ObjectivesTo simulate hemodynamic changes after extraluminal compression in pulsatile tinnitus patients with a prominent transverse-sigmoid sinus junction.MethodsOne patient-specific case was reconstructed based on computed tomography venography images of a PT patient. The compression degree served as a new index in this study. Cases with 10, 20, 30, 40, 50, 60, 70, 80, and 90% of the compression degree of the control subject were constructed. Steady-state computational fluid dynamics were assessed. The wall pressure distribution, wall maximum pressure and flow pattern of (...) the PTSJ were calculated to evaluate hemodynamic differences among all cases.ResultsWith increasing compression, the wall pressure at the compression point and downstream of the PTSJ decreased but increased upstream. When the compression degree exceeded 70%, the upstream pressure increased significantly. Above 50% compression, the blood flow pattern downstream of the sigmoid sinus tended to spiral, especially after 80% compression. Beyond 60% compression, the blood flow pattern under the compression axis became more medial.ConclusionMechanical compression of PTSJ changes wall pressure and blood flow patterns. The degree of compression should be carefully observed to avoid possible complications or reoccurrence. (shrink)

From the end of 2018 in China, the Big-data Driven Price Discrimination (BDPD) of online consumption raised public debate on social media. To study the consumers’ attitude about the BDPD, this study constructed a semantic recognition frame to deconstruct the Affection-Behavior-Cognition (ABC) consumer attitude theory using machine learning models inclusive of the Labeled Latent Dirichlet Allocation (LDA), Long Short-Term Memory (LSTM), and Snow Natural Language Processing (NLP), based on social media comments text dataset. Similar to the questionnaires published results, this (...) article verified that 61% of consumers expressed negative sentiment toward BDPD in general. Differently, on a finer scale, this study further measured the negative sentiments that differ significantly among different topics. The measurement results show that the topics “Regular Customers Priced High” (69%) and “Usage Intention” (67%) occupy the top two places of negative sentiment among consumers, and the topic “Precision Marketing” (42%) is at the bottom. Moreover, semantic recognition results that 49% of consumers’ comments involve multiple topics, indicating that consumers have a pretty clear cognition of the complex status of the BDPD. Importantly, this study found some topics that had not been focused on in previous studies, such as more than 8% of consumers calling for government and legal departments to regulate BDPD behavior, which indicates that quite enough consumers are losing confidence in the self-discipline of the platform enterprises. Another interesting result is that consumers who pursue solutions to the BDPD belong to two mutually exclusive groups: government protection and self-protection. The significance of this study is that it reminds the e-commerce platforms to pay attention to the potential harm for consumers’ psychology while bringing additional profits through the BDPD. Otherwise, the negative consumer attitudes may cause damage to brand image, business reputation, and the sustainable development of the platforms themselves. It also provides the government supervision departments an advanced analysis method reference for more effective administration to protect social fairness. (shrink)

DNA–protein interactions are fundamental to many biological processes, including the regulation of gene expression. Determining the binding affinities of transcription factors (TFs) to different DNA sequences allows the quantitative modeling of transcriptional regulatory networks and has been a significant technical challenge in molecular biology for many years. A recent paper by Maerkl and Quake1 demonstrated the use of microfluidic technology for the analysis of DNA–protein interactions. An array of short DNA sequences was spotted onto a glass slide, which was then (...) covered with a microfluidic device allowing each spot to be within a chamber into which the flow of materials was controlled by valves. By trapping the DNA–protein complexes on the surface and measuring their concentrations microscopically, they could determine the binding affinity to a large number of DNA sequences that were varied systematically. They studied four TFs from the basic helix–loop–helix family of proteins, all of which bind to E‐box sites with the consensus CAnnTG (where “n” can be any base), and showed that variations in affinity for different sites allows each TF to regulate different genes. BioEssays 29:717–721, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

Growth mindset refers to our core belief that our talents can be developed through practice, which may influence our thoughts and behaviors. Growth mindset has been studied in a variety of fields, including education, sports, and management. However, few studies have explored whether differences in individuals’ growth mindsets influence college students’ self-reported mental health. Using the Growth Mindset Scale, Adolescent Self-rating Life Events Checklist, and SCL-90 Scale, data was collected from 2,505 freshmen in a University in China. Findings revealed that (...) the students within the growth mindset group scored significantly lower on “mental health issues” and “stress due to life events” than the students in the fixed mindset group. Our findings suggest that individuals with a growth mindset are less prone to mental health problems than individuals with a fixed mindset. (shrink)

