The augmented convention offering: the impact of destination and product images on attendees' perceived benefits

In order to benefit from the significant dual spending of meetings, incentives, conventions/conferences, exhibitions/events (MICE) attendees, destination marketers have attempted to identify key success criteria that enable increased convention and exhibition participation. Given the significant growth of the MICE industry in Asia, this study examines the role of destination and product images on Chinese attendees' perceptions of the benefits acquired through convention and exhibition participation in the regions of Macau and Hong Kong. Data were collected using an intercept survey and a systematic random sampling procedure. Structural Equation Modeling was used to test a model that integrates two strands of literature from the fields of marketing and international business: Product–Country Image (PCI) and the Augmented Service Offering (ASO). Results show that a favorable overall destination image positively impacts the image of the MICE product of the destination, which, in turn, leads to a greater perception of personal and professional benefit acquisition. Based on these findings, the authors propose the Augmented MICE Offering as a theoretical framework that can serve as a foundation for more comprehensive inquiry into the decision-making process of the MICE attendee and postattendance behavioral impacts. The study also provides important positioning and communication implications for MICE destinations

Knowledge-driven entity recognition and disambiguation in biomedical text

Entity recognition and disambiguation (ERD) for the biomedical domain are notoriously difficult problems due to the variety of entities and their often long names in many variations. Existing works focus heavily on the molecular level in two ways. First, they target scientific literature as the input text genre. Second, they target single, highly specialized entity types such as chemicals, genes, and proteins. However, a wealth of biomedical information is also buried in the vast universe of Web content. In order to fully utilize all the information available, there is a need to tap into Web content as an additional input. Moreover, there is a need to cater for other entity types such as symptoms and risk factors since Web content focuses on consumer health. The goal of this thesis is to investigate ERD methods that are applicable to all entity types in scientific literature as well as Web content. In addition, we focus on under-explored aspects of the biomedical ERD problems -- scalability, long noun phrases, and out-of-knowledge base (OOKB) entities. This thesis makes four main contributions, all of which leverage knowledge in UMLS (Unified Medical Language System), the largest and most authoritative knowledge base (KB) of the biomedical domain. The first contribution is a fast dictionary lookup method for entity recognition that maximizes throughput while balancing the loss of precision and recall. The second contribution is a semantic type classification method targeting common words in long noun phrases. We develop a custom set of semantic types to capture word usages; besides biomedical usage, these types also cope with non-biomedical usage and the case of generic, non-informative usage. The third contribution is a fast heuristics method for entity disambiguation in MEDLINE abstracts, again maximizing throughput but this time maintaining accuracy. The fourth contribution is a corpus-driven entity disambiguation method that addresses OOKB entities. The method first captures the entities expressed in a corpus as latent representations that comprise in-KB and OOKB entities alike before performing entity disambiguation.Die Erkennung und Disambiguierung von Entitäten für den biomedizinischen Bereich stellen, wegen der vielfältigen Arten von biomedizinischen Entitäten sowie deren oft langen und variantenreichen Namen, große Herausforderungen dar. Vorhergehende Arbeiten konzentrieren sich in zweierlei Hinsicht fast ausschließlich auf molekulare Entitäten. Erstens fokussieren sie sich auf wissenschaftliche Publikationen als Genre der Eingabetexte. Zweitens fokussieren sie sich auf einzelne, sehr spezialisierte Entitätstypen wie Chemikalien, Gene und Proteine. Allerdings bietet das Internet neben diesen Quellen eine Vielzahl an Inhalten biomedizinischen Wissens, das vernachlässigt wird. Um alle verfügbaren Informationen auszunutzen besteht der Bedarf weitere Internet-Inhalte als zusätzliche Quellen zu erschließen. Außerdem ist es auch erforderlich andere Entitätstypen wie Symptome und Risikofaktoren in Betracht zu ziehen, da diese für zahlreiche Inhalte im Internet, wie zum Beispiel Verbraucherinformationen im Gesundheitssektor, relevant sind. Das Ziel dieser Dissertation ist es, Methoden zur Erkennung und Disambiguierung von Entitäten zu erforschen, die alle Entitätstypen in Betracht ziehen und sowohl auf wissenschaftliche Publikationen als auch auf andere Internet-Inhalte anwendbar sind. Darüber hinaus setzen wir Schwerpunkte auf oft vernachlässigte Aspekte der biomedizinischen Erkennung und Disambiguierung von Entitäten, nämlich Skalierbarkeit, lange Nominalphrasen und fehlende Entitäten in einer Wissensbank. In dieser Hinsicht leistet diese Dissertation vier Hauptbeiträge, denen allen das Wissen von UMLS (Unified Medical Language System), der größten und wichtigsten Wissensbank im biomedizinischen Bereich, zu Grunde liegt. Der erste Beitrag ist eine schnelle Methode zur Erkennung von Entitäten mittels Lexikonabgleich, welche den Durchsatz maximiert und gleichzeitig den Verlust in Genauigkeit und Trefferquote (precision and recall) balanciert. Der zweite Beitrag ist eine Methode zur Klassifizierung der semantischen Typen von Nomen, die sich auf gebräuchliche Nomen von langen Nominalphrasen richtet und auf einer selbstentwickelten Sammlung von semantischen Typen beruht, die die Verwendung der Nomen erfasst. Neben biomedizinischen können diese Typen auch nicht-biomedizinische und allgemeine, informationsarme Verwendungen behandeln. Der dritte Beitrag ist eine schnelle Heuristikmethode zur Disambiguierung von Entitäten in MEDLINE Kurzfassungen, welche den Durchsatz maximiert, aber auch die Genauigkeit erhält. Der vierte Beitrag ist eine korpusgetriebene Methode zur Disambiguierung von Entitäten, die speziell fehlende Entitäten in einer Wissensbank behandelt. Die Methode wandelt erst die Entitäten, die in einem Textkorpus ausgedrückt aber nicht notwendigerweise in einer Wissensbank sind, in latente Darstellungen um und führt anschließend die Disambiguierung durch

