Flipping the classoom in teaching Chinese as a foreign language

Through an in-depth analysis of quantitative and qualitative data, this article offers a case study of the advantages and challenges in the application of the flipped learning approach in the instruction of Chinese as a foreign language at the beginning level. Data were collected from two first-year Chinese classes (one in traditional and the other in flipped format) to investigate whether there were statistically significant differences in learning outcomes and students’ levels of satisfaction between the two classes. Final exam and oral test scores showed that students in the flipped class performed better in speaking, since more time was devoted to meaningful interactions in class. As indicated in the results of the end-of-the-semester questionnaire, these students also gave higher average ratings on three aspects of their learning experience: level of required self-directedness, amount of practice in class, and stimulation of interest in the subject

On the distance-edge-monitoring numbers of graphs

Foucaud et al. [Discrete Appl. Math. 319 (2022), 424-438] recently introduced and initiated the study of a new graph-theoretic concept in the area of network monitoring. For a set $M$ of vertices and an edge $e$ of a graph $G$, let $P(M, e)$ be the set of pairs $(x, y)$ with a vertex $x$ of $M$ and a vertex $y$ of $V(G)$ such that $d_G(x, y)\neq d_{G-e}(x, y)$. For a vertex $x$, let $EM(x)$ be the set of edges $e$ such that there exists a vertex $v$ in $G$ with $(x, v) \in P(\{x\}, e)$. A set $M$ of vertices of a graph $G$ is distance-edge-monitoring set if every edge $e$ of $G$ is monitored by some vertex of $M$, that is, the set $P(M, e)$ is nonempty. The distance-edge-monitoring number of a graph $G$, denoted by $dem(G)$, is defined as the smallest size of distance-edge-monitoring sets of $G$. The vertices of $M$ represent distance probes in a network modeled by $G$; when the edge $e$ fails, the distance from $x$ to $y$ increases, and thus we are able to detect the failure. It turns out that not only we can detect it, but we can even correctly locate the failing edge. In this paper, we continue the study of \emph{distance-edge-monitoring sets}. In particular, we give upper and lower bounds of $P(M,e)$, $EM(x)$, $dem(G)$, respectively, and extremal graphs attaining the bounds are characterized. We also characterize the graphs with $dem(G)=3$

TTVFI: Learning Trajectory-Aware Transformer for Video Frame Interpolation

Video frame interpolation (VFI) aims to synthesize an intermediate frame between two consecutive frames. State-of-the-art approaches usually adopt a two-step solution, which includes 1) generating locally-warped pixels by flow-based motion estimations, 2) blending the warped pixels to form a full frame through deep neural synthesis networks. However, due to the inconsistent warping from the two consecutive frames, the warped features for new frames are usually not aligned, which leads to distorted and blurred frames, especially when large and complex motions occur. To solve this issue, in this paper we propose a novel Trajectory-aware Transformer for Video Frame Interpolation (TTVFI). In particular, we formulate the warped features with inconsistent motions as query tokens, and formulate relevant regions in a motion trajectory from two original consecutive frames into keys and values. Self-attention is learned on relevant tokens along the trajectory to blend the pristine features into intermediate frames through end-to-end training. Experimental results demonstrate that our method outperforms other state-of-the-art methods in four widely-used VFI benchmarks. Both code and pre-trained models will be released soon

Angelica sinensis polysaccharide promotes apoptosis by inhibiting JAK/STAT pathway in breast cancer cells

Purpose: To determine whether Angelica polysaccharide (APS) induced apoptosis via regulation of the Janus kinase (JAK)/signal transducers and activators of transcription (STAT) pathway in breast cancer cells. Methods: Human MCF-7 cells were treated with APS. Cell proliferation, apoptosis, expression of apoptotic proteins, and the phosphorylation level of Janus kinase (JAK) and STAT were measured, respectively. For further analysis, MCF-7 cells were transfected with a JAK2 overexpression plasmid or treated with a classical JAK inhibitor, ruxolitinib. Results: Treatment with APS dose-dependently reduced cell proliferation, induced apoptosis, and downregulated the levels of phosphorylated JAK and STAT in MCF-7 cells. JAK inhibitor, ruxolitinib, blocked JAK/STAT pathway and induced cell apoptosis in MCF-7 cells. Besides, JAK2 overexpression reversed the effects of APS on cell viability and apoptosis. Conclusion: The results indicate that polysaccharide isolated from Angelica sinensis promotes apoptosis by inhibiting JAK/STAT pathway in breast cancer cells. Thus, APS may be useful as a potential therapeutic agent for breast cancer

