Measuring Brand-Related Content in Social Media: A Socialization Theory Perspective

Purpose- Building on consumer socialization theory, this study examined antecedents and consequences of generating and sharing brand-related content on social media in a restaurant context. Design/methodology/approach- A scale development process was undertaken to develop the scale for brand-related user-generated content. Then we tested the antecedents and consequences of brand-related user-generated content using 375 responses obtained through a mall-intercept survey. The hypotheses were tested using structural equation modelling with AMOS. Findings- Study findings revealed that age, time on Facebook, number of Facebook friends, Facebook usage intensity, and need for self-enhancement were key antecedents of both the generation and sharing of brand-related user-generated content. The results also indicated that gender, race, and need for self-affirmation were not significantly related to generating and sharing brand-related user-generated content. Both generating and sharing brand-related user-generated content were positively associated with attitude and intentions toward the restaurants. Originality/value- This study is the first to develop a brand-related user-generated content scale through a rigorous scale development process. It thus contributes to consumer socialization theory literature in considering social media as a socialization agent. The findings provide valuable insights for both academicians and social media managers and aid in enhancing brand-related user-generated content

Children and older adults exhibit distinct sub-optimal cost-benefit functions when preparing to move their eyes and hands

"© 2015 Gonzalez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited"Numerous activities require an individual to respond quickly to the correct stimulus. The provision of advance information allows response priming but heightened responses can cause errors (responding too early or reacting to the wrong stimulus). Thus, a balance is required between the online cognitive mechanisms (inhibitory and anticipatory) used to prepare and execute a motor response at the appropriate time. We investigated the use of advance information in 71 participants across four different age groups: (i) children, (ii) young adults, (iii) middle-aged adults, and (iv) older adults. We implemented 'cued' and 'non-cued' conditions to assess age-related changes in saccadic and touch responses to targets in three movement conditions: (a) Eyes only; (b) Hands only; (c) Eyes and Hand. Children made less saccade errors compared to young adults, but they also exhibited longer response times in cued versus non-cued conditions. In contrast, older adults showed faster responses in cued conditions but exhibited more errors. The results indicate that young adults (18 -25 years) achieve an optimal balance between anticipation and execution. In contrast, children show benefits (few errors) and costs (slow responses) of good inhibition when preparing a motor response based on advance information; whilst older adults show the benefits and costs associated with a prospective response strategy (i.e., good anticipation)

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

Universal features of correlated bursty behaviour

Inhomogeneous temporal processes, like those appearing in human communications, neuron spike trains, and seismic signals, consist of high-activity bursty intervals alternating with long low-activity periods. In recent studies such bursty behavior has been characterized by a fat-tailed inter-event time distribution, while temporal correlations were measured by the autocorrelation function. However, these characteristic functions are not capable to fully characterize temporally correlated heterogenous behavior. Here we show that the distribution of the number of events in a bursty period serves as a good indicator of the dependencies, leading to the universal observation of power-law distribution in a broad class of phenomena. We find that the correlations in these quite different systems can be commonly interpreted by memory effects and described by a simple phenomenological model, which displays temporal behavior qualitatively similar to that in real systems

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

INTRODUCTION Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice. METHODS More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account. RESULTS The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working. CONCLUSIONS With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years

Temperature influence on DXA measurements: bone mineral density acquisition in frozen and thawed human femora

<p>Abstract</p> <p>Background</p> <p>Determining bone mineral density (BMD) with dual-energy x-ray absorptiometry (DXA) is an established and widely used method that is also applied prior to biomechanical testing. However, DXA is affected by a number of factors. In order to delay decompositional processes, human specimens for biomechanical studies are usually stored at about -20°C; similarly, bone mineral density measurements are usually performed in the frozen state. The aim of our study was to investigate the influence of bone temperature on the measured bone mineral density.</p> <p>Methods</p> <p>Using DXA, bone mineral density measurements were taken in 19 fresh-frozen human femora, in the frozen and the thawed state. Water was used to mimic the missing soft tissue around the specimens. Measurements were taken with the specimens in standardized internal rotation. Total-BMD and single-BMD values of different regions of interest were used for evaluation.</p> <p>Results</p> <p>Fourteen of the 19 specimens showed a decrease in BMD after thawing. The measured total-BMD of the frozen specimens was significantly (1.4%) higher than the measured BMD of the thawed specimens.</p> <p>Conclusion</p> <p>Based on our findings we recommend that the measurement of bone density, for example prior to biomechanical testing, should be standardized to thawed or frozen specimens. Temperature should not be changed during measurements. When using score systems for data interpretation (e.g. T- or Z-score), BMD measurements should be performed only on thawed specimens.</p

Web-based monitoring tools for Resistive Plate Chambers in the CMS experiment at CERN

The Resistive Plate Chambers (RPC) are used in the CMS experiment at the trigger level and also in the standard offline muon reconstruction. In order to guarantee the quality of the data collected and to monitor online the detector performance, a set of tools has been developed in CMS which is heavily used in the RPC system. The Web-based monitoring (WBM) is a set of java servlets that allows users to check the performance of the hardware during data taking, providing distributions and history plots of all the parameters. The functionalities of the RPC WBM monitoring tools are presented along with studies of the detector performance as a function of growing luminosity and environmental conditions that are tracked over time