General Education Learning Outcomes and Demographic Correlates in University Students in Hong Kong

Although there are studies showing that higher education would benefit university students, empirical research that comprehensively assesses student general education learning outcomes and related demographic correlates based on longitudinal data is minimal, especially in the Chinese context. To address the research gaps, the present study was conducted to investigate learning outcomes amongst university students in one university in Hong Kong based on a four-year longitudinal design (N = 460). Four dimensions of student general education learning outcomes were measured, including effective reasoning and problem solving, leadership, moral character, and integration of learning. Results suggested a U-shaped pattern of student learning outcomes for most dimensions, with no improvement or even a decrement in the second year and a steady growth thereafter. While family background did not affect student development, gender showed a significant moderating effect on students’ development in two dimensions (i.e., effective reasoning and problem solving, and integration of learning). These findings suggest that students benefit from general education-embedded university study in multiple dimensions, especially after the first year of transition period. Practical implications of the findings and future research directions were also discussed

Reconstruction and thermal stability of the cubic SiC(001) surfaces

The (001) surfaces of cubic SiC were investigated with ab-initio molecular dynamics simulations. We show that C-terminated surfaces can have different c(2x2) and p(2x1) reconstructions, depending on preparation conditions and thermal treatment, and we suggest experimental probes to identify the various reconstructed geometries. Furthermore we show that Si-terminated surfaces exhibit a p(2x1) reconstruction at T=0, whereas above room temperature they oscillate between a dimer row and an ideal geometry below 500 K, and sample several patterns including a c(4x2) above 500 K.Comment: 12 pages, RevTeX, figures 1 and 2 available in gif form at http://irrmawww.epfl.ch/fg/sic/fig1.gif and http://irrmawww.epfl.ch/fg/sic/fig2.gi

Theoretical study of the (3x2) reconstruction of beta-SiC(001)

By means of ab initio molecular dynamics and band structure calculations, as well as using calculated STM images, we have singled out one structural model for the (3x2) reconstruction of the Si-terminated (001) surface of cubic SiC, amongst several proposed in the literature. This is an alternate dimer-row model, with an excess Si coverage of 1/3, yielding STM images in good accord with recent measurements [F.Semond et al. Phys. Rev. Lett. 77, 2013 (1996)].Comment: To be published in PRB Rapid. Com

Multi-domain clinical natural language processing with MedCAT: The Medical Concept Annotation Toolkit

Electronic health records (EHR) contain large volumes of unstructured text, requiring the application of information extraction (IE) technologies to enable clinical analysis. We present the open source Medical Concept Annotation Toolkit (MedCAT) that provides: (a) a novel self-supervised machine learning algorithm for extracting concepts using any concept vocabulary including UMLS/SNOMED-CT; (b) a feature-rich annotation interface for customizing and training IE models; and (c) integrations to the broader CogStack ecosystem for vendor-agnostic health system deployment. We show improved performance in extracting UMLS concepts from open datasets (F1:0.448-0.738 vs 0.429-0.650). Further real-world validation demonstrates SNOMED-CT extraction at 3 large London hospitals with self-supervised training over ∼8.8B words from ∼17M clinical records and further fine-tuning with ∼6K clinician annotated examples. We show strong transferability (F1 > 0.94) between hospitals, datasets and concept types indicating cross-domain EHR-agnostic utility for accelerated clinical and research use cases

