English Language Learners of Chinese Immigrant Families in Canadian Schools

Given the context that many Chinese immigrant families are settling in Canada, their children, as English language learners (ELLs), have encountered a variety of obstacles and barriers while studying at local schools. The purpose of this Major Research Paper (MRP) is to understand the obstacles and barriers that Chinese newcomer ELLs in Ontario have encountered and hence to offer some helpful suggestions. A series of official documents of Ontario ELL curriculum has been introduced to school educators by the Ontario Ministry of Education (2005, 2008), such as Many Roots, Many Voices: Supporting English Language Learners in Every Classroom and Support English Language Learners Grade 1 to 8. Meanwhile, Chinese newcomer English learners have accepted systemic English language education in China before immigration. Therefore, to better understand the needs and challenges of Chinese newcomer ELLs, English curriculum in compulsory education in China and educational documents for ELLs in Ontario Canada will be discussed in this paper, followed by a comparison of pedagogies applied in compulsory education in Canada and China. Comparing the similarities and differences, and giving suggestions to pre-service, and in-service educators may help ELLs and EFLs to improve their academic performance. Other literature in the field is concerned with Chinese ELLs in Ontario elementary schools and the obstacles that they face at school. However, only a few studies compare ELL curriculum documents in Canada and English curricula standards in China, then give suggestions to schoolteachers, parents, and students\u27 home countries about the challenges faced by Chinese immigrant children. Those barriers and challenges reflect the problems that still exist in curriculum and educational policies. Therefore, it is important to introduce Chinese EFLs to Ontario teachers in order to help Chinese ELLs get involved in their unfamiliar environmen

Graph Neural Networks based Log Anomaly Detection and Explanation

Event logs are widely used to record the status of high-tech systems, making log anomaly detection important for monitoring those systems. Most existing log anomaly detection methods take a log event count matrix or log event sequences as input, exploiting quantitative and/or sequential relationships between log events to detect anomalies. Unfortunately, only considering quantitative or sequential relationships may result in low detection accuracy. To alleviate this problem, we propose a graph-based method for unsupervised log anomaly detection, dubbed Logs2Graphs, which first converts event logs into attributed, directed, and weighted graphs, and then leverages graph neural networks to perform graph-level anomaly detection. Specifically, we introduce One-Class Digraph Inception Convolutional Networks, abbreviated as OCDiGCN, a novel graph neural network model for detecting graph-level anomalies in a collection of attributed, directed, and weighted graphs. By coupling the graph representation and anomaly detection steps, OCDiGCN can learn a representation that is especially suited for anomaly detection, resulting in a high detection accuracy. Importantly, for each identified anomaly, we additionally provide a small subset of nodes that play a crucial role in OCDiGCN's prediction as explanations, which can offer valuable cues for subsequent root cause diagnosis. Experiments on five benchmark datasets show that Logs2Graphs performs at least on par with state-of-the-art log anomaly detection methods on simple datasets while largely outperforming state-of-the-art log anomaly detection methods on complicated datasets.Comment: Preprint submitted to Engineering Applications of Artificial Intelligenc

Multi-stage Deep Learning Artifact Reduction for Computed Tomography

In Computed Tomography (CT), an image of the interior structure of an object is computed from a set of acquired projection images. The quality of these reconstructed images is essential for accurate analysis, but this quality can be degraded by a variety of imaging artifacts. To improve reconstruction quality, the acquired projection images are often processed by a pipeline consisting of multiple artifact-removal steps applied in various image domains (e.g., outlier removal on projection images and denoising of reconstruction images). These artifact-removal methods exploit the fact that certain artifacts are easier to remove in a certain domain compared with other domains. Recently, deep learning methods have shown promising results for artifact removal for CT images. However, most existing deep learning methods for CT are applied as a post-processing method after reconstruction. Therefore, artifacts that are relatively difficult to remove in the reconstruction domain may not be effectively removed by these methods. As an alternative, we propose a multi-stage deep learning method for artifact removal, in which neural networks are applied to several domains, similar to a classical CT processing pipeline. We show that the neural networks can be effectively trained in succession, resulting in easy-to-use and computationally efficient training. Experiments on both simulated and real-world experimental datasets show that our method is effective in reducing artifacts and superior to deep learning-based post-processing

Phytophthora infestans RXLR effectors act in concert at diverse subcellular locations to enhance host colonization

