Achieving Online Relationship Marketing via Tourism Blogs: A Social Network Perspective

Drawing upon the literature on social network analysis, this research examines how part-time marketers use tourism blogs to conduct relationship marketing with their customers. The findings from an interpretive case study indicate that the network pictures of part-time blog marketers can be categorized into three distinct models: the “fan club,” the “compliance,” and the “creative outlet” models. Our findings also suggest that different network pictures lead to different network management strategies for blogs. Moreover, providing instrumental support and especially material support by blog marketers play significant roles in aggrandizing this transitivity, which helps to attract more visitors to blog sites. We believe that the innovation and the potential connections derived from the individualistic styles of some bloggers and the hedonic emotional support given to tourism blogs should not be overlooked. Our findings also indicate that more incentives and freedom should be provided to tourism business bloggers in order to prosper in their grassroots use of technology. Available at: https://aisel.aisnet.org/pajais/vol5/iss4/2

The Power Of Networks And Information Flows--In Circuits Of Power Perspective On Online Religion

This paper examines the tension between ICT users and legitimate authority in a network society. To explore this tension, this study reports a case study in the setting of a Taiwanese Christian church, particularly how the church authority was affected by the adoption of new technology. Drawing from a circuits of power perspective, the result of this study reveals that the intertwined relationship among information technology, social structure and users during the process of technology adoption and assimilation. The findings indicate that the implementation of Internet technologies in the church has challenged the traditional role of authority and distorted the power of information flow among stakeholders in the church. Our work shed light on how Internet technologies shape, and are shaped by the membership and belief in the context of religion

Making Sense of Corporate Tour-Guide Bloggers’ Networking Behavior: A Social Network Perspective

Drawing on studies of social networks and technology sensemaking, this study examines tour guide bloggers’ perceptions of their corporate blogs and how their perceptions and interpretations lead to different types of relationships in their blog networks. We conduct a qualitative case study of a major Taiwanese travel agency. Our findings suggest that corporate bloggers as actors make different senses on blogging and these senses lead them to establish different levels of closeness to their alters (other network actors). Providing social support and especially material support play significant roles in aggrandizing the transitivity, which help to attract more visitors to their blogs. However, the innovation and potential connections that may follow from the individualistic styles of some bloggers in addition to the hedonic emotional support to a travel blog should not be overlooked. Corporate bloggers should thus consider offering more incentives and should be given freedom to prosper in their grassroots use of technology

Building Legitimacy for Green IS Innovations in Taiwan

The environmental concerns are leading to the growing interest in the adoption of Green IS. From legitimacy perspective, this paper argues that the adoption and diffusion of Green IS among organizations are modulated by pragmatic, normative, and cultural-cognitive influences in the institutional environment. The study therefore applies topology of legitimacy to develop a taxonomy to understand actors’ strategies in shaping the understanding and development of Green IS. Using content analysis of news articles in Taiwan, the study contributes to a practical understanding of the complex institutional influences in forming the greener industry

Generalizing Terwilliger's likelihood approach: a new score statistic to test for genetic association

<p>Abstract</p> <p>Background:</p> <p>In this paper, we propose a one degree of freedom test for association between a candidate gene and a binary trait. This method is a generalization of Terwilliger's likelihood ratio statistic and is especially powerful for the situation of one associated haplotype. As an alternative to the likelihood ratio statistic, we derive a score statistic, which has a tractable expression. For haplotype analysis, we assume that phase is known.</p> <p>Results:</p> <p>By means of a simulation study, we compare the performance of the score statistic to Pearson's chi-square statistic and the likelihood ratio statistic proposed by Terwilliger. We illustrate the method on three candidate genes studied in the Leiden Thrombophilia Study.</p> <p>Conclusion:</p> <p>We conclude that the statistic follows a chi square distribution under the null hypothesis and that the score statistic is more powerful than Terwilliger's likelihood ratio statistic when the associated haplotype has frequency between 0.1 and 0.4 and has a small impact on the studied disorder. With regard to Pearson's chi-square statistic, the score statistic has more power when the associated haplotype has frequency above 0.2 and the number of variants is above five.</p