ACR Appropriateness Criteria® Non-Spine Bone Metastases

Abstract Bone is one of the most common sites of metastatic spread of malignancy, with possible deleterious effects including pain, hypercalcemia, and pathologic fracture. External beam radiotherapy (EBRT) remains the mainstay for treatment of painful bone metastases. EBRT may be combined with other local therapies like surgery or with systemic treatments like chemotherapy, hormonal therapy, osteoclast inhibitors, or radiopharmaceuticals. EBRT is not commonly recommended for patients with asymptomatic bone metastases unless they are associated with a risk of pathologic fracture. For those who do receive EBRT, appropriate fractionation schemes include 30?Gy in 10 fractions, 24?Gy in 6 fractions, 20?Gy in 5 fractions, or a single 8?Gy fraction. Single fraction treatment maximizes convenience, while fractionated treatment courses are associated with a lower incidence of retreatment. The appropriate postoperative dose fractionation following surgical stabilization is uncertain. Reirradiation with EBRT may be safe and provide pain relief, though retreatment might create side effect risks which warrant its use as part of a clinical trial. All patients with bone metastases should be considered for concurrent management by a palliative care team, with patients whose life expectancy is less than six months appropriate for hospice evaluation. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every two years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98458/1/jpm%2E2011%2E0512.pd

ACR Appropriateness Criteria® Spinal Bone Metastases

The spine is a common site of involvement in patients with bone metastases. Apart from pain, hypercalcemia, and pathologic fracture, progressive tumor can result in neurologic deterioration caused by spinal cord compression or cauda equina involvement. The treatment of spinal bone metastases depends on histology, site of disease, extent of epidural disease, extent of metastases elsewhere, and neurologic status. Treatment recommendations must weigh the risk-benefit profile of external beam radiation therapy (EBRT) for the particular individual's circumstance, including neurologic status, performance status, extent of spinal disease, stability of the spine, extra-spinal disease status, and life expectancy. Patients with spinal instability should be evaluated for surgical intervention. Research studies are needed that evaluate the combination or sequencing of localized therapies with systemic therapies including chemotherapy, hormonal therapy (HT), osteoclast inhibitors (OI), and radiopharmaceuticals. The roles of stereotactic body radiation therapy (SBRT) in the management of spinal oligometastasis, radioresistant spinal metastasis, and previously irradiated but progressive spinal metastasis are emerging, but more research is needed to validate the findings from retrospective studies. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140115/1/jpm.2012.0376.pd

Modeling the series of (n x 2) Si-rich reconstructions of beta-SiC(001): a prospective atomic wire?

We perform ab initio plane wave supercell density functional calculations on three candidate models of the (3 x 2) reconstruction of the beta-SiC(001) surface. We find that the two-adlayer asymmetric-dimer model (TAADM) is unambiguously favored for all reasonable values of Si chemical potential. We then use structures derived from the TAADM parent to model the silicon lines that are observed when the (3 x 2) reconstruction is annealed (the (n x 2) series of reconstructions), using a tight-binding method. We find that as we increase n, and so separate the lines, a structural transition occurs in which the top addimer of the line flattens. We also find that associated with the separation of the lines is a large decrease in the HOMO-LUMO gap, and that the HOMO state becomes quasi-one-dimensional. These properties are qualititatively and quantitatively different from the electronic properties of the original (3 x 2) reconstruction.Comment: 22 pages, including 6 EPS figure

A knowledge distillation ensemble framework for predicting short- and long-term hospitalization outcomes from electronic health records data

The ability to perform accurate prognosis is crucial for proactive clinical decision making, informed resource management and personalised care. Existing outcome prediction models suffer from a low recall of infrequent positive outcomes. We present a highly-scalable and robust machine learning framework to automatically predict adversity represented by mortality and ICU admission and readmission from time-series of vital signs and laboratory results obtained within the first 24 hours of hospital admission. The stacked ensemble platform comprises two components: a) an unsupervised LSTM Autoencoder that learns an optimal representation of the time-series, using it to differentiate the less frequent patterns which conclude with an adverse event from the majority patterns that do not, and b) a gradient boosting model, which relies on the constructed representation to refine prediction by incorporating static features. The model is used to assess a patient's risk of adversity and provides visual justifications of its prediction. Results of three case studies show that the model outperforms existing platforms in ICU and general ward settings, achieving average Precision-Recall Areas Under the Curve (PR-AUCs) of 0.891 (95% CI: 0.878-0.939) for mortality and 0.908 (95% CI: 0.870-0.935) in predicting ICU admission and readmission