A new framework for assessing subject-specific whole brain circulation and perfusion using MRI-based measurements and a multi-scale continuous flow model

With the gradual emergence of the separation and dislocation of urban jobs-housing space, rational planning of urban jobs-housing space has become the core issue of national land-spatial planning. To study the existing relationship between workspaces and living spaces, a new method to identify jobs-housing space is proposed, which not only considers the static spatial distribution of urban public facilities but also identifies the jobs-housing space by analyzing the real mobility characteristics of people from a humanistic perspective. This method provides a new framework for the identification of urban jobs-housing space by integrating point-of-interest (POI) and trajectory data. The method involves three steps: Firstly, based on the trajectory data, we analyze the characteristics of the dynamic flow of passengers in the grid and construct the living factors and working factors to identify the distribution of jobs-housing space. Secondly, we reclassify the POIs to calculate the category ratios of different types of POIs in the grid to identify the jobs-housing space. Finally, an OR operation is performed on the results obtained by the two methods to obtain the final recognition result. We selected Haikou City as the experimental area to verify the method proposed in this paper. The experimental results show that the recognition accuracy of the travel flow model is 72.43%, the POI quantitative recognition method’s accuracy is 74.94%, and the accuracy of the method proposed in this paper is 85.90%, which is significantly higher than the accuracy of the previous two methods. Therefore, the method proposed here can serve as a reference for subsequent research on urban jobs-housing space.

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A Continuous-Flow Model for Phonatory Reaction Time

Journal of Speech Language and Hearing Research ◽

10.1044/jshr.3403.517 ◽

1991 ◽

Vol 34 (3) ◽

pp. 517-525 ◽

Cited By ~ 7

Author(s):

Carole Ferrand ◽

Gordon W. Blood ◽

Harvey R. Gilbert

Keyword(s):

Reaction Time ◽

Continuous Flow ◽

Vocal Fold ◽

Flow Model ◽

Reaction Time Task ◽

Central Process ◽

Brain Potentials ◽

Time Task ◽

Vocal Fold Vibration ◽

Yield Information

The purpose of this study was to validate a proposed continuous-flow model of phonatory reaction time by investigating the temporal order of selected laryngeal and neurophysiological events involved in a phonatory reaction time task. Ten normal speakers participated in a phonatory reaction time task. Laryngeal positioning movements prior to vocal fold closure (laryngeal shift) and onset of vocal fold vibration (acoustic onset) were recorded with an electroglottograph. P300 brain potentials were collected simultaneously, and they served as an index of a central process underlying reaction time. The obtained temporal ordering of laryngeal shift, P300, and acoustic onset supported a continuous-flow model of phonatory reaction time. Use of this model might yield information that is more accurate in explaining physiological function and more precise in describing temporal patterning than the serial model.

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A New Subject-Specific Discriminative and Multi-Scale Filter Bank Tangent Space Mapping Method for Recognition of Multiclass Motor Imagery

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.595723 ◽

2021 ◽

Vol 15 ◽

Author(s):

Fan Wu ◽

Anmin Gong ◽

Hongyun Li ◽

Lei Zhao ◽

Wei Zhang ◽

...

Keyword(s):