Supply chain financing guaranteed by third-party logistics firms is an effective way to solve the financing difficulties of small and medium-sized enterprises. Studies have explored factors that affect the willingness of supply chain financial credit providers under guarantee of 3PL firms. However, whether the scale of 3PL firms will affect the bank’s credit decision has not been studied, as well as the neural processing of credit decisions. To clarify these issues, this study extracted behavioral and event-related potentials data when participants (...) performed a selection task of judging whether to grant credit to guaranteed financing-seeking enterprises according to the large or small scale of the 3PL guaranteeing firms. The behavioral results showed that under the condition of a large-scale 3PL guaranteeing firm, the willingness to provide credit to SMEs was higher than that under the condition of a small-scale 3PL guaranteeing firm. This finding indicates there was credit scale discrimination against 3PL guaranteeing firms in supply chain finance. The ERP results showed that compared with the condition of a large-scale 3PL guaranteeing firm, a greater N2 amplitude was induced under the condition of a small-scale 3PL guaranteeing firm, which indicated that credit decision makers experienced greater perceived risk and more decision-making conflict. In contrast, a larger LPP amplitude was detected under the condition of a large-scale 3PL guaranteeing firm, which indicated that large-scale 3PL guaranteeing firms received more positive comments and more positive emotions from credit decision makers than small-scale 3PL guaranteeing firms. Based on these results, this study reveals the cognition process of credit decision makers regarding the impact of the 3PL guaranteeing firm scale on the willingness to provide credit in supply chain finance and explains the theory of credit scale discrimination from the perspective of decision neuroscience. (shrink)

Expletive pronouns have posed significant challenges to both linguistic studies and natural language processing in Chinese. Based on the data from the Chinese corpus at the Center for Chinese Linguistics of Peking University, this paper investigates the automatic dependency parsing errors of expletive ta and relative constructions and provides a detailed quantitative analysis of the characteristics of the constructions in question. The findings not only provide evidence to show that even in radical pro-drop languages such as Mandarin, pleonastics can occur (...) in both object and subject positions but also offer important insights for Chinese natural language processing. (shrink)

In order to highlight the role of music teaching in the teaching of ideological and political courses, this study puts forward research on the integration of music teaching and ideological and political teaching. This study analyzes the promotion and necessity of college music teaching to ideological and political work, constructs a fusion model of college music teaching and ideological and political work, introduces deep learning methods, and weakens the influence of errors in the data of college music teaching and ideological (...) and political work. This study also optimized the integration mode of college music teaching and ideological and political work and realized the model research of college music teaching and ideological and political work. The experimental results show that the resource output amplitude controlled by the deep learning method has the best stability, and there is no large amplitude fluctuation during the experiment. The output amplitude and control time of the fusion resource are guaranteed and the fusion path of music teaching and ideological and political education is clearer. The maximum control time of the fusion resource of this method is 23.55 ms. (shrink)

Mobile English learning has multiple advantages and brings enormous benefits to EFL learners. However, not everyone adopts it, and the determinants of learners’ adoption intention have not yet been investigated fully. This study aimed to better understand learners’ adoption by employing the theory of planned behaviour in conjunction with the influences of technostress and compatibility. Based on existing literature, a research model was proposed and verified with a sample of 409 undergraduates from a Chinese university. The results indicated that in (...) the context of mobile English learning: Individuals with higher adoption intention are more likely to engage in mobile English learning with higher frequency. Practical implications related to mobile English learning were discussed. (shrink)

In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition, and individual differences as a function of phonological short-term memory and associative capacity. Further results from lesioned models indicate developmental plasticity in the network's recovery from damage, in (...) a non-monotonic fashion. We attribute the network's abilities in accounting for lexical development to interactive dynamics in the learning process. In particular, variations displayed by the model in the rate and size of early vocabulary development are modulated by (a) input characteristics, such as word frequency and word length, (b) consolidation of lexical-semantic representation, meaning-form association, and phonological short-term memory, and (c) delayed processes due to interactions among timing, severity, and recoverability of lesion. Together, DevLex and DevLex-II provide an accurate computational account of early lexical development. (shrink)

