975 resultados para IoT platforms


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High quality wind measurements in cities are needed for numerous applications including wind engineering. Such data-sets are rare and measurement platforms may not be optimal for meteorological observations. Two years' wind data were collected on the BT Tower, London, UK, showing an upward deflection on average for all wind directions. Wind tunnel simulations were performed to investigate flow distortion around two scale models of the Tower. Using a 1:160 scale model it was shown that the Tower causes a small deflection (ca. 0.5°) compared to the lattice on top on which the instruments were placed (ca. 0–4°). These deflections may have been underestimated due to wind tunnel blockage. Using a 1:40 model, the observed flow pattern was consistent with streamwise vortex pairs shed from the upstream lattice edge. Correction factors were derived for different wind directions and reduced deflection in the full-scale data-set by <3°. Instrumental tilt caused a sinusoidal variation in deflection of ca. 2°. The residual deflection (ca. 3°) was attributed to the Tower itself. Correction of the wind-speeds was small (average 1%) therefore it was deduced that flow distortion does not significantly affect the measured wind-speeds and the wind climate statistics are reliable.

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This paper proposes a Dual-Magnet Magnetic Compliance Unit (DMCU) for use in medium sized space rover platforms to enhance terrain handling capabilities and speed of traversal. An explanation of magnetic compliance and how it can be applied to space robotics is shown, along with an initial mathematical model for this system. A design for the DMCU is proposed along with a 4-wheeled DMCU Testing Rig.

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We analyze four years of transaction data for euro-area sovereign bonds traded on the MTS electronic platforms. In order to measure the informational content of trading activity, we estimate the permanent price response to trades. We find not only strong evidence of information asymmetry in sovereign bond markets, but we also show the relevance of information asymmetry in explaining the cross-sectional variations of bond yields across a wide range of bond maturities and countries. Our results confirm that trades of more recently issued bonds and longer maturity bonds have a greater permanent effect on prices. We compare the price impact of trades for bonds across different maturity categories and find that trades of French and German bonds have the highest long-term price impact in the short maturity class whereas trades of German bonds have the highest permanent price impacts in the long maturity class. More importantly, we study the cross-section of bond yields and find that after controlling for conventional factors, investors demand higher yields for bonds with larger permanent trading impact. Interestingly, when investors face increased market uncertainty, they require even higher compensation for information asymmetry.

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Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

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A focused library of potential hydrogelators each containing two substituted aromatic residues separated by a urea or thiourea linkage have been synthesised and characterized. Six of these novel compounds are highly efficient hydrogelators, forming gels in aqueous solution at low concentrations (0.03–0.60 wt %). Gels were formed through a pH switching methodology, by acidification of a basic solution (pH 14 to ≈4) either by addition of HCl or via the slow hydrolysis of glucono-δ-lactone. Frequently, gelation was accompanied by a dramatic switch in the absorption spectra of the gelators, resulting in a significant change in colour, typically from a vibrant orange to pale yellow. Each of the gels was capable of sequestering significant quantities of the aromatic cationic dye, methylene blue, from aqueous solution (up to 1.02 g of dye per gram of dry gelator). Cryo-transmission electron microscopy of two of the gels revealed an extensive network of high aspect ratio fibers. The structure of the fibers altered dramatically upon addition of 20 wt % of the dye, resulting in aggregation and significant shortening of the fibrils. This study demonstrates the feasibility for these novel gels finding application as inexpensive and effective water purification platforms.

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Marine and terrestrial sediments of the Valanginian age display a distinct positive δ13C excursion, which has recently been interpreted as the expression of an oceanic anoxic episode (OAE) of global importance. Here we evaluate the extent of anaerobic conditions in marine bottom waters and explore the mechanisms involved in changing carbon storage on a global scale during this time interval. We asses redox-sensitive trace-element distributions (RSTE; uranium, vanadium, cobalt, arsenic and molybdenum) and the quality and quantity of preserved organic matter (OM) in representative sections along a shelf-basin transect in the western Tethys, in the Polish Basin and on Shatsky Rise. OM-rich layers corresponding in time to the δ13C shift are generally rare in the Tethyan sections and if present, the layers are not thicker than several centimetres and total organic carbon (TOC) contents do not surpass 1.68 wt..%. Palynological observations and geochemical properties of the preserved OM suggest a mixed marine and terrestrial origin and deposition in an oxic environment. In the Polish Basin, OM-rich layers show evidence for an important continental component. RSTE exhibit no major enrichments during the δ13C excursion in all studied Tethyan sections. RSTE enrichments are, however, observed in the pre-δ13C excursion OM-rich “Barrande” levels of the Vocontian Trough. In addition, all Tethyan sections record higher Mn contents during the δ13C shift, indicating rather well-oxygenated bottom waters in the western Tethys and the presence of anoxic basins elsewhere, such as the restricted basins of the North Atlantic and Weddell Sea. We propose that the Valanginian δ13C shift is the consequence of a combination of increased OM storage in marginal seas and on continents (as a sink of 12C-enriched organic carbon), coupled with the demise of shallow-water carbonate platforms (diminishing the storage capacity of 13C-enriched carbonate carbon). As such the Valanginian provides a more faithful natural analogue to present-day environmental change than most other Mesozoic OAEs, which are characterized by the development of ocean-wide dysaerobic to anaerobic conditions.

