Student\u27s attitude to using the internet at school after limited classroom exposure

This study focused on student\u27s attitude to using the Internet at school. A questionnaire (the School Internet Attitude questionnaire) measuring student attitude to using the Internet at school incorporating three dimensions (cognitive, behavioural and affective) was administered twice to a sample of 64 Year 12 students from a Perth Metropolitan Independent school. The questionnaire was administered before and after a six lesson \u27exposure\u27 (the limited classroom exposure) to the Internet. Pre and post test attitude measures of all students were compared using dependent sample t_ test to determine if there were significant differences in student\u27s attitude after the limited classroom exposure to using the Internet at school and for each of the three dimensions of the School Internet Attitude questionnaire. Within the sample, the attitudes of current regular users of the Internet (students who use the Internet at least a few times a week) and current non-regular users of the Internet (students who have never used the Internet or use the Internet less than a few times a week) were compared before and again after the limited classroom exposure. A MANOV A design was used to measure the student\u27s attitude to using the Internet at school, the dependent variables were the cognitive, behavioural and affective dimensions of the School Internet Attitude questionnaire, with repeated measures on the independent variable, level of current use of the Internet. The study found that the limited classroom exposure caused no significant change in the student\u27s attitude to using the Internet at school from the pretest to the post test nor was there a significant change in attitude in any of the three dimensions, cognitive, behavioural and affective of the School Internet Attitude questionnaire. However, there was a significant difference in the attitude to using the Internet at school of regular and non-regular Internet users in the pretest with the cognitive and affective dimension showing significant differences and in the post test with the cognitive, behavioural and affective dimensions showing significant differences. Regular Internet users showed a more positive attitude than non-regular Internet users to using the Internet at school in both the pretest and the post test and for all three of the dependent variables the cognitive, behavioural and affective dimensions of the School Internet Attitude questionnaire

Enhanced mechanical, thermal and flame retardant properties by combining graphene nanosheets and metal hydroxide nanorods for Acrylonitrile–Butadiene–Styrene copolymer composite

Three metal hydroxide nanorods (MHR) with uniform diameters were synthesized, and then combined with graphene nanosheets (GNS) to prepare acrylonitrile–butadiene–styrene (ABS) copolymer composites. An excellent dispersion of exfoliated two-dimensional (2-D) GNS and 1-D MHR in the ABS matrix was achieved. The effects of combined GNS and MHR on the mechanical, thermal and flame retardant properties of the ABS composites were investigated. With the addition of 2 wt% GNS and 4 wt% Co(OH)2, the tensile strength, bending strength and storage modulus of the ABS composites were increased by 45.1%, 40.5% and 42.3% respectively. The ABS/GNS/Co(OH)2 ternary composite shows the lowest maximum weight loss rate and highest residue yield. Noticeable reduction in the flammability was achieved with the addition of GNS and Co(OH)2, due to the formation of more continuous and compact charred layers that retarded the mass and heat transfer between the flame and the polymer matrix

Model Checking Access Control Policies: A Case Study using Google Cloud IAM

Authoring access control policies is challenging and prone to misconfigurations. Access control policies must be conflict-free. Hence, administrators should identify discrepancies between policy specifications and their intended function to avoid violating security principles. This paper aims to demonstrate how to formally verify access control policies. Model checking is used to verify access control properties against policies supported by an access control model. The authors consider Google's Cloud Identity and Access Management (IAM) as a case study and follow NIST's guidelines to verify access control policies automatically. Automated verification using model checking can serve as a valuable tool and assist administrators in assessing the correctness of access control policies. This enables checking violations against security principles and performing security assessments of policies for compliance purposes. The authors demonstrate how to define Google's IAM underlying role-based access control (RBAC) model, specify its supported policies, and formally verify a set of properties through three examples

Chinese Children's Knowledge of Topicalization : Experimental Evidence from a Comprehension Study

There is a debate as to whether topic structures in Chinese involve A'-movement or result from base-generation of the topic in the left periphery. If Chinese topicalization was derived by movement, under the assumptions of Friedmann et al.'s Relativized Minimality (Lingua 119:67-88, ), we would expect children's comprehension of object topicalization (with OSV order) to be worse than their comprehension of subject topicalization (with SVO order). This study examined 146 Mandarin-speaking children from age three to age six by means of a picture-sentence matching task with an appropriate context. The results showed a subject/object asymmetry when the topic marker is overt, and no asymmetry when the topic marker is covert. This suggests that the presence or absence of topic markers play an important role in children's comprehension of topicalization. We propose that both structures involve movement in the adult grammar, but not in the child grammar, at least initially. Sentences without overt topic markers are base-generated on a par with gapless sentences with a topic, and the base-generation analysis is abandoned as soon as children learn the syntax and semantics of topic markers, which function as attractors of topics

