Cultural citizenship and its implications for citizenship education: Chinese university students’ civic experience in relation to mass media and the university citizenship curriculum

A growing body of research has argued that university citizenship curricula are inefficient in promoting civic participation, while there is a tendency towards a broader citizenship understanding and new forms of civic engagements and citizenship learning in everyday life. The notion of cultural citizenship in this thesis concentrates on media practices’ relation to civic expression and civic engagement. This research thus argues that not enough attention has been paid to the effects of citizenship education policy on students and students’ active citizenship learning in China. This thesis examines the civic experience of university students in China in the parallel contexts of widespread adoption of mass media and of university citizenship education courses, which have been explicitly mandatory for promoting civic morality education in Chinese universities since 2007. This research project raises significant questions about the meditating influences of these two contexts on students’ perceptions of civic knowledge and civic participation, with particular interest to examine whether and how the notion of cultural citizenship could be applied in the Chinese context and whether it could provide certain implications for citizenship education in China. University students in one university in Beijing contributed to this research by providing both quantitative and qualitative data collected from mixed-methods research. 212 participants contributed to the questionnaire data collection and 12 students took part in interviews. Guided by the theoretical framework of cultural citizenship, a central focus of this study is to explore whether new forms of civic engagement and civic learning and a new direction of citizenship understanding can be identified among university students’ mass media use. The study examines the patterns of students’ mass media use and its relationship to civic participation, and also explores the ways in which mass media shape students and how they interact and perform through the media use. In addition, this study discusses questions about how national context, citizenship tradition and civic education curricula relate to students’ civic perceptions, civic participation and civic motivation in their enactment of cultural citizenship. It thus tries to provide insights and identify problems associated with citizenship courses in Chinese universities. The research finds that Chinese university students can also identify civic issues and engage in civic participation through the influence of mass media, thus indicating the application of cultural citizenship in the wider higher education arena in China. In particular, the findings demonstrate that students’ citizenship knowledge has been influenced by their entertainment experiences with TV programs, social networks and movies. However, the study argues that the full enactment of cultural citizenship in China is conditional with regards to characteristics related to two prerequisites: the quality of participation and the influence of the public sphere in the Chinese context. Most students in the study are found to be inactive civic participants in their everyday lives, especially in political participation. Students express their willingness to take part in civic activities, but they feel constrained by both the current citizenship education curriculum in universities and the strict national policy framework. They mainly choose to accept ideological and political education for the sake of personal development rather than to actively resist it, however, they employ creative ways online to express civic opinions and conduct civic discussion. This can be conceptualised as the cultural dimension of citizenship observed from students who are not passively prescribed by traditional citizenship but who have opportunities to build their own civic understanding in everyday life. These findings lead to the conclusion that the notion of cultural citizenship not only provides a new mode of civic learning for Chinese students but also offers a new direction for configuring citizenship in China. This study enriches the existing global literature on cultural citizenship by providing contemporary evidence from China which is a developing democratic country, as well as offering useful information for Chinese university practitioners, policy makers and citizenship researchers on possible directions for citizenship understanding and citizenship education. In particular, it indicates that it is important for efforts to be made to generate a culture of authentic civic participation for students in the university as well as to promote the development of the public sphere in the community and the country generally.

An Information Theoretic Approach to Automatic Query Expansion

International audience

Optimization of quantum states for signaling across an arbitrary qubit noise channel with minimum-error detection

International audience

Mutual Information-based RBM Neural Networks

(Deep) neural networks are increasingly being used for various computer vision and pattern recognition tasks due to their strong ability to learn highly discriminative features. However, quantitative analysis of their classication ability and design philosophies are still nebulous. In this work, we use information theory to analyze the concatenated restricted Boltzmann machines (RBMs) and propose a mutual information-based RBM neural networks (MI-RBM). We develop a novel pretraining algorithm to maximize the mutual information between RBMs. Extensive experimental results on various classication tasks show the eectiveness of the proposed approach.

Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

Temporal solitonic crystals and non-Hermitian informational lattices

Clusters of temporal optical solitons—stable self-localized light pulses preserving their form during propagation—exhibit properties characteristic of that encountered in crystals. Here, we introduce the concept of temporal solitonic information crystals formed by the lattices of optical pulses with variable phases. The proposed general idea offers new approaches to optical coherent transmission technology and can be generalized to dispersion-managed and dissipative solitons as well as scaled to a variety of physical platforms from fiber optics to silicon chips. We discuss the key properties of such dynamic temporal crystals that mathematically correspond to non-Hermitian lattices and examine the types of collective mode instabilities determining the lifetime of the soliton train. This transfer of techniques and concepts from solid state physics to information theory promises a new outlook on information storage and transmission.

