Mechanism of Action and Clinical Potential of Fingolimod for the Treatment of Stroke

Fingolimod (FTY720) is an orally bio-available immunomodulatory drug currently approved by the FDA for the treatment of multiple sclerosis. Currently, there is a significant interest in the potential benefits of FTY720 on stroke outcomes. FTY720 and the sphingolipid signaling pathway it modulates has a ubiquitous presence in the central nervous system and both rodent models and pilot clinical trials seem to indicate that the drug may improve overall functional recovery in different stroke subtypes. Although the precise mechanisms behind these beneficial effects are yet unclear, there is evidence that FTY720 has a role in regulating cerebrovascular responses, blood brain barrier permeability, and cell survival in the event of cerebrovascular insult. In this article, we critically review the data obtained from the latest laboratory findings and clinical trials involving both ischemic and hemorrhagic stroke, and attempt to form a cohesive picture of FTY720’s mechanisms of action in strok

Cross-Lingual Adaptation for Type Inference

Deep learning-based techniques have been widely applied to the program analysis tasks, in fields such as type inference, fault localization, and code summarization. Hitherto deep learning-based software engineering systems rely thoroughly on supervised learning approaches, which require laborious manual effort to collect and label a prohibitively large amount of data. However, most Turing-complete imperative languages share similar control- and data-flow structures, which make it possible to transfer knowledge learned from one language to another. In this paper, we propose cross-lingual adaptation of program analysis, which allows us to leverage prior knowledge learned from the labeled dataset of one language and transfer it to the others. Specifically, we implemented a cross-lingual adaptation framework, PLATO, to transfer a deep learning-based type inference procedure across weakly typed languages, e.g., Python to JavaScript and vice versa. PLATO incorporates a novel joint graph kernelized attention based on abstract syntax tree and control flow graph, and applies anchor word augmentation across different languages. Besides, by leveraging data from strongly typed languages, PLATO improves the perplexity of the backbone cross-programming-language model and the performance of downstream cross-lingual transfer for type inference. Experimental results illustrate that our framework significantly improves the transferability over the baseline method by a large margin

Learning to Learn Kernels with Variational Random Features

In this work, we introduce kernels with random Fourier features in the meta-learning framework to leverage their strong few-shot learning ability. We propose meta variational random features (MetaVRF) to learn adaptive kernels for the base-learner, which is developed in a latent variable model by treating the random feature basis as the latent variable. We formulate the optimization of MetaVRF as a variational inference problem by deriving an evidence lower bound under the meta-learning framework. To incorporate shared knowledge from related tasks, we propose a context inference of the posterior, which is established by an LSTM architecture. The LSTM-based inference network can effectively integrate the context information of previous tasks with task-specific information, generating informative and adaptive features. The learned MetaVRF can produce kernels of high representational power with a relatively low spectral sampling rate and also enables fast adaptation to new tasks. Experimental results on a variety of few-shot regression and classification tasks demonstrate that MetaVRF delivers much better, or at least competitive, performance compared to existing meta-learning alternatives.Comment: ICML'2020; code is available in: https://github.com/Yingjun-Du/MetaVR

Research on rainy day traffic sign recognition algorithm based on PMRNet

The recognition of traffic signs is of great significance to intelligent driving and traffic systems. Most current traffic sign recognition algorithms do not consider the impact of rainy weather. The rain marks will obscure the recognition target in the image, which will lead to the performance degradation of the algorithm, a problem that has yet to be solved. In order to improve the accuracy of traffic sign recognition in rainy weather, we propose a rainy traffic sign recognition algorithm. The algorithm in this paper includes two modules. First, we propose an image deraining algorithm based on the Progressive multi-scale residual network (PMRNet), which uses a multi-scale residual structure to extract features of different scales, so as to improve the utilization rate of the algorithm for information, combined with the Convolutional long-short term memory (ConvLSTM) network to enhance the algorithm's ability to extract rain mark features. Second, we use the CoT-YOLOv5 algorithm to recognize traffic signs on the recovered images. In this paper, in order to improve the performance of YOLOv5 (You-Only-Look-Once, YOLO), the 3 × 3 convolution in the feature extraction module is replaced by the Contextual Transformer (CoT) module to make up for the lack of global modeling capability of Convolutional Neural Network (CNN), thus improving the recognition accuracy. The experimental results show that the deraining algorithm based on PMRNet can effectively remove rain marks, and the evaluation indicators Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) are better than the other representative algorithms. The mean Average Precision (mAP) of the CoT-YOLOv5 algorithm on the TT100k datasets reaches 92.1%, which is 5% higher than the original YOLOv5

