Showing papers by "Delft University of Technology published in 2011"
TL;DR: Considering future bottlenecks in raw materials, options for the recycling of rare-earth intermetallics for hard magnets will be discussed and their potential impact on energy efficiency is discussed.
Abstract: A new energy paradigm, consisting of greater reliance on renewable energy sources and increased concern for energy effi ciency in the total energy lifecycle, has accelerated research into energy-related technologies. Due to their ubiquity, magnetic materials play an important role in improving the effi ciency and performance of devices in electric power generation, conditioning, conversion, transportation, and other energy-use sectors of the economy. This review focuses on the state-of-the-art hard and soft magnets and magnetocaloric materials, with an emphasis on their optimization for energy applications. Specifi cally, the impact of hard magnets on electric motor and transportation technologies, of soft magnetic materials on electricity generation and conversion technologies, and of magnetocaloric materials for refrigeration technologies, are discussed. The synthesis, characterization, and property evaluation of the materials, with an emphasis on structure‐property relationships, are discussed in the context of their respective markets, as well as their potential impact on energy effi ciency. Finally, considering future bottlenecks in raw materials, options for the recycling of rare-earth intermetallics for hard magnets will be discussed.
2,465 citations
TL;DR: A short-time objective intelligibility measure (STOI) is presented, which shows high correlation with the intelligibility of noisy and time-frequency weighted noisy speech (e.g., resulting from noise reduction) of three different listening experiments and showed better correlation with speech intelligibility compared to five other reference objective intelligible models.
Abstract: In the development process of noise-reduction algorithms, an objective machine-driven intelligibility measure which shows high correlation with speech intelligibility is of great interest. Besides reducing time and costs compared to real listening experiments, an objective intelligibility measure could also help provide answers on how to improve the intelligibility of noisy unprocessed speech. In this paper, a short-time objective intelligibility measure (STOI) is presented, which shows high correlation with the intelligibility of noisy and time-frequency weighted noisy speech (e.g., resulting from noise reduction) of three different listening experiments. In general, STOI showed better correlation with speech intelligibility compared to five other reference objective intelligibility models. In contrast to other conventional intelligibility models which tend to rely on global statistics across entire sentences, STOI is based on shorter time segments (386 ms). Experiments indeed show that it is beneficial to take segment lengths of this order into account. In addition, a free Matlab implementation is provided.
1,847 citations
TL;DR: The results indicate that the current clouds need an order of magnitude in performance improvement to be useful to the scientific community, and show which improvements should be considered first to address this discrepancy between offer and demand.
Abstract: Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time sharing, clouds serve with a single set of physical resources a large user base with different needs. Thus, clouds have the potential to provide to their owners the benefits of an economy of scale and, at the same time, become an alternative for scientists to clusters, grids, and parallel production environments. However, the current commercial clouds have been built to support web and small database workloads, which are very different from typical scientific computing workloads. Moreover, the use of virtualization and resource time sharing may introduce significant performance penalties for the demanding scientific computing workloads. In this work, we analyze the performance of cloud computing services for scientific computing workloads. We quantify the presence in real scientific computing workloads of Many-Task Computing (MTC) users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific goals. Then, we perform an empirical evaluation of the performance of four commercial cloud computing services including Amazon EC2, which is currently the largest commercial cloud. Last, we compare through trace-based simulation the performance characteristics and cost models of clouds and other scientific computing platforms, for general and MTC-based scientific computing workloads. Our results indicate that the current clouds need an order of magnitude in performance improvement to be useful to the scientific community, and show which improvements should be considered first to address this discrepancy between offer and demand.
915 citations
TL;DR: In this article, a two-component bio-chemical self-healing agent consisting of bacterial spores and calcium lactate is released from the particle by crack ingress water, which results in physical closure of micro cracks.
