14 resultados para human-action recognition

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Self-conscious emotions (guilt, shame, embarrassment, pride, etc) are social emotions, and involve complex appraisals of how one’s behavior has been evaluated by the self and other people according to some value standards. Self-conscious emotions play an important role in human life by arousing and regulating human action tendencies, feeling and thoughts, which can promote people to work hard in achievement and task fields, maintain good interpersonal relationship according with social morality and expectation. The present study aimed to examine complex self-conscious emotional understanding capabilities in junior middle school students with and without learning disabilities, how the self-conscious emotions generate, and relationship between self-conscious emotions and self-representation in academic and interpersonal fields. Situational experimental methods were used in this research, and the results would give further supports for learning disabilities intervention. The main results of present research are as follows. 1. The study included 4 parts and 6 experiments. The aim of study 1 was to explore whether juveniles with learning disabilities understood complex self-conscious emotions differently from juveniles without learning disabilities. We surveyed the self-conscious emotions understanding of 37 learning disabilities and 45 non-learning disabilities with the emotional situation stories. The results indicated that the self-conscious emotional recognition in others for learning disabilities was lower than that of non-learning disabilities in different emotional recognition tasks. Moreover, children with learning disabilities were more inclined to recognize emotions in themselves as elemental emotions, however, children without learning disabilities were more inclined to recognize emotions in themselves as self-conscious emotions. 2. The aim of study 2 was to explore the generative mechanism of self-conscious emotions in academic and interpersonal fields with the method of situational experiments, namely to examine whether the self-discrepancy could cause self-conscious emotions for learning disabilities. 84 learning disabilities (in experiment 1) and 80 learning disabilities (in experiment 2) participated in the research, and the results were as follows. (1) Self discrepancy caused participants’ self-conscious emotions effectively in academic and interpersonal fields. One’s own and parents’ perspercive on the actual-ideal self-discrepancy both produced dejection-related emotions (shame、embarrassment) and agitation-related emotions (guilt). (2)In academic fields, children with learning disabilities caused higher level negative self-conscious emotions (embarrassment, shame, and guilt) and lower level positive self-conscious emotion (pride). However, there were no differences of self-conscious emotions for children with and without learning disabilities in non-academic fields. 3. The aim of study 3 was to explore what influence had self-conscious emotions on self-representation for learning disabilities with the method of situational experiments. 57 learning disabilities (in experiment 1) and 67 learning disabilities (in experiment 2) participated in the research, and the results were as follows. (1)The negative self-conscious for learning disabilities could influence their positive or negative academic and positive interpersonal self-representation stability, the ways in which self-evaluation of ability mediate these effects. However, there was no significant effect for the negative self-conscious and self-evaluation of ability predicting negative interpersonal self-representation stability. (2)The stability level of positive academic and interpersonal self-representation for learning disabilities was lower than that of non-learning disabilities. There was no significant difference of the negative interpersonal self-representation stability for children with and without learning disabilities in the positive self-conscious valence condition. However, the stability level of negative interpersonal self-representation for learning disabilities was lower than that of non-learning disabilities in the negative self-conscious valence condition. 4. The aim of study 4 was to explore the intervention effects for self-conscious emotions training course on emotional comprehension cability. 65 learning disabilities (34 in experimental group, and 31 in control group) participated in the research. The results showed that self-conscious emotions course boosted the self-conscious emotions apprehensive level for children with learning disabilities.

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土壤水是重要的生态水源和水文要素之一 ,黄土高原位于干旱半干旱地区 ,降水量的年际变化大和季节分配极不均匀 ,土壤水资源对植物生长发育的影响尤为重要。同时 ,土壤水的数量及其分布也受人类活动影响。水土保持措施是黄土高原人类改造下垫面过程之一 ,这种改造会影响土壤水分的静态分布和动态过程。水土保持坡面工程措施能有效地提高土壤含水率。深根系人工林草植被使土壤含水率降低 ,甚至造成利用性土壤干层 ,影响人工植被的永续发展。尽管天然植被也有较高的生产力水平 ,但并未引起土壤水分状况的恶化 ,这是黄土高原植被营造及规划中值得注意和进一步研究的问题

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人脸识别是模式识别研究领域的重要课题,具有广阔的应用前景。本文提出了基于模糊神 经网络的人脸识别方法。首先用最优鉴别分析方法提取人脸的最优鉴别矢量集,构成特征空间,然后在 特征空间中设计模糊神经网络分类器。在ORL人脸图象库上的实验结果表明了该方法的有效性。

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Trichosanthin (TCS) is a type I ribosome-inactivating protein possessing multiple biological and pharmacological activities. One of its major actions is inhibition of human immunodeficiency virus (HIV) replication. The mechanism is still not clear. It is

