Anxiety and self-efficacy in Chinese international students’ L3 French learning with L2 English and L3 French

The present study explored the relationship between international students’ Third Language Anxiety (TLA) and self-efficacy. The research data were collected through questionnaires involving 243 Chinese International students’ L3 French Learning with L2 English and L3 French at one university in the U.K. Three of them were interviewed about their experience of anxiety and self-efficacy. Major findings include four underlying factors correlated with TLA and two underlying factors correlated with self-efficacy. Also, levels of these students’ TLA were negatively correlated with the level of their self-efficacy, as shown in the correlational analysis. Then, two linear regression models were built to contribute to the prediction of their self-efficacy levels. Lastly, participants reported that grammatical and pronunciation similarities between English (L2) and French (L3) positively decreased their anxiety levels. All of these interviewees encountered communication apprehension. These findings can provide educational implications for L3 teaching and learning, inspiring teachers to consider international students’ TLA and self-efficacy and thus propose some coping strategies

Anomaly detection in spatiotemporal data via regularized non-negative tensor analysis

Anomaly detection in multidimensional data is a challenging task. Detecting anomalous mobility patterns in a city needs to take spatial, temporal, and traffic information into consideration. Although existing techniques are able to extract spatiotemporal features for anomaly analysis, few systematic analysis about how different factors contribute to or affect the anomalous patterns has been proposed. In this paper, we propose a novel technique to localize spatiotemporal anomalous events based on tensor decomposition. The proposed method employs a spatial-feature-temporal tensor model and analyzes latent mobility patterns through unsupervised learning. We first train the model based on historical data and then use the model to capture the anomalies, i.e., the mobility patterns that are significantly different from the normal patterns. The proposed technique is evaluated based on the yellow-cab dataset collected from New York City. The results show several interesting latent mobility patterns and traffic anomalies that can be deemed as anomalous events in the city, suggesting the effectiveness of the proposed anomaly detection method

Pengembangan Media Pembelajaran Fisika Berupa Buletin Dalam Bentuk Buku Saku Untuk Pembelajaran Fisikakelas VIII Materi Gaya Ditinjau Dari Minat Baca Siswa

Tujuan dari penelitian ini untuk mengembangkan media pembelajaran berupa buletin dalam bentuk buku saku untuk pembelajaran Fisika kelas VIII pada materi Gaya ditinjau dari aspek materi, konstruk, dan bahasa serta minat baca siswa. Penelitian ini termasuk penelitian pengembangan yang menggunakan metode Research and Development (R&D). Penelitian ini menggunakan model pengembangan model prosedural yaitu model yang bersifat deskriptif yang menunjukkan tahapan-tahapan yang harus diikuti untuk menghasilkan produk berupa media pembelajaran.Jenis data yang diperoleh bersifat kualitatif dan kuantitatif yaitu angket dan wawancara. Teknik analisis data yang digunakan adalah analisis deskriptif kualitatif dan kuantitatif. Hasil penelitian menunjukkan bahwa media pembelajaran yang dikembangkan berupa buletin Fisika dalam bentuk buku saku memiliki kriteria sangat baik berdasarkan penilaian dari ahli materi, ahli bahasa Indonesia, dan ahli media memberikan rata-rata penilaian sebesar 86,56%. Media pembelajaran yang dikembangkan juga memiliki kriteria sangat baik bila ditinjau dari peningkatan minat baca siswa. Hal ini terbukti pada hasil angket minat baca awal dan akhir yang diberikan kepada siswa yang memberikan rata-rata peningkatan sebesar 11,13%. Selain itu juga dianalisis dengan menggunakan uji-t berpasangan terhadap data masing-masing kelompok uji coba untuk mengetahui signifikansi dari peningkatan minat baca siswa. Untuk uji coba perorangan diperoleh hasil perhitungan thitung = 6,957 > ttabel = 1,943 dan nilai Sig. = 0,001 < 0,05 yang berarti sangat signifikan. Untuk kelompok kecil didapatkan hasil perhitungan bahwa thitung = 7,848 > ttabel = 1,725 dan nilai Sig. = 0,000 < 0,05 yang berarti sangat signifikan. Untuk kelompok besar juga didapatkan hasil perhitungan bahwa thitung = 20,214 > ttabel = 1,725 dan nilai Sig. = 0,000 < 0,05 yang berarti sangat signifikan. Simpulan dari penelitian ini adalah media pembelajaran berupa buletin dalam bentuk buku saku memiliki kriteria sangat baik bila ditinjau dari aspek materi, konstruk, dan bahasa serta minat baca siswa