Classification Accuracy ◽

Tangent Space ◽

Filter Bank ◽

Space Mapping ◽

Training Time ◽

Frequency Bands ◽

Multi Scale ◽

Average Accuracy ◽

Subject Specific ◽

The Subject

Objective: Tangent Space Mapping (TSM) using the geometric structure of the covariance matrices is an effective method to recognize multiclass motor imagery (MI). Compared with the traditional CSP method, the Riemann geometric method based on TSM takes into account the nonlinear information contained in the covariance matrix, and can extract more abundant and effective features. Moreover, the method is an unsupervised operation, which can reduce the time of feature extraction. However, EEG features induced by MI mental activities of different subjects are not the same, so selection of subject-specific discriminative EEG frequency components play a vital role in the recognition of multiclass MI. In order to solve the problem, a discriminative and multi-scale filter bank tangent space mapping (DMFBTSM) algorithm is proposed in this article to design the subject-specific Filter Bank (FB) so as to effectively recognize multiclass MI tasks.Methods: On the 4-class BCI competition IV-2a dataset, first, a non-parametric method of multivariate analysis of variance (MANOVA) based on the sum of squared distances is used to select discriminative frequency bands for a subject; next, a multi-scale FB is generated according to the range of these frequency bands, and then decompose multi-channel EEG of the subject into multiple sub-bands combined with several time windows. Then TSM algorithm is used to estimate Riemannian tangent space features in each sub-band and finally a liner Support Vector Machines (SVM) is used for classification.Main Results: The analysis results show that the proposed discriminative FB enhances the multi-scale TSM algorithm, improves the classification accuracy and reduces the execution time during training and testing. On the 4-class BCI competition IV-2a dataset, the average session to session classification accuracy of nine subjects reached 77.33 ± 12.3%. When the training time and the test time are similar, the average classification accuracy is 2.56% higher than the latest TSM method based on multi-scale filter bank analysis technology. When the classification accuracy is similar, the training speed is increased by more than three times, and the test speed is increased two times more. Compared with Supervised Fisher Geodesic Minimum Distance to the Mean (Supervised FGMDRM), another new variant based on Riemann geometry classifier, the average accuracy is 3.36% higher, we also compared with the latest Deep Learning method, and the average accuracy of 10-fold cross validation improved by 2.58%.Conclusion: Research shows that the proposed DMFBTSM algorithm can improve the classification accuracy of MI tasks.Significance: Compared with the MFBTSM algorithm, the algorithm proposed in this article is expected to select frequency bands with good separability for specific subject to improve the classification accuracy of multiclass MI tasks and reduce the feature dimension to reduce training time and testing time.

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Ventilatory modes and mechanics of the hedgehog skate (Leucoraja erinacea): testing the continuous flow model

Journal of Experimental Biology ◽

10.1242/jeb.204.9.1577 ◽

2001 ◽

Vol 204 (9) ◽

pp. 1577-1587 ◽

Cited By ~ 3

Author(s):

A.P. Summers ◽

L.A. Ferry-Graham

Keyword(s):

System Design ◽

Continuous Flow ◽

Flow Model ◽

Pressure Measurements ◽

Suction Pump ◽

Experimental Animals ◽

Pressure Transducers ◽

Oropharyngeal Cavity ◽

Elasmobranch Fishes ◽

System 1

The movement of water across the gills of non-ram-ventilating fishes involves the action of two pumps: a pressure pump that pushes water across the gills from the oropharyngeal to the parabranchial cavity, and a suction pump that draws water across the gills from the oropharyngeal into the parabranchial cavity. Together, the two are thought to keep water flowing continuously anteroposteriorly through the head of the respiring animal. However, there is evidence that the pressure and suction pumps do not always work in perfect phase in elasmobranch fishes, leading to periods of higher pressure in the parabranchial than in the oropharyngeal cavity. We investigated the existence and consequence of such pressure reversals in the hedgehog skate Leucoraja erinacea using pressure transducers, sonomicrometry and flow visualization including internal visualization using endoscopy. We noted four patterns of respiration in the experimental skates distinguished by the flow pattern at the three openings into the respiratory system: (1) in through the spiracle only, (2) in through the mouth + spiracle, (3) in through the mouth only, and (4) the mouth held open throughout the respiratory cycle. The first two were by far the dominant modes recorded from experimental animals. We determined that pressure reversals exist in the hedgehog skate, and that the gill bars adducted during such pressure reversals. Direct observation confirmed that these pressure reversals do correspond to pulsatile flow across the gills. During mouth+spiracle ventilation the flow completely reversed direction, flowing from the parabranchial chambers back across the gills and into the oropharyngeal cavity. Finally, we addressed the utility of sonomicrometry as a technique for determining kinematics in aquatic animals. Despite some problems involving errors inherent to the system design, we found the technique useful for complementing such techniques as pressure measurements and endoscopy.

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