A CONJOINT STUDY OF THE RELATIONSHIP BETWEEN WEBSITE ATTRIBUTES AND CONSUMER PURCHASE INTENTIONS

This paper extends and modifies the Schaupp and Belanger model (2005) to develop and propose a model of on-line shopping intentions. Four on-line websites were designed as the test platforms. Respondents of this study were asked to visit these web-sites that represent differing shopping scenarios before they completed our on-line survey. Findings of this study are as follows. First, on-line contract signing mechanism was ranked as the most desired option in building trust in on-line shopping websites by all respondents. Second, respondents of this study were found able to be categorized into three groups according to the website factors they valued most. The three were logistic/security, security/trust, and convenience/trust. The specific attributes of on-line shopping websites valued most within each of the three groups are discussed in this paper. This study presents findings that support the use of many existing on-line technologies that have been found little used in on-line shopping websites such as digital certificate and on-line contracting. The inclusion of these technologies in on-line shopping websites may increase the cost of building and maintaining them and may create worries about user inconvenience. However, it is important that these technologies increase the attractiveness of the on-line shopping website and web surfers purchase intentions

Burden of rheumatoid arthritis among US Medicare population: co-morbidities, health-care resource utilization and costs

Objectives. The study aimed to assess the burden of RA among the US Medicare population (aged 65 years) by comparing co-morbidities, health-care resource utilization (HCRU) and costs against matched non-RA Medicare patients. Methods. Data were obtained from the Medicare fee-for-service claims database from 2010 to 2013. RA Medicare patients were identically matched with Medicare patients without RA (controls) based on demographics. Bivariate analyses were conducted to examine differences between cohorts for comorbidities, HCRU and costs. A generalized linear model was used to test relationships between patient-level characteristics, HCRU and costs. Results. The study population included 115 867 RA patients and 115 867 age-, sex-, race- and region-matched non-RA controls. Mean age was 75.2 years; 79.4% were female. Co-morbidities were greater in RA vs non-RA patients [Charlson Co-morbidity Index (excluding RA): 1.86 vs 1.00; P Conclusions. Among US Medicare patients, those with an RA diagnosis had a significantly greater burden of co-morbidities, HCRU and costs compared with a matched cohort without RA

The glucocorticoid-Angptl4-ceramide axis induces insulin resistance through PP2A and PKCζ.

Chronic glucocorticoid exposure is associated with the development of insulin resistance. We showed that glucocorticoid-induced insulin resistance was attenuated upon ablation of Angptl4, a glucocorticoid target gene encoding the secreted protein angiopoietin-like 4, which mediates glucocorticoid-induced lipolysis in white adipose tissue. Through metabolomic profiling, we revealed that glucocorticoid treatment increased hepatic ceramide concentrations by inducing enzymes in the ceramide synthetic pathway in an Angptl4-dependent manner. Angptl4 was also required for glucocorticoids to stimulate the activities of the downstream effectors of ceramide, protein phosphatase 2A (PP2A) and protein kinase Cζ (PKCζ). We further showed that knockdown of PP2A or inhibition of PKCζ or ceramide synthesis prevented glucocorticoid-induced glucose intolerance in wild-type mice. Moreover, the inhibition of PKCζ or ceramide synthesis did not further improve glucose tolerance in Angptl4-/- mice, suggesting that these molecules were major downstream effectors of Angptl4. Overall, our study demonstrates the key role of Angptl4 in glucocorticoid-augmented hepatic ceramide production that induces whole-body insulin resistance

EvIcon: Designing High-Usability Icon with Human-in-the-loop Exploration and IconCLIP

Interface icons are prevalent in various digital applications. Due to limited time and budgets, many designers rely on informal evaluation, which often results in poor usability icons. In this paper, we propose a unique human-in-the-loop framework that allows our target users, i.e., novice and professional UI designers, to improve the usability of interface icons efficiently. We formulate several usability criteria into a perceptual usability function and enable users to iteratively revise an icon set with an interactive design tool, EvIcon. We take a large-scale pre-trained joint image-text embedding (CLIP) and fine-tune it to embed icon visuals with icon tags in the same embedding space (IconCLIP). During the revision process, our design tool provides two types of instant perceptual usability feedback. First, we provide perceptual usability feedback modeled by deep learning models trained on IconCLIP embeddings and crowdsourced perceptual ratings. Second, we use the embedding space of IconCLIP to assist users in improving icons' visual distinguishability among icons within the user-prepared icon set. To provide the perceptual prediction, we compiled IconCEPT10K, the first large-scale dataset of perceptual usability ratings over $10,000$ interface icons, by conducting a crowdsourcing study. We demonstrated that our framework could benefit UI designers' interface icon revision process with a wide range of professional experience. Moreover, the interface icons designed using our framework achieved better semantic distance and familiarity, verified by an additional online user study