In this study we present a self‐organizing connectionist model of early lexical development. We call this model DevLex‐II, based on the earlier DevLex model. DevLex‐II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition, and individual differences as a function of phonological short‐term memory and associative capacity. Further results from lesioned models indicate developmental plasticity in the network's recovery from damage, in (...) a non‐monotonic fashion. We attribute the network's abilities in accounting for lexical development to interactive dynamics in the learning process. In particular, variations displayed by the model in the rate and size of early vocabulary development are modulated by (a) input characteristics, such as word frequency and word length, (b) consolidation of lexical‐semantic representation, meaning‐form association, and phonological short‐term memory, and (c) delayed processes due to interactions among timing, severity, and recoverability of lesion. Together, DevLex and DevLex‐II provide an accurate computational account of early lexical development. (shrink)

Scholars have paid so much academic attention to UPB in the past decade. However, there is lacking a quantitative review to uncover the relationship between UPB and its antecedents. To address this, we make a meta-analytic review about UPB. Specifically, we propose a theoretical framework of antecedents of UPB and test it using meta-analysis technology (k = 67, n = 20,957). We found moral disengagement, organizational identification, identification with supervisors, leader UPB, ethical judgments, psychological entitlement, transformational leadership, and job satisfaction (...) are positively related to UPB. Moral identity and taking responsibility are negatively related to UPB. Besides, ethical leadership, abusive supervision, and authoritarian leadership have double-edged sword effects on UPB. For ethical leadership, it increases UPB via LMX, on the other hand, it decreases UPB via moral disengagement. For abusive supervision and authoritarian leadership, they increase UPB via moral disengagement and decrease UPB via LMX meanwhile. We discuss the results of the current meta-analysis and put some future research directions. (shrink)

Because they are key components of aircraft, improving the safety, reliability and economy of engines is crucial. To ensure flight safety and reduce the cost of maintenance during aircraft engine operation, a prognostics and health management system that focuses on fault diagnosis, health assessment, and life prediction is introduced to solve the problems. Predicting the remaining useful life is the most important information for making decisions about aircraft engine operation and maintenance, and it relies largely on the selection of performance (...) degradation features. The choice of such features is highly significant, but there are some weaknesses in the current algorithm for RUL prediction, notably, the inability to obtain tendencies from the data. Especially with aircraft engines, extracting useful degradation features from multisensor data with complex correlations is a key technical problem that has hindered the implementation of degradation assessment. To solve these problems, deep learning has been proposed in recent years to exploit multiple layers of nonlinear information processing for unsupervised self-learning of features. This paper presents a deep learning approach to predict the RUL of an aircraft engine based on a stacked sparse autoencoder and logistic regression. The stacked sparse autoencoder is used to automatically extract performance degradation features from multiple sensors on the aircraft engine and to fuse multiple features through multilayer self-learning. Logistic regression is used to predict the remaining useful life. However, the hyperparameters of the deep learning, which significantly impact the feature extraction and prediction performance, are determined based on expert experience in most cases. The grid search method is introduced in this paper to optimize the hyperparameters of the proposed aircraft engine RUL prediction model. An application of this method of predicting the RUL of an aircraft engine with a benchmark dataset is employed to demonstrate the effectiveness of the proposed approach. (shrink)

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably ) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as “doctors' opinions.” Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. (...) Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities. (shrink)

The Myelin Regulator Factor (MYRF) is a master regulator governing myelin formation and maintenance in the central nervous system. The conservation of MYRF across metazoans and its broad tissue expression suggest it has functions extending beyond the well‐established role in myelination. Loss of MYRF results in developmental lethality in both invertebrates and vertebrates, and MYRF haploinsufficiency in humans causes MYRF‐related Cardiac Urogenital Syndrome, underscoring its importance in animal development; however, these mechanisms are largely unexplored. MYRF, an unconventional transcription factor, begins (...) embedded in the membrane and undergoes intramolecular chaperone mediated trimerization, which triggers self‐cleavage, allowing its N‐terminal segment with an Ig‐fold DNA‐binding domain to enter the nucleus for transcriptional regulation. Recent research suggests developmental regulation of cleavage, yet the mechanisms remain enigmatic. While some parts of MYRF's structure have been elucidated, others remain obscure, leaving questions about how these motifs are linked to its intricate processing and function. (shrink)

The object of this study was to investigate whether level of processing (LOP) modulates enhanced memory performance for emotional stimuli, and, if so, whether the LOP effects relate to their gist and details. During the study phase, participants were presented with colourful pictures with negative, neutral and positive valences and encoded the emotional pictures under either a semantic (living/non-living judgement) or a perceptual (left/right position judgement) condition. During the test phase, they judged whether the presented picture was old or new (...) in Experiments 1 and 2, and also judged whether a specific concept, labelled using words, had been studied in Experiment 2. The results showed that under both encoding conditions, the details of both negative and positive pictures were recognised better than those of neutral pictures. Also, the gist of negative pictures was recognised better than that of neutral pictures but only under the semantic condition. These data provide evidence that the LOP differentially modulates enhanced emotional memory for gist and details of pictures. (shrink)

