Engaging students in learning and creating different translanguaging sub-spaces in Hong Kong English Medium Instruction history classrooms

A key pedagogical goal in any classroom is to engage students in learning. This study examines how an English-Medium-Instruction (EMI) teacher employs available resources to engage his students in the classroom for promoting participation, keeping the lesson moving forward and meeting the pedagogical goals. The data for this study is based on a intensive fieldwork in an EMI secondary history classroom in Hong Kong. Multimodal Conversation Analysis is deployed to analyse the classroom interactional data. The classroom analysis is triangulated with the video-stimulated-recall-interviews that are analysed using Interpretative Phenomenological Analysis. The study’s crucial theoretical contribution is that it broadens our comprehension of an EMI classroom as an integrated translanguaging space, which may involve various fluid and mobile translanguaging sub-spaces. This paper aims to illustrate the process of engaging students affords the teacher to create different translanguaging sub-spaces at a whole-class level and at an individual level. It is argued that creating these translanguaging sub-spaces requires the teacher to mobilise available resources for catering for the different needs of all students, which promotes interaction and inclusion in the classrooms

Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project

OBJECTIVE: The objective of this study was to employ ensemble clustering and tree-based risk model approaches to identify interactions between clinicogenomic features for colorectal cancer using the 100,000 Genomes Project. RESULTS: Among the 2211 patients with colorectal cancer (mean age of diagnosis: 67.7; 59.7% male), 16.3%, 36.3%, 39.0% and 8.4% had stage 1, 2, 3 and 4 cancers, respectively. Almost every patient had surgery (99.7%), 47.4% had chemotherapy, 7.6% had radiotherapy and 1.4% had immunotherapy. On average, tumour mutational burden (TMB) was 18 mutations/Mb and 34.4%, 31.3% and 25.7% of patients had structural or copy number mutations in KRAS, BRAF and NRAS, respectively. In the fully adjusted Cox model, patients with advanced cancer [stage 3 hazard ratio (HR)  =  3.2; p  <  0.001; stage 4 HR  =  10.2; p  <  0.001] and those who had immunotherapy (HR  =  1.8; p  <  0.04) or radiotherapy (HR  =  1.5; p  <  0.02) treatment had a higher risk of dying. The ensemble clustering approach generated four distinct clusters where patients in cluster 2 had the best survival outcomes (1-year: 98.7%; 2-year: 96.7%; 3-year: 93.0%) while patients in cluster 3 (1-year: 87.9; 2-year: 70.0%; 3-year: 53.1%) had the worst outcomes. Kaplan-Meier analysis and log rank test revealed that the clusters were separated into distinct prognostic groups (p  <  0.0001). Survival tree or recursive partitioning analyses were performed to further explore risk groups within each cluster. Among patients in cluster 2, for example, interactions between cancer stage, grade, radiotherapy, TMB, BRAF mutation status were identified. Patients with stage 4 cancer and TMB  ≥  1.6 mutations/Mb had 4 times higher risk of dying relative to the baseline hazard in that cluster

Molecular Diversity and Potential Anti-neuroinflammatory Activities of Cyathane Diterpenoids from the Basidiomycete Cyathus africanus

Ten new polyoxygenated cyathane diterpenoids, named neocyathins A-J (1-10), together with four known diterpenes (11-14), were isolated from the liquid culture of the medicinal basidiomycete fungus Cyathus africanus. The structures and configurations of these new compounds were elucidated through comprehensive spectroscopic analyses including 1D NMR, 2D NMR (HSQC, HMBC, NOESY) and HRESIMS, and electronic circular dichroism (ECD) data. Neuroinflammation is implicated in the pathogenesis of various neurodegenerative diseases, such as Alzheimers' disease (AD). All isolated compounds were evaluated for the potential anti-neuroinflammatory activities in BV2 microglia cells. Several compounds showed differential effects on the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) in lipopolysaccharide (LPS)-stimulated and Aβ1-42-treated mouse microglia cell line BV-2. Molecular docking revealed that bioactive compounds (e.g., 11) could interact with iNOS protein other than COX-2 protein. Collectively, our results suggested that this class of cyathane diterpenoids might serve as important lead compounds for drug discovery against neuroinflammation in AD.published_or_final_versio

Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system

[[abstract]]Real-time traffic information collection and data fusion is one of the most important tasks in the advanced traffic management system (ATMS), and sharing traffic information to users is an essential part of the advance traveler information system (ATIS) among the intelligent transportation systems (ITS). Traditionally, sensor-based schemes or probing-vehicle based schemes have been used for collecting traffic information, but the coverage, cost, and real-time issues have remained unsolved. In this paper, a wiki-like collaborative real-time traffic information collection, fusion and sharing framework is proposed, which includes user-centric traffic event reacting mechanism, and automatic agent-centric traffic information aggregating scheme. Smart traffic agents (STA) developed for various front-end devices have the location-aware two-way real-time traffic exchange capability, and built-in event-reporting mechanism to allow users to report the real-time traffic events around their locations. In addition to collecting traffic information, the framework also integrates heterogeneous external real-time traffic information data sources and internal historical traffic information database to predict real-time traffic status by knowledge base system technique. (C) 2009 Published by Elsevier Inc

Design and implementation of electronic toll collection system based on vehicle positioning system techniques

[[abstract]]Currently, most electronic toll collection (ETC) systems around the world are implemented by DSRC (dedicated short range communication) technology. However, area wide integrated MLFF (multilane free flow) road charging system is now currently on its development to replace DSRC-based ETC systems. VPS (vehicle positioning system) based ETC system is a category of location based service which tolls vehilces by determining if they move into the charging zone. It is an evolutional technology for area wide integrated road charging solution, which achieves the goal of electronic payment or electronic toll collection by a totally different scheme comparing to traditional DSRC-based technology. In this paper, the design and implementation of VPS-based ETC system is detailedly discussed, and a debit transaction VPS system field test had been practiced in the freeway of Taiwan. (C) 2008 Elsevier B.V. All rights reserved

A knowledge based real-time travel time prediction system for urban network

[[abstract]]Many approaches had been proposed for travel time prediction in these decades; most of them focus on the predicting the travel time on freeway or simple arterial network. Travel time prediction for urban network in real time is hard to achieve for several reasons: complexity and path routing problem in urban network, unavailability of real-time sensor data, spatiotemporal data coverage problem, and lacking real-time events consideration. In this paper, we propose a knowledge based real-time travel time prediction model which contains real-time and historical travel time predictors to discover traffic patterns from the raw data of location based services by data mining technique and transform them to travel time prediction rules. Besides, dynamic weight combination of the two predictors by meta-rules is proposed to provide a real-time traffic event response mechanism to enhance the precision of the travel time prediction. (c) 2008 Elsevier Ltd. All rights reserved

Ruptured pseudocyst of pancreas presenting with paraplegia: a case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

ERα inhibits epithelial-mesenchymal transition by suppressing Bmi1 in breast cancer

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ERα inhibits epithelial-mesenchymal transition by suppressing Bmi1 in breast cancer

published_or_final_versio

Electronic Properties of Boron and Nitrogen doped graphene: A first principles study

Effect of doping of graphene either by Boron (B), Nitrogen (N) or co-doped by B and N is studied using density functional theory. Our extensive band structure and density of states calculations indicate that upon doping by N (electron doping), the Dirac point in the graphene band structure shifts below the Fermi level and an energy gap appears at the high symmetric K-point. On the other hand, by B (hole doping), the Dirac point shifts above the Fermi level and a gap appears. Upon co-doping of graphene by B and N, the energy gap between valence and conduction bands appears at Fermi level and the system behaves as narrow gap semiconductor. Obtained results are found to be in well agreement with available experimental findings.Comment: 11 pages, 4 figures, 1 table, submitted to J. Nanopart. Re