4,671 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Innovation in Energy Security and Long-Term Energy Efficiency â…¡

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    The sustainable development of our planet depends on the use of energy. The increasing world population inevitably causes an increase in the demand for energy, which, on the one hand, threatens us with the potential to encounter a shortage of energy supply, and, on the other hand, causes the deterioration of the environment. Therefore, our task is to reduce this demand through different innovative solutions (i.e., both technological and social). Social marketing and economic policies can also play their role by affecting the behavior of households and companies and by causing behavioral change oriented to energy stewardship, with an overall switch to renewable energy resources. This reprint provides a platform for the exchange of a wide range of ideas, which, ultimately, would facilitate driving societies toward long-term energy efficiency

    Constitutions of Value

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    Gathering an interdisciplinary range of cutting-edge scholars, this book addresses legal constitutions of value. Global value production and transnational value practices that rely on exploitation and extraction have left us with toxic commons and a damaged planet. Against this situation, the book examines law’s fundamental role in institutions of value production and valuation. Utilising pathbreaking theoretical approaches, it problematizes mainstream efforts to redeem institutions of value production by recoupling them with progressive values. Aiming beyond radical critique, the book opens up the possibility of imagining and enacting new and different value practices. This wide-ranging and accessible book will appeal to international lawyers, socio-legal scholars, those working at the intersections of law and economy and others, in politics, economics, environmental studies and elsewhere, who are concerned with rethinking our current ideas of what has value, what does not, and whether and how value may be revalued

    Developing a novel and versatile approach to study populations of microbes on surfaces

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    Spatial structure, for example regarding antibiotic gradients, is an important topic of investigation in microbial ecology and evolution. Experiments investigating pop- ulation dynamics in spatially-structured environments are often performed on agar plates. Whilst inexpensive and straightforward, these provide only rudimentary temporal and spatial control of environmental conditions. In chemostats and microfluidic devices, for well-mixed and micrometre-scale environments, respectively, regulating media inflow and outflow enables environ- mental control. We combine proven use of agar surfaces with such flow-enabled control in a novel, low-cost fluidic device; the device comprises an elastomer supporting base with a thin agar sheet on top on which microbes grow. Indented channels in the base allow flow of media/antibiotics below the agar surface. A Raspberry-Pi-operated camera allows for time-lapse imaging suitable for quantita- tive image analysis. As a proof of principle, we used our device for extended and robust growth of non-motile E. coli and motile P. aeruginosa maintaining the initial speed with which colonies propagate over three days, whilst a continual speed decrease occurred on agar plates. Guided by simulations of flow and diffusion, we then used the device to create stable antibiotic gradients within the agar. Along these gradients, we found P. aeruginosa exhibit unique microbial growth patterns with local adaptations. Because flow below the agar surface can be controlled spatially and temporally, the device promises a range of applications for studying microbial ecology and evolution in spatially continuous environments at a substrate-air interface.Engineering and Physical Sciences Research Council (EPSRC

    Histograms: An educational eye

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    Many high-school students are not able to draw justified conclusions from statistical data in histograms. A literature review showed that most misinterpretations of histograms are related to difficulties with two statistical key concepts: data and distribution. The review also pointed to a lack of knowledge about students’ strategies when solving histogram tasks. As the literature provided little guidance for the design of lesson materials, several studies were conducted in preparation. In a first study, five solution strategies were found through qualitative analysis of students’ gazes when solving histograms and case-value plot tasks. Quantitative analysis of several histogram tasks through a mathematical model and a machine learning algorithm confirmed these results, which implied that these strategies could reliably and automatically be identified. Literature also suggested that dotplot tasks can support students’ learning to interpret histograms. Therefore, gazes on histogram tasks were compared before and after students solved dotplot tasks. The "after" tasks contained more gazes associated with correct strategies and fewer gazes associated with incorrect strategies. Although answers did not improve significantly, students’ verbal descriptions suggest that some students changed to a correct strategy. Newly designed materials thus started with dotplot tasks. From the previous studies, we conjectured that students lacked embodied experiences with actions related to histograms. Designed from an embodied instrumentation perspective, the tested materials provide starting points for scaling up. Together, the studies address the knowledge gaps identified in the literature. The studies contribute to knowledge about learning histograms and use in statistics education of eye-tracking research, interpretable models and machine learning algorithms, and embodied instrumentation design

