Do psychosocial factors moderate the association of fixed-term employment with work interference with family and sleeping problems in registered nurses: A cross-sectional questionnaire survey

Background: The use affixed-term employment has increased lately, particularly in Europe and in the health care sector. Previous studies have shown that especially among the health care sector employee's organizational justice perceptions and job control are important factors that are directly related to the welfare and attitudes of employees and may also help to buffer the negative impacts of many detrimental factors.

Interference between Competing Pathways in Atomic Harmonic Generation

We investigate the influence of the autoionizing 3s3p6nl resonances on the fifth harmonic generated by 200–240 nm laser fields interacting with Ar. To determine the influence of a multielectron response we develop the capability within time-dependent R-matrix theory to determine the harmonic spectra generated. The fifth harmonic is affected by interference between the response of a 3s electron and the response of a 3p electron, as demonstrated by the asymmetric profiles in the harmonic yields as functions of wavelength.

Enhanced approach for latent semantic indexing using wavelet transform

Latent semantic indexing (LSI) is a technique used for intelligent information retrieval (IR). It can be used as an alternative to traditional keyword matching IR and is attractive in this respect because of its ability to overcome problems with synonymy and polysemy. This study investigates various aspects of LSI: the effect of the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the key stage of the LSI process; and the effect of different threshold types in the HWT on the search results. The developed method allows the visualisation and processing of the term document matrix, generated in the LSI process, using HWT. The results have shown that precision can be increased by applying the HWT as a preprocessing step, with better results for hard thresholding than soft thresholding, whereas standard SVD-based LSI remains the most effective way of searching in terms of recall value.

RNA interference targeting cathepsin B of the carcinogenic liver fluke, Opisthorchis viverrini

Functional genomics have not been reported for Opisthorchis viverrini or the related fish-borne fluke, Clonorchis sinensis. Here we describe the introduction by square wave electroporation of Cy3-labeled small RNA into adult O. viverrini worms. Adult flukes were subjected to square wave electroporation employing a single pulse for 20 ms of 125V in the presence of 50 µg/ml of Cy3-siRNA. The parasites tolerated this manipulation and, at 24 and 48 h after electroporation, fluorescence from the Cy3-siRNA was evident throughout the parenchyma of the worms, with strong fluorescence evident in the guts and reproductive organs of the adult worms. Second, other worms were treated using the same electroporation settings with double stranded RNA targeting an endogenous papain-like cysteine protease, cathepsin B. This manipulation resulted in a significant reduction in specific mRNA levels encoding cathepsin B, and a significant reduction in cathepsin B activity against the diagnostic peptide, Z-Arg-Arg-AMC. This appears to be the first report of introduction of reporter genes into O. viverrini and the first report of experimental RNA interference (RNAi) in this fluke. The findings indicated the presence of an intact RNAi pathway in these parasites which, in turn, provides an opportunity to probe gene functions in this neglected tropical disease pathogen.

Turning the tide: A critique of Natural Semantic Metalanguage from a translation studies perspective

Starting from the premise that human communication is predicated on translational phenomena, this paper applies theoretical insights and practical findings from Translation Studies to a critique of Natural Semantic Metalanguage (NSM), a theory of semantic analysis developed by Anna Wierzbicka. Key tenets of NSM, i.e. (1) culture-specificity of complex concepts; (2) the existence of a small set of universal semantic primes; and (3) definition by reductive paraphrase, are discussed critically with reference to the notions of untranslatability, equivalence, and intra-lingual translation, respectively. It is argued that a broad spectrum of research and theoretical reflection in Translation Studies may successfully feed into the study of cognition, meaning, language, and communication. The interdisciplinary exchange between Translation Studies and linguistics may be properly balanced, with the former not only being informed by but also informing and interrogating the latter.

Extracting Query Interfaces Based on Form Structures and Semantic Similarity

Web databases are now pervasive. Such a database can be accessed via its query interface (usually HTML query form) only. Extracting Web query interfaces is a critical step in data integration across multiple Web databases, which creates a formal representation of a query form by extracting a set of query conditions in it. This paper presents a novel approach to extracting Web query interfaces. In this approach, a generic set of query condition rules are created to define query conditions that are semantically equivalent to SQL search conditions. Query condition rules represent the semantic roles that labels and form elements play in query conditions, and how they are hierarchically grouped into constructs of query conditions. To group labels and form elements in a query form, we explore both their structural proximity in the hierarchy of structures in the query form, which is captured by a tree of nested tags in the HTML codes of the form, and their semantic similarity, which is captured by various short texts used in labels, form elements and their properties. We have implemented the proposed approach and our experimental results show that the approach is highly effective.

