Quantum Complexity of Testing Group Commutativity

We consider the problem of testing the commutativity of a black-box group specified by its k generators. The complexity (in terms of k) of this problem was first considered by Pak, who gave a randomized algorithm involving O(k) group operations. We construct a quite optimal quantum algorithm for this problem whose complexity is in . The algorithm uses and highlights the power of the quantization method of Szegedy. For the lower bound of , we give a reduction from a special case of Element Distinctness to our problem. Along the way, we prove the optimality of the algorithm of Pak for the randomized model.     

Fast Minor Testing in Planar Graphs

Minor Containment is a fundamental problem in Algorithmic Graph Theory used as a subroutine in numerous graph algorithms. A model of a graph H in a graph G is a set of disjoint connected subgraphs of G indexed by the vertices of H, such that if {u,v} is an edge of H, then there is an edge of G between components C _u and C _v . A graph H is a minor of G if G contains a model of H as a subgraph. We give an algorithm that, given a planar n-vertex graph G and an h-vertex graph H, either finds in time $\mathcal{O}(2^{\mathcal{O}(h)} \cdot n +n^{2}\cdot\log n)$ a model of H in G, or correctly concludes that G does not contain H as a minor. Our algorithm is the first single-exponential algorithm for this problem and improves all previous minor testing algorithms in planar graphs. Our technique is based on a novel approach called partially embedded dynamic programming.     

New wireless connection between user and VE using speech processing

This paper presents a novel speak-to-VR virtual-reality peripheral network (VRPN) server based on speech processing. The server uses a microphone array as a speech source and streams the results of the process through a Wi-Fi network. The proposed VRPN server provides a handy, portable and wireless human machine interface that can facilitate interaction in a variety interfaces and application domains including HMD- and CAVE-based virtual reality systems, flight and driving simulators and many others. The VRPN server is based on a speech processing software development kits and VRPN library in C++. Speak-to-VR VRPN works well even in the presence of background noise or the voices of other users in the vicinity. The speech processing algorithm is not sensitive to the user’s accent because it is trained while it is operating. Speech recognition parameters are trained by hidden Markov model in real time. The advantages and disadvantages of the speak-to-VR server are studied under different configurations. Then, the efficiency and the precision of the speak-to-VR server for a real application are validated via a formal user study with ten participants. Two experimental test setups are implemented on a CAVE system by using either Kinect Xbox or array microphone as input device. Each participant is asked to navigate in a virtual environment and manipulate an object. The experimental data analysis shows promising results and motivates additional research opportunities.     

Influence of nitrogen uptake and heat treatment on the microstructural characteristics and corrosion performance of X190CrVMo20-4-1 steel produced by supersolidus liquid-phase sintering

Martensitic stainless steel powder exhibits a high nitrogen uptake when densified by supersolidus liquid-phase sintering in a nitrogen atmosphere, but the optimum uptake, which is beneficial to its resistance to corrosion, is unknown. In this study, the resistance of high-carbon martensitic stainless steel X190CrVMo20-4-1 densified in a nitrogen atmosphere against pitting corrosion was explored. This was to clarify the impact of nitrogen uptake in the steel matrix in the quenched and tempered condition on its corrosion resistance in an aqueous solution. Samples were subjected to potentiodynamic polarisation tests in a de-aerated, 1 wt% NaCl solution. Results revealed that the X190 steel densified in a nitrogen atmosphere at 40-kPa pressure, subjected to deep cryogenic treatment in liquid nitrogen at an austenitising temperature of 1150°C and tempered at 200°C, had the best pitting corrosion resistance with a breakdown potential of 142 ± 11 mV/SCE and a hardness of 738 ± 4 HV10. The matrix around the M₇C₃ carbides and MX carbonitrides suffered high pitting susceptibility. The implications of this study serve as a basis for the improvement of the functional properties of steels.     

Characterization of GPVI- or GPVI-CD39-Coated Nanoparticles and Their Impact on In Vitro Thrombus Formation

Traditional antithrombotic agents commonly share a therapy-limiting side effect, as they increase the overall systemic bleeding risk. A novel approach for targeted antithrombotic therapy is nanoparticles. In other therapeutic fields, nanoparticles have enabled site-specific delivery with low levels of toxicity and side effects. Here, we paired nanotechnology with an established dimeric glycoprotein VI-Fc (GPVI-Fc) and a GPVI-CD39 fusion protein, thereby combining site-specific delivery and new antithrombotic drugs. Poly(lactic-co-glycolic acid) (PLGA) nanoparticles, NP-BSA, NP-GPVI and NP-GPVI-CD39 were characterized through electron microscopy, atomic force measurements and flow cytometry. Light transmission aggregometry enabled analysis of platelet aggregation. Thrombus formation was observed through flow chamber experiments. NP-GPVI and NP-GPVI-CD39 displayed a characteristic surface coating pattern. Fluorescence properties were identical amongst all samples. NP-GPVI and NP-GPVI-CD39 significantly impaired platelet aggregation. Thrombus formation was significantly impaired by NP-GPVI and was particularly impaired by NP-GPVI-CD39. The receptor-coated nanoparticles NP-GPVI and the bifunctional molecule NP-GPVI-CD39 demonstrated significant inhibition of in vitro thrombus formation. Consequently, the nanoparticle-mediated antithrombotic effect of GPVI-Fc, as well as GPVI-CD39, and an additive impact of CD39 was confirmed. In conclusion, NP-GPVI and NP-GPVI-CD39 may serve as a promising foundation for a novel therapeutic approach regarding targeted antithrombotic therapy.     

Efficacy of an advanced sewage treatment plant in southeast Queensland, Australia, to remove estrogenic chemicals

The estrogenicity profile of domestic sewage during treatment at a medium-sized (3800 EP) advanced biological nutrient removal plant in Queensland, Australia, was characterized using a sheep estrogen receptor binding assay (ERBA) and the MCF-7 breast cancer cell proliferation assay (E-Screen). The raw influent was highly estrogenic (20-54 ng/L EEq), and primary treatment resulted in a slight increase in estrogenicity that was detected in one of the assays (6-80 ng/L). Concurrent chemical analysis suggested that most of the estrogenicity in the influent was due to natural hormones (>48%). Secondary activated sludge treatment followed by nitrification/denitrification effectively removed > 95% of the estrogenic activity (to <0.75-2.6 ng/L), and estrogenicity of the final tertiary-treated effluent was below the detection limit of both assays (<0.75 ng/L).