PEMBELAJARAN LUKIS TOTEBAG PADA MATA PELAJARAN SENI BUDAYA DI KELAS X MIA 3 SMA NEGERI 3 BOYOLALI TAHUN AJARAN 2017/2018

ABSTRAK Muhammad Fahmi Al Amiq. PEMBELAJARAN LUKIS PADA TOTEBAG DALAM MATA PELAJARAN SENI BUDAYA DI KELAS X MIA 3 SMA NEGERI 3 BOYOLALI TAHUN AJARAN 2017/2018. Skripsi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Sebelas Maret Surakarta, Januari 2018. Tujuan penelitian ini adalah untuk mengetahui: (1) Proses pelaksanaan pembelajaran Lukis Totebag di kelas X MIA 3 SMA Negeri 3 Boyolali tahun ajaran 2017/2018. Dan (2) Bagaimana bentuk hasil karya Lukis Totebag yang dihasilkan siswa di kelas X MIA 3 SMA Negeri 3 Boyolali tahun ajaran 2017/2018. Penelitian ini menggunakan pendekatan kualitatif. Sumber data yang digunakan adalah informan yang dipilih yaitu Bapak Subandiyo S.Pd selaku guru mata pelajaran seni budaya di kelas X MIA 3 SMA Negeri 3 Boyolali, serta foto proses pembelajaran, hasil karya siswa dan dokumen arsip. Teknik yang digunakan dalam pengumpulan data adalah observasi langsung, wawancara terstruktur dan mendalam, serta dokumentasi. Uji validitas data dilakukan dengan membandingkan sumber data yang di peroleh berupa daftar hasil wawancara dengan Bapak Subandiyo S.Pd selaku guru mata pelajaran Seni Budaya dengan siswa di kelas X MIA 3 SMA Negeri 3 Boyolali, serta review informant. Analisis data yang digunakan adalah model analisis mengalir, yaitu: reduksi data, sajian data, dan penarikan kesimpulan. Hasil penelitian ini menunjukkan bahwa: (1) Pembelajaran Lukis Totebag diawali dengan pembuatan RPP, selanjutnya pembelajaran dilaksanakan selama tiga kali pertemuan. Strategi yang digunakan guru dalam pembelajaran ini adalah pendekatan scientific. Metode pembelajaran yang digunakan meliputi metode ceramah, tanya jawab, diskusi, dan pemberian tugas. Media pembelajaran yang digunakan berupa slide power point dan media visual berupa sampel karya dari guru. Evaluasi pembelajaran dilakukan dengan menilai aspek kognitif, afektif, dan psikomotorik. Proses pembuatan karya dilakukan dengan beberapa langkah, yaitu membuat sketsa, proses pewarnaan, dan finishing. (2) Secara umum pembuatan karya lukis totebag siswa sudah baik, teknik lukis pada pewarnaan dan finishing dalam membuat karya lukis totebag sudah baik. Karya lukis totebag yang dihasilkan oleh siswa sudah mengandung unsur-unsur seni rupa, yaitu: garis, bentuk, bidang, gelap terang, dan warna. Selain itu, karya lukis totebag yang dihasilkan oleh siswa juga sudah mengandung prinsip-prinsip seni rupa, yaitu: irama (rhytm), dominasi (dominance), keseimbangan (balance), kesatuan (unity), keserasian (harmony), dan kesebandingan (proportion). Kata Kunci: Seni Budaya, Pembelajaran Seni Rupa, Lukis Toteba

