Tuning of metal-insulator transition of two-dimensional electrons at parylene/SrTiO3_3 interface by electric field

Electrostatic carrier doping using a field-effect-transistor structure is an intriguing approach to explore electronic phases by critical control of carrier concentration. We demonstrate the reversible control of the insulator-metal transition (IMT) in a two dimensional (2D) electron gas at the interface of insulating SrTiO$_3$ single crystals. Superconductivity was observed in a limited number of devices doped far beyond the IMT, which may imply the presence of 2D metal-superconductor transition. This realization of a two-dimensional metallic state on the most widely-used perovskite oxide is the best manifestation of the potential of oxide electronics

The extragalactic background and its fluctuations in the far-infrared wavelengths

A Cosmic Far-InfraRed Background (CFIRB) has long been predicted that would traces the intial phases of galaxy formation. It has been first detected by Puget et al.(1996) using COBE data and has been later confirmed by several recent studies (Fixsen et al. 1998, Hauser et al. 1998, Lagache et al. 1999). We will present a new determination of the CFIRB that uses for the first time, in addition to COBE data, two independent gas tracers: the HI survey of Leiden/Dwingeloo (hartmann, 1998) and the WHAM H$_{\alpha}$ survey (Reynolds et al 1998). We will see that the CFIRB above 100 micron is now very well constrained. The next step is to see if we can detect its fluctuations. To search for the CFIRB fluctuations, we have used the FIRBACK observations. FIRBACK is a deep cosmological survey conducted at 170 micron with ISOPHOT (Dole et al., 2000). We show that the emission of unresolved extra-galactic sources clearly dominates, at arcminute scales, the background fluctuations in the lowest galactic emission regions. This is the first detection of the CFIRB fluctuations.Comment: To appear in "ISO Surveys of a Dusty Universe", Workshop at Ringberg Castle, November 8 - 12, 199

Thermal simulation software outputs: a conceptual data model of information presentation for building design decision-making

Building simulation outputs are inherently complex and numerous. Extracting meaningful information from them requires knowledge which mainly resides only in the hands of experts. Initiatives to address this problem tend either to provide very constrained output data interfaces or leave it to the user to customize data organisation and query. This work proposes a conceptual data model from which meaningful dynamic thermal simulation information for building design decision-making may be constructed and presented to the user. It describes how the model was generated and can become operational, with examples of its applications to practical problems. The paper therefore contains useful information for software developers to help in specifying and designing simulation outputs which better respond to building designers’ needs

The harvest plot: A method for synthesising evidence about the differential effects of interventions

<p>Abstract</p> <p>Background</p> <p>One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies.</p> <p>Methods</p> <p>We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality.</p> <p>Results</p> <p>We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups.</p> <p>Conclusion</p> <p>The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.</p

Designing visual analytics methods for massive collections of movement data

Exploration and analysis of large data sets cannot be carried out using purely visual means but require the involvement of database technologies, computerized data processing, and computational analysis methods. An appropriate combination of these technologies and methods with visualization may facilitate synergetic work of computer and human whereby the unique capabilities of each “partner” can be utilized. We suggest a systematic approach to defining what methods and techniques, and what ways of linking them, can appropriately support such a work. The main idea is that software tools prepare and visualize the data so that the human analyst can detect various types of patterns by looking at the visual displays. To facilitate the detection of patterns, we must understand what types of patterns may exist in the data (or, more exactly, in the underlying phenomenon). This study focuses on data describing movements of multiple discrete entities that change their positions in space while preserving their integrity and identity. We define the possible types of patterns in such movement data on the basis of an abstract model of the data as a mathematical function that maps entities and times onto spatial positions. Then, we look for data transformations, computations, and visualization techniques that can facilitate the detection of these types of patterns and are suitable for very large data sets – possibly too large for a computer's memory. Under such constraints, visualization is applied to data that have previously been aggregated and generalized by means of database operations and/or computational techniques