'Who will I become?': possible selves and depression symptoms in adolescents

Adolescence is an important period for the development of the possible self. It is also a time when depression is prevalent. The cognitive theory of depression proposes that a negative view of the future is a key feature of depression. Targeting these negative thoughts about the future during cognitive behavioural therapy may be helpful in depression. However, little is known about how adolescents envisage their future (i.e. possible) self, or if the content is associated with affect. The aim of this quantitative study is to describe how adolescents describe their 'possible self' and examine the relationship between the valence of the possible self and depression in adolescents. Adolescents ( = 584) aged 13-18 years were recruited via opportunity sampling via their schools and completed measures of depression symptoms (the Mood and Feelings Questionnaire) and the 'possible self' (a variant of the 'I Will Be' task). Possible selves were coded for content and valence. Despite depression severity, the most common possible selves generated by adolescents were positive and described interpersonal roles. The valence of the possible self was associated with depression severity but only accounted for 3.4% of the variance in severity. The results support the cognitive model of depression. However, adolescents with elevated symptoms of depression were able to generate positive, possible selves and therefore may remain somewhat 'hopeful' about their future despite clinically significant depression symptoms. Future-oriented treatment approaches such as cognitive behavioural therapy that focus on changing unhelpful negative future thinking may not be appropriate for this population

Comprehensive Peroxidase-Based Hematologic Profiling for The Prediction of 1-Year Myocardial Infarction and Death

Background— Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone. Methods and Results— Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in ≥10% of subjects with events) and 24 low-risk (observed in ≥10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% (P\u3c0.001) of patients to different risk categories for death/MI when added to traditional risk factors. Conclusion— Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI

Comprehensive Peroxidase-Based Hematologic Profiling for The Prediction of 1-Year Myocardial Infarction and Death

Background— Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone. Methods and Results— Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in ≥10% of subjects with events) and 24 low-risk (observed in ≥10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% (P\u3c0.001) of patients to different risk categories for death/MI when added to traditional risk factors. Conclusion— Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI

Theory of imaging a photonic crystal with transmission near-field optical microscopy

While near-field scanning optical microscopy (NSOM) can provide optical images with resolution much better than the diffraction limit, analysis and interpretation of these images is often difficult. We present a theory of imaging with transmission NSOM that includes the effects of tip field, tip/sample coupling, light propagation through the sample and light collection. We apply this theory to analyze experimental NSOM images of a nanochannel glass (NCG) array obtained in transmission mode. The NCG is a triangular array of dielectric rods in a dielectric glass matrix with a two-dimensional photonic band structure. We determine the modes for the NCG photonic crystal and simulate the observed data. The calculations show large contrast at low numerical aperture (NA) of the collection optics and detailed structure at high NA consistent with the observed images. We present calculations as a function of NA to identify how the NCG photonic modes contribute to and determine the spatial structure in these images. Calculations are presented as a function of tip/sample position, sample index contrast and geometry, and aperture size to identify the factors that determine image formation with transmission NSOM in this experiment.Comment: 28 pages of ReVTex, 14 ps figures, submitted to Phys. Rev.

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Active galactic nuclei (AGN) are believed to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The variability of an AGN's brightness over time can reveal important information about the physical properties of the underlying black hole. The temporal variability is believed to follow a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). With upcoming wide-field surveys set to observe 100 million AGN in multiple bandpass filters, there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are well-suited for modeling AGN time series data, as they can explicitly capture the underlying stochastic dynamics. In this work, we modify latent SDEs to jointly reconstruct the unobserved portions of multivariate AGN light curves and infer their physical properties such as the black hole mass. Our model is trained on a realistic physics-based simulation of ten-year AGN light curves, and we demonstrate its ability to fit AGN light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multi-output Gaussian process regression baseline.Comment: 10 pages, 5 figures, accepted at the ICLR 2023 Workshop on Physics for Machine Learnin