Mining methodologies from NLP publications: A case study in automatic terminology recognition

The task of reviewing scientific publications and keeping up with the literature in a particular domain is extremely time-consuming. Extraction and exploration of methodological information, in particular, requires systematic understanding of the literature, but in many cases is performed within a limited context of publications that can be manually reviewed by an individual or group. Automated methodology identification could provide an opportunity for systematic retrieval of relevant documents and for exploring developments within a given discipline. In this paper we present a system for the identification of methodology mentions in scientific publications in the area of natural language processing, and in particular in automatic terminology recognition. The system comprises two major layers: the first layer is an automatic identification of methodological sentences; the second layer highlights methodological phrases (segments). Each mention is categorised in four semantic categories: Task, Method, Resource/Feature and Implementation. Extraction and classification of the segments is formalised as a sequence tagging problem and four separate phrase-based Conditional Random Fields are used to accomplish the task. The system has been evaluated on a manually annotated corpus comprising 45 full text articles. The results for the segment level annotation show an F-measure of 53% for identification of Task and Method mentions (with 70% precision), whereas the F-measures for Resource/Feature and Implementation identification were 61% (with 67% precision) and 75% (with 86% precision) respectively. At the document-level, an F-measure of 72% (with 81% precision) for Task mentions, 60% (with 81% precision) for Method mentions, 74% (with 78% precision) for the Resource/Feature and 79% (with 81% precision) for the Implementation categories have been achieved. We provide a detailed analysis of errors and explore the impact that the particular groups of features have on the extraction of methodological segments.     

The stress stability of olanzapine: studies of interactions with excipients in solid state pharmaceutical formulations

Stress stability testing represents an important part of the drug development process. It is used as an important tool for the identification of degradation products and degradation pathways, as well as for the assessment of changes in physical form of drug molecules. The impact of excipients on the stability of olanzapine confirms that levels of impurities and degradants are limiting parameters and are therefore used for stability evaluation. The major degradation product of olanzapine was identified as 2-methyl-5,10-dihydro-4H-thieno[2,3-b][1,5]benzodiazepine-4-one (III). The structure of III was determined by using LC-MS, IR and NMR. Compatibility and stress stability results demonstrated that tablet formulations of olanzapine are sensitive to temperature and moisture. In samples protected from moisture, the increase in concentration of III was shown to be highly temperature dependent and the degradation followed zero-order kinetics. In addition, studies of olanzapine with excipients and in formulated tablets revealed polymorphic phase changes in some samples, influenced by a combination of stress temperature and humidity conditions. Polymorphic transitions were monitored using x-ray powder diffraction (XRPD) analysis and exhibited no correlation between the phase change (appearance of a new polymorph) and the degradation process.     

Multiexcitonic dual emission in CdSe/CdS tetrapods and nanorods

CdSe/CdS semiconductor nanocrystal heterostructures are currently of high interest for the peculiar electronic structure offering unique optical properties. Here, we show that nanorods and tetrapods made of such material combination enable efficient multiexcitonic emission, when the volume of the nanoparticle is maximized. This condition is fulfilled by tetrapods with an arm length of 55 nm and results in a dual emission with comparable intensities from the CdS arms and CdSe core. The relative intensities of the dual emission, originating from exciton phase-space filling and reduced Auger recombination, can be effectively modulated by the photon fluence of the pump laser. The results, obtained under steady-state detection conditions, highlight the properties of tetrapods as multiexciton dual-color emitters.     

Linearisation of asymmetrical Doherty amplifier by the even-order non-linear signals

This paper considers the linearisation of an asymmetrical two-way Doherty amplifier by the method that uses the second harmonics and fourth-order non-linear signals for linearisation. These even-order signals for linearisation are extracted at the output of the peaking amplifier, adjusted in amplitude and phase and injected at the input and output of the carrier amplifier transistor in the Doherty configuration. The effect of linearisation has been experimentally confirmed on a fabricated asymmetrical Doherty amplifier with the additional circuit for linearisation. The suppression of the third-order intermodulation products has been carried out for two-tone test, 64QAM and WCDMA digitally modulated signals in a range of signal power.     