Abstract: Crack formation is a commonly observed phenomenon in concrete structures. Although micro crack formation hardly affects structural properties of constructions, increased permeability due to micro crack networking may substantially reduce the durability of concrete structures due to risk of ingress of aggressive substances particularly in moist environments. In order to increase the often observed autogenous crack-healing potential of concrete, specific healing agents can be incorporated in the concrete matrix. The aim of this study was to quantify the crack-healing potential of a specific and novel two-component bio-chemical self-healing agent embedded in porous expanded clay particles, which act as reservoir particles and replace part of regular concrete aggregates. Upon crack formation the two-component bio-chemical agent consisting of bacterial spores and calcium lactate are released from the particle by crack ingress water. Subsequent bacterially mediated calcium carbonate formation results in physical closure of micro cracks. Experimental results showed crack-healing of up to 0.46 mm-wide cracks in bacterial concrete but only up to 0.18 mm-wide cracks in control specimens after 100 days submersion in water. That the observed doubling of crack-healing potential was indeed due to metabolic activity of bacteria was supported by oxygen profile measurements which revealed O2 consumption by bacteria-based but not by control specimens. We therefore conclude that this novel bio-chemical self-healing agent shows potential for particularly increasing durability aspects of concrete constructions in wet environments.
809 citations
TL;DR: In this article, the authors studied metabolic networks and the reactions of organisms to various external conditions and showed that metabolic networks are a major tool for studying the metabolism of organisms and cells, and through this approach much has been learned about metabolic networks.
Abstract: Over the past decade, metabolomics has developed into a major tool for studying the metabolism of organisms and cells, and through this approach much has been learned about metabolic networks and the reactions of organisms to various external conditions ([Lay et al., 2006][1]). Most of this work
801 citations
TL;DR: An overview of the main additions and improvements implemented in GATE since the publication of the initial GATE paper is presented, which includes new models available to simulate optical and hadronic processes, novelties in modelling tracer, organ or detector motion, new options for speeding up GATE simulations, and preliminary results regarding the validation of GATE V6 for radiation therapy applications.
Abstract: GATE (Geant4 Application for Emission Tomography) is a Monte Carlo simulation platform developed by the OpenGATE collaboration since 2001 and first publicly released in 2004. Dedicated to the modelling of planar scintigraphy, single photon emission computed tomography (SPECT) and positron emission tomography (PET) acquisitions, this platform is widely used to assist PET and SPECT research. A recent extension of this platform, released by the OpenGATE collaboration as GATE V6, now also enables modelling of x-ray computed tomography and radiation therapy experiments. This paper presents an overview of the main additions and improvements implemented in GATE since the publication of the initial GATE paper (Jan et al 2004 Phys. Med. Biol. 49 4543–61). This includes new models available in GATE to simulate optical and hadronic processes, novelties in modelling tracer, organ or detector motion, new options for speeding up GATE simulations, examples illustrating the use of GATE V6 in radiotherapy applications and 0031-9155/11/040881+21$33.00 © 2011 Institute of Physics and Engineering in Medicine Printed in the UK 881
706 citations
Princeton University1, Utrecht University2, Goethe University Frankfurt3, University of California, Irvine4, National Center for Atmospheric Research5, Delft University of Technology6, George Mason University7, University of Bonn8, McGill University9, University of Washington10, Goddard Space Flight Center11, University of Illinois at Urbana–Champaign12, University of Reading13, University of Oxford14
TL;DR: In this article, the authors discuss the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles, and they call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
Abstract: Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
704 citations
TL;DR: It is shown that N2H4 is produced from the anammox substrates ammonium and nitrite and that nitric oxide is the direct precursor of N2 H4, which presents a new biochemical reaction forging an N–N bond and fills a lacuna in understanding of the biochemical synthesis of the N2 in the atmosphere.