Assessing Graphical Robot Aids for Interactive Co-working

The shift towards more collaborative working between humans and robots increases the need for improved interfaces. Alongside robust measures to ensure safety and task performance, humans need to gain the confidence in robot co-operators to enable true collaboration. This research investigates how graphical signage can support human–robot co-working, with the intention of increased productivity. Participants are required to co-work with a KUKA iiwa lightweight manipulator on a manufacturing task. The three conditions in the experiment differ in the signage presented to the participants – signage relevant to the task, irrelevant to the task, or no signage. A change between three conditions is expected in anxiety and negative attitudes towards robots; error rate; response time; and participants’ complacency, suggested by facial expressions. In addition to understanding how graphical languages can support human–robot co-working, this study provides a basis for further collaborative research to explore human–robot co-working in more detail

Geovisual analytics for spatial decision support: Setting the research agenda

This article summarizes the results of the workshop on Visualization, Analytics & Spatial Decision Support, which took place at the GIScience conference in September 2006. The discussions at the workshop and analysis of the state of the art have revealed a need in concerted cross‐disciplinary efforts to achieve substantial progress in supporting space‐related decision making. The size and complexity of real‐life problems together with their ill‐defined nature call for a true synergy between the power of computational techniques and the human capabilities to analyze, envision, reason, and deliberate. Existing methods and tools are yet far from enabling this synergy. Appropriate methods can only appear as a result of a focused research based on the achievements in the fields of geovisualization and information visualization, human‐computer interaction, geographic information science, operations research, data mining and machine learning, decision science, cognitive science, and other disciplines. The name ‘Geovisual Analytics for Spatial Decision Support’ suggested for this new research direction emphasizes the importance of visualization and interactive visual interfaces and the link with the emerging research discipline of Visual Analytics. This article, as well as the whole special issue, is meant to attract the attention of scientists with relevant expertise and interests to the major challenges requiring multidisciplinary efforts and to promote the establishment of a dedicated research community where an appropriate range of competences is combined with an appropriate breadth of thinking

CaII K interstellar observations towards early disc and halostars - Paper II; distances to IVCs and HVCs

We compare existing high spectral resolution (R=40,000) CaII K observations towards 88 mainly B-type stars, and new observations at R=10,000 towards 3 stars, with 21-cm HI emission-line profiles, in order to search for optical absorption towards known intermediate and high velocity cloud complexes. Given certain assumptions, limits to the gas phase abundance of CaII are estimated for the cloud components. We use the data to derive the following distances from the Galactic plane (z); 1) Tentative lower z-height limits of 2800 pc and 4100 pc towards Complex C using lack of absorption in the spectra of HD 341617 and PG 0855+294. 2) A weak lower z-height of 1400 pc towards Complex WA-WB using lack of absorption in EC 09470-1433 and weak lower limit of 2470 pc with EC 09452-1403. 3) An upper z-height of 2470 pc towards a southern intermediate velocity cloud (IVC) with v_LSR=-55 km/s using PG 2351+198. 4) Detection of a possible IVC in CaK absorption at v_LSR=+52 km/s using EC 20104-2944. No associated HI in emission is detected. At this position, normal Galactic rotation predicts velocities of up to +25 km/s. The detection puts an upper z-height of 1860 pc to the cloud. 5) Tentative HI and CaK detections towards an IVC at +70 km/s in the direction of HVC Complex WE, sightline EC 06387-8045, indicating that the IVC may be at a z-height lower than 1770 pc. 6) Detection of CaK absorption in the spectrum of PG 0855+294 in the direction of IV20, indicating that this IVC has a z-height smaller than 4100 pc. 7) A weak lower z-height of 4300 pc towards a small HVC with v_LSR=+115 km/s at l,b=200,+52, using lack of absorption in the CaK spectrum of PG 0955+291.Comment: 13 pages, 5 figures. Accepted for publication in MNRAS, May 13 200