51 research outputs found

    Processing of Individual Items during Ensemble Coding of Facial Expressions

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    There is growing evidence that human observers are able to extract the mean emotion or other type of information from a set of faces. The most intriguing aspect of this phenomenon is that observers often fail to identify or form a representation for individual faces in a face set. However, most of these results were based on judgments under limited processing resource. We examined a wider range of exposure time and observed how the relationship between the extraction of a mean and representation of individual facial expressions would change. The results showed that with an exposure time of 50 ms for the faces, observers were more sensitive to mean representation over individual representation, replicating the typical findings in the literature. With longer exposure time, however, observers were able to extract both individual and mean representation more accurately. Furthermore, diffusion model analysis revealed that the mean representation is also more prone to suffer from the noise accumulated in redundant processing time and leads to a more conservative decision bias, whereas individual representations seem more resistant to this noise. Results suggest that the encoding of emotional information from multiple faces may take two forms: single face processing and crowd face processi

    Fatigue Life Simulation and Analysis of Aluminum Alloy Sheet Self-piercing Riveting

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    The fatigue life prediction model of self-piecing riveting components of aluminum alloy is established and the effects of roughness and residual stress on fatigue life of self-piercing riveting components is analyzed by the model. Finite element software ABAQUS and fatigue analysis software FE-SAFE are used to study the effects of roughness and residual stress on the fatigue life of self-piecing riveting components through finite element simulation and mathematical statistics multivariate orthogonal regression experiment. The quantitative relations between fatigue life and three variables (roughness, residual stress and maximum stress) are fitted, and the variation trend of fatigue life with roughness and residual stress is obtained. The order of influence of roughness, residual stress, maximum stress and two interactions on fatigue life is as follows: residual stress, interaction between roughness and residual stress, roughness. When the maximum stress is fixed, the fatigue life decreases with the increase of roughness with a certain residual stress, and the fatigue life decreases with the increase of roughness with a certain residual stress. The average error between the fatigue experiment results and the simulation results is 9.74%, which proves that the simulation results are reliable

    Testing the Hypothesis of Multiple Origins of Holoparasitism in Orobanchaceae: Phylogenetic Evidence from the Last Two Unplaced Holoparasitic Genera, Gleadovia and Phacellanthus

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    Orobanchaceae is the largest family among the parasitic angiosperms. It comprises non-parasites, hemi- and holoparasites, making this family an ideal test case for studying the evolution of parasitism. Previous phylogenetic analyses showed that holoparasitism had arisen at least three times from the hemiparasitic taxa in Orobanchaceae. Until now, however, not all known genera of Orobanchaceae were investigated in detail. Among them, the unknown phylogenetic positions of the holoparasites Gleadovia and Phacellanthus are the key to testing how many times holoparasitism evolved. Here, we provide clear evidence for the first time that they are members of the tribe Orobancheae, using sequence data from multiple loci (nuclear genes ITS, PHYA, PHYB, and plastid genes rps2, matK). Gleadovia is an independent lineage whereas Phacellanthus should be merged into genus Orobanche section Orobanche. Our results unambiguously support the hypothesis that there are only three origins of holoparasitism in Orobanchaceae. Divergence dating reveals for the first time that the three origins of holoparasitism were not synchronous. Our findings suggest that holoparasitism can persist in specific clades for a long time and holoparasitism may evolve independently as an adaptation to certain hosts

    Circulating tumor DNA clearance predicts prognosis across treatment regimen in a large real-world longitudinally monitored advanced non-small cell lung cancer cohort