The Fokker-Planck equation for bistable potential in the optimized expansion

The optimized expansion is used to formulate a systematic approximation scheme to the probability distribution of a stochastic system. The first order approximation for the one-dimensional system driven by noise in an anharmonic potential is shown to agree well with the exact solution of the Fokker-Planck equation. Even for a bistable system the whole period of evolution to equilibrium is correctly described at various noise intensities.Comment: 12 pages, LATEX, 3 Postscript figures compressed an

Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems

End-to-end (E2E) task-oriented dialogue (ToD) systems are prone to fall into the so-called 'likelihood trap', resulting in generated responses which are dull, repetitive, and often inconsistent with dialogue history. Comparing ranked lists of multiple generated responses against the 'gold response' (from training data) reveals a wide diversity in response quality, with many good responses placed lower in the ranked list. The main challenge, addressed in this work, is then how to reach beyond greedily generated system responses, that is, how to obtain and select such high-quality responses from the list of overgenerated responses at inference without availability of the gold response. To this end, we propose a simple yet effective reranking method which aims to select high-quality items from the lists of responses initially overgenerated by the system. The idea is to use any sequence-level (similarity) scoring function to divide the semantic space of responses into high-scoring versus low-scoring partitions. At training, the high-scoring partition comprises all generated responses whose similarity to the gold response is higher than the similarity of the greedy response to the gold response. At inference, the aim is to estimate the probability that each overgenerated response belongs to the high-scoring partition, given only previous dialogue history. We validate the robustness and versatility of our proposed method on the standard MultiWOZ dataset: our methods improve a state-of-the-art E2E ToD system by 2.4 BLEU, 3.2 ROUGE, and 2.8 METEOR scores, achieving new peak results. Additional experiments on the BiTOD dataset and human evaluation further ascertain the generalisability and effectiveness of the proposed framework.Comment: 22 pages, 10 figure

Insanity as a Defense to the Civil Fraud Penalty

Most neurological diseases are associated with chronic inflammation initiated by the activation of microglia, which produce cytotoxic and inflammatory factors. Signal transducers and activators of transcription (STATs) are potent regulators of gene expression but contribution of particular STAT to inflammatory gene expression and STAT-dependent transcriptional networks underlying brain inflammation need to be identified. In the present study, we investigated the genomic distribution of Stat binding sites and the role of Stats in the gene expression in lipopolysaccharide (LPS)-activated primary microglial cultures. Integration of chromatin immunoprecipitation-promoter microarray data and transcriptome data revealed novel Stat-target genes including Jmjd3, Ccl5, Ezr, Ifih1, Irf7, Uba7, and Pim1. While knockdown of individual Stat had little effect on the expression of tested genes, knockdown of both Stat1 and Stat3 inhibited the expression of Jmjd3 and inflammatory genes. Transcriptional regulation of Jmjd3 by Stat1 and Stat3 is a novel mechanism crucial for launching inflammatory responses in microglia. The effects of Jmjd3 on inflammatory gene expression were independent of its H3K27me3 demethylase activity. Forced expression of constitutively activated Stat1 and Stat3 induced the expression of Jmjd3, inflammation-related genes, and the production of proinflammatory cytokines as potently as lipopolysacharide. Gene set enrichment and gene function analysis revealed categories linked to the inflammatory response in LPS and Stat1C + Stat3C groups. We defined upstream pathways that activate STATs in response to LPS and demonstrated contribution of Tlr4 and Il-6 and interferon-. signaling. Our findings define novel direct transcriptional targets of Stat1 and Stat3 and highlight their contribution to inflammatory gene expression

Large-Scale Landslide Susceptibility Mapping Using an Integrated Machine Learning Model: A Case Study in the Lvliang Mountains of China

Integration of different models may improve the performance of landslide susceptibility assessment, but few studies have tested it. The present study aims at exploring the way to integrating different models and comparing the results among integrated and individual models. Our objective is to answer this question: Will the integrated model have higher accuracy compared with individual model? The Lvliang mountains area, a landslide-prone area in China, was taken as the study area, and ten factors were considered in the influencing factors system. Three basic machine learning models (the back propagation (BP), support vector machine (SVM), and random forest (RF) models) were integrated by an objective function where the weight coefficients among different models were computed by the gray wolf optimization (GWO) algorithm. 80 and 20% of the landslide data were randomly selected as the training and testing samples, respectively, and different landslide susceptibility maps were generated based on the GIS platform. The results illustrated that the accuracy expressed by the area under the receiver operating characteristic curve (AUC) of the BP-SVM-RF integrated model was the highest (0.7898), which was better than that of the BP (0.6929), SVM (0.6582), RF (0.7258), BP-SVM (0.7360), BP-RF (0.7569), and SVM-RF models (0.7298). The experimental results authenticated the effectiveness of the BP-SVM-RF method, which can be a reliable model for the regional landslide susceptibility assessment of the study area. Moreover, the proposed procedure can be a good option to integrate different models to seek an "optimal" result. Keywords: landslide susceptibility, random forest, integrated model, causal factor, GI