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The last decade has seen successful clinical application of polymer–protein conjugates (e.g. Oncaspar, Neulasta) and promising results in clinical trials with polymer–anticancer drug conjugates. This, together with the realisation that nanomedicines may play an important future role in cancer diagnosis and treatment, has increased interest in this emerging field. More than 10 anticancer conjugates have now entered clinical development. Phase I/II clinical trials involving N-(2-hydroxypropyl)methacrylamide (HPMA) copolymer-doxorubicin (PK1; FCE28068) showed a four- to fivefold reduction in anthracycline-related toxicity, and, despite cumulative doses up to 1680 mg/m2 (doxorubicin equivalent), no cardiotoxicity was observed. Antitumour activity in chemotherapy-resistant/refractory patients (including breast cancer) was also seen at doxorubicin doses of 80–320 mg/m2, consistent with tumour targeting by the enhanced permeability (EPR) effect. Hints, preclinical and clinical, that polymer anthracycline conjugation can bypass multidrug resistance (MDR) reinforce our hope that polymer drugs will prove useful in improving treatment of endocrine-related cancers. These promising early clinical results open the possibility of using the water-soluble polymers as platforms for delivery of a cocktail of pendant drugs. In particular, we have recently described the first conjugates to combine endocrine therapy and chemotherapy. Their markedly enhanced in vitro activity encourages further development of such novel, polymer-based combination therapies. This review briefly describes the current status of polymer therapeutics as anticancer agents, and discusses the opportunities for design of second-generation, polymer-based combination therapy, including the cocktail of agents that will be needed to treat resistant metastatic cancer.

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Measurements of the electrical characteristics of the atmosphere above the surface have been made for over 200 years, from a variety of different platforms, including kites, balloons, rockets and aircraft. From these measurements, a great deal of information about the electrical characteristics of the atmosphere has been gained, assisting our understanding of the global atmospheric electric circuit, thunderstorm electrification and lightning generation mechanisms, discovery of transient luminous events above thunderstorms, and many other electrical phenomena. This paper surveys the history of atmospheric electrical measurements aloft, from the earliest manned balloon ascents to current day observations with free balloons and aircraft. Measurements of atmospheric electrical parameters in a range of meteorological conditions are described, including clear air conditions, polluted conditions, non-thunderstorm clouds, and thunderstorm clouds, spanning a range of atmospheric conditions, from fair weather, to the most electrically active.

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The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

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The increasing use of social media, applications or platforms that allow users to interact online, ensures that this environment will provide a useful source of evidence for the forensics examiner. Current tools for the examination of digital evidence find this data problematic as they are not designed for the collection and analysis of online data. Therefore, this paper presents a framework for the forensic analysis of user interaction with social media. In particular, it presents an inter-disciplinary approach for the quantitative analysis of user engagement to identify relational and temporal dimensions of evidence relevant to an investigation. This framework enables the analysis of large data sets from which a (much smaller) group of individuals of interest can be identified. In this way, it may be used to support the identification of individuals who might be ‘instigators’ of a criminal event orchestrated via social media, or a means of potentially identifying those who might be involved in the ‘peaks’ of activity. In order to demonstrate the applicability of the framework, this paper applies it to a case study of actors posting to a social media Web site.

