Accurate gradient computations at interfaces using finite element methods

New finite element methods are proposed for elliptic interface problems in one and two dimensions. The main motivation is not only to get an accurate solution but also an accurate first order derivative at the interface (from each side). The key in 1D is to use the idea from \cite{wheeler1974galerkin}. For 2D interface problems, the idea is to introduce a small tube near the interface and introduce the gradient as part of unknowns, which is similar to a mixed finite element method, except only at the interface. Thus the computational cost is just slightly higher than the standard finite element method. We present rigorous one dimensional analysis, which show second order convergence order for both of the solution and the gradient in 1D. For two dimensional problems, we present numerical results and observe second order convergence for the solution, and super-convergence for the gradient at the interface

On the Application of Translation Quality Assessment Model in MTI Teaching

The 21st century is an era of globalization with rapid development of information technology and there are more and more close exchanges among countries. Under this background, the importance of translation is self-evident, and MTI (Master of Translation and Interpreting) teaching, which is closely related to it, has also attracted increasing attention. On the whole, after over ten years of development, translation teaching in China has begun to take shape. Both major foreign language colleges and foreign language departments of various comprehensive colleges have set up corresponding translation courses. But at present, the teaching effect of MTI is far from satisfaction. Based on the translation quality assessment model of Malcolm Williams, the necessity and possibility of the application of the translation quality assessment model in MTI teaching is explored, and the concept of the application of the translation quality assessment model in the classroom is put forward, aiming to establish an objective and effective evaluation system in MTI teaching so as to further promote the development of MTI teaching

On the Translation Strategies of Human-computer Interaction Based on Machine Translation

With the rapid development of language service industry and artificial intelligence technology, machine translation plays a more prominent role in the translation industry. Human-computer interaction translation greatly improves the speed and quality of translation, and pre-translation editing and post-translation editing are two important links and manifestations in human-computer interaction collaborative translation. On the basis of summarizing machine translation problems, this paper proposes translation strategies including replacing well-translated terms in advance, rewriting, addition, omission, and shift via pre-editing and post-editing, which greatly improves the quality of machine translation

High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning

Zero-shot learning(ZSL) aims to recognize new classes without prior exposure to their samples, relying on semantic knowledge from observed classes. However, current attention-based models may overlook the transferability of visual features and the distinctiveness of attribute localization when learning regional features in images. Additionally, they often overlook shared attributes among different objects. Highly discriminative attribute features are crucial for identifying and distinguishing unseen classes. To address these issues, we propose an innovative approach called High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning (HDAFL). HDAFL optimizes visual features by learning attribute features to obtain discriminative visual embeddings. Specifically, HDAFL utilizes multiple convolutional kernels to automatically learn discriminative regions highly correlated with attributes in images, eliminating irrelevant interference in image features. Furthermore, we introduce a Transformer-based attribute discrimination encoder to enhance the discriminative capability among attributes. Simultaneously, the method employs contrastive loss to alleviate dataset biases and enhance the transferability of visual features, facilitating better semantic transfer between seen and unseen classes. Experimental results demonstrate the effectiveness of HDAFL across three widely used datasets

Acoustic monitoring of wind turbine blades using wavelet packet analysis and 1D convolutional neural networks

Wind turbine blades (WTBs) are susceptible to faults in the harsh wind farm environments, making their safety a matter of paramount importance. Unfortunately, existing composite blade monitoring methods face various limitations in practical use. To address this issue, the study presents an intelligent fault detection method to assess the health of both the structural integrity and its skin. This has never been tried before by scholars. The study begins with the collection of acoustic signals from the blade chamber. Second, these signals are processed using wavelet packet decomposition (WPD) and Fast Fourier Transform to generate two-dimensional feature matrices. Third, apply the obtained matrices to train a one-dimensional convolutional neural network (CNN), enabling advanced feature extraction and classification, which forms the basis of the WPD-CNN model. Finally, the proposed method was experimentally verified. It has been found that the proposed WPD-CNN model achieves fault detection accuracies ranging from 87.14% to 98.57%, depending on the types of feature matrices used for training the model. These results highlight the model’s strong performance in diagnosing WTBs. Additionally, the study emphasizes the advantage of using frequency spectrum-derived features over traditional time-domain waveform features for effective WTB fault detection.</p

Educational degree differences in the association between work stress and depression among Chinese healthcare workers: Job satisfaction and sleep quality as the mediators

