Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet

We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like “large”, “huge” and “gigantic” with respect to their attribute (“size”). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.     

A decision support system for environmental effects monitoring

The Environmental Effects Monitoring (EEM) Statistical Assessment Tool (SAT) Decision Support System (DSS) has been developed to provide a user-friendly data analysis, display and decision support tool for Canada's federal environmental effects monitoring program for the pulp and paper and mining industries. The target users include industries, consultants, regional EEM coordinators, National EEM Office and scientists involved in EEM-related research. The tool allows the assessment of the effects of effluent from industrial or other sources on fish and benthic populations. Effect endpoints, which are used as indicators of potentially important effluent effects, are measured at effluent-exposed sites and are compared statistically to measures at reference sites, in order to determine if changes have occurred and the magnitude of the changes. The main driver of the EEM-SAT DSS is its rule-based expert system. The results are used in assessing the adequacy of existing regulations for protecting aquatic environments.     

Finding the number of clusters in ordered dissimilarities

As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational data. Several numerical examples are presented to illustrate the effectiveness of the proposed method.     

Utilizing Iron's Attractive Chemical and Magnetic Properties in Microrocket Design,Extended Motion,and Unique Performance

All‐in‐one material for microrocket propulsion featuring acid‐based bubble generation and magnetic guidance is presented. Electrochemically deposited iron serves as both a propellant, toward highly efficient self‐propulsion in acidic environments, and as a magnetic component enabling complete motion control. The new microrockets display longer lifetime and higher propulsion efficiency compared to previously reported active metal zinc‐based microrockets due to the chemical properties of iron and the unique structure of the microrockets. These iron‐based microrockets also demonstrate unique and attractive cargo towing and autonomous release capabilities. The latter is realized upon loss of the magnetic properties due to acid‐driven iron dissolution. More interestingly, these bubble‐propelled microrockets assemble via magnetic interactions into a variety of complex configurations and train structures, which enrich the behavior of micromachines. Modeling of the magnetic forces during the microrocket assembly and cargo capture confirms these unique experimentally observed assembly and cargo‐towing behaviors. These findings provide a new concept of blending propellant and magnetic components into one, toward simplifying the design and fabrication of artificial micro/nanomachines, realizing new functions and capabilities for a variety of future applications.     

Fungal xylanases‐mediated synthesis of silver nanoparticles for catalytic and biomedical applications

Green synthesis of nanoparticles has fuelled the use of biomaterials to synthesise a variety of metallic nanoparticles. The current study investigates the use of xylanases of Aspergillus niger L3 (NEA) and Trichoderma longibrachiatum L2 (TEA) to synthesise silver nanoparticles (AgNPs). Characterisation of AgNPs was carried out using UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy, while their effectiveness as antimicrobial, antioxidant, catalytic, anticoagulant, and thrombolytic agents were determined. The colloidal AgNPs was brownish with surface plasmon resonance at 402.5 and 410 nm for NEA‐AgNPs and TEA‐AgNPs, respectively; while FTIR indicated that protein molecules were responsible for the capping and stabilisation of the nanoparticles. The spherical nanoparticles had size of 15.21–77.49 nm. The nanoparticles significantly inhibited the growth of tested bacteria (63.20–88.10%) and fungi (82.20–86.10%), and also scavenged DPPH (37.48–79.42%) and hydrogen peroxide (20.50–96.50%). In addition, the AgNPs degraded malachite green (78.97%) and methylene blue (25.30%). Furthermore, the AgNPs displayed excellent anticoagulant and thrombolytic activities using human blood. This study has demonstrated the potential of xylanases to synthesise AgNPs which is to the best of our knowledge the first record of such. The present study underscores the relevance of xylanases in nanobiotechnology.Inspec keywords: visible spectra, catalysis, ultraviolet spectra, silver, microorganisms, antibacterial activity, transmission electron microscopy, surface plasmon resonance, nanoparticles, nanofabrication, colloids, blood, Fourier transform infrared spectra, particle sizeOther keywords: Ag, fungal xylanases‐mediated synthesis, silver nanoparticles, catalytic applications, biomedical applications, green synthesis, metallic nanoparticles, Trichoderma longibrachiatum L2, transmission electron microscopy, antimicrobial agents, antioxidant agents, catalytic agents, thrombolytic agents, surface plasmon resonance, spherical nanoparticles, FTIR spectra, anticoagulant agents, colloidal nanoparticles, biomaterials, Aspergillus niger L3, UV‐vis spectroscopy, Fourier transform infrared spectroscopy, protein molecules, DPPH, hydrogen peroxide, malachite green, methylene blue, human blood, nanobiotechnology     

Metamaterial-based graphene thermal emitter

A thermal emitter composed of a frequency-selective surface metamaterial layer and a hexagonal boron nitride-encapsulated graphene filament is demonstrated. The broadband thermal emission of the metamaterial (consisting of ring resonators) was tailored into two discrete bands, and the measured reflection and emission spectra agreed well with the simulation results. The high modulation frequencies that can be obtained in these devices, coupled with their operation in air, confirm their feasibility for use in applications such as gas sensing.

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Map‐aided localization in sparse global positioning system environments using vision and particle filtering

A map‐aided localization approach using vision, inertial sensors when available, and a particle filter is proposed and empirically evaluated. The approach, termed PosteriorPose, uses a Bayesian particle filter to augment global positioning system (GPS) and inertial navigation solutions with vision‐based measurements of nearby lanes and stop lines referenced against a known map of environmental features. These map‐relative measurements are shown to improve the quality of the navigation solution when GPS is available, and they are shown to keep the navigation solution converged in extended GPS blackouts. Measurements are incorporated with careful hypothesis testing and error modeling to account for non‐Gaussian and multimodal errors committed by GPS and vision‐based detection algorithms. Using a set of data collected with Cornell's autonomous car, including a measure of truth via a high‐precision differential corrections service, an experimental investigation of important design elements of the PosteriorPose estimator is conducted. The algorithm is shown to statistically outperform a tightly coupled GPS/inertial navigation solution both in full GPS coverage and in extended GPS blackouts. Statistical performance is also studied as a function of road type, filter likelihood models, bias models, and filter integrity tests. © 2011 Wiley Periodicals, Inc.     

Static timing analysis for modeling QoS in networks-on-chip

Networks-on-chip (NoCs) are used in a growing number of SoCs and multi-core processors. Because messages compete for the NoC’s shared resources, quality of service and resource allocation are major concerns for system designers. In particular, a model for the properties of packet delivery through the network is desirable. We present a methodology for packet-level static timing analysis in NoCs. Our methodology quickly and accurately gauges the performance parameters of a virtual-channel wormhole NoC without simulation. The network model can handle any topology, link capacities, and buffer sizes. It provides per-flow delay analysis that is orders-of-magnitude faster than simulation while being significantly more accurate than prior static modeling techniques. Using a carefully derived and reduced Markov chain, the model can statically represent the dynamic network state. Usage of the model in a placement optimization problem is shown as an example application.