Time‐multiplexed tiled projection system with improved pixel and spatial resolution

We propose two methods to increase the pixel and spatial resolution of Digital Micromirror Devices (DMD)‐based projectors by utilizing the large bandwidth provided by their high pattern rates. By varying the intensity of the illumination for each binary pattern displayed on the DMD, the time required to display an 8‐bit grayscale image can be reduced by up to factor 32 compared to using constant illumination and binary pulse‐width modulation (BPWM). The high image rate projection is then spatially separated by either using a galvanometer scanner or sequentially illuminating the DMD from different directions, thus creating multiple independently addressable projections which are then tiled to form a larger, higher resolution image.     

Flow-based reputation with uncertainty: evidence-based subjective logic

The concept of reputation is widely used as a measure of trustworthiness based on ratings from members in a community. The adoption of reputation systems, however, relies on their ability to capture the actual trustworthiness of a target. Several reputation models for aggregating trust information have been proposed in the literature. The choice of model has an impact on the reliability of the aggregated trust information as well as on the procedure used to compute reputations. Two prominent models are flow-based reputation (e.g., EigenTrust, PageRank) and subjective logic-based reputation. Flow-based models provide an automated method to aggregate trust information, but they are not able to express the level of uncertainty in the information. In contrast, subjective logic extends probabilistic models with an explicit notion of uncertainty, but the calculation of reputation depends on the structure of the trust network and often requires information to be discarded. These are severe drawbacks. In this work, we observe that the ‘opinion discounting’ operation in subjective logic has a number of basic problems. We resolve these problems by providing a new discounting operator that describes the flow of evidence from one party to another. The adoption of our discounting rule results in a consistent subjective logic algebra that is entirely based on the handling of evidence. We show that the new algebra enables the construction of an automated reputation assessment procedure for arbitrary trust networks, where the calculation no longer depends on the structure of the network, and does not need to throw away any information. Thus, we obtain the best of both worlds: flow-based reputation and consistent handling of uncertainties.     

Insights into virus capsid assembly from non-covalent mass spectrometry

The assembly of viral proteins into a range of macromolecular complexes of strictly defined architecture is one of Nature's wonders. Unraveling the details of these complex structures and the associated self-assembly pathways that lead to their efficient and precise construction will play an important role in the development of anti-viral therapeutics. It will also be important in bio-nanotechnology where there is a plethora of applications for such well-defined macromolecular complexes, including cell-specific drug delivery and as substrates for the formation of novel materials with unique electrical and magnetic properties. Mass spectrometry has the ability not only to measure masses accurately but also to provide vital details regarding the composition and stoichiometry of intact, non-covalently bound macromolecular complexes under near-physiological conditions. It is thus ideal for exploring the assembly and function of viruses. Over the past decade or so, significant advances have been made in this field, and these advances are summarized in this review, which covers the literature up to the end of 2007.     

Light Controlled Biohybrid Microbots

Biohybrid microbots integrate biological actuators and sensors into synthetic chassis with the aim of providing the building blocks of next-generation micro-robotics. One of the main challenges is the development of self-assembled systems with consistent behavior and such that they can be controlled independently to perform complex tasks. Herein, it is shown that, using light-driven bacteria as propellers, 3D printed microbots can be steered by unbalancing light intensity over different microbot parts. An optimal feedback loop is designed in which a central computer projects onto each microbot a tailor-made light pattern, calculated from its position and orientation. In this way, multiple microbots can be independently guided through a series of spatially distributed checkpoints. By exploiting a natural light-driven proton pump, these bio-hybrid microbots are able to extract mechanical energy from light with such high efficiency that, in principle, hundreds of these systems can be controlled simultaneously with a total optical power of just a few milliwatts.     

Photonic-aware neural networks

Neural Computing and Applications - Photonics-based neural networks promise to outperform electronic counterparts, accelerating neural network computations while reducing power consumption and...     

A Novel Particle/Photon Detector Based on a Superconducting Proximity Array of Nanodots

The current frontiers in the investigation of high-energy particles demand for new detection methods. Higher sensitivity to low-energy deposition, high-energy resolution to identify events and improve the background rejection, and large detector masses have to be developed to detect even an individual particle that weakly interacts with ordinary matter. Here, we will describe the concept and the layout of a novel superconducting proximity array which show dynamic vortex Mott insulator to metal transitions, as an ultra-sensitive compact radiation-particle detector.     

Nanostructured Materials for Room‐Temperature Gas Sensors

Sensor technology has an important effect on many aspects in our society, and has gained much progress, propelled by the development of nanoscience and nanotechnology. Current research efforts are directed toward developing high‐performance gas sensors with low operating temperature at low fabrication costs. A gas sensor working at room temperature is very appealing as it provides very low power consumption and does not require a heater for high‐temperature operation, and hence simplifies the fabrication of sensor devices and reduces the operating cost. Nanostructured materials are at the core of the development of any room‐temperature sensing platform. The most important advances with regard to fundamental research, sensing mechanisms, and application of nanostructured materials for room‐temperature conductometric sensor devices are reviewed here. Particular emphasis is given to the relation between the nanostructure and sensor properties in an attempt to address structure–property correlations. Finally, some future research perspectives and new challenges that the field of room‐temperature sensors will have to address are also discussed.