Abstract: Two distinct microbial processes, denitrification and anaerobic ammonium oxidation (anammox), are responsible for the release of fixed nitrogen as dinitrogen gas (N(2)) to the atmosphere. Denitrification has been studied for over 100 years and its intermediates and enzymes are well known. Even though anammox is a key biogeochemical process of equal importance, its molecular mechanism is unknown, but it was proposed to proceed through hydrazine (N(2)H(4)). Here we show that N(2)H(4) is produced from the anammox substrates ammonium and nitrite and that nitric oxide (NO) is the direct precursor of N(2)H(4). We resolved the genes and proteins central to anammox metabolism and purified the key enzymes that catalyse N(2)H(4) synthesis and its oxidation to N(2). These results present a new biochemical reaction forging an N-N bond and fill a lacuna in our understanding of the biochemical synthesis of the N(2) in the atmosphere. Furthermore, they reinforce the role of nitric oxide in the evolution of the nitrogen cycle.
694 citations
TL;DR: The preparation and measurement of a multi-spin quantum register in a low-temperature solid-state system is demonstrated by implementing resonant optical excitation techniques originally developed in atomic physics, and compatibility with qubit control is shown.
Abstract: Initialization and read-out of coupled quantum systems are essential ingredients for the implementation of quantum algorithms. Single-shot read-out of the state of a multi-quantum-bit (multi-qubit) register would allow direct investigation of quantum correlations (entanglement), and would give access to further key resources such as quantum error correction and deterministic quantum teleportation. Although spins in solids are attractive candidates for scalable quantum information processing, their single-shot detection has been achieved only for isolated qubits. Here we demonstrate the preparation and measurement of a multi-spin quantum register in a low-temperature solid-state system by implementing resonant optical excitation techniques originally developed in atomic physics. We achieve high-fidelity read-out of the electronic spin associated with a single nitrogen-vacancy centre in diamond, and use this read-out to project up to three nearby nuclear spin qubits onto a well-defined state. Conversely, we can distinguish the state of the nuclear spins in a single shot by mapping it onto, and subsequently measuring, the electronic spin. Finally, we show compatibility with qubit control: we demonstrate initialization, coherent manipulation and single-shot read-out in a single experiment on a two-qubit register, using techniques suitable for extension to larger registers. These results pave the way for a test of Bell's inequalities on solid-state spins and the implementation of measurement-based quantum information protocols.
690 citations
California Institute of Technology1, New Mexico Institute of Mining and Technology2, Alfred Wegener Institute for Polar and Marine Research3, Langley Research Center4, Royal Netherlands Meteorological Institute5, Delft University of Technology6, Environment Canada7, Earth System Research Laboratory8, Finnish Meteorological Institute9, Danish Meteorological Institute10, Eindhoven University of Technology11, Arctic and Antarctic Research Institute12, National Institute for Environmental Studies13, Instituto Nacional de Técnica Aeroespacial14, University of Toronto15
TL;DR: It is demonstrated that chemical ozone destruction over the Arctic in early 2011 was—for the first time in the observational record—comparable to that in the Antarctic ozone hole.
Abstract: Chemical ozone destruction occurs over both polar regions in local winter–spring. In the Antarctic, essentially complete removal of lower-stratospheric ozone currently results in an ozone hole every year, whereas in the Arctic, ozone loss is highly variable and has until now been much more limited. Here we demonstrate that chemical ozone destruction over the Arctic in early 2011 was—for the first time in the observational record—comparable to that in the Antarctic ozone hole. Unusually long-lasting cold conditions in the Arctic lower stratosphere led to persistent enhancement in ozone-destroying forms of chlorine and to unprecedented ozone loss, which exceeded 80 per cent over 18–20 kilometres altitude. Our results show that Arctic ozone holes are possible even with temperatures much milder than those in the Antarctic. We cannot at present predict when such severe Arctic ozone depletion may be matched or exceeded. Since its emergence in the 1980s, the Antarctic ozone hole, the near-complete loss of lower-stratospheric ozone, has occurred every year. The possibility that a similar effect might occur in the Northern Hemisphere has been debated, but despite considerable variation in ozone levels in the Arctic, they had not reached the extremes seen in the south. Until this year. Observations made in the late winter and early spring of 2011 reveal ozone loss far outside the range previously observed over the Northern Hemisphere, comparable to some Antarctic ozone holes. The formation of the hole was driven by an unusually long cold snap and a high level of ozone-destroying chlorine. Although this effect is dramatic, it is difficult to predict whether similar Arctic ozone holes will develop in future.