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    Background: Although growth advantage of certain clones would ultimately translate into a clinically visible disease progression, radiological imaging does not reflect clonal evolution at molecular level. Circulating tumor DNA (ctDNA), validated as a tool for mutation detection in lung cancer, could reflect dynamic molecular changes. We evaluated the utility of ctDNA as a predictive and a prognostic marker in disease monitoring of advanced non-small cell lung cancer (NSCLC) patients.Methods: This is a multicenter prospective cohort study. We performed capture-based ultra-deep sequencing on longitudinal plasma samples utilizing a panel consisting of 168 NSCLC-related genes on 949 advanced NSCLC patients with driver mutations to monitor treatment responses and disease progression. The correlations between ctDNA and progression-free survival (PFS)/overall survival (OS) were performed on 248 patients undergoing various treatments with the minimum of 2 ctDNA tests.Results: The results of this study revealed that higher ctDNA abundance (P=0.012) and mutation count (P=8.5x10(-4)) at baseline are associated with shorter OS. We also found that patients with ctDNA clearance, not just driver mutation clearance, at any point during the course of treatment were associated with longer PFS (P=2.2x10(-1)6, HR 0.28) and OS (P=4.5x10(-6), HR 0.19) regardless of type of treatment and evaluation schedule.Conclusions: This prospective real-world study shows that ctDNA clearance during treatment may serve as predictive and prognostic marker across a wide spectrum of treatment regimens

    GRIK3 rs490647 is a Common Genetic Variant between Personality and Subjective Well-being in Chinese Han Population

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    Personality and subjective well-being (SWB) have been suggested to be strongly related in previous studies. This study was intended to confirm the relationship between personality and SWB and tried to seek out the genetic variants which underlie both personality and SWB. The subjects were 890 participants from Chinese Han population. We evaluated their personality using the Big Five Inventory (BFI) and used the Satisfaction With Life Scale (SWLS) to reflect their SWB. Five single nucleotide polymorphisms (SNPs) were selected from the literature (rs1426371, rs2164273, rs322931, rs3756290, rs490647) and genotyped for genetic association study. We found negative correlations between neuroticism and SWB. On the contrary, extraversion and agreeableness were positively associated with SWB. Three SNPs (rs2164273, rs3756290, rs490647) out of the five were found to connect with personality (extraversion, neuroticism, conscientiousness and openness to experience) and rs490647 variants of GRIK3 was also associated with SWB. Individuals carrying G allele at this site were predisposed to have lower risk to be neuroticism and greater chance to be extraverted, open and satisfied with their life. In summary, our study revealed that rs490647 might be a good candidate genetic variant for personality and SWB in Chinese Han population

    The causal nexus between energy consumption, carbon emissions and economic growth: New evidence from China, India and G7 countries using convergent cross mapping.

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    Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth

    Electric Field: A Key Signal in Wound Healing

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    SUMMARY: Wound healing is a complex biological process that involves proliferation, migration, and differentiation. Endogenous electric field (EF)-directed migration of keratinocytes (galvanotaxis) is an essential step in wound re-epithelialization. Endogenous EFs are generated instantaneously after an injury because of the collapse of transepithelial potentials. The application of exogenous EF has become increasingly widespread in promoting wound healing, leading to a paradigm shift in patient outcomes. Here, we summarize the role and value of EF in wound healing through a review of the current research

    Clutter Covariance Matrix Estimation for Radar Adaptive Detection Based on a Complex-Valued Convolutional Neural Network

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    In this paper, we address the problem of covariance matrix estimation for radar adaptive detection under non-Gaussian clutter. Traditional model-based estimators may suffer from performance loss due to the mismatch between real data and assumed models. Therefore, we resort to a data-driven deep-learning method and propose a covariance matrix estimation method based on a complex-valued convolutional neural network (CV-CNN). Moreover, a real-valued (RV) network with the same framework as the proposed CV network is also constructed to serve as a natural competitor. The obtained clutter covariance matrix estimation based on the network is applied to the adaptive normalized matched filter (ANMF) detector for performance assessment. The detection results via both simulated and real sea clutter illustrate that the estimator based on CV-CNN outperforms other traditional model-based estimators as well as its RV competitor in terms of probability of detection (PD)
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