Reasons For Visiting Destinations Motives Are Not Motives For Visiting — Caveats and Questions For Destination Marketers

Many tourism studies consider elicited reasons for undertaking a behavior (e.g., visiting a destination) as the basis from which tourist motives are inferred. Such an approach is problematic principally because it ignores a dual motivational system in which explicit as well as implicit types of motives drive behavior. This paper tackles the conceptual challenge of differentiating explicit from implicit motives in tourism studies or the lack thereof. It reviews the need to discriminate between the two constructs, theorize their interrelationship and assess their relative significance in predicting a wide and varied interconnected array of travel behavior

Impact of Probe Substrate Selection on Cytochrome P450 Reaction Phenotyping Using the Relative Activity Factor

ABSTRACT Accurately assessing the contribution of cytochrome P450 (P450) isoforms to overall metabolic clearance is important for prediction of clinical drug-drug interactions (DDIs). The relative activity factor (RAF) approach in P450 reaction phenotyping assumes that the interaction between P450-selective probes and testing systems is the same as the interaction of drug candidate with those systems. To test this assumption, an intersystem clearance ratio (ICR) was created to evaluate the difference in values between RAF-scaled intrinsic clearance (CL int ) and measured CL int in human liver microsomes (HLMs). The RAF value for CYP3A4 or CYP2C9 derived from a particular P450-selective probe reaction was applied to calculate RAF-scaled CL int for other probe reactions of the same P450 isoform in a crossover manner and compared with the measured HLM CL int . When RAF derived from midazolam or nifedipine was used for CYP3A4, the ICR for testosterone 6b-hydroxylation was 31 and 25, respectively, suggesting significantly diverse interactions of CYP3A4 probes with the testing systems. Such ICR differences were less profound among probes for CYP2C9. In addition, these RAF values were applied to losartan and meloxicam, whose metabolism is mostly CYP2C9 mediated. Only using the RAF derived from testosterone for CYP3A4 produced the expected CYP2C9 contribution of 72%-87% and 47%-69% for metabolism of losartan and meloxicam, respectively. RAF derived from other CYP3A4 probes would have attributed predominantly to CYP3A4 and led to incorrect prediction of DDIs. Our study demonstrates a significant impact of probe substrate selection on P450 phenotyping using the RAF approach, and the ICR may provide a potential solution

Redesigning inpatient care: testing the effectiveness of an Accountable Care Team model

BACKGROUND US healthcare underperforms on quality and safety metrics. Inpatient care constitutes an immense opportunity to intervene to improve care. OBJECTIVE Describe a model of inpatient care and measure its impact. DESIGN A quantitative assessment of the implementation of a new model of care. The graded implementation of the model allowed us to follow outcomes and measure their association with the dose of the implementation. SETTING AND PATIENTS Inpatient medical and surgical units in a large academic health center. INTERVENTION Eight interventions rooted in improving interprofessional collaboration (IPC), enabling data-driven decisions, and providing leadership were implemented. MEASUREMENTS Outcome data from August 2012 to December 2013 were analyzed using generalized linear mixed models for associations with the implementation of the model. Length of stay (LOS) index, case-mix index–adjusted variable direct costs (CMI-adjusted VDC), 30-day readmission rates, overall patient satisfaction scores, and provider satisfaction with the model were measured. RESULTS The implementation of the model was associated with decreases in LOS index (P < 0.0001) and CMI-adjusted VDC (P = 0.0006). We did not detect improvements in readmission rates or patient satisfaction scores. Most providers (95.8%, n = 92) agreed that the model had improved the quality and safety of the care delivered. CONCLUSIONS Creating an environment and framework in which IPC is fostered, performance data are transparently available, and leadership is provided may improve value on both medical and surgical units. These interventions appear to be well accepted by front-line staff. Readmission rates and patient satisfaction remain challenging