Treatment Learning Causal Transformer for Noisy Image Classification

Current top-notch deep learning (DL) based vision models are primarily based on exploring and exploiting the inherent correlations between training data samples and their associated labels. However, a known practical challenge is their degraded performance against "noisy" data, induced by different circumstances such as spurious correlations, irrelevant contexts, domain shift, and adversarial attacks. In this work, we incorporate this binary information of "existence of noise" as treatment into image classification tasks to improve prediction accuracy by jointly estimating their treatment effects. Motivated from causal variational inference, we propose a transformer-based architecture, Treatment Learning Causal Transformer (TLT), that uses a latent generative model to estimate robust feature representations from current observational input for noise image classification. Depending on the estimated noise level (modeled as a binary treatment factor), TLT assigns the corresponding inference network trained by the designed causal loss for prediction. We also create new noisy image datasets incorporating a wide range of noise factors (e.g., object masking, style transfer, and adversarial perturbation) for performance benchmarking. The superior performance of TLT in noisy image classification is further validated by several refutation evaluation metrics. As a by-product, TLT also improves visual salience methods for perceiving noisy images.Comment: Accepted to IEEE WACV 2023. The first version was finished in May 201

Composite type A thymoma and diffuse large B-cell lymphoma

AbstractThe concurrent occurrence of thymoma and diffuse large B-cell lymphoma in the thymus has not been previously reported. We describe a 74-year-old man who presented with general weakness, neck lymphadenopathy, night sweats, and body weight loss. A right anterior mediastinal mass was found on computed tomography of the chest. The immunohistochemical stains AE1/AE3, CD20, CD3, and MUM-1 confirmed the different components of the mediastinal tumor. A heavy-chain gene clonality assay and light-chain gene clonality assay confirmed the B-cell clonality of the mediastinal tumor and neck lymph node. The patient had received a complete course of chemotherapy, and the result of positron emission tomography–computed tomography showed complete remission. The pathologic report of this mass revealed composite type A thymoma and diffuse large B-cell lymphoma. If concurrent or composite thymoma and lymphoma are suspected, a thorough examination of the thymoma with a combination of ancillary studies is recommended to rule out the possibility of concurrent lymphoma

Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume

LrrA, a novel leucine-rich repeat protein involved in cytoskeleton remodeling, is required for multicellular morphogenesis in Dictyostelium discoideum

AbstractCell sorting by differential cell adhesion and movement is a fundamental process in multicellular morphogenesis. We have identified a Dictyostelium discoideum gene encoding a novel protein, LrrA, which composes almost entirely leucine-rich repeats (LRRs) including a putative leucine zipper motif. Transcription of lrrA appeared to be developmentally regulated with robust expression during vegetative growth and early development. lrrA null cells generated by homologous recombination aggregated to form loose mounds, but subsequent morphogenesis was blocked without formation of the apical tip. The cells adhered poorly to a substratum and did not form tight cell–cell agglomerates in suspension; in addition, they were unable to polarize and exhibit chemotactic movement in the submerged aggregation and Dunn chamber chemotaxis assays. Fluorescence-conjugated phalloidin staining revealed that both vegetative and aggregation competent lrrA− cells contained numerous F-actin-enriched microspikes around the periphery of cells. Quantitative analysis of the fluorescence-stained F-actin showed that lrrA− cells exhibited a dramatically increase in F-actin as compared to the wild-type cells. When developed together with wild-type cells, lrrA− cells were unable to move to the apical tip and sorted preferentially to the rear and lower cup regions. These results indicate that LrrA involves in cytoskeleton remodeling, which is needed for normal chemotactic aggregation and efficient cell sorting during multicellular morphogenesis, particularly in the formation of apical tip

Provider Behavior Under Global Budgeting and Policy Responses: An Observational Study on Eye Care Services in Taiwan

Third-party payer systems are consistently associated with health care cost escalation. Taiwan’s single-payer, universal coverage National Health Insurance (NHI) adopted global budgeting (GB) to achieve cost control. This study captures ophthalmologists’ response to GB, specifically service volume changes and service substitution between low-revenue and high-revenue services following GB implementation, the subsequent Bureau of NHI policy response, and the policy impact. De-identified eye clinic claims data for the years 2000, 2005, and 2007 were analyzed to study the changes in Simple Claim Form (SCF) claims versus Special Case Claims (SCCs). The 3 study years represent the pre-GB period, post-GB but prior to region-wise service cap implementation period, and the post-service cap period, respectively. Repeated measures multilevel regression analysis was used to study the changes adjusting for clinic characteristics and competition within each health care market. SCF service volume (low-revenue, fixed-price patient visits) remained constant throughout the study period, but SCCs (covering services involving variable provider effort and resource use with flexibility for discretionary billing) increased in 2005 with no further change in 2007. The latter is attributable to a 30% cap negotiated by the NHI Bureau with the ophthalmology association and enforced by the association. This study demonstrates that GB deployed with ongoing monitoring and timely policy responses that are designed in collaboration with professional stakeholders can contain costs in a health insurance–financed health care system