This research investigated how interpersonal communication with a large audience can influence communicators’ attitudes. Research on the saying-is-believing effect has shown that when an individual’s attitude is perceived in advance by a communicator, the communicator tunes the message to the person, which biases the communicator’s attitude toward the person’s attitude. In this study, we examined the conditions under which audience tuning and attitude bias can occur with audiences containing more than one individual. We manipulated communicators’ perceived group entity for a (...) large audience and the audience’s prior attitudinal valence and measured the audience’s epistemic trust. The results showed that communicators tuned their messages to the audience’s attitude when they perceived group entitativity and epistemic trust. Furthermore, tuning the message to the audience was found to bias communicators’ subsequent impressions of the topic in a direction closer to the audience’s attitude. These results suggest that perceiving a large audience as a group influences the subsequent impressions of electronic word-of-mouth product or service communicators. (shrink)

The COVID-19 pandemic has had a substantial impact on the retail industry around the globe, including in the vast market of India. The response to the pandemic required stores to close and develop new ways to approach shoppers more efficiently. The worldwide usage of social media enabled the growth of social commerce. Influencers on s-commerce platforms use live broadcasting on their channels to promote endorsed products. The features of s-commerce influencers enhance users' trust in the online community and s-commerce intention, (...) impacting their online purchasing intentions. In this study, we collected data from 379 Indian consumers to test the measurement and structural model using Partial Least Square-Structural Equation Modeling to verify our conceptual framework. We found that trust in the online community and s-commerce intention are antecedents of online purchase intentions. Additionally, the results demonstrate that trust in Indian social media influencers and s-commerce intentions are vital for boosting consumers' purchase intention, verifying the hypothesized mediating effect of these factors. Based on these results, we suggest several managerial actions that could enhance the value of s-commerce for franchises, executives, e-retailers, and e-marketplaces. (shrink)

The gray prediction model, based on the GM method, is an important branch of gray theory with the most active research and the most fruitful results, and it is the most widely used because of its small sample size, simple modeling process, and easy to use. Such advantages have been successfully applied in many fields such as transportation, agriculture, energy, medicine, and environment and have been gradually developed into a mainstream predictive modeling method. This study combines the Three-parameter Whitenization Grey (...) Model ), which fits the inhomogeneous exponential law sequence, and the Particle Swarm Algorithm to optimize the order and background value coefficients under the condition of the minimum sum of squares of simulation errors, and hence, to solve the problem that the cumulative order is fixed to “1” and the background value coefficient value is fixed to “0.5.” As a result, a parameter-optimized gray system model with flexibility, adaptability, and dynamic adjustment is designed to simulate and predict China’s higher education gross enrollment rate. The application shows that the model has better overall simulation and prediction performance than others. On the one hand, the parametric optimization model significantly improves its own performance, and on the other hand, its intelligent and adjustable adaptivity improves the accuracy and further extends its application. (shrink)

A major challenge for semantic video segmentation is how to exploit the spatiotemporal information and produce consistent results for a video sequence. Many previous works utilize the precomputed optical flow to warp the feature maps across adjacent frames. However, the imprecise optical flow and the warping operation without any learnable parameters may not achieve accurate feature warping and only bring a slight improvement. In this paper, we propose a novel framework named Dynamic Warping Network to adaptively warp the interframe features (...) for improving the accuracy of warping-based models. Firstly, we design a flow refinement module to optimize the precomputed optical flow. Then, we propose a flow-guided convolution to achieve the adaptive feature warping based on the refined optical flow. Furthermore, we introduce the temporal consistency loss including the feature consistency loss and prediction consistency loss to explicitly supervise the warped features instead of simple feature propagation and fusion, which guarantees the temporal consistency of video segmentation. Note that our DWNet adopts extra constraints to improve the temporal consistency in the training phase, while no additional calculation and postprocessing are required during inference. Extensive experiments show that our DWNet can achieve consistent improvement over various strong baselines and achieves state-of-the-art accuracy on the Cityscapes and CamVid benchmark datasets. (shrink)