MTERF1 Binds mtDNA to Prevent Transcriptional Interference at the Light-Strand Promoter but Is Dispensable for rRNA Gene Transcription Regulation

Mitochondrial transcription termination factor 1, MTERF1, has been reported to couple rRNA gene transcription initiation with termination and is therefore thought to be a key regulator of mammalian mitochondrial ribosome biogenesis. The prevailing model is based on a series of observations published over the last two decades, but no in vivo evidence exists to show that MTERF1 regulates transcription of the heavy-strand region of mtDNA containing the rRNA genes. Here, we demonstrate that knockout of Mterf1 in mice has no effect on mitochondrial rRNA levels or mitochondrial translation. Instead, loss of Mterf1 influences transcription initiation at the light-strand promoter, resulting in a decrease of de novo transcription manifested as reduced 7S RNA levels. Based on these observations, we suggest that MTERF1 does not regulate heavy-strand transcription, but rather acts to block transcription on the opposite strand of mtDNA to prevent transcription interference at the light-strand promoter.

Characterization of Inter-Body Interference in Context Aware Body Area Networking (CABAN)

The characterization and understanding of body to body communication channels is a pivotal step in the development of emerging wireless applications such as ad-hoc personnel localisation and context aware body area networks (CABAN). The latter is a recent innovation where the inherent mobility of body area networks can be used to improve the coexistence of multiple co-located BAN users. Rather than simply accepting reductions in communication performance, sensed changes in inter-network co-channel interference levels may facilitate intelligent inter-networking; for example merging or splitting with other BANs that remain in the same domain. This paper investigates the inter-body interference using controlled measurements of the full mesh interconnectivity between two ambulatory BANs operating in the same environment at 2.45 GHz. Each of the twelve network nodes reported received signal strength to allow for the creation of carrier to interference ratio time series with an overall entire mesh sampling period of 54 ms. The results indicate that even with two mobile networks, it is possible to identify the onset of co-channel interference as the BAN users move towards each other and, similarly, the transition to more favourable physical layer channel conditions as they move apart. © 2011 IEEE.

Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding

In this paper, we introduce an application of matrix factorization to produce corpus-derived, distributional
models of semantics that demonstrate cognitive plausibility. We find that word representations
learned by Non-Negative Sparse Embedding (NNSE), a variant of matrix factorization, are sparse,
effective, and highly interpretable. To the best of our knowledge, this is the first approach which
yields semantic representation of words satisfying these three desirable properties. Though extensive
experimental evaluations on multiple real-world tasks and datasets, we demonstrate the superiority
of semantic models learned by NNSE over other state-of-the-art baselines.

Strudel: A corpus-based semantic model based on properties and types

Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.

EEG decoding of semantic category reveals distributed representations for single concepts

Achieving a clearer picture of categorial distinctions in the brain is essential for our understanding of the conceptual lexicon, but much more fine-grained investigations are required in order for this evidence to contribute to lexical research. Here we present a collection of advanced data-mining techniques that allows the category of individual concepts to be decoded from single trials of EEG data. Neural activity was recorded while participants silently named images of mammals and tools, and category could be detected in single trials with an accuracy well above chance, both when considering data from single participants, and when group-training across participants. By aggregating across all trials, single concepts could be correctly assigned to their category with an accuracy of 98%. The pattern of classifications made by the algorithm confirmed that the neural patterns identified are due to conceptual category, and not any of a series of processing-related confounds. The time intervals, frequency bands and scalp locations that proved most informative for prediction permit physiological interpretation: the widespread activation shortly after appearance of the stimulus (from 100. ms) is consistent both with accounts of multi-pass processing, and distributed representations of categories. These methods provide an alternative to fMRI for fine-grained, large-scale investigations of the conceptual lexicon. © 2010 Elsevier Inc.