On the Feedback Capacity of Power-Constrained Gaussian Noise Channels With Memory

For a stationary additive Gaussian-noise channel with a rational noise power spectrum of a finite-order L, we derive two new results for the feedback capacity under an average channel input power constraint. First, we show that a very simple feedback-dependent Gauss-Markov source achieves the feedback capacity, and that Kalman-Bucy filtering is optimal for processing the feedback. Based on these results, we develop a new method for optimizing the channel inputs for achieving the Cover-Pombra block-length- n feedback capacity by using a dynamic programming approach that decomposes the computation into n sequentially identical optimization problems where each stage involves optimizing O(L ²) variables. Second, we derive the explicit maximal information rate for stationary feedback-dependent sources. In general, evaluating the maximal information rate for stationary sources requires solving only a few equations by simple nonlinear programming. For first-order autoregressive and/or moving average (ARMA) noise channels, this optimization admits a closed-form maximal information rate formula. The maximal information rate for stationary sources is a lower bound on the feedback capacity, and it equals the feedback capacity if the long-standing conjecture, that stationary sources achieve the feedback capacity, holds     

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

General purpose graphics processing units (GPGPUs) have gained much popularity in scientific computing to speedup computational intensive workloads. Resource allocation in terms of power and subcarriers assignment, in current wireless standards, is one of the challenging problems due to its high computational complexity requirement. The Hungarian algorithm (HA), which has been extensively applied to linear assignment problems (LAPs), has been seen to provide encouraging result in resource allocation for wireless communication systems. This paper presents a compute unified device architecture (CUDA) implementation of the HA on graphics processing unit (GPU) for this problem. HA has been implemented on a parallel architecture to solve the subcarrier assignment problem and maximize spectral efficiency. The proposed implementation is achieved by using the “Kuhn‐Munkres” algorithm with effective modifications, in order to fully exploit the capabilities of modern GPU devices. A cost matrix for maximum assignment has been defined leading to a low complexity matrix compression along with highly optimized CUDA reduction and parallel alternating path search process. All these optimizations lead to an efficient implementation with superior performance when compared with existing parallel implementations.     

Optimal Scheduling of Utility Electric Vehicle Fleet Offering Ancillary Services

Vehicle‐to‐grid presents a mechanism to meet the key requirements of an electric power system, using electric vehicles (EVs) when they are parked. The most economic ancillary service is that of frequency regulation, which imposes some constraints regarding the period and duration of time the vehicles have to be connected to the grid. The majority of research explores the profitability of the aggregator, while the perspective of the EV fleet owner, in terms of their need for usage of their fleet, remains neglected. In this paper, the optimal allocation of available vehicles on a day‐ahead basis using queuing theory and fuzzy multi‐criteria methodology has been determined. The proposed methodology is illustrated on the daily scheduling of EVs in an electricity distribution company.     

Detection of Structural Features in Biological Signals

In this article structures in biological signals are treated. The simpler—directly visible in the signals, which still demand serious methods and algorithms in the feature detection, similarity investigation and classification. The major actions in this domain are of geometric, thus simpler sort, though there are still hard problems related to simple situations. The other large class of less simple signals unsuitable for direct geometric or statistic approach, are signals with interesting frequency components and behavior, those suitable for spectroscopic analysis. Semantics of spectroscopy, spectroscopic structures and research demanded operations and transformations on spectra and time spectra are presented. The both classes of structures and related analysis methods and tools share a large common set of algorithms, all of which aiming to the full automatization. Some of the signal features present in the brain signal patterns are demonstrated, with the contexts relevant in BCI, brain computer interfaces. Mathematical representations, invariants and complete characterization of structures in broad variety of biological signals are in the central focus.