2,644 research outputs found

    Exploring the Brain Responses to Driving Fatigue through Simultaneous EEG and fNIRS Measurements

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    © 2020 World Scientific Publishing Company. Fatigue is one problem with driving as it can lead to difficulties with sustaining attention, behavioral lapses, and a tendency to ignore vital information or operations. In this research, we explore multimodal physiological phenomena in response to driving fatigue through simultaneous functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) recordings with the aim of investigating the relationships between hemodynamic and electrical features and driving performance. Sixteen subjects participated in an event-related lane-deviation driving task while measuring their brain dynamics through fNIRS and EEGs. Three performance groups, classified as Optimal, Suboptimal, and Poor, were defined for comparison. From our analysis, we find that tonic variations occur before a deviation, and phasic variations occur afterward. The tonic results show an increased concentration of oxygenated hemoglobin (HbO2) and power changes in the EEG theta, alpha, and beta bands. Both dynamics are significantly correlated with deteriorated driving performance. The phasic EEG results demonstrate event-related desynchronization associated with the onset of steering vehicle in all power bands. The concentration of phasic HbO2 decreased as performance worsened. Further, the negative correlations between tonic EEG delta and alpha power and HbO2 oscillations suggest that activations in HbO2 are related to mental fatigue. In summary, combined hemodynamic and electrodynamic activities can provide complete knowledge of the brain's responses as evidence of state changes during fatigue driving

    EOG-Based Eye Movement Classification and Application on HCI Baseball Game

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    © 2013 IEEE. Electrooculography (EOG) is considered as the most stable physiological signal in the development of human-computer interface (HCI) for detecting eye-movement variations. EOG signal classification has gained more traction in recent years to overcome physical inconvenience in paralyzed patients. In this paper, a robust classification technique, such as eight directional movements is investigated by introducing a concept of buffer along with a variation of the slope to avoid misclassification effects in EOG signals. Blinking detection becomes complicated when the magnitude of the signals are considered. Hence, a correction technique is introduced to avoid misclassification for oblique eye movements. Meanwhile, a case study has been considered to apply these correction techniques to HCI baseball game to learn eye-movements

    AFM, SEM and TEM Studies on Porous Anodic Alumina

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    Porous anodic alumina (PAA) has been intensively studied in past decade due to its applications for fabricating nanostructured materials. Since PAA’s pore diameter, thickness and shape vary too much, a systematical study on the methods of morphology characterization is meaningful and essential for its proper development and utilization. In this paper, we present detailed AFM, SEM and TEM studies on PAA and its evolvements with abundant microstructures, and discuss the advantages and disadvantages of each method. The sample preparation, testing skills and morphology analysis are discussed, especially on the differentiation during characterizing complex cross-sections and ultrasmall nanopores. The versatility of PAAs is also demonstrated by the diversity of PAAs’ microstructure

    Postnatal expression of myostain (MSTN) and myogenin (MYoG) genes in Hu sheep of China

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    The study of candidate genes is an important tool to identify genes associated with economic traits. Skeletal muscle development is an important physiological process in meat animals, and it directly affects meat production. The expression of myostain (MSTN) and myogenin (MYoG) genes in longissimus dorsi, during the early growth stage of Hu sheep, was studied by semi-quantitative Reverse transcription polymerase chain reaction (RT-PCR). The results demonstrate that age and gender were playing a very important role in the expression of sheep muscle. MSTN and MYOG genes showed similar variation pattern for the male and female. The expression level of the MSTN and MYoG genes all showed a positive correlation with live weight, carcass weight and meat percentage, but only showed a significant relationship with meat percentage. MSTN gene showed an extreme significant positive relationship with MYoG.Key words: Sheep, myostain (MSTN), myogenin (MYoG), gene expression, muscle trait

    Sign-reversal of the in-plane resistivity anisotropy in hole-doped iron pnictides

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    The in-plane anisotropy of the electrical resistivity across the coupled orthorhombic and magnetic transitions of the iron pnictides has been extensively studied in the parent and electron-doped compounds. All these studies universally show that the resistivity ρa\rho_{a} across the long orthorhombic axis aOa_{O} - along which the spins couple antiferromagnetically below the magnetic transition temperature - is smaller than the resistivity ρb\rho_{b} of the short orthorhombic axis bOb_{O}, i. e. ρa<ρb\rho_{a}<\rho_{b}. Here we report that in the hole-doped compounds Ba1x_{1-x}Kx_{x}Fe2_{2}As2_{2}, as the doping level increases, the resistivity anisotropy initially becomes vanishingly small, and eventually changes sign for sufficiently large doping, i. e. ρb<ρa\rho_{b}<\rho_{a}. This observation is in agreement with a recent theoretical prediction that considers the anisotropic scattering of electrons by spin-fluctuations in the orthorhombic/nematic state.Comment: This paper has been replaced by the new version offering new explanation of the experimental results first reported her

    Deep generative modeling for single-cell transcriptomics.

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    Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task

    Observation of a pairing pseudogap in a two-dimensional Fermi gas

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    Pairing of fermions is ubiquitous in nature and it is responsible for a large variety of fascinating phenomena like superconductivity, superfluidity of 3^3He, the anomalous rotation of neutron stars, and the BEC-BCS crossover in strongly interacting Fermi gases. When confined to two dimensions, interacting many-body systems bear even more subtle effects, many of which lack understanding at a fundamental level. Most striking is the, yet unexplained, effect of high-temperature superconductivity in cuprates, which is intimately related to the two-dimensional geometry of the crystal structure. In particular, the questions how many-body pairing is established at high temperature and whether it precedes superconductivity are crucial to be answered. Here, we report on the observation of pairing in a harmonically trapped two-dimensional atomic Fermi gas in the regime of strong coupling. We perform momentum-resolved photoemission spectroscopy, analogous to ARPES in the solid state, to measure the spectral function of the gas and we detect a many-body pairing gap above the superfluid transition temperature. Our observations mark a significant step in the emulation of layered two-dimensional strongly correlated superconductors using ultracold atomic gases

    Next-generation sequencing reveals substantial genetic contribution to dementia with Lewy bodies

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    Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia after Alzheimer's disease. Although an increasing number of genetic factors have been connected to this debilitating condition, the proportion of cases that can be attributed to distinct genetic defects is unknown. To provide a comprehensive analysis of the frequency and spectrum of pathogenic missense mutations and coding risk variants in nine genes previously implicated in DLB, we performed exome sequencing in 111 pathologically confirmed DLB patients. All patients were Caucasian individuals from North America. Allele frequencies of identified missense mutations were compared to 222 control exomes. Remarkably, ~ 25% of cases were found to carry a pathogenic mutation or risk variant in APP, GBA or PSEN1, highlighting that genetic defects play a central role in the pathogenesis of this common neurodegenerative disorder. In total, 13% of our cohort carried a pathogenic mutation in GBA, 10% of cases carried a risk variant or mutation in PSEN1, and 2% were found to carry an APP mutation. The APOE ε4 risk allele was significantly overrepresented in DLB patients (p-value < 0.001). Our results conclusively show that mutations in GBA, PSEN1, and APP are common in DLB and consideration should be given to offer genetic testing to patients diagnosed with Lewy body dementia
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