Translation Studies from the Perspective of Corpus Translation Studies and Digital Humanities

As a translation research method and paradigm, corpus translation studies have gradually gained attention from the translation community since their introduction to China in the 1970s. With the rapid development of information technology and artificial intelligence, corpus translation studies have continuously made new progress. With the support of digital humanities technologies such as Big data, artificial intelligence and cloud computing, the development of corpus translatology presents new features and trends. This article explores the application of corpus translation studies in translation studies from both theoretical and practical perspectives. At the theoretical level, this article believes that corpus translation studies have significant implications for the paradigm shift, theoretical innovation, and disciplinary development of translation studies. At the practical level, this article points out that corpus translation studies have strong data support, which can improve the efficiency and accuracy of translation research. Based on this, this article proposes that future translation research should focus on data-driven research paradigms, attach importance to the important role of data in translation, and build a theoretical model of translation studies on this basis, in order to provide theoretical guidance for comprehensively improving the quality of translation research

Research on unbalance vibration signal de-noising of motorized spindle

Using the adaptive redundant lifting wavelet to the vibration signal de-noising has better de-noising effect, but the traditional threshold function of the method has the problems of discontinuous wavelet coefficients or constant deviation. In order to meet the high precision demand of the active balancing of the motorized spindle and improve the extraction accuracy of the unbalance signal, the improved bivariate threshold function was introduced into the method, and then a new de-noising method on unbalance vibration signal of the motorized spindle based on improving adaptive redundant lifting wavelet was put forward. The new method was applied to the engineering unbalance vibration signal. The result showed that the new method can retain the original signal feature of amplitude and phase, as well as eliminate noise more effectively, when the actual vibration signal of motorized spindle is low SNR and non-stationary

Hard rock deep hole cutting blasting technology in vertical shaft freezing bedrock section construction

Using the traditional cutting blasting technology in vertical shaft construction has some features, e.g. slows driving speed, gangue with large volume and throwing high. Moreover, large explosive charge initiation has a serious influence on freezing pipes and freezing wall. In this study, the periphery hole charge and charge structure was optimized, and the blasting model of the bedrock vertical shaft section was established by using the ANSYS/LS-DYNA numerical simulation software. In addition, stress concentration of the large diameter empty hole and its influence of blasting efficiency in blasting were analyzed. The field experiment was conducted to verify the blasting results. The results show that using large diameter empty hole blasting technology in vertical shaft construction of frozen hard rock section can significantly improve the speed of vertical shaft construction, obtain the excellent blasting effect and guarantee the safety of freezing pipes and freezing wall

Feature extraction of vibration signal using OMP-NWE method

Feature extraction is one of the core problems in condition monitoring and fault diagnosis of mechanical equipment. In this study, an OMP-NWE method of feature extraction is proposed, aiming at the problem of low accuracy of existing feature extraction method. The OMP-NWE method integrates the strengths of orthogonal matching pursuit (OMP) algorithm with the benefits of nonparametric waveform estimation (NWE). Signal feature extraction model is constructed by design of filter bank and adaptive template signal. Then the vibration signal is linearly decomposed into a set of best matching waveform, which solves the problem that the basis function must be chosen in advance in OMP algorithm. The OMP-NWE method is applied to the feature extraction of the simulation and experimental vibration signal of rolling bearing, compared with the traditional OMP algorithm. Results show that the SNR of the extracted feature signal using OMP-NWE method increased by 19.22 % compared with that using the OMP method, which illustrates that OMP-NWE method has a higher accuracy in the feature extraction of unknown complex vibration signals. This work provides a new idea and a successful example for the feature extraction of vibration signal in the condition monitoring and fault diagnosis of mechanical equipment

Unified learning-based lossy and lossless JPEG recompression

JPEG is still the most widely used image compression algorithm. Most image compression algorithms only consider uncompressed original image, while ignoring a large number of already existing JPEG images. Recently, JPEG recompression approaches have been proposed to further reduce the size of JPEG files. However, those methods only consider JPEG lossless recompression, which is just a special case of the rate-distortion theorem. In this paper, we propose a unified lossly and lossless JPEG recompression framework, which consists of learned quantization table and Markovian hierarchical variational autoencoders. Experiments show that our method can achieve arbitrarily low distortion when the bitrate is close to the upper bound, namely the bitrate of the lossless compression model. To the best of our knowledge, this is the first learned method that bridges the gap between lossy and lossless recompression of JPEG images

Hard rock deep hole cutting blasting technology in vertical shaft freezing bedrock section construction