Recent research on the synthesis pentazolate anion cyclo-N5−

Polynitrogen compounds contain a large amount of NN and N=N, and their decomposition products are mainly nitrogen, with the advantages of high density, high heat, high energy and pollution-free products. Such compounds have potential application prospects and are candidates for a new generation of energetic materials. The pentazolate anion, or cyclo-N5−, which is the first polynitrogen anion of azoles, has an impressive stable aromatic structure and has become a hot topic. In this review, we summary the research progress of pentazole synthesis in recent years, including the precursors, synthesis, properties and derivatives, which involves the following topics: (1) the preparation of cyclo-N5−; (2) synthesis of pentazole complexes; (3) properties and derivatives of cyclo-N5−. This review is intended to improve the understanding of pentazole for their further development and applications

Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data

The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifying anomalies in large, dynamic and heterogeneous data, interpreting anomalies in their multifaceted, spatiotemporal context, and allowing users to provide feedback in the analysis loop. In this work, we introduce a unified visual interactive system and framework, Voila, for interactively detecting anomalies in spatiotemporal data collected from a streaming data source. The system is designed to meet two requirements in real-world applications, i.e., online monitoring and interactivity. We propose a novel tensor-based anomaly analysis algorithm with visualization and interaction design that dynamically produces contextualized, interpretable data summaries and allows for interactively ranking anomalous patterns based on user input. Using the “smart city” as an example scenario, we demonstrate the effectiveness of the proposed framework through quantitative evaluation and qualitative case studies

Effect of Hydrogen Bond Interaction on the Decomposition Temperature, Aromaticity, and Bond Order of Nonmetallic Pentazolate Salts

Nonmetallic pentazolate (cyclo-N5–) salts are novel polynitrogen high-energy-density materials with great potential and application prospects. Hydrogen bond networks play a vital role in improving the thermal stability of these compounds. In order to further increase the decomposition temperature (Td) and attain a more thorough exploration of these compounds, we evaluated and visualized the energy of hydrogen bonds (E_HBs) and the effects of HBs on Td, aromaticity, and the Mayer bond order (MBO). The increase in the total E_HBs can increase the Td, such as with 3,6,7-triamino-7H-[1,2,4]­triazolo­[4,3-b]­[1,2,4]­triazol-2-ium and biguanidinium pentazolates. Moreover, an increase in the maximum E_HBs can reduce the aromaticity of the cyclo-N5– anion and increase the difference between the maximum and minimum MBO, like 3,9-diamino-6,7-dihydro-5H-bis­([1,2,4]­triazolo)­[4,3-e:3′,4′-g]­[1,2,4,5]­tetrazepine-2,10- diium and O-(carboxymethyl)­hydroxylammonium pentazolates. In addition, increasing the number of donors of hydrogen bonds, especially the proportion of O–H bonds, can significantly increase the Td of pentazolate salts

UBXN1 interacts with the S1 protein of transmissible gastroenteritis coronavirus and plays a role in viral replication

Abstract Transmissible gastroenteritis coronavirus (TGEV) is an enteropathogenic coronavirus that causes diarrhea in pigs and is associated with high morbidity and mortality in sucking piglets. S1 is one of two protein domains in the spike (S) glycoprotein and is responsible for enteric tropism, sialic acid recognition, and host receptor binding. Although there has been extensive research on the S1 protein of TGEV, little is known about the intracellular role of TGEV-S1. In the present study, we used yeast two-hybrid screening of a cDNA library from porcine intestinal cells to identify proteins that interact with TGEV-S1. Among 120 positive clones from the library, 12 intracellular proteins were identified after sequencing and a BLAST search. These intracellular proteins are involved in protein synthesis and degradation, biological signal transduction, and negative control of signaling pathways. Using a glutathione-S-transferase (GST) pulldown assay and Co-IP, we found that UBXN1 interacts with the S1 protein. Here, we observed that TGEV infection led to increased UBXN1 expression levels during the late phase of infection in IPEC-J2 cells. Inhibition of UBXN1 in IPEC-J2 cells via siRNA interference significantly decreased the viral titer and downregulated the expression of S1. UBXN1 overexpression significantly increased the viral copy number. Additionally, we provided data suggesting that UBXN1 negatively regulates IFN-β expression after TGEV infection. Finally, our research indicated that UBXN1 plays a vital role in the process of TGEV infection, making it a candidate target for the development of a novel antiviral method