Euclidean Distance Between Haar Orthogonal and Gaussian Matrices

In this work, we study a version of the general question of how well a Haar-distributed orthogonal matrix can be approximated by a random Gaussian matrix. Here, we consider a Gaussian random matrix (Formula presented.) of order n and apply to it the Gram–Schmidt orthonormalization procedure by columns to obtain a Haar-distributed orthogonal matrix (Formula presented.). If (Formula presented.) denotes the vector formed by the first m-coordinates of the ith row of (Formula presented.) and (Formula presented.), our main result shows that the Euclidean norm of (Formula presented.) converges exponentially fast to (Formula presented.), up to negligible terms. To show the extent of this result, we use it to study the convergence of the supremum norm (Formula presented.) and we find a coupling that improves by a factor (Formula presented.) the recently proved best known upper bound on (Formula presented.). Our main result also has applications in Quantum Information Theory.

Behavioural agency theory and the family business

The behavioural agency theory was developed to provide a more comprehensive explanation and prediction of managerial risk taking, in response to some shortcomings of agency theory. In general, the theory offers explanations of why decision makers prefer some strategic choices to others. The use of behavioural agency theory in family business research has, however, been very limited. Family business scholars recently adapted this theory to construct the family business variant, the ‘socioemotional wealth’ construct, which offers better explanations for the risk taking and decision making behaviours of family firms. This chapter provides an overview of behavioural agency theory and the socioemotional wealth construct, explores how they have been used in family business research, and offers suggestions for how this theory can be used in further research to contribute to both the family business and the general management literature. Keywords: family business, behavioural agency theory, socioemotional wealth, family firm heterogeneity.

The Geometric Curvature Of The Spine Of Runners During Maximal Incremental Effort Test.

This study sought to analyse the behaviour of the average spinal posture using a novel investigative procedure in a maximal incremental effort test performed on a treadmill. Spine motion was collected via stereo-photogrammetric analysis in thirteen amateur athletes. At each time percentage of the gait cycle, the reconstructed spine points were projected onto the sagittal and frontal planes of the trunk. On each plane, a polynomial was fitted to the data, and the two-dimensional geometric curvature along the longitudinal axis of the trunk was calculated to quantify the geometric shape of the spine. The average posture presented at the gait cycle defined the spine Neutral Curve. This method enabled the lateral deviations, lordosis, and kyphosis of the spine to be quantified noninvasively and in detail. The similarity between each two volunteers was a maximum of 19% on the sagittal plane and 13% on the frontal (p<0.01). The data collected in this study can be considered preliminary evidence that there are subject-specific characteristics in spinal curvatures during running. Changes induced by increases in speed were not sufficient for the Neutral Curve to lose its individual characteristics, instead behaving like a postural signature. The data showed the descriptive capability of a new method to analyse spinal postures during locomotion; however, additional studies, and with larger sample sizes, are necessary for extracting more general information from this novel methodology.

A segunda lei da termodinâmica

Considering intrinsic characteristics of the system exclusively, both statistical and information theory interpretations of the second law are used to provide more comprehensive meanings for the concepts of entropy, temperature, and Helmholtz and Gibbs energies. The coherence of Clausius inequality to these concepts is emphasized. The aim of this work is to re-discuss the second law of thermodynamics in accordance to homogeneous processes thermodynamics, a temporal science which is the very special oversimplification of continuum mechanics for spatially constant intensive properties.

A formação de profissionais de educação fisica : alongamento muscular, uma proposta de conteudo

Universidade Estadual de Campinas . Faculdade de Educação Física

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

A mathematical view of biological complexity

This essay is a trial on giving some mathematical ideas about the concept of biological complexity, trying to explore four different attributes considered to be essential to characterize a complex system in a biological context: decomposition, heterogeneous assembly, self-organization, and adequacy. It is a theoretical and speculative approach, opening some possibilities to further numerical and experimental work, illustrated by references to several researches that applied the concepts presented here. (C) 2008 Elsevier B.V. All rights reserved.

Bounds on integrals of the Wigner function

The integral of the Wigner function over a subregion of the phase space of a quantum system may be less than zero or greater than one. It is shown that for systems with 1 degree of freedom, the problem of determining the best possible upper and lower bounds on such an integral, over an possible states, reduces to the problem of finding the greatest and least eigenvalues of a Hermitian operator corresponding to the subregion. The problem is solved exactly in the case of an arbitrary elliptical region. These bounds provide checks on experimentally measured quasiprobability distributions.