BackgroundDepressive status of medical personnel worldwide and especially in China is an important public health and social problem. There is a strong relationship between education and depression, but no studies have studied grouping healthcare workers (HCWs) with different educational degree to discuss whether there are differences in the factors that affect depression. This study aims to examine the role of job satisfaction and sleep quality in the relationship between work stress and depression among Chinese HCWs, and teste whether the mediation models are differed by the differences of educational degree.MethodsPatient Health Questionnaire-9 (PHQ-9) scale was used to test depression. Work stress was assessed using the Challenge-blocking stress scale (CBSS). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). HCWs’ satisfaction with their current work was assessed using the Job Satisfaction Index (JSI). The representative sample of HCWs was chosen using a multi-stage stratified cluster random sampling procedure and 844 HCWs were utilized to the statistical analysis of the study.ResultsIn the overall sample, sleep quality could mediate the relationship between work stress and depression in healthcare workers (p &lt; 0.001, CMIN/DF = 3.816, GFI = 0.911, AGFI = 0.886, IFI = 0.943, TLI = 0.933, CFI = 0.942, RMSEA = 0.058, SRMR = 0.055, AIC = 1039.144), and the mediating effect accounted for 36.5%. After grouping educational qualifications, the model with sleep quality and job satisfaction as mediating variables reported a better fit in the group with low educational qualifications. The intermediary effect accounted for 50.6 and 4.43%, respectively. The highly educated group only has sleep quality as an intermediary variable in the structural model, and the mediating effect accounted for 75.4% (p &lt; 0.001, CMIN/DF = 2.596, GFI = 0.887, AGFI = 0.857, IFI = 0.937, TLI = 0.926, CFI = 0.937, RMSEA = 0.044, SRMR = 0.056, AIC = 1481.322).ConclusionIn the overall sample, sleep quality could mediate the relationship between work stress and depression in HCWs. Among HCWs with technical secondary school education and below, job satisfaction can mediate the positive relationship between work stress and depression, while this mediating effect is not significant among HCWs with college degree and above

1-(2-Nitro­phen­yl)-3-phenyl­thio­urea

The title compound, C13H11N3O2S, was prepared by reaction of 2-nitro­benzenamine, KOH and 1-isothio­cyanato­benzene in an ethanol solution at room temperature. The dihedral angles formed between the thiourea plane and the phenyl rings are 61.9 and 31.0°. The dihedral angle between the two phenyl rings is 78.1°. In the crystal structure, there are weak inter­molecular N—H⋯S and C—H⋯S hydrogen-bonding inter­actions

Perspectives on early childhood development in China: key dimensions and contextual contributions

IntroductionThe recognition of culture and context as pivotal influences on the developmental trajectory of young children has been underscored by numerous developmental theories. Localized knowledge is essential for comprehending cultural universality with specificity for early childhood development (ECD).MethodsThirteen focus group discussions were conducted with professionals, caregivers, and teachers from four regions in China. Thematic content analysis was employed to identify patterns and themes, followed by coding to identify more conceptual units of meaning.ResultsThe findings reveal distinct culture-based skills across four domains of ECD in China. These highlight a local culture that embraces a comprehensive, dynamic, and staged perspective on the development of young children. This study elucidates the multidimensional impact of the environment on young children’s development, with a focus on children’s behavioral characteristics and temperament traits, ECEC practices, and ECEC beliefs that transcend identity, culture, and the economy.DiscussionThis study contributes to the assessment of ECD for future cultural comparisons and enhances the scientific understanding of the interplay between developmental skills in young children and diverse cultural expectations and backgrounds

Cluster aggregates surrounding Pismis 5 in the Vela Molecular Ridge

Context. In the Gaia era, the precision of astrometric data is unprecedented. High-quality data make it easier to find more cluster aggregates and support further confirmation of these open clusters. Aims. We use Gaia DR3 to redetermine the open clusters surrounding Pismis 5 in the Vela Molecular Ridge. We also investigate the basic properties of these clusters. Methods. We apply two clustering algorithms (StarGO and pyUPMASK) to identify the open cluster members in a five-dimensional space with Gaia DR3. Results. We identify eight open clusters surrounding Pismis 5 in the Vela Molecular Ridge. The open cluster QZ 1 is newly discovered. Through investigating the comprehensive properties of the clusters, one open binary cluster candidate (Alessi 43 and Collinder 197) and one triple open cluster candidate (Pismis 5, Pismis 5A, and Pismis 5B) are discussed. Conclusions. Binary and triple open cluster candidates have been identified as potential primordial aggregates based on their similar age, position, and motion. According to kinematic speculations, the two aggregate candidates will gradually separate, and their interiors will slowly disintegrate.Comment: 10 pages, 7 figure