Dynamic Analysis of the Rod-Fastened Rotor Considering the Characteristics of Circumferential Tie Rods

The research on the dynamic performance of the rod-fastened rotor (RFR) has always been a hotspot. However, the structural complexity of RFR has brought significant challenges to the dynamic study of the RFR. The tie rods provide preload for the rotor shaft segment, while the coordinate deformation of the tie rods will occur during the process of vibration. In addition, the tie rods and the rotor shaft segments are structurally connected in parallel. These factors all will influence the dynamic performance of the RFR. In this paper, for a RFR system, the vibration equation of the RFR considering all factors of the tie rods is deduced in detail. The influence of various factors on the dynamic performance of the rotor is investigated. Results show that the preload directly affects the dynamic performance of the RFR system. When the preload is small, the tie rod has a larger influence on the natural frequencies of the rotor. However, when the preload force reaches a certain value, the influence of the tie rod on the natural frequencies of the rotor is almost negligible. The research results provide a theoretical reference for the understanding of and further research on RFR

Interactive Effects of Rarefaction and Surface Roughness on Aerodynamic Lubrication of Microbearings

The aerodynamic lubrication performance of gas microbearing has a particularly critical impact on the stability of the bearing-rotor system in micromachines. Based on the Duwensee’s slip correction model and the fractal geometry theory, the interactive effects of gas rarefaction and surface roughness on the static and dynamic characteristics were investigated under various operation conditions and structure parameters. The modified Reynolds equation, which governs the gas film pressure distribution in rough bearing, is solved by employing the partial derivative method. The results show that high values of the eccentricity ratio and bearing number tend to increase the principal stiffness coefficients significantly, and the fractal roughness surface considerably affects the ultra-thin film damping characteristics compared to smooth surface bearing

Digital trade and environmental sustainability: the role of financial development and ecological innovation for a greener revolution in China

AbstractChina’s government has pledged to attain net-zero emissions by 2050 and aims to create the world’s most resilient and forward-looking border by 2025. It has outlined a high-level vision for digital trade and a freeport plan and guarantees to implement new free trade agreements, develop infrastructure, and equalise the economy. Therefore, this study explores the dynamic impact of digital trade and financial development on ecological sustainability from 2000-Q1 to 2020-Q4. We apply the Bootstrap ARDL model for empirical analysis and found that digital trade in goods and services, financial development, and green innovation are conducive to long-term environmental sustainability. Similar results are also observed in the short run; however, the influence of short-run parameters is relatively lower. Moreover, the error correction term endorses convergence towards stable equilibrium with a 32.7% quarterly adjustment rate. Granger causality test report uni-direction casualty in all variables, except green innovation and carbon emissions. These findings recommend an inclusive policy for promoting digital trade, financial integration, and green innovation in China

Packet Loss Measurement Based on Sampled Flow

This paper is devoted to further strengthening, in the current asymmetric information environment, the informed level of operators about network performance. Specifically, in view of the burst and perishability of a packet loss event, to better meet the real-time requirements of current high-speed backbone performance monitoring, a model for Packet Loss Measurement at the access network boundary Based on Sampled Flow (PLMBSF) is presented in this paper under the premise of both cost and real-time. The model overcomes problems such as the inability of previous estimation to distinguish between packet losses before and after the monitoring point, deployment difficulties and cooperative operation consistency. Drawing support from the Mathis equation and regression analysis, the measurement for packet losses before and after the monitoring point can be realized when using only the sampled flows generated by the access network boundary equipment. The comparison results with the trace-based passive packet loss measurement show that although the proposed model is easily affected by factors such as flow length, loss rate, sampling rate, the overall accuracy is still within the acceptable range. In addition, the proposed model PLMBSF, compared with the trace-based loss measurement is only different in the input data granularity. Therefore, PLMBSF and its advantages are also applicable to aggregated traffic