Based on the data of Chinese industrial enterprises from 2004 to 2009, a fixed-effect model is adopted in this paper to analyze the effect and the mechanism of the enterprises using the Internet on tax avoidance. The result shows that using the Internet will produce the peer effect, which enables enterprises to learn tax avoidance strategies on the Internet and makes the degree of tax avoidance between enterprises and other enterprises in the same industry converge. At the same time, using (...) the Internet has a network effect, and the more the enterprises access the Internet, the higher the degree of tax avoidance for enterprises is. In addition, the effect of the Internet on tax avoidance is influenced by the intensity of tax collection and the nature of enterprises. With a further examination, it has been found that enterprises not only acquire the two tax avoidance strategies of underreporting profits and underpaying taxes through the Internet but also master the planning strategy. (shrink)

The growth of strawberry will be stressed by biological or abiotic factors, which will cause a great threat to the yield and quality of strawberry, in which various strawberry diseased. However, the traditional identification methods have high misjudgment rate and poor real-time performance. In today's era of increasing demand for strawberry yield and quality, it is obvious that the traditional strawberry disease identification methods mainly rely on personal experience and naked eye observation and cannot meet the needs of people for (...) strawberry disease identification and control. Therefore, it is necessary to find a more effective method to identify strawberry diseases efficiently and provide corresponding disease description and control methods. In this paper, based on the deep convolution neural network technology, the recognition of strawberry common diseases was studied, as well as a new method based on deep convolution neural network strawberry disease recognition algorithm, through the normal training of strawberry image feature representation in different scenes, and then through the application of transfer learning method, the strawberry disease image features are added to the training set, and finally the features are classified and recognized to achieve the goal of disease recognition. Moreover, attention mechanism and central damage function are introduced into the classical convolutional neural network to solve the problem that the information loss of key feature areas in the existing classification methods of convolutional neural network affects the classification effect, and further improves the accuracy of convolutional neural network in image classification. (shrink)

With the global pandemic of COVID-19, it has been striking psychological burdens on individuals. Under this background, more and more people get wellbeing by watching live broadcasts. However, the psychological mechanism behind this phenomenon is still a black box. This study finds that when people watch a live broadcast and interact with anchors and other people, an interaction ritual chain is formed, and emotional energy is generated, thus making people experience and understand the meaning of the live interaction ritual chains. (...) Under the effect of the meaning transfer model, people will generate wellbeing. Specifically, the basic meaning of live interaction drives people’s generation of wellbeing. The meanings of self-participation, self-display, self-concept, and self-renewal play a role in mediation in enhancing people’s wellbeing with the basic meaning of live broadcast interaction. (shrink)

Here we present and develop the hypothesis that the derepression of endogenous retrotransposable elements (RTEs) – “genomic parasites” – is an important and hitherto under‐unexplored molecular aging process that can potentially occur in most tissues. We further envision that the activation and continued presence of retrotransposition contribute to age‐associated tissue degeneration and pathology. Chromatin is a complex and dynamic structure that needs to be maintained in a functional state throughout our lifetime. Studies of diverse species have revealed that chromatin undergoes (...) extensive rearrangements during aging. Cellular senescence, an important component of mammalian aging, has recently been associated with decreased heterochromatinization of normally silenced regions of the genome. These changes lead to the expression of RTEs, culminating in their transposition. RTEs are common in all kingdoms of life, and comprise close to 50% of mammalian genomes. They are tightly controlled, as their activity is highly destabilizing and mutagenic to their resident genomes. (shrink)

The mammalian dentition is a segmented organ system with shape differences among its serially homologous elements (individual teeth). It is believed to have evolved from simpler precursors with greater similarities in shape among teeth, and a wealth of descriptive data exist on changes to the dentition that have occurred within mammals. Recent progress has been made in determining the genetic basis of the processes that form an individual tooth, but patterning of the dentition as a whole (i.e. the number, location (...) and shape of the teeth) is less well understood. In contrast to similarly organized systems, such as the vertebral column and limb, Hox genes are not involved in specifying differences among elements. Nevertheless, recent work on a variety of systems is providing clues to the transcription factors and extracellular signalling molecules involved. (shrink)

Di yi juan. Si wei xue, yuan li lun he zhe xue juan -- Di er juan. Mei xue juan -- Di san juan. Fu hao fen xi he yu yan fen xi juan -- Di si juan. Wen hua xue yu dao de zhe xue juan -- Di wu juan. Shi wen juan.

本书收录“关于命运的知识”、“从知识眼光到创作眼光”、“一个或所有问题”、“千年观念故事”、“理解20世纪的精神财富”等19篇文章。.