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AIM: To study the interaction between human interleukin-16 (IL-16) and the receptor CD4 (T-lymphocyte differentiation antigen) of human immunodeficiency virus type 1 (HIV-1). METHODS: Two structurally con served regions (SCRs) of human IL-16 were built by the SYBYL/Biopolymer module using the corresponding transmembrane (TM) domain of human interleukin-1 (HIL-4) and HIL-2 as the templates. The coordinates for amino-terminal residue sequence, carboxyl-terminal residue sequences, and cytoplasm loops were generated using Biopolymer's LOOP SEARCH algorithm. RESULTS: HIL-16 first formed a homodimer, then contacted with CD4 dimer further forming a dimeric complex. Subsequently, the dimeric complex constructed the tetrameric complex by two disulfide bridges between the cysteines of HIL-16 (Cys31-Cys31). CONCLUSION: The interaction model is useful to propose the action mechanism of HIL-16 and is beneficial for rational designing of novel anti-HIV drugs.

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Polybrominated diphenyl ethers (PBDEs) are used extensively as flame-retardants and are ubiquitous in the environment and in wildlife and human tissue. Recent studies have shown that PBDEs induce neurotoxic effects in vivo and apoptosis in vitro. However, the signaling mechanisms responsible for these events are still unclear. In this study, we investigated the action of a commercial mixture of PBDEs (pentabrominated diphenyl ether, DE-71) on a human neuroblastoma cell line, SK-N-SH. A cell viability test showed a dose-dependent increase in lactate dehydrogenase leakage and 3-(4,5-dimethylthia-zol-2-yl)-2,5-diphenyl-tetrazolium bromide reduction. Cell apoptosis was observed through morphological examination, and DNA degradation in the cell cycle and cell apoptosis were demonstrated using flow cytometry and DNA laddering. The formation of reactive oxygen species was not observed, but DE-71 was found to significantly induce caspase-3, -8, and -9 activity, which suggests that apoptosis is not induced by oxidative stress but via a caspase-dependent pathway. We further investigated the intracellular calcium ([Ca2+](i)) levels using flow cytometry and observed an increase in the intracellular Ca2+ concentration with a time-dependent trend. We also found that the N-methyl d-aspartate (NMDA) receptor antagonist MK801 (3 mu M) significantly reduced DE-71-induced cell apoptosis. The results of a Western blotting test demonstrated that DE-71 treatment increases the level of Bax translocation to the mitochondria in a dose-dependent fashion and stimulates the release of cytochrome c (Cyt c) from the mitochondria into the cytoplasm. Overall, our results indicate that DE-71 induces the apoptosis of ([Ca2+](i)) in SK-N-SH cells via Bax insertion, Cyt c release in the mitochondria, and the caspase activation pathway.

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Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.

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Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.

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In this paper, a novel approach for mandarin speech emotion recognition, that is mandarin speech emotion recognition based on high dimensional geometry theory, is proposed. The human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. According to the characteristics of these emotional speech signals, the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. The new method called high dimensional geometry theory is applied for recognition. Compared with traditional GSVM model, the new method has some advantages. It is noted that this method has significant values for researches and applications henceforth.

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The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.

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A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

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Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e. g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

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Single-walled carbon nanotubes (SWNTs) binding to human telomeric i-motif DNA can significantly accelerate S1 nuclease cleavage rate by increasing the enzyme turnover number.

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The family of fibrinogen-related proteins (FREPs) is a group of proteins with fibrinogen-like domains. Many members of this family play important roles as pattern recognition receptors in innate immune responses. The cDNA of bay scallop Argopecten irradians FREP (designated as AiFREP) was cloned by rapid amplification of cDNA ends (RACE) method based on the expressed sequence tag (EST). The full-length cDNA of AiFREP was of 990 bp. The open reading frame encoded a polypeptide of 251 amino acids, including a signal sequence and a 213 amino acids fibrinogen-like domain. The fibrinogen-like domain of AiFREP was highly similar to those of mammalian ficolins and other FREPs. The temporal expression of AiFREP mRNA in hemolymph was examined by fluorescent quantitative real-time PCR. The mRNA level of scallops challenged by Listonella anguillarum was significantly up-regulated, peaked to 9.39-fold at 9 h after stimulation, then dropped back to 4.37-fold at 12 h, while there was no significant change in the Micrococcus luteus challenged group in all periods of treatment. The function of AiFREP was investigated by recombination and expression of the cDNA fragment encoding its mature peptide in Escherichia coli Rosetta gami (DE3). The recombinant AiFREP (rAiFREP) agglutinated chicken erythrocytes and human A, B, O-type erythrocytes. The agglutinating activities were calcium-dependent and could be inhibited by acetyl group-containing carbohydrates. rAiFREP also agglutinated Gram-negative bacteria E. coli JM109, L anguillarum and Gram-positive bacteria M. luteus in the presence of calcium ions. These results collectively suggested that AiFREP functions as a pattern recognition receptor in the immune response of bay scallop and contributed to nonself recognition in invertebrates, which would also provide clues for elucidating the evolution of the lectin pathway of the complement system. (C) 2008 Elsevier Ltd. All rights reserved.