597 citations
TL;DR: In this article, a computational procedure has been developed for simulating non-hydrostatic, free-surface, rotational flows in one and two horizontal dimensions using SWASH.
TL;DR: The resulting integrated SWAN + ADCIRC system is highly scalable and allows for localized increases in resolution without the complexity or cost of nested meshes or global interpolation between heterogeneous meshes.
TL;DR: In this paper, the authors advocate using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology and discuss how the multiple-hypothesis approach provides the flexibility to formulate alternative representations describing both individual processes and the overall system.
Abstract: Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This commentary advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple-hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple-hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component nonidentifiabilities. As part of discussing the advantages and limitations of multiple-hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple-hypothesis methodologies.
TL;DR: A survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000 is presented.
TL;DR: In this paper, a new MIL-101 material based on aluminum and containing amine functional groups has been synthesized, which can only be formed in very specific synthesis conditions, where both the metal source and the solvent used play a key role.
Abstract: A new MIL-101 material based on aluminum and containing amine functional groups has been synthesized. The pure phase NH2-MIL-101(Al) can only be formed in very specific synthesis conditions, where both the metal source and the solvent used play a key role. The resulting porous solid shows a high thermal and chemical stability, decomposing at temperatures above 650 K in air. The NH2-MIL-101(Al) framework offers an excellent trade off for separation of CO2: the combination of high stability, acceptable capacity at low adsorbate partial pressures, high selectivity, and fast regenerability makes this new material a very attractive candidate for applications like natural gas or biogas upgrading. CO2 capacities up to 62 wt % are obtained at room temperature and 3 MPa. In addition to an excellent separation performance, the NH2-MIL-101(Al) shows a high activity in the basic catalyzed Knoevenagel condensation of benzaldehyde with ethyl cyanoacetate at 313 K even in an as apolar a solvent as toluene (turn over fre...
TL;DR: In this paper, the authors used a heterogeneous dataset of 280 catchments located in the Eastern US to understand hydrologic similarity in a 6-dimensional signature space across a region with strong environmental gradients.
Abstract: Hydrologic similarity between catchments, derived from similarity in how catchments respond to precipitation input, is the basis for catchment classification, for transferability of information, for generalization of our hydrologic understanding and also for understanding the potential impacts of environmental change. An important question in this context is, how far can widely available hydrologic information (precipitation-temperature-streamflow data and generally available physical descriptors) be used to create a first order grouping of hydrologically similar catchments? We utilize a heterogeneous dataset of 280 catchments located in the Eastern US to understand hydrologic similarity in a 6-dimensional signature space across a region with strong environmental gradients. Signatures are defined as hydrologic response characteristics that provide insight into the hydrologic function of catchments. A Bayesian clustering scheme is used to separate the catchments into 9 homogeneous classes, which enable us to interpret hydrologic similarity with respect to similarity in climatic and landscape attributes across this region. We finally derive several hypotheses regarding controls on individual signatures from the analysis performed here.
TL;DR: Results demonstrate that fluorescent components extracted from F-EEMs using PARAFAC could be related to previously defined NOM fractions and that they could provide an alternative tool for evaluating the removal of Nom fractions of interest during water treatment.
TL;DR: The currently available data does not support the hypothesis that there is a significant difference between the ground reaction force of subjects experiencing lower-limb stress fracture and control groups, and the vertical loading rate was found to be significantly different between the two groups.
TL;DR: A comprehensive review of Uncertainty-Based Multidisciplinary Design Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace vehicles is presented.
TL;DR: An exact solution for G of an hourglass-shaped pore is presented, which agrees very well with the measurements without any adjustable parameters, and which is an improvement over the cylindrical approximation.