Initial uptake, time to treatment, and real-world effectiveness of all-oral direct-acting antivirals for hepatitis C virus infection in the United States: A retrospective cohort analysis

BACKGROUND: Data on initiation and utilization of direct-acting antiviral therapies for hepatitis C virus infection in the United States are limited. This study evaluated treatment initiation, time to treatment, and real-world effectiveness of direct-acting antiviral therapy in individuals with hepatitis C virus infection treated during the first 2 years of availability of all-oral direct-acting antiviral therapies. METHODS: A retrospective cohort analysis was undertaken using electronic medical records and chart review abstraction of hepatitis C virus-infected individuals aged >18 years diagnosed with chronic hepatitis C virus infection between January 1, 2014, and December 31, 2015 from the Indiana University Health database. RESULTS: Eight hundred thirty people initiated direct-acting antiviral therapy during the 2-year observation window. The estimated incidence of treatment initiation was 8.8%±0.34% at the end of year 1 and 15.0%±0.5% at the end of year 2. Median time to initiating therapy was 300 days. Using a Cox regression analysis, positive predictors of treatment initiation included age (hazard ratio, 1.008), prior hepatitis C virus treatment (1.74), cirrhosis (2.64), and history of liver transplant (1.5). History of drug abuse (0.43), high baseline alanine aminotransferase levels (0.79), hepatitis B virus infection (0.41), and self-pay (0.39) were negatively associated with treatment initiation. In the evaluable population (n = 423), 83.9% (95% confidence interval, 80.1-87.3%) of people achieved sustained virologic response. CONCLUSION: In the early years of the direct-acting antiviral era, <10% of people diagnosed with chronic hepatitis C virus infection received direct-acting antiviral treatment; median time to treatment initiation was 300 days. Future analyses should evaluate time to treatment initiation among those with less advanced fibrosis

Perfectionism and exam performance: The mediating effect of task-approach goals

Perfectionistic strivings are positively correlated with students’ achievement goals and exam performance. However, so far no study has employed a prospective design investigating whether achievement goals mediate the positive relationship between perfectionistic strivings and exam performance. In the present study, 100 university students completed a measure of self-oriented perfectionism and socially prescribed perfectionism (Hewitt & Flett, 1991) and received a chapter from a textbook to study for 2-4 days. Then they returned to the lab to complete a measure of achievement goals following the 3 x 2 model (Elliot, Murayama, & Pekrun, 2011) and sit a mock exam testing their knowledge of the chapter. Multiple regressions showed that socially prescribed perfectionism negatively predicted exam performance when the overlap with self-oriented perfectionism was controlled for. In contrast, self-oriented perfectionism—a defining indicator of perfectionistic strivings—positively predicted exam performance. Moreover, task-approach goals mediated the positive relationship between self-oriented perfectionism and exam performance. The findings suggest that perfectionistic strivings make students adopt task-approach goals that help them achieve better results on exams

Human Tissue-Resident Memory T Cells Are Defined by Core Transcriptional and Functional Signatures in Lymphoid and Mucosal Sites

Tissue-resident memory T cells (TRMs) in mice mediate optimal protective immunity to infection and vaccination, while in humans, the existence and properties of TRMs remain unclear. Here, we use a unique human tissue resource to determine whether human tissue memory T cells constitute a distinct subset in diverse mucosal and lymphoid tissues. We identify a core transcriptional profile within the CD69+ subset of memory CD4+ and CD8+ T cells in lung and spleen that is distinct from that of CD69− TEM cells in tissues and circulation and defines human TRMs based on homology to the transcriptional profile of mouse CD8+ TRMs. Human TRMs in diverse sites exhibit increased expression of adhesion and inhibitory molecules, produce both pro-inflammatory and regulatory cytokines, and have reduced turnover compared with circulating TEM, suggesting unique adaptations for in situ immunity. Together, our results provide a unifying signature for human TRM and a blueprint for designing tissue-targeted immunotherapies

Findings of the WMT 2017 Biomedical Translation Shared Task

Automatic translation of documents is an important task in many domains, including the biological and clinical domains. The second edition of the Biomedical Translation task in the Conference of Machine Translation focused on the automatic translation of biomedical-related documents between English and various European languages. This year, we addressed ten languages: Czech, German, English, French, Hungarian, Polish, Portuguese, Spanish, Romanian and Swedish. Test sets included both scientific publications (from the Scielo and EDP Sciences databases) and health-related news (from the Cochrane and UK National Health Service web sites). Seven teams participated in the task, submitting a total of 82 runs. Herein we describe the test sets, participating systems and results of both the automatic and manual evaluation of the translations