basis of a survey of a wide range of regions appearing to be become more internationally competitive. This year’s report also contains a special chapter on economic development in the three leading Chinese regions.

Standardisation and benchmarking for improving translator training

The worldwide growth of the translation industry requires qualified professional translators. During the last decade, we have seen an enormous increase in translator training programmes offered by universities, mainly at postgraduate level. A challenge for such university programmes is to make sure that they prepare graduates who are qualified for the needs of the diverse profession in the rapidly changing market. This means that programmes need to be developed with the market needs in mind and that they need to ensure a good match between graduates' competences and employers' requirements. This paper addresses the following questions: How can universities adapt translator training programmes to the rapidly changing industry and the accompanying changes in professional profiles? How can we reconcile the requests of the industry for graduates who have practical and professional skills with the requests of the universities for graduates who have in-depth academic knowledge and intellectual skills? What standards and benchmarks are in place to assure quality of translator training programmes? Some such developments in respect of benchmarking are illustrated at first for the United Kingdom, followed by information on the European Master’s in Translation (EMT) project, an initiative at the European level. Finally, the paper reflects on the challenges which the EMT translator competence profile poses for university programmes.

The reward pocketbook

This book covers a broad spectrum from job evaluation systems and how they help staff to understand different job benchmarks, to a range of financial incentive schemes and other benefits which are important to employees - helping you to build loyalty, motivation and productivity. The author highlights the pitfalls of some schemes, using real case studies and offers advice and guidance on packages that work.

Green operations initiatives in the automotive industry:an environmental reports analysis and benchmarking study

Purpose: The purpose of this paper is to focus on investigating and benchmarking green operations initiatives in the automotive industry documented in the environmental reports of selected companies. The investigation roadmaps the main environmental initiatives taken by the world's three major car manufacturers and benchmarks them against each other. The categorisation of green operations initiatives that is provided in the paper can also help companies in other sectors to evaluate their green practices. Design/methodology/approach: The first part of the paper is based on existing literature on the topic of green and sustainable operations and the "unsustainable" context of automotive production. The second part relates to the roadmap and benchmarking of green operations initiatives based on an analysis of secondary data from the automotive industry. Findings: The findings show that the world's three major car manufacturers are pursuing various environmental initiatives involving the following green operations practices: green buildings, eco-design, green supply chains, green manufacturing, reverse logistics and innovation. Research limitations/implications: The limitations of this paper start from its selection of the companies, which was made using production volume and country of origin as the principal criteria. There is ample evidence that other, smaller, companies are pursuing more sophisticated and original environmental initiatives. Also, there might be a gap between what companies say they do in their environmental reports and what they actually do. Practical implications: This paper helps practitioners in the automotive industry to benchmark themselves against the major volume manufacturers in three different continents. Practitioners from other industries will also find it valuable to discover how the automotive industry is pursuing environmental initiatives beyond manufacturing, apart from the green operations practices covering broadly all the activities of operations function. Originality/value: The originality of the paper is in its up-to-date analysis of environmental reports of automotive companies. The paper offers value for researchers and practitioners due to its contribution to the green operations literature. For instance, the inclusion of green buildings as part of green operations practices has so far been neglected by most researchers and authors in the field of green and sustainable operations. © Emerald Group Publishing Limited.

Reflections on five years of evaluating semantic search systems

Evaluations of semantic search systems are generally small scale and ad hoc due to the lack of appropriate resources such as test collections, agreed performance criteria and independent judgements of performance. By analysing our work in building and evaluating semantic tools over the last five years, we conclude that the growth of the semantic web led to an improvement in the available resources and the consequent robustness of performance assessments. We propose two directions for continuing evaluation work: the development of extensible evaluation benchmarks and the use of logging parameters for evaluating individual components of search systems.

Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.

Introduction to performance improvement management software (PIM-DEA)

This chapter provides information on the use of Performance Improvement Management Software (PIMDEA). This advanced DEA software enables users to make the best possible analysis of the data, using the latest theoretical developments in Data Envelopment Analysis (DEA). PIM-DEA software gives full capacity to assess efficiency and productivity, set targets, identify benchmarks, and much more, allowing users to truly manage the performance of organizational units. PIM-DEA is easy to use and powerful, and it has an extensive range of the most up-to-date DEA models and which can handle large sets of data.

Causality in crude oil prices

Crude oil markets witness growing disparity between the quality of crudes supplied and demanded in the market. The market share of low-quality crudes is increasing due to the depletion of old fields and increasing demand. This is unnerving the practitioners and affecting the relevance of the traditional benchmark crudes due to the lack of lower quality benchmarks (Montepeque, 2005). In this article, we apply Granger causality tests to study the price dependence of 32 crudes in order to establish which crudes drive other prices and which ones simply follow general market trends. Our results indicate that some of the old benchmarks are still relevant while others can be disregarded. Our results also interestingly show that the low-quality Mediterranean Russian Urals crude, introduced in the late 1990s, has emerged recently as a significant driver of global prices. © 2011 Taylor & Francis.

Improved inference in the evaluation of mutual fund performance using bootstrap methods

Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund returns, we find that fund size has a negative effect on the average fund manager’s benchmark-adjusted performance. Further, when we allow for time effects and the non-normality of fund returns, we find that there is no evidence that even the best performing fund managers can significantly out-perform the augmented benchmarks after fund management charges are taken into account.