Oomycetes such as the potato blight pathogen Phytophthora infestans deliver RXLR effectors into plant cells to manipulate host processes and promote disease. Knowledge of where they localize inside host cells is important in understanding their function. Fifty-two P. infestans RXLR effectors (PiRXLRs) up-regulated during early stages of infection were expressed as fluorescent protein (FP) fusions inside cells of the model host Nicotiana benthamiana. FP-PiRXLR fusions were predominantly nucleo-cytoplasmic, nuclear, or plasma membrane-associated. Some also localized to the endoplasmic reticulum, mitochondria, peroxisomes, or microtubules, suggesting diverse sites of subcellular activity. Seven of the 25 PiRXLRs examined during infection accumulated at sites of haustorium penetration, probably due to co-localization with host target processes; Pi16663 (Avr1), for example, localized to Sec5-associated mobile bodies which showed perihaustorial accumulation. Forty-five FP-RXLR fusions enhanced pathogen leaf colonization when expressed in Nicotiana benthamiana, revealing that their presence was beneficial to infection. Co-expression of PiRXLRs that target and suppress different immune pathways resulted in an additive enhancement of colonization, indicating the potential to study effector combinations using transient expression assays. We provide a broad platform of high confidence P. infestans effector candidates from which to investigate the mechanisms, singly and in combination, by which this pathogen causes disease.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Tolerance study of travelling-wave accelerating structure for the main linac of the klystron-based first stage of Compact Linear Collider

This work aims to analyse the tolerances given by two effects on the performance of the travelling-wave accelerating structure: the reflection along the structure and the change in the nominal accelerating voltage, which is essential for the projects with a large number of accelerating structures. The detuning and dephasing caused by systematic temperature shifts, systematic geometric errors and random geometric errors has been investigated in this paper. RF parameters of travelling-wave accelerating structure CLIC-K designed for klystron-based first stage of CLIC is used to defining the fabrication shape accuracy specification as well as the working temperature control for the high-gradient structurer if tuning is unfeasible

Disinfection of <i>Escherichia coli</i> by a Reactive Electrochemical Membrane System Involving Activated Carbon Fiber Cloth (ACFC)

This study examined a novel reactive electrochemical membrane (REM) system with activated carbon fiber cloth (ACFC) serving simultaneously as the anode and the membrane to effectively disinfect water that was filtered through the device. An Escherichia coli strain was inoculated to water as a model pathogen. The influence of REM operation parameters, including the number of ACFC layers, voltage, flow rate and operation time, was evaluated. Up to 7.5 log unit reduction of E. coli concentration in water was achieved at the optimal treatment condition, while the energy consumption was 1.5 kWh/m3 per log unit reduction of E. coli. This makes it possible to use this ACFC-based REM technology for point-of-use water disinfection to provide clean water for underdeveloped regions. Further tests by free radical probing, Linear Scan Voltammetry (LSV) and Scanning Electron Microscopy (SEM) suggest that the disinfection involved the filtration/retention of bacteria on ACFC and attack by reactive oxygen species generated electrochemically on the anode

Wakefield suppression in the main linac of the klystron-based first stage of CLIC at 380 GeV

An alternative klystron-based scenario for the first stage of Compact Linear Collider (CLIC) at 380 GeV centre-of-mass energy was proposed. To preserve the beam stability and luminosity of CLIC, the beam-induced transverse long-range wakefield in main linac must be suppressed to an acceptable value. The design of klystron-based accelerating structure is based on waveguide damping structure (WDS). The high-order modes (HOMs) propagating into four waveguides are absorbed by HOM damping loads. In this paper, the wakefield suppression in CLIC-K based on GdfidL code simulations are presented

A continuous-wave superconducting linear accelerator scheme for the drive beam acceleration of the Compact Linear Collider

The Compact Linear Collider (CLIC) utilizes two 2.5-km-long normal-conducting linear accelerators (LINACs) to produce a drive beam with 140μs pulse length at a repetition rate of 50 Hz. This setup is relatively expensive in the early stages due to both the length of the drive beam LINACs and the amount of the power sources for one drive beam complex are the same in all energy stages. A new concept of accelerating the CLIC drive beam in superconducting LINACs as an alternative scheme is investigates in this work. This scheme requires a minimal number of power sources at the early stages of the CLIC and consequently has the potential to reduce the entry cost. A dimensionless parameter named capacity factor η which determines the number of the superconducting structures and the power is introduced. Two proof-of-concept schemes to compensate the beam-loading effect are also proposed in this paper. The mixed-structure scheme finally selected as the nominal design achieves an optimum η of approximately 1.16 compared to a value of 50.5 without the beam-loading compensation. A rough estimation on the cost of this scheme has also been studied