Classification of taste responses in brain stem: membership in fuzzy sets

1994 ◽  
Vol 71 (6) ◽  
pp. 2139-2150 ◽  
Author(s):  
R. P. Erickson ◽  
P. M. Di Lorenzo ◽  
M. A. Woodbury
Keyword(s):  
Fuzzy Set ◽  
Published Data ◽  
Classification Methods ◽  
Neural Responses ◽  
Temporal Course ◽  
Fuzzy Set Analysis ◽  
Grade Of Membership ◽  
Underlying Mechanisms ◽  
Mathematical Process

1. Classification methods in sensory systems in general, and gustation in particular, tend to place each of the relevant objects, such as stimuli or neurons, into one class each. Some of these methods are based on the responsiveness of neurons to various stimuli; in these, each group must contain a variety of nonidentical members because of the individuality of each neuron or stimulus. 2. The “fuzzy” set method is appropriate for more accurate classification in such heterogeneous populations. In this method each member is given graded membership in several sets rather than membership in only one set. In the present paper we subjected previously published data on the responses of individual taste neurons to a variety of stimuli to fuzzy set analysis. 3. We found that the amounts of response of 46 neurons in the solitary nucleus of the rat to NaCl, HCl, sucrose, quinine HCl, and KCl could accurately be accounted for by giving each a grade of membership in three sets; the same held in the parabrachial nucleus of the rat for the responses of 41 neurons to the first four of these stimuli. The response was calculated as the sum of the products of the stimulus times neuron ratings in each set. 4. Temporal patterns of response have often been related, but with only moderate success, to the identity of the stimulus or neuron. These patterns could be accurately accounted for with the present method. Each of the products of designated parts of the stimulus ratings times the neuron ratings gave the basis for accurate description of the temporal course of the response of each neuron to each stimulus. 5. This method appears to account for the varieties of amount and temporal pattern of response of taste neurons with a simple mathematical process of few parameters. This suggests that within the known complexities of receptor mechanisms and mechanisms of neural processing, the neural message is reduced to a rather simple form. 6. The fuzzy set approach, which is based on disclosing underlying sets rather than placement of heterogeneous members into one of several essentialistic groups, may be useful in disclosure of the underlying mechanisms producing the neural responses in taste.

Application of Fractal Fuzzy Set Pair Analysis in Flood Classification

2014 ◽  
Vol 955-959 ◽  
pp. 3111-3115
Author(s):  
Yun Xia Xie ◽  
Shang Chun Zeng ◽  
Yu Quan Yuan ◽  
Yan Fei Hu
Keyword(s):  
Fuzzy Set ◽  
Yellow River ◽  
Suggested Method ◽  
The Yellow River ◽  
Set Pair Analysis ◽  
Classification Methods ◽  
Evaluation Standard ◽  
Index Weight ◽  
Pair Analysis

The mathematic theories of traditional flood classification methods are complicated and difficult to calculate. And it is difficult to determine the weights of evaluation index objectively. In this paper the idea of fractal dimension which reflects the target complexity as an index weight is put forward. At the same time paying attention to the fuzzy character of evaluation standard boundary value, the new flood classification method which based on fractal fuzzy set pair analysis is suggested. The suggested method is used in flood classification of the Tuwei River basin (a sub-basin of the Yellow River). The results show that the suggested method is objective, simple and effect, the result of classification is feasible.

scholarly journals Towards a contemporary approach for understanding personality pathology in developmental context: An integrative model

2021 ◽  
pp. 1-10
Author(s):  
Melody R. Altschuler ◽  
Robert F. Krueger
Keyword(s):  
Personality Disorders ◽  
Personality Pathology ◽  
Integrative Model ◽  
Research Domain Criteria ◽  
Developmental Context ◽  
Dimensional Classification ◽  
Developmental Theories ◽  
Underlying Mechanisms ◽  
Research Domain

Abstract Traditional categorical approaches to classifying personality disorders are limited in important ways, leading to a shift in the field to dimensional approaches to conceptualizing personality pathology. Different areas of psychology – personality, developmental, and psychopathology – can be leveraged to understand personality pathology by examining its structure, development, and underlying mechanisms. However, an integrative model that encompasses these distinct lines of inquiry has not yet been proposed. In order to address this gap, we review the latest evidence for dimensional classification of personality disorders based on structural models of maladaptive personality traits, provide an overview of developmental theories of pathological personality, and summarize the Research Domain Criteria (RDoC) initiative, which seeks to understand underlying mechanisms of psychopathology. We conclude by proposing an integrative model of personality pathology development that aims to elucidate the developmental pathways of personality pathology and its underlying mechanisms.

Fuzzy Set Based Clustering Algorithm of Web Text

2014 ◽  
Vol 678 ◽  
pp. 19-22
Author(s):  
Hong Xin Wan ◽  
Yun Peng
Keyword(s):  
Key Words ◽  
Fuzzy Set ◽  
Clustering Algorithm ◽  
Text Clustering ◽  
Classification Methods ◽  
Comparative Experiment ◽  
Fuzzy Algorithm ◽  
Pattern Clustering ◽  
The Web ◽  
Computing Accuracy

Web text exists non-certain and non-structure contents ,and it is difficult to cluster the text by normal classification methods. We propose a web text clustering algorithm based on fuzzy set to increase the computing accuracy with the web text. After abstracting the key words of the text, we can look it as attributes and design the fuzzy algorithm to decide the membership of the words. The algorithm can improve the algorithm complexity of time and space, increase the robustness comparing to the normal algorithm. To test the accuracy and efficiency of the algorithm, we take the comparative experiment between pattern clustering and our algorithm. The experiment shows that our method has a better result.