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A new record of sea surface temperature (SST) for climate applications is described. This record provides independent corroboration of global variations estimated from SST measurements made in situ. Infrared imagery from Along-Track Scanning Radiometers (ATSRs) is used to create a 20 year time series of SST at 0.1° latitude-longitude resolution, in the ATSR Reprocessing for Climate (ARC) project. A very high degree of independence of in situ measurements is achieved via physics-based techniques. Skin SST and SST estimated for 20 cm depth are provided, with grid cell uncertainty estimates. Comparison with in situ data sets establishes that ARC SSTs generally have bias of order 0.1 K or smaller. The precision of the ARC SSTs is 0.14 K during 2003 to 2009, from three-way error analysis. Over the period 1994 to 2010, ARC SSTs are stable, with better than 95% confidence, to within 0.005 K yr−1(demonstrated for tropical regions). The data set appears useful for cleanly quantifying interannual variability in SST and major SST anomalies. The ARC SST global anomaly time series is compared to the in situ-based Hadley Centre SST data set version 3 (HadSST3). Within known uncertainties in bias adjustments applied to in situ measurements, the independent ARC record and HadSST3 present the same variations in global marine temperature since 1996. Since the in situ observing system evolved significantly in its mix of measurement platforms and techniques over this period, ARC SSTs provide an important corroboration that HadSST3 accurately represents recent variability and change in this essential climate variable.

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We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

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We have optimised the atmospheric radiation algorithm of the FAMOUS climate model on several hardware platforms. The optimisation involved translating the Fortran code to C and restructuring the algorithm around the computation of a single air column. Instead of the existing MPI-based domain decomposition, we used a task queue and a thread pool to schedule the computation of individual columns on the available processors. Finally, four air columns are packed together in a single data structure and computed simultaneously using Single Instruction Multiple Data operations. The modified algorithm runs more than 50 times faster on the CELL’s Synergistic Processing Elements than on its main PowerPC processing element. On Intel-compatible processors, the new radiation code runs 4 times faster. On the tested graphics processor, using OpenCL, we find a speed-up of more than 2.5 times as compared to the original code on the main CPU. Because the radiation code takes more than 60% of the total CPU time, FAMOUS executes more than twice as fast. Our version of the algorithm returns bit-wise identical results, which demonstrates the robustness of our approach. We estimate that this project required around two and a half man-years of work.

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Hydrophilic interaction chromatography–mass spectrometry (HILIC–MS) was used for anionic metabolic profiling of urine from antibiotic-treated rats to study microbial–host co-metabolism. Rats were treated with the antibiotics penicillin G and streptomycin sulfate for four or eight days and compared to a control group. Urine samples were collected at day zero, four and eight, and analyzed by HILIC–MS. Multivariate data analysis was applied to the urinary metabolic profiles to identify biochemical variation between the treatment groups. Principal component analysis found a clear distinction between those animals receiving antibiotics and the control animals, with twenty-nine discriminatory compounds of which twenty were down-regulated and nine up-regulated upon treatment. In the treatment group receiving antibiotics for four days, a recovery effect was observed for seven compounds after cessation of antibiotic administration. Thirteen discriminatory compounds could be putatively identified based on their accurate mass, including aconitic acid, benzenediol sulfate, ferulic acid sulfate, hippuric acid, indoxyl sulfate, penicillin G, phenol and vanillin 4-sulfate. The rat urine samples had previously been analyzed by capillary electrophoresis (CE) with MS detection and proton nuclear magnetic resonance (1H NMR) spectroscopy. Using CE–MS and 1H NMR spectroscopy seventeen and twenty-five discriminatory compounds were found, respectively. Both hippuric acid and indoxyl sulfate were detected across all three platforms. Additionally, eight compounds were observed with both HILIC–MS and CE–MS. Overall, HILIC–MS appears to be highly complementary to CE–MS and 1H NMR spectroscopy, identifying additional compounds that discriminate the urine samples from antibiotic-treated and control rats.

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SOA (Service Oriented Architecture), workflow, the Semantic Web, and Grid computing are key enabling information technologies in the development of increasingly sophisticated e-Science infrastructures and application platforms. While the emergence of Cloud computing as a new computing paradigm has provided new directions and opportunities for e-Science infrastructure development, it also presents some challenges. Scientific research is increasingly finding that it is difficult to handle “big data” using traditional data processing techniques. Such challenges demonstrate the need for a comprehensive analysis on using the above mentioned informatics techniques to develop appropriate e-Science infrastructure and platforms in the context of Cloud computing. This survey paper describes recent research advances in applying informatics techniques to facilitate scientific research particularly from the Cloud computing perspective. Our particular contributions include identifying associated research challenges and opportunities, presenting lessons learned, and describing our future vision for applying Cloud computing to e-Science. We believe our research findings can help indicate the future trend of e-Science, and can inform funding and research directions in how to more appropriately employ computing technologies in scientific research. We point out the open research issues hoping to spark new development and innovation in the e-Science field.