Adonis: Practical and Efficient Control Flow Recovery through OS-Level Traces

Control flow recovery is critical to promise the software quality, especially for large-scale software in production environment. However, the efficiency of most current control flow recovery techniques is compromised due to their runtime overheads along with deployment and development costs. To tackle this problem, we propose a novel solution, Adonis, which harnesses OS-level traces, such as dynamic library calls and system call traces, to efficiently and safely recover control flows in practice. Adonis operates in two steps: it first identifies the call-sites of trace entries, then it executes a pair-wise symbolic execution to recover valid execution paths. This technique has several advantages. First, Adonis does not require the insertion of any probes into existing applications, thereby minimizing runtime cost. Second, given that OS-level traces are hardware-independent, Adonis can be implemented across various hardware configurations without the need for hardware-specific engineering efforts, thus reducing deployment cost. Third, as Adonis is fully automated and does not depend on manually created logs, it circumvents additional development cost. We conducted an evaluation of Adonis on representative desktop applications and real-world IoT applications. Adonis can faithfully recover the control flow with 86.8% recall and 81.7% precision. Compared to the state-of-the-art log-based approach, Adonis can not only cover all the execution paths recovered, but also recover 74.9% of statements that cannot be covered. In addition, the runtime cost of Adonis is 18.3× lower than the instrument-based approach; the analysis time and storage cost (indicative of the deployment cost) of Adonis is 50× smaller and 443× smaller than the hardware-based approach, respectively. To facilitate future replication and extension of this work, we have made the code and data publicly available

Uterine perivascular epithelioid tumors (PEComas) with lung metastasis showed good responses to mTOR and VEGFR inhibitors: A case report

Perivascular epithelioid cell tumors (PEComas) are extremely rare mesenchymal neoplasms for which the uterus is the most common site. The prognosis of malignant PEComa is poor as it is characterized by resistance to classical chemotherapies. Both mTOR inhibitors and VEGFR inhibitors exhibited clinical utility in treating malignant PEComas, but the combination of these two regimens has rarely been reported. In the present case, a uterine PEComa patient developed lung and bone metastases after the failure of chemotherapies and derived benefit from the combination regimen of an mTOR inhibitor (everolimus) and a VEGFR inhibitor (apatinib), achieving a 15-month progression-free survival. Targeted NGS revealed TP53 and TSC2 mutations in the patient’s primary uterine tumors and plasma ctDNA at disease progression. Plasma ctDNA clearance was consistent with a radiologic partial response determined by RECIST 1.1 and a reduction of neuron-specific enolase (NSE) and cancer antigen 125 (CA125) levels. Thus, we provided clinical evidence supporting the administration of combined therapy of mTOR and VEGFR inhibitors to metastatic uterine PEComa patients and highlighted the application of serial plasma ctDNA profiling for dynamic disease monitoring

Cobalt Nanoparticles Encapsulated in Nitrogen-Doped Carbon Nanotube as Bifunctional-Catalyst for Rechargeable Zn-Air Batteries

Developing economic and efficient non-noble-metal electrocatalysts toward oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is vitally important to improve the performance and economic outlook of alkaline-based rechargeable Zn-air battery technologies. In this work, a nitrogen-doped carbon nanotube encapsulated with metallic cobalt nanoparticles (Co@NC) was synthesized through a facile method and subsequent pyrolysis treatment. The field emission scanning electron microscope (FESEM), high resolution transmission electron microscopy (HRTEM), Raman spectra investigations demonstrate that the presence of Co induces the formation of carbon nanotube during the pyrolysis process and increase degree of graphitization of carbon nanotubes. The electrode activity is assessed by comparing OER with ORR indicators (ΔE). The ΔE value of Co@NC is 0.91 V, which is lower than the commercialized Pt/C (1.1 V) and nitrogen-doped carbon (NC) (1.17 V). The Co@NC-based primary Zn-air battery display an open circuit potential of 1.4 V, a high power density of 137 mW·cm−2, and outstanding energy density (708.3 mAh·kgZn-1 and 868.9 Wh kgZn-1 at 10 mA·cm−2), which batter than the commercialized Pt/C

Spatial Distribution Pattern and Sampling Plans for Two Sympatric <i>Tomicus</i> Species Infesting <i>Pinus yunnanensis</i> during the Shoot-Feeding Phase

Tomicus minor (Hartig) and Tomicus yunnanensis Kirkendall and Faccoli are two sympatric species that infest Pinus yunnanensis (Franchet) in southwest China, contributing to growth losses. Accurate sampling plans are needed to make informed control decisions for these species. We investigated three pine forests within experimental sites in Yuxi, Yunnan province, China from 2016 to 2018. The spatial distribution patterns of two pine shoot beetles during the shoot-feeding phase were determined using Taylor’s power law. The optimum sample sizes and stop lines for precision levels of 0.25 and 0.10 were calculated. The model was validated using an additional 15 and 17 independent field datasets ranging in density from 0.06 to 1.90 beetles per tree. T. minor and T. yunnanensis adults showed aggregated spatial distributions. For T. minor, sample sizes of 41 and 259 trees were adequate for a D of 0.25 and 0.10, respectively, while for T. yunnanensis, a mean density of one individual per tree required sample sizes of 33 plants (D = 0.25) and 208 plants (D = 0.10). The software simulations of this sampling plan showed precision levels close to the desired levels. At a fixed-precision level of 0.25, sampling is easily achievable. This sampling program is useful for the integrated pest management (IPM) of two sympatric Tomicus species