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods

2017 ◽  
Vol 100 (2) ◽  
pp. 345-350 ◽  
Author(s):  
Ana M Jiménez-Carvelo ◽  
Antonio González-Casado ◽  
Estefanía Pérez-Castaño ◽  
Luis Cuadros-Rodríguez
Keyword(s):  
Olive Oil ◽  
Vegetable Oils ◽  
Edible Oils ◽  
Support Vector ◽  
Classification Methods ◽  
Multivariate Classification ◽  
Chromatographic Fingerprint ◽  
K Nearest Neighbors ◽  
Pls Discriminant Analysis

Abstract A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phaseLC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis tookonly 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil wereused: one input-class, two input-class, and pseudo two input-class.

scholarly journals Who promotes a value-in-diversity perspective? A fuzzy set analysis of executives’ individual and organizational characteristics

2018 ◽  
Vol 58 (2) ◽  
pp. 203-217 ◽  
Author(s):  
Anna Katharina Bader ◽  
Lena Elisabeth Kemper ◽  
Fabian Jintae Froese
Keyword(s):  
Fuzzy Set ◽  
Organizational Characteristics ◽  
A Value ◽  
Fuzzy Set Analysis

Color naming, unique hues, and hue cancellation predicted from singularities in reflection properties

2006 ◽  
Vol 23 (3-4) ◽  
pp. 331-339 ◽  
Author(s):  
DAVID L. PHILIPONA ◽  
J. KEVIN O'REGAN
Keyword(s):  
Color Naming ◽  
Surface Reflection ◽  
Unique Hues ◽  
Neuronal Representation ◽  
Underlying Mechanisms ◽  
The One ◽  
Unique Green ◽  
Psychophysical Studies ◽  
Hue Cancellation

Psychophysical studies suggest that different colors have different perceptual status: red and blue for example are thought of as elementary sensations whereas yellowish green is not. The dominant account for such perceptual asymmetries attributes them to specificities of the neuronal representation of colors. Alternative accounts involve cultural or linguistic arguments. What these accounts have in common is the idea that there are no asymmetries in the physics of light and surfaces that could underlie the perceptual structure of colors, and this is why neuronal or cultural processes must be invoked as the essential underlying mechanisms that structure color perception. Here, we suggest a biological approach for surface reflection properties that takes into account only the information about light that is accessible to an organism given the photopigments it possesses, and we show that now asymmetries appear in the behavior of surfaces with respect to light. These asymmetries provide a classification of surface properties that turns out to be identical to the one observed in linguistic color categorization across numerous cultures, as pinned down by cross cultural studies. Further, we show that data from psychophysical studies about unique hues and hue cancellation are consistent with the viewpoint that stimuli reported by observers as special are those associated with this singularity-based categorization of surfaces under a standard illuminant. The approach predicts that unique blue and unique yellow should be aligned in chromatic space while unique red and unique green should not, a fact usually conjectured to result from nonlinearities in chromatic pathways.

scholarly journals Interferon Kappa Inhibits Human Papillomavirus 31 Transcription by Inducing Sp100 Proteins

2015 ◽  
Vol 90 (2) ◽  
pp. 694-704 ◽  
Author(s):  
Christina Habiger ◽  
Günter Jäger ◽  
Michael Walter ◽  
Thomas Iftner ◽  
Frank Stubenrauch
Keyword(s):  
High Risk ◽  
Human Keratinocytes ◽  
Human Papillomaviruses ◽  
Common Mechanism ◽  
Published Data ◽  
Viral Transcription ◽  
Type I ◽  
Type I Ifn ◽  
Persistent Infections ◽  
Underlying Mechanisms

ABSTRACTHigh-risk human papillomaviruses (hr-HPV) establish persistent infections in keratinocytes, which can lead to cancer of the anogenital tract. Interferons (IFNs) are a family of secreted cytokines that induce IFN-stimulated genes (ISGs), many of which display antiviral activities. Transcriptome studies have indicated that established hr-HPV-positive cell lines display a reduced expression of ISGs, which correlates with decreased levels of interferon kappa (IFN-κ), a type I IFN constitutively expressed in keratinocytes. Prior studies have also suggested that IFN-β has anti-hr-HPV activity but the underlying mechanisms are not well understood. The downregulation of IFN-κ by hr-HPV raises the possibility that IFN-κ has anti-HPV activity. Using doxycycline-inducible IFN-κ expression in CIN612-9E cells, which maintain extrachromosomally replicating HPV31 genomes, we demonstrated that IFN-κ inhibits the growth of these cells and reduces viral transcription and replication. Interestingly, the initiation of viral early transcription was already inhibited at 4 to 6 h after IFN-κ expression. This was also observed with recombinant IFN-β, suggesting a common mechanism of IFNs. Transcriptome sequencing (RNA-seq) analysis identified 1,367 IFN-κ-regulated genes, of which 221 were modulated >2-fold. The majority of those (71%) matched known ISGs, confirming that IFN-κ acts as abona fidetype I IFN in hr-HPV-positive keratinocytes. RNA interference (RNAi) and cotransfection experiments indicated that the inhibition of viral transcription is mainly due to the induction of Sp100 proteins by IFN-κ. Consistent with published data showing that Sp100 acts as a restriction factor for HPV18 infection, our results suggest that hr-HPV target IFN-κ to prevent Sp100 expression and identify Sp100 as an ISG with anti-HPV activity.IMPORTANCEHigh-risk HPV can establish persistent infections which may progress to anogenital cancers. hr-HPV interfere with the expression of interferon (IFN)-stimulated genes (ISGs), which is due to reduced levels of IFN-κ, an IFN that is constitutively expressed in human keratinocytes. This study reveals that IFN-κ rapidly inhibits HPV transcription and that this is due to the induction of Sp100 proteins. Thus, Sp100 represents an ISG for hr-HPV.

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