Chinese International Students\u27 Informal Second Language (L2) Learning Through Technology for Enhancing Lived Experiences in Canada

An increasing amount of attention has been drawn to international students’ academic development in the context of studying abroad; however, few studies shed light on students’ studying and lived experiences outside of school. This thesis explores how technology can enhance Chinese international students’ informal acquisition of second language (L2) and their lived experiences in Canada. Through a qualitative case study, I describe what language difficulties newly arrived Chinese international students encounter, and how they cope with those language difficulties through technology-assisted informal L2 learning. Data sources include in-depth interviews and follow-up interviews, participants’ personal narratives, and researchers’ reflective journals. Theories of multiliteracies, basic interpersonal communicative skills and cognitive academic language proficiency distinction, as well as a communicative competence framework have been adopted as the theoretical frameworks for data analysis. The findings show that newly arrived Chinese international students’ major language difficulties includes lack of non-academic vocabulary, lack of understanding of sociocultural differences, and unfamiliarity with informal context embedded phrases. To overcome these language difficulties, they creatively design informal L2 learning experiences through the combinational use of technology tools. The results have significant implications for newly arrived Chinese international students’ informal L2 learning

Quantitative Research on the Evolution Stages of We-media Network Public Opinion based on a Logistic Equation

We-media network public opinion is a new force in the current social public opinion field that has an important impact on the guidance of social public opinion and social stability. Studying the periodic law of we-media network public opinion dissemination and constructing a quantitative model of we-media network public opinion dissemination stages provide the basis for guiding social public opinion and governing we-media network public opinion dissemination. Based on this, this paper explores the life cycle of we-media network public opinion evolution, analyzes the characteristics and connotations of each evolution stage, and determines the dominant indicators of we-media network public opinion evolution stages; in addition, this paper constructs a logistic quantitative model and its stage refinement model for the evolution and development of we-media network public opinion and uses MATLAB software to simulate the event of the academic fraud of the Chinese actor Zhai. This paper studies the four key points on the logistic curve of we-media network public opinion evolution and the five key intervals, analyzes the connotation of the quantified stage of each interval, and puts forward the governance strategy of we-media network public opinion events, through the simulation of initial values, growth rates and upper limits

Analysis of Multi-Element Blended Course Teaching and Learning Mode Based on Student-Centered Concept under the Perspective of “Internet+”

The integration of Internet and education has changed students’ learning environment and affected their learning behavior, which poses a greater challenge to the traditional teaching mode. Through the SWOT analysis of the “student centered” multi-element blended teaching mode in the era of “Internet + education”, it is concluded that the adaptability of learners themselves and the mismatch between teachers’ educational ideas and this teaching model delay the development of education to a certain extent. Some suggestions are put forward, such as strengthening the supervision and guidance, implementing the teaching and learning model scientifically, improving teachers’ ideology and comprehensive quality, and making full use of the characteristics of Internet opening, sharing and collaboration to construct the public service system and platform of national educational resources

LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the global layout map and each detailed object remains a challenging task. In this paper, we propose a diffusion model named LayoutDiffusion that can obtain higher generation quality and greater controllability than the previous works. To overcome the difficult multimodal fusion of image and layout, we propose to construct a structural image patch with region information and transform the patched image into a special layout to fuse with the normal layout in a unified form. Moreover, Layout Fusion Module (LFM) and Object-aware Cross Attention (OaCA) are proposed to model the relationship among multiple objects and designed to be object-aware and position-sensitive, allowing for precisely controlling the spatial related information. Extensive experiments show that our LayoutDiffusion outperforms the previous SOTA methods on FID, CAS by relatively 46.35%, 26.70% on COCO-stuff and 44.29%, 41.82% on VG. Code is available at https://github.com/ZGCTroy/LayoutDiffusion.Comment: Accepted by CVPR202

Combined Effect of Thermal Shock and Hot Corrosion on the Failure of Yttria Stabilized Zirconia Thermal Barrier Coatings