    An investigation of the use of gradients in imaging, including best approximation and the Structural Similarity image quality measure

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    The L^2-based mean squared error (MSE) and its variations continue to be the most widely employed metrics in image processing. This is most probably due to the fact that (1) the MSE is simple to compute and (2) it possesses a number of convenient mathematical properties, including differentiability and convexity. It is well known, however, that these L^2-based measures perform poorly in terms of measuring the visual quality of images. Their failure is partially due to the fact that the L^2 metric does not capture spatial relationships between pixels. This was a motivation for the introduction of the so-called Structural Similarity (SSIM) image quality measure [1] which, along with is variations, continues to be one of the most effective measure of visual quality. The SSIM index measures the similarity between two images by combining three components of the human visual system--luminance, contrast, and structure. It is our belief that the structure term, which measures the correlation between images, is the most important component of the SSIM. A considerable portion of this thesis focusses on adapting the L^2 distance for image processing applications. Our first approach involves inserting an intensity-dependent weight function into the integral such that it conforms to generalized Weber's model of perception. We solve the associated best approximation problem and discuss examples in both one- and two-dimensions. Motivated by the success of the SSIM, we also solve the Weberized best approximation problem with an added regularization term involving the correlation. Another approach we take towards adapting the MSE for image processing involves introducing gradient information into the metric. Specifically, we study the traditional L^2 best approximation problem with an added regularization term involving the L^2 distance between gradients. We use orthonormal functions to solve the best approximation problem in both the continuous and discrete setting. In both cases, we prove that the Fourier coefficients remain optimal provided certain assumptions on the orthonormal basis hold. Our final best approximation problem to be considered involves maximizing the correlation between gradients. We obtain the relevant stationarity conditions and show that an infinity of solutions exists. A unique solution can be obtained using two assumptions adapted from [2]. We demonstrate that this problem is equivalent to maximizing the entire SSIM function between gradients. During this work, we prove that the discrete derivatives of the DCT and DFT basis functions form an orthogonal set, a result which has not appeared in the literature to the best of our knowledge. Our study of gradients is not limited to best approximation problems. A second major focus of this thesis concerns the development of gradient-based image quality measures. This was based on the idea that the human visual system may also be sensitive to distortions in the magnitudes and/or direction of variations in greyscale or colour intensities--in other words, their gradients. Indeed, as we show in a persuasive simple example, the use of the L^2 distances between image gradients already yields a significant improvement over the MSE. One naturally wonders whether a measure of the correlation between image gradients could yield even better results--in fact, possibly "better" than the SSIM itself! (We will define what we mean by "better" in this thesis.) For this reason, we pursue many possible forms of a "gradient-based SSIM". First, however, we must address the question of how to define the correlation between the gradient vectors of two images. We formulate and compare many novel gradient similarity measures. Among those, we justify our selection of a preferred measure which, although simple-minded, we show to be highly correlated with the "rigorous" canonical correlation method. We then present many attempts at incorporating our gradient similarity measure into the SSIM. We finally arrive at a novel gradient-based SSIM, our so-called "gradSSIM1", which we argue does, in fact, improve the SSIM. The novelty of our approach lies in its use of SSIM-dependent exponents, which allow us to seamlessly blend our measure of gradient correlation and the traditional SSIM. To compare two image quality measures, e.g., the SSIM and our "gradSSIM1", we require use of the LIVE image database [3]. This database contains numerous distorted images, each of which is associated with a single score indicating visual quality. We suggest that these scores be considered as the independent variable, an understanding that does not appear to be have been adopted elsewhere in the literature. This work also necessitated a detailed analysis of the SSIM, including the roles of its individual components and the effect of varying its stability constants. It appears that such analysis has not been performed elsewhere in the literature. References: [1] Z. Wang, A.C. Bovik, H.R. Sheikh, E.P. Simoncelli. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, 13(4):600-612, 2004. [2] P. Bendevis and E.R. Vrscay. Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Components Functions S_k(x,y). In Aurelio Campilho and Mohamed Kamel, editors, Image Analysis and Recognition - 11th International COnference, ICIAR 2014, Vilamoura, Portugal, October 22-24, 2014, Proceedings, Part 1, volume 8814 of Lecture Notes in Computer Science, pages 55-64, 2014. [3] H.R. Sheikh, M.F. Sabir, and A.C. Bovik. A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms. IEEE Transactions on Image Processing, 15(11):3440-2451, November 2006