Abstract: We present measurements and theoretical modeling of the ionic conductance G of solid-state nanopores with 5-100 nm diameters, with and without DNA inserted into the pore. First, we show that it is essential to include access resistance to describe the conductance, in particular for larger pore diameters. We then present an exact solution for G of an hourglass-shaped pore, which agrees very well with our measurements without any adjustable parameters, and which is an improvement over the cylindrical approximation. Subsequently we discuss the conductance blockade ΔG due to the insertion of a DNA molecule into the pore, which we study experimentally as a function of pore diameter. We find that ΔG decreases with pore diameter, contrary to the predictions of earlier models that forecasted a constant ΔG. We compare three models for ΔG, all of which provide good agreement with our experimental data.
TL;DR: Another advantage derives from the possibility to co-immobilize two or more enzymes to provide CLEAs that are capable of catalyzing multiple biotransformations, independently or in sequence as catalytic cascade processes.
Abstract: Cross-linked enzyme aggregates (CLEAs) have many economic and environmental benefits in the context of industrial biocatalysis. They are easily prepared from crude enzyme extracts, and the costs of (often expensive) carriers are circumvented. They generally exhibit improved storage and operational stability towards denaturation by heat, organic solvents, and autoproteolysis and are stable towards leaching in aqueous media. Furthermore, they have high catalyst productivities (kilograms product per kilogram biocatalyst) and are easy to recover and recycle. Yet another advantage derives from the possibility to co-immobilize two or more enzymes to provide CLEAs that are capable of catalyzing multiple biotransformations, independently or in sequence as catalytic cascade processes.
TL;DR: Analysis and simulations demonstrate the practical impact of S-TLS in calibrating the mismatch effects of contemporary grid-based approaches to cognitive radio sensing, and robust direction-of-arrival estimation using antenna arrays, as well as formulating and solving (regularized) TLS optimization problems under sparsity constraints.
Abstract: Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data vector as well as in the regression matrix. However, existing TLS approaches do not account for sparsity possibly present in the unknown vector of regression coefficients. On the other hand, sparsity is the key attribute exploited by modern compressive sampling and variable selection approaches to linear regression, which include noise in the data, but do not account for perturbations in the regression matrix. The present paper fills this gap by formulating and solving (regularized) TLS optimization problems under sparsity constraints. Near-optimum and reduced-complexity suboptimum sparse (S-) TLS algorithms are developed to address the perturbed compressive sampling (and the related dictionary learning) challenge, when there is a mismatch between the true and adopted bases over which the unknown vector is sparse. The novel S-TLS schemes also allow for perturbations in the regression matrix of the least-absolute selection and shrinkage selection operator (Lasso), and endow TLS approaches with ability to cope with sparse, under-determined “errors-in-variables” models. Interesting generalizations can further exploit prior knowledge on the perturbations to obtain novel weighted and structured S-TLS solvers. Analysis and simulations demonstrate the practical impact of S-TLS in calibrating the mismatch effects of contemporary grid-based approaches to cognitive radio sensing, and robust direction-of-arrival estimation using antenna arrays.
TL;DR: The TOE (Technical, Organizational, and Environmental) framework as mentioned in this paper is a framework for characterising project complexity in large engineering projects, which can be used to adapt the front-end development phase of engineering projects to the particular complexity.
11 Jul 2011
TL;DR: A framework for user modeling on Twitter which enriches the semantics of Twitter messages and identifies topics and entities mentioned in tweets is introduced and how semantic enrichment enhances the variety and quality of the generated user profiles is revealed.
Abstract: How can micro-blogging activities on Twitter be leveraged for user modeling and personalization? In this paper we investigate this question and introduce a framework for user modeling on Twitter which enriches the semantics of Twitter messages (tweets) and identifies topics and entities (e.g. persons, events, products) mentioned in tweets. We analyze how strategies for constructing hashtag-based, entity-based or topic-based user profiles benefit from semantic enrichment and explore the temporal dynamics of those profiles. We further measure and compare the performance of the user modeling strategies in context of a personalized news recommendation system. Our results reveal how semantic enrichment enhances the variety and quality of the generated user profiles. Further, we see how the different user modeling strategies impact personalization and discover that the consideration of temporal profile patterns can improve recommendation quality.