The application of thermal barrier coatings (TBCs) always undergo severe environment, concluding hot corrosion, high temperature oxidation and higher stress, which result in the failure of TBCs. The study of failure mechanisms of TBCs under various combined environmental factors, different with single factor, is more significant to further promote the applications of TBCs. In the present work, the combined effect of thermal shock and hot corrosion on the failure of TBCs was highlighted investigated. The 8wt.% yttria stabilized zirconia (8YSZ) thermal barrier coatings on a GH2132 alloy were deposited by air plasma spraying. The results showed that the transformation of ZrO2 from tetragonal phase to monoclinic phase induced internal stress in the topcoat, when combined with the thermal stress, the topcoat even the bondcoat were both cracked. The main failure of TBCs under the combined effect was in the form of penetrating crack to the bondcoat/substrate interface and oxidation at the penetrating crack front

Diagnostic Evasion of Highly-Resistant Microorganisms:A Critical Factor in Nosocomial Outbreaks

Highly resistant microorganisms (HRMOs) may evade screening strategies used in routine diagnostics. Bacteria that have evolved to evade diagnostic tests may have a selective advantage in the nosocomial environment. Evasion of resistance detection can result from the following mechanisms: low-level expression of resistance genes not resulting in detectable resistance, slow growing variants, mimicry of wild-type-resistance, and resistance mechanisms that are only detected if induced by antibiotic pressure. We reviewed reports on hospital outbreaks in the Netherlands over the past 5 years. Remarkably, many outbreaks including major nation-wide outbreaks were caused by microorganisms able to evade resistance detection by diagnostic screening tests. We describe various examples of diagnostic evasion by several HRMOs and discuss this in a broad and international perspective. The epidemiology of hospital-associated bacteria may strongly be affected by diagnostic screening strategies. This may result in an increasing reservoir of resistance genes in hospital populations that is unnoticed. The resistance elements may horizontally transfer to hosts with systems for high-level expression, resulting in a clinically significant resistance problem. We advise to communicate the identification of HRMOs that evade diagnostics within national and regional networks. Such signaling networks may prevent inter-hospital outbreaks, and allow collaborative development of adapted diagnostic tests

Enterococcus faecium:from microbiological insights to practical recommendations for infection control and diagnostics

Early in its evolution, Enterococcus faecium acquired traits that allowed it to become a successful nosocomial pathogen. E. faecium inherent tenacity to build resistance to antibiotics and environmental stressors that allows the species to thrive in hospital environments. The continual wide use of antibiotics in medicine has been an important driver in the evolution of E. faecium becoming a highly proficient hospital pathogen.For successful prevention and reduction of nosocomial infections with vancomycin resistant E. faecium (VREfm), it is essential to focus on reducing VREfm carriage and spread. The aim of this review is to incorporate microbiological insights of E. faecium into practical infection control recommendations, to reduce the spread of hospital-acquired VREfm (carriage and infections). The spread of VREfm can be controlled by intensified cleaning procedures, antibiotic stewardship, rapid screening of VREfm carriage focused on high-risk populations, and identification of transmission routes through accurate detection and typing methods in outbreak situations. Further, for successful management of E. faecium, continual innovation in the fields of diagnostics, treatment, and eradication is necessary

Bridging Cross-task Protocol Inconsistency for Distillation in Dense Object Detection

Knowledge distillation (KD) has shown potential for learning compact models in dense object detection. However, the commonly used softmax-based distillation ignores the absolute classification scores for individual categories. Thus, the optimum of the distillation loss does not necessarily lead to the optimal student classification scores for dense object detectors. This cross-task protocol inconsistency is critical, especially for dense object detectors, since the foreground categories are extremely imbalanced. To address the issue of protocol differences between distillation and classification, we propose a novel distillation method with cross-task consistent protocols, tailored for the dense object detection. For classification distillation, we address the cross-task protocol inconsistency problem by formulating the classification logit maps in both teacher and student models as multiple binary-classification maps and applying a binary-classification distillation loss to each map. For localization distillation, we design an IoU-based Localization Distillation Loss that is free from specific network structures and can be compared with existing localization distillation losses. Our proposed method is simple but effective, and experimental results demonstrate its superiority over existing methods. Code is available at https://github.com/TinyTigerPan/BCKD.Comment: Accepted by ICCV 202