    Getting the gist of it: An investigation of gist processing and the learning of novel gist categories

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    Gist extraction rapidly processes global structural regularities to provide access to the general meaning and global categorizations of our visual environment – the gist. Medical experts can also extract gist information from mammograms to categorize them as normal or abnormal. However, the visual properties influencing the gist of medical abnormality are largely unknown. It is also not known how medical experts, or any observer for that matter, learned to recognise the gist of new categories. This thesis investigated the processing and acquisition of the gist of abnormality. Chapter 2 observed no significant differences in performance between 500 ms and unlimited viewing time, suggesting that the gist of abnormality is fully accessible after 500 ms and remains available during further visual processing. Next, chapter 3 demonstrated that certain high-pass filters enhanced gist signals in mammograms at risk of future cancer, without affecting overall performance. These filters could be used to enhance mammograms for gist risk-factor scoring. Chapter 4’s multi-session training showed that perceptual exposure with global feedback is sufficient to induce learning of a new gist categorisation. However, learning was affected by individual differences and was not significantly retained after 7-10 days, suggesting that prolonged perceptual exposure might be needed for consolidation. Chapter 5 observed evidence for the neural signature of gist extraction in medical experts across a network of regions, where neural activity patterns showed clear individual differences. Overall, the findings of this thesis confirm the gist extraction of medical abnormality as a rapid, global process that is sensitive to spatial structural regularities. Additionally, it was shown that a gist category can be learned via global feedback, but this learning is hard to retain and is affected by individual differences. Similarly, individual differences were observed in the neural signature of gist extraction by medical experts

    Google search and the mediation of digital health information: a case study on unproven stem cell treatments

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    Google Search occupies a unique space within broader discussions of direct-to-consumer marketing of stem cell treatments in digital spaces. For patients, researchers, regulators, and the wider public, the search platform influences the who, what, where, and why of stem cell treatment information online. Ubiquitous and opaque, Google Search mediates which users are presented what types of content when these stakeholders engage in online searches around health information. The platform also sways the activities of content producers and the characteristics of the content they produce. For those seeking and studying information on digital health, this platform influence raises difficult questions around risk, authority, intervention, and oversight. This thesis addresses a critical gap in digital methodologies used in mapping and characterising that influence as part of wider debates around algorithmic accountability within STS and digital health scholarship. By adopting a novel methodological approach to Blackbox auditing and data collection, I provide a unique evidentiary base for the analysis of ads, organic results, and the platform mechanisms of influence on queries related to stem cell treatments. I explore the question: how does Google Search mediate information that people access online about ‘proven’ and ‘unproven’ stem cell treatments? Here I show that, in spite of a general ban on advertisements of stem cell treatments, users continue to be presented with content promoting unproven treatments. The types, frequency, and commercial intent of results related to stem cell treatments shifted across user groups including geography and, more troublingly, those impacted by Parkinson’s Disease and Multiple Sclerosis. Additionally, I find evidence that the technological structure of Google Search itself enables primary and secondary commercial activities around the mediation and dissemination of health information online. It suggests that Google Search’s algorithmically-mediated rendering of search results – including both commercial and non-commercial activities - has critical implications for the present and future of digital health studies
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