Using the traditional cutting blasting technology in vertical shaft construction has some features, e.g. slows driving speed, gangue with large volume and throwing high. Moreover, large explosive charge initiation has a serious influence on freezing pipes and freezing wall. In this study, the periphery hole charge and charge structure was optimized, and the blasting model of the bedrock vertical shaft section was established by using the ANSYS/LS-DYNA numerical simulation software. In addition, stress concentration of the large diameter empty hole and its influence of blasting efficiency in blasting were analyzed. The field experiment was conducted to verify the blasting results. The results show that using large diameter empty hole blasting technology in vertical shaft construction of frozen hard rock section can significantly improve the speed of vertical shaft construction, obtain the excellent blasting effect and guarantee the safety of freezing pipes and freezing wall

Hard rock deep hole cutting blasting technology in vertical shaft freezing bedrock section construction

Using the traditional cutting blasting technology in vertical shaft construction has some features, e.g. slows driving speed, gangue with large volume and throwing high. Moreover, large explosive charge initiation has a serious influence on freezing pipes and freezing wall. In this study, the periphery hole charge and charge structure was optimized, and the blasting model of the bedrock vertical shaft section was established by using the ANSYS/LS-DYNA numerical simulation software. In addition, stress concentration of the large diameter empty hole and its influence of blasting efficiency in blasting were analyzed. The field experiment was conducted to verify the blasting results. The results show that using large diameter empty hole blasting technology in vertical shaft construction of frozen hard rock section can significantly improve the speed of vertical shaft construction, obtain the excellent blasting effect and guarantee the safety of freezing pipes and freezing wall

Lack of association between the CALM1 core promoter polymorphism (-16C/T) and susceptibility to knee osteoarthritis in a Chinese Han population

<p>Abstract</p> <p>Background</p> <p><it>CALM1 </it>gene encodes calmodulin (CaM), an important and ubiquitous eukaryotic Ca²⁺-binding protein. Several studies have indicated that a deficient CaM function is likely to be involved in the pathogenesis of osteoarthritis (OA). Using a convincing genome-wide association study, a Japanese group has recently demonstrated a genetic association between the <it>CALM1 </it>core promoter polymorphism (-16C/T transition SNP, rs12885713) and OA susceptibility. However, the subsequent association studies failed to provide consistent results in OA patients of differently selected populations. The present study is to evaluate the association of the -16C/T polymorphism with knee OA in a Chinese Han population.</p> <p>Methods</p> <p>A case-control association study was conducted. The polymorphism was genotyped in 183 patients who had primary symptomatic knee OA with radiographic confirmation and in 210 matched controls. Allelic and genotypic frequencies were compared between patients and control subjects.</p> <p>Results</p> <p>No significant difference was detected in genotype or allele distribution between knee OA and control groups (all <it>P </it>> 0.05). The association was also negative even after stratification by sex. Furthermore, no association between the -16C/T SNP genotype and the clinical variables age, sex, BMI (body mass index) and K/L (Kellgren/Lawrence) score was observed in OA patients.</p> <p>Conclusion</p> <p>The present study suggests that the CALM1 core promoter polymorphism -16C/T is not a risk factor for knee OA susceptibility in the Chinese Han population. Further studies are needed to give a global view of this polymorphism in pathogenesis of OA.</p

Disrupted neural variability during propofol‐induced sedation and unconsciousness

Variability quenching is a widespread neural phenomenon in which trial‐to‐trial variability (TTV) of neural activity is reduced by repeated presentations of a sensory stimulus. However, its neural mechanism and functional significance remain poorly understood. Recurrent network dynamics are suggested as a candidate mechanism of TTV, and they play a key role in consciousness. We thus asked whether the variability‐quenching phenomenon is related to the level of consciousness. We hypothesized that TTV reduction would be compromised during reduced level of consciousness by propofol anesthetics. We recorded functional magnetic resonance imaging signals of resting‐state and stimulus‐induced activities in three conditions: wakefulness, sedation, and unconsciousness (i.e., deep anesthesia). We measured the average (trial‐to‐trial mean, TTM) and variability (TTV) of auditory stimulus‐induced activity under the three conditions. We also examined another form of neural variability (temporal variability, TV), which quantifies the overall dynamic range of ongoing neural activity across time, during both the resting‐state and the task. We found that (a) TTM deceased gradually from wakefulness through sedation to anesthesia, (b) stimulus‐induced TTV reduction normally seen during wakefulness was abolished during both sedation and anesthesia, and (c) TV increased in the task state as compared to resting‐state during both wakefulness and sedation, but not anesthesia. Together, our results reveal distinct effects of propofol on the two forms of neural variability (TTV and TV). They imply that the anesthetic disrupts recurrent network dynamics, thus prevents the stabilization of cortical activity states. These findings shed new light on the temporal dynamics of neuronal variability and its alteration during anesthetic‐induced unconsciousness.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146388/1/hbm24304_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146388/2/hbm24304.pd