Examining the online reading behavior and performance of fifth-graders: evidence from eye-movement data

Online reading is developing at an increasingly rapid rate, but the debate concerning whether learning is more effective when using hypertexts than when using traditional linear texts is still persistent. In addition, several researchers stated that online reading comprehension always starts with a question, but little empirical evidence has been gathered to investigate this claim. This study used eye-tracking technology and retrospective think aloud technique to examine online reading behaviors of fifth-graders (N = 50). The participants were asked to read four texts on the website. The present study employed a three-way mixed design: 2 (reading ability: high vs. low) 2 (reading goals: with vs. without) 2 (text types: hypertext vs. linear text). The dependent variables were eye-movement indices and the frequencies of using online reading strategy. The results show that fifth-graders, irrespective of their reading ability, found it difficult to navigate the nonlinear structure of hypertexts when searching for and integrating information. When they read with goals, they adjusted their reading speed and the focus of their attention. Their offline reading ability also influenced their online reading performance. These results suggest that online reading skills and strategies have to be taught in order to enhance the online reading abilities of elementary-school students

Generating Function for Tensor Network Diagrammatic Summation

The understanding of complex quantum many-body systems has been vastly boosted by tensor network (TN) methods. Among others, excitation spectrum and long-range interacting systems can be studied using TNs, where one however confronts the intricate summation over an extensive number of tensor diagrams. Here, we introduce a set of generating functions, which encode the diagrammatic summations as leading order series expansion coefficients. Combined with automatic differentiation, the generating function allows us to solve the problem of TN diagrammatic summation. We illustrate this scheme by computing variational excited states and dynamical structure factor of a quantum spin chain, and further investigating entanglement properties of excited states. Extensions to infinite size systems and higher dimension are outlined.Comment: v1: 6 pages, 2 figures. v2: published versio

High Altitude Pulmonary Edema in a Patient with Previous Pneumonectomy

High altitude pulmonary edema (HAPE) is a life-threatening illness that can occur in individuals ascending to altitudes exceeding 2400 m. The risk factors are rapid ascent, physical exertion and a previous history of HAPE. This work presents a case study of a 74-year-old man who underwent left side pneumonectomy 40 years ago and subsequently experienced several instances of HAPE. The well-known risk factors for HAPE were excluded in this patient. We suspect that the post-pneumonectomy condition may be a risk factor for HAPE based on this case. [J Formos Med Assoc 2007;106(4):320-322

Prevalence of latent tuberculosis infection in BCG-vaccinated healthcare workers by using an interferon-gamma release assay and the tuberculin skin test in an intermediate tuberculosis burden country

BackgroundThe risk of healthcare workers (HCWs) acquiring tuberculosis (TB) infection is high. We determined the prevalence of latent TB infection (LTBI) in HCWs with a high Bacille Calmette-Guérin (BCG) vaccine coverage in an intermediate TB burden country by using an interferon-gamma release assay [QuantiFERON-TB Gold (QFT-G)] and by using the tuberculin skin test (TST). Risk factors associated with a positive test were determined.MethodsThis prospective cross-sectional study enrolled HCWs from a medical center in Taiwan. Participants were grouped into workers without exposure (Group 1) and workers who self-reported a history of TB exposure (Group 2). All participants completed a questionnaire to collect demographic information and risk factors for acquiring TB. The QFT-G test and the TST were administered and risk factors for a positive test were analyzed.ResultsWe recruited 193 HCWs [149 (77.2%) female workers] with a mean age of 35.6 years. All were BCG-vaccinated. The prevalence of LTBI was 88.8% (based on the TST) and 14.5% (based on the QFT-G test). There was no difference between HCWs with and without known exposure to TB. Agreement between the tests was poor (i.e., the kappa value was less than 0.05). Multivariable logistic regression showed that only the QFT-G test was associated with age (35 years or greater) (adjusted OR, 2.53; p = 0.03).ConclusionBy using the QFT-G test or TST, this study found a similar prevalence of LTBI in HCWs with and without known exposure to TB. This suggests that in intermediate TB burden countries exposure to TB may occur within the hospital and within the community. Compared to the TST, the QFT-G test was correlated better with age, which is a known risk factor for latent TB infection

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the computing paradigms, i.e., cloud computing and edge computing. In recent years, we have witnessed significant progress in developing more advanced AI models on cloud servers that surpass traditional deep learning models owing to model innovations (e.g., Transformers, Pretrained families), explosion of training data and soaring computing capabilities. However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed. In this survey, we conduct a systematic review for both cloud and edge AI. Specifically, we are the first to set up the collaborative learning mechanism for cloud and edge modeling with a thorough review of the architectures that enable such mechanism. We also discuss potentials and practical experiences of some on-going advanced edge AI topics including pretraining models, graph neural networks and reinforcement learning. Finally, we discuss the promising directions and challenges in this field.Comment: 20 pages, Transactions on Knowledge and Data Engineerin