TL;DR: The present state of the art in the use of enzymes and microorganisms for catalytic oxidation and oxyfunctionalization chemistry is reviewed.
TL;DR: In this paper, the influence of packaging design on taste impressions was examined and it was found that associations portrayed by shape curvature in particular transfer to taste experiences, but that these effects are most pronounced for participants with a sensitivity to design.
TL;DR: This paper analyzed the influence of commuters' attitudes toward the benefits of travel by bicycle (e.g. convenience, low cost, health benefits) on the mode choice decision for commutes to work.
Abstract: This paper analyses the influence of commuters' attitudes toward the benefits of travel by bicycle (e.g. convenience, low cost, health benefits) on the mode choice decision for commutes to work. We assume that when the commute journey intensifies, either in terms of distance or frequency, attitudes toward cycling become more positive. Factor analysis reveals three underlying attitudinal factors toward cycling to work: awareness, direct trip-based benefits and safety. The decision to cycle is influenced by the factor "direct trip-based benefit" at all distances, whereas the "awareness" is influential only over long distances. The decision to cycle every day is again affected by the "direct benefit" factor. The factors "safety" and "awareness" are important over shorter distances. Having a cycling habit increases the likelihood of cycling and a higher frequency of cycling. The perceived opinion of others only affects the mode choice over short distances suggesting indicates mode choice on longer commutes is based on one's own attitudes. These findings indicate that attitudes and other psychological factors have a relatively strong impact on the choice to commute by bicycle.
TL;DR: In this paper, a spray pyrolysis recipe was proposed to improve the external quantum efficiency of spray-deposited BiVO4 photoanodes by a factor of ∼7, leading to an unprecedented IPCE of 46%.
Abstract: BiVO4 has received much recent interest as a promising photocatalyst for oxygen evolution from water, but little is known about the factors that limit its performance as a photoanode. In this article, we report on highly efficient and reproducible BiVO4 photoanodes prepared by a new spray pyrolysis recipe. For undoped films deposited on a transparent conducting substrate (F-doped SnO2, FTO), electron transport and charge collection at the back-contact were found to limit the photoresponse. Electron transport could be greatly enhanced by donor-doping with 1% W, while the charge collection problem has been solved by introducing a thin (∼10 nm) interfacial layer of SnO2 in between the FTO and the BiVO4. This layer presumably acts as a hole mirror that prevents recombination via FTO-related defect states at the FTO/BiVO4 interface. By addressing these two issues, the external quantum efficiency (IPCE) of spray-deposited BiVO4 films was improved by a factor of ∼7, leading to an unprecedented IPCE of 46% (at 45...
TL;DR: A high-resolution imaging system based on the combination of ultrawideband transmission, multiple-input-multiple-output (MIMO) array, and synthetic aperture radar (SAR) is suggested and studied, showing a strong potential of the MIMO-SAR-based UWB system for security applications.
Abstract: A high-resolution imaging system based on the combination of ultrawideband (UWB) transmission, multiple-input-multiple-output (MIMO) array, and synthetic aperture radar (SAR) is suggested and studied. Starting from the resolution requirements, spatial sampling criteria for nonmonochromatic waves are investigated. Exploring the decisive influence of the system's fractional bandwidth (instead of previously claimed aperture sparsity) on the imaging capabilities of sparse aperture arrays, a MIMO linear array is designed based on the principle of effective aperture. For the antenna array, an optimized UWB antenna is designed allowing for distortionless impulse radiation with more than 150% fractional bandwidth. By combining the digital beamforming in the MIMO array with the SAR in the orthogonal direction, a high-resolution 3-D volumetric imaging system with a significantly reduced number of antenna elements is proposed. The proposed imaging system is experimentally verified against the conventional 2-D SAR under different conditions, including a typical concealed-weapon-detection scenario. The imaging results confirm the correctness of the proposed system design and show a strong potential of the MIMO-SAR-based UWB system for security applications.
TL;DR: It is demonstrated that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.
Abstract: It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.