67 research outputs found

    NeuroIS-Alternative or Complement to Existing Methods? Illustrating the Holistic Effects of Neuroscience and Self-Reported Data in the Context of Technostress Research

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    This is the final version. Available from Association for Information Systems via the DOI in this recordRecent research has made a strong case for the importance of NeuroIS methods for IS research. It has suggested that NeuroIS contributes to an improved explanation and prediction of IS phenomena. Yet, such research is unclear on the source of this improvement; while some studies indicate that NeuroIS constitutes an alternative to psychometrics, implying that the two methods assess the same dimension of an underlying IS construct, other studies indicate that NeuroIS constitutes a complement to psychometrics, implying that the two methods assess different dimensions of an IS construct. To clarify the role of NeuroIS in IS research and its contribution to IS research, in this study, we examine whether NeuroIS and psychometrics/psychological methods constitute alternatives or complements. We conduct this examination in the context of technostress, an emerging IS phenomenon to which both methods are relevant. We use the triangulation approach to explore the relationship between physiological and psychological/self-reported data. Using this approach, we argue that both kinds of data tap into different aspects of technostress and that, together, they can yield a more complete or holistic understanding of the impact of technostress on a theoretically-related outcome, rendering them complements. Then, we test this proposition empirically by probing the correlation between a psychological and a physiological measure of technostress in combination with an examination of their incremental validity in explaining performance on a computer-based task. The results show that the physiological stress measure (salivary alpha-amylase) explains and predicts variance in performance on the computer-based task over and above the prediction afforded by the self-reported stress measure. We conclude that NeuroIS is a critical complement to IS research

    New Method to Calculate the Sign and Relative Strength of Magnetic Interactions in Low-Dimensional Systems on the Basis of Structural Data

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    The connection of strength of magnetic interactions and type ordering the magnetic moments with crystal chemical characteristics in low-dimensional magnets is investigated. The new method to calculate the sign and relative strength of magnetic interactions in low-dimensional systems on the basis of the structural data is proposed. This method allows to estimate magnetic interactions not only inside low-dimensional fragments but also between them, and also to predict the possibility of the occurrence of magnetic phase transitions and anomalies of the magnetic interactions. Moreover, it can be used for search of low-dimensional magnets among the compounds whose crystal structures are known. The possibilities of the method are illustrated in an example of research of magnetic interactions in familiar low-dimensional magnets SrCu2(BO3)2, CaCuGe2O6, CaV4O9, Cu2Te2O5Cl2, Cu2Te2O5Br2, BaCu2Si2O7, BaCu2Ge2O7, BaCuSi2O6, LiCu2O2, and NaCu2O2.Comment: 18 pages, 8 figures, 2 tables, published versio

    Quantitative PCR reveals strong spatial and temporal variation of the wasting disease pathogen, Labyrinthula zosterae in northern European eelgrass (Zostera marina) beds

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    Seagrass beds are the foundation species of functionally important coastal ecosystems worldwide. The world’s largest losses of the widespread seagrass Zostera marina (eelgrass) have been reported as a consequence of wasting disease, an infection with the endophytic protist Labyrinthula zosterae. During one of the most extended epidemics in the marine realm, ~90% of East and Western Atlantic eelgrass beds died-off between 1932 and 1934. Today, small outbreaks continue to be reported, but the current extent of L. zosterae in European meadows is completely unknown. In this study we quantify the abundance and prevalence of the wasting disease pathogen among 19 Z. marina populations in northern European coastal waters, using quantitative PCR (QPCR) with primers targeting a species specific portion of the internally transcribed spacer (ITS1) of L. zosterae. Spatially, we found marked variation among sites with abundances varying between 0 and 126 cells mg−1 Z. marina dry weight (mean: 5.7 L. zosterae cells mg−1 Z. marina dry weight ±1.9 SE) and prevalences ranged from 0–88.9%. Temporarily, abundances varied between 0 and 271 cells mg−1 Z. marina dry weight (mean: 8.5±2.6 SE), while prevalences ranged from zero in winter and early spring to 96% in summer. Field concentrations accessed via bulk DNA extraction and subsequent QPCR correlated well with prevalence data estimated via isolation and cultivation from live plant tissue. L. zosterae was not only detectable in black lesions, a sign of Labyrinthula-induced necrosis, but also occurred in green, apparently healthy tissue. We conclude that L. zosterae infection is common (84% infected populations) in (northern) European eelgrass populations with highest abundances during the summer months. In the light of global climate change and increasing rate of marine diseases our data provide a baseline for further studies on the causes of pathogenic outbreaks of L. zosterae

    Detection of segregation distortion loci in triticale (x Triticosecale Wittmack) based on a high-density DArT marker consensus genetic linkage map

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    <p>Abstract</p> <p>Background</p> <p>Triticale is adapted to a wide range of abiotic stress conditions, is an important high-quality feed stock and produces similar grain yield but more biomass compared to other crops. Modern genomic approaches aimed at enhancing breeding progress in cereals require high-quality genetic linkage maps. Consensus maps are genetic maps that are created by a joint analysis of the data from several segregating populations and different approaches are available for their construction. The phenomenon that alleles at a locus deviate from the Mendelian expectation has been defined as segregation distortion. The study of segregation distortion is of particular interest in doubled haploid (DH) populations due to the selection pressure exerted on the plants during the process of their establishment.</p> <p>Results</p> <p>The final consensus map, constructed out of six segregating populations derived from nine parental lines, incorporated 2555 DArT markers mapped to 2602 loci (1929 unique). The map spanned 2309.9 cM with an average number of 123.9 loci per chromosome and an average marker density of one unique locus every 1.2 cM. The R genome showed the highest marker coverage followed by the B genome and the A genome. In general, locus order was well maintained between the consensus linkage map and the component maps. However, we observed several groups of loci for which the colinearity was slightly uneven. Among the 2602 loci mapped on the consensus map, 886 showed distorted segregation in at least one of the individual mapping populations. In several DH populations derived by androgenesis, we found chromosomes (2B, 3B, 1R, 2R, 4R and 7R) containing regions where markers exhibited a distorted segregation pattern. In addition, we observed evidence for segregation distortion between pairs of loci caused either by a predominance of parental or recombinant genotypes.</p> <p>Conclusions</p> <p>We have constructed a reliable, high-density DArT marker consensus genetic linkage map as a basis for genomic approaches in triticale research and breeding, for example for multiple-line cross QTL mapping experiments. The results of our study exemplify the tremendous impact of different DH production techniques on allele frequencies and segregation distortion covering whole chromosomes.</p

    Human plasma protein N-glycosylation

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