Research on Repatriates’ Incentive Mechanism: Based on Knowledge Transfer Perspective

Repatriates’ experience and knowledge is important competition advantage for the parent company in international business. This paper discussed repatriates’ incentive mechanism based on the perspective of knowledge transfer, established theoretic model of repatriates’ knowledge transfer incentive mechanism, and pointed out that knowledge transfer was a process of repeated game between the parent company and the repatriates, the establishing of knowledge transfer incentive mechanism was trying to reach the equilibrium of the game, it provided theoretic basis for promoting repatriates’ knowledge transfer effectivel

Incentive Decision on Safety Investment of Supply Chain of Agricultural Products in “Agricultural Super-Docking”

Since the “agriculture super-docking” mode was introduced in China in 2007, remarkable success has been made in reducing the transaction cost and improving the quality safety of agricultural products. However, the quality safety issues of agricultural products still occur frequently because both specialized farmers’ cooperatives and supermarkets have insufficient safety investment. In order to study the necessity, goal, and incentive decision schemes of safety investment in “agriculture super-docking” supply chain, three kinds of models, which include noncooperatives distributed decision-making model, centralized decision-making model, and incentive coordination models led by cooperatives and supermarkets, are, respectively, set up in this paper. Conclusions are drawn as follows: when making the uncooperative decentralized decision, both cooperatives and supermarkets have the moral risks to decrease the safety investment, but appropriate measures can achieve the coordination of the supply chain; when achieving the coordination of supply chain, the two contacts under the guidance of cooperatives and supermarkets are the same, and the schemes of distributing profits are also the same. Moreover, a practical case is given to improve the effectiveness and feasibility of the incentive decision schemes

Towards Effective Bug Triage with Software Data Reduction Techniques

International audienceSoftware companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer to a new bug. To decrease the time cost in manual work, text classification techniques are applied to conduct automatic bug triage. In this paper, we address the problem of data reduction for bug triage, i.e., how to reduce the scale and improve the quality of bug data. We combine instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word dimension. To determine the order of applying instance selection and feature selection, we extract attributes from historical bug data sets and build a predictive model for a new bug data set. We empirically investigate the performance of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and Mozilla. The results show that our data reduction can effectively reduce the data scale and improve the accuracy of bug triage. Our work provides an approach to leveraging techniques on data processing to form reduced and high-quality bug data in software development and maintenance

Flexible Alignment Super-Resolution Network for Multi-Contrast MRI

Magnetic resonance images play an essential role in clinical diagnosis by acquiring the structural information of biological tissue. However, during acquiring magnetic resonance images, patients have to endure physical and psychological discomfort, including irritating noise and acute anxiety. To make the patient feel cozier, technically, it will reduce the retention time that patients stay in the strong magnetic field at the expense of image quality. Therefore, Super-Resolution plays a crucial role in preprocessing the low-resolution images for more precise medical analysis. In this paper, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast magnetic resonance images Super-Resolution. The core of multi-contrast SR is to match the patches of low-resolution and reference images. However, the inappropriate foreground scale and patch size of multi-contrast MRI sometimes lead to the mismatch of patches. To tackle this problem, the Flexible Alignment module is proposed to endow receptive fields with flexibility. Flexible Alignment module contains two parts: (1) The Single-Multi Pyramid Alignmet module serves for low-resolution and reference image with different scale. (2) The Multi-Multi Pyramid Alignment module serves for low-resolution and reference image with the same scale. Extensive experiments on the IXI and FastMRI datasets demonstrate that the FASR-Net outperforms the existing state-of-the-art approaches. In addition, by comparing the reconstructed images with the counterparts obtained by the existing algorithms, our method could retain more textural details by leveraging multi-contrast images

Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech

Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems. In this paper, a cross-utterance conditional VAE (CUC-VAE) is proposed to estimate a posterior probability distribution of the latent prosody features for each phoneme by conditioning on acoustic features, speaker information, and text features obtained from both past and future sentences. At inference time, instead of the standard Gaussian distribution used by VAE, CUC-VAE allows sampling from an utterance-specific prior distribution conditioned on cross-utterance information, which allows the prosody features generated by the TTS system to be related to the context and is more similar to how humans naturally produce prosody. The performance of CUC-VAE is evaluated via a qualitative listening test for naturalness, intelligibility and quantitative measurements, including word error rates and the standard deviation of prosody attributes. Experimental results on LJ-Speech and LibriTTS data show that the proposed CUC-VAE TTS system improves naturalness and prosody diversity with clear margins

Kesesakan Dan Agresivitas Pada Remaja Di Kawasan Tambak Lorok Semarang

Penelitian ini bertujuan untuk mengetahui hubungan antara kesesakan dengan agresivitas pada remaja yang tinggal di Kawasan Tambak Lorok Semarang. Populasi dalam penelitian ini adalah remaja yang tinggal di Kawasan Tambak Lorok Semarang. Pengumpulan data menggunakan dua buah skala yaitu, Skala Agresivitas (22 aitem; α=0,864) dan Skala Kesesakan (16 aitem; α=0,828). Subjek penelitian berjumlah 230 remaja yang tinggal di Kawasan Tambak Lorok Semarang yang dipilih melalui teknik simple random sampling. Hasil analisis data menggunakan teknik analisis regresi sederhana menunjukkan terdapat hubungan positif antara kesesakan dengan agresivitas pada remaja yang tinggal Kawasan Tambak Lorok Semarang (r=0,578; p=0,000). Semakin tinggi kesesakan yang dirasakan subjek maka semakin tinggi agresivitas. Kesesakan memberikan sumbangan efektif sebesar 33,4% pada agresivitas dan sisanya sebesar 66,6% dipengaruhi oleh faktor lain yang tidak diteliti dalam penelitian ini

Upregulated CD8+ MAIT cell differentiation and KLRD1 gene expression after inactivated SARS-CoV-2 vaccination identified by single-cell sequencing

BackgroundThe primary strategy for reducing the incidence of COVID-19 is SARS-CoV-2 vaccination. Few studies have explored T cell subset differentiation and gene expressions induced by SARS-CoV-2 vaccines. Our study aimed to analyze T cell dynamics and transcriptome gene expression after inoculation with an inactivated SARS-CoV-2 vaccine by using single-cell sequencing.MethodsSingle-cell sequencing was performed after peripheral blood mononuclear cells were extracted from three participants at four time points during the inactivated SARS-CoV-2 vaccination process. After library preparation, raw read data analysis, quality control, dimension reduction and clustering, single-cell T cell receptor (TCR) sequencing, TCR V(D)J sequencing, cell differentiation trajectory inference, differentially expressed genes, and pathway enrichment were analyzed to explore the characteristics and mechanisms of postvaccination immunodynamics.ResultsInactivated SARS-CoV-2 vaccination promoted T cell proliferation, TCR clone amplification, and TCR diversity. The proliferation and differentiation of CD8+ mucosal-associated invariant T (MAIT) cells were significantly upregulated, as were KLRD1 gene expression and the two pathways of nuclear-transcribed mRNA catabolic process, nonsense-mediated decay, and translational initiation.ConclusionUpregulation of CD8+ MAIT cell differentiation and KLRD1 expression after inactivated SARS-CoV-2 vaccination was demonstrated by single-cell sequencing. We conclude that the inactivated SARS-CoV-2 vaccine elicits adaptive T cell immunity to enhance early immunity and rapid response to the targeted virus