Dworkinian Liberalism & Gay Rights: A Defense of Same-Sex Relations

Recent changes in the politics of gay rights have led to a gay rights demand for liberal governments: i) decriminalization of sodomy and ii) full governmental recognition of civil, same-sex marriages. Challengers to liberalism argue that a neutral liberalism cannot satisfy the gay rights demand. I argue that the liberal political framework put forth by Ronald Dworkin can adequately fulfill the gay rights demand. Dworkinian liberalism, which is neutral with respect to the ethical life, need not be neutral with respect to moral and non-ethical values. I argue for the more modest claim that Dworkinian liberalism has the conceptual tools and principles for satisfying the gay rights demand. In arguing for my claim, I discuss the internal criticisms of Carlos Ball and Michael Sandel and the external criticism of John Finnis. I argue that these concerns are surmountable. Dworkinian liberalism is capable of offering a robust defense of same-sex relations

I\u27d Rather Play the Saxophone : Conflicts in Identity Between Vietnamese Students and Their Parents

Members of the Vietnamese community in Lincoln, Nebraska range in time of resettlement, background and experience in adjustment to their new home. The impact of cultural change and education on the Vietnamese youth in this community is of particular importance. The Vietnamese youth are under-examined in the areas of adjustment and identity formation. The effects of cultural conflict have profound impact on the future of Vietnamese youth. The following study presents an examination of the variables that may affect Vietnamese youth, specifically culture and education as factors in ethnic identity formation. It also presents how these factors can affect the relationship between students and parents

Acculturation and Linguistic Factors on International Students’ Self-Esteem and Language Confidence

Acculturation and linguistic factors were examined as predictors of self-esteem and language confidence among 91 international college students. The majority of participants were Asian (64.8%), female (59.3%), and graduate students (76.9%). Assimilative (adopting host cultural values) and integrative (blending both host and home cultural values) modes of acculturation, less frequency of contact with host culture members, and lower quality of contact predicted higher self-esteem. Less social support and lower English language confidence also predicted higher self-esteem. Also, higher self-esteem was positively related to greater perceived daily hassles (minor stressors faced by students). Furthermore, longer length of stay and greater assimilation and integration scores significantly predicted greater English language confidence. Limitations and implications for international students and educational institutions are discussed

Data-driven structural health monitoring using feature fusion and hybrid deep learning

Smart structural health monitoring (SHM) for large-scale infrastructures is an intriguing subject for engineering communities thanks to its significant advantages such as timely damage detection, optimal maintenance strategy, and reduced resource requirement. Yet, it is a challenging topic as it requires handling a large amount of collected sensors data continuously, which is inevitably contaminated by random noises. Therefore, this study developed a practical end-to-end framework that makes use of physical features embedded in raw data and an elaborated hybrid deep learning model, namely 1DCNN-LSTM, featuring two algorithms - Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). In order to extract relevant features from sensory data, the method combines various signal processing techniques such as the autoregressive model, discrete wavelet transform, and empirical mode decomposition. The hybrid deep learning 1DCNN-LSTM is designed based on the CNN’s capacity of capturing local information and the LSTM network’s prominent ability to learn long-term dependencies. Through three case studies involving both experimental and synthetic datasets, it is demonstrated that the proposed approach achieves highly accurate damage detection, as accurate as the powerful two-dimensional CNN, but with a lower time and memory complexity, making it suitable for real-time SHM

On the solutions of universal differential equation by noncommutative Picard-Vessiot theory

Basing on Picard-Vessiot theory of noncommutative differential equations and algebraic combinatorics on noncommutative formal series with holomorphic coefficients, various recursive constructions of sequences of grouplike series converging to solutions of universal differential equation are proposed. Basing on monoidal factorizations, these constructions intensively use diagonal series and various pairs of bases in duality, in concatenation-shuffle bialgebra and in a Loday's generalized bialgebra. As applications, the unique solution, satisfying asymptotic conditions, of Knizhnik-Zamolodchikov equations is provided by d\'evissage

Families of eulerian functions involved in regularization of divergent polyzetas

Extending the Eulerian functions, we study their relationship with zeta function of several variables. In particular, starting with Weierstrass factorization theorem (and Newton-Girard identity) for the complex Gamma function, we are interested in the ratios of $\zeta(2k)/\pi^{2k}$ and their multiindexed generalization, we will obtain an analogue situation and draw some consequences about a structure of the algebra of polyzetas values, by means of some combinatorics of noncommutative rational series. The same combinatorial frameworks also allow to study the independence of a family of eulerian functions.Comment: preprin

On The Global Renormalization and Regularization of Several Complex Variable Zeta Functions by Computer

This review concerns the resolution of a special case of Knizhnik-Zamolodchikov equations ($KZ_3$) using our recent results on combinatorial aspects of zeta functions on several variables and software on noncommutative symbolic computations. In particular, we describe the actual solution of $(KZ_3)$ leading to the unique noncommutative series, $\Phi_{KZ}$, so-called Drinfel'd associator (or Drinfel'd series). Non-trivial expressions for series with rational coefficients, satisfying the same properties with $\Phi_{KZ}$, are also explicitly provided due to the algebraic structure and the singularity analysis of the polylogarithms and harmonic sums

Computer Controlled Automated Assay for Comprehensive Studies of Enzyme Kinetic Parameters

Stability and biological activity of proteins is highly dependent on their physicochemical environment. The development of realistic models of biological systems necessitates quantitative information on the response to changes of external conditions like pH, salinity and concentrations of substrates and allosteric modulators. Changes in just a few variable parameters rapidly lead to large numbers of experimental conditions, which go beyond the experimental capacity of most research groups. We implemented a computer-aided experimenting framework (“robot lab assistant”) that allows us to parameterize abstract, human-readable descriptions of micro-plate based experiments with variable parameters and execute them on a conventional 8 channel liquid handling robot fitted with a sensitive plate reader. A set of newly developed R-packages translates the instructions into machine commands, executes them, collects the data and processes it without user-interaction. By combining script-driven experimental planning, execution and data-analysis, our system can react to experimental outcomes autonomously, allowing outcome-based iterative experimental strategies. The framework was applied in a response-surface model based iterative optimization of buffer conditions and investigation of substrate, allosteric effector, pH and salt dependent activity profiles of pyruvate kinase (PYK). A diprotic model of enzyme kinetics was used to model the combined effects of changing pH and substrate concentrations. The 8 parameters of the model could be estimated from a single two-hour experiment using nonlinear least-squares regression. The model with the estimated parameters successfully predicted pH and PEP dependence of initial reaction rates, while the PEP concentration dependent shift of optimal pH could only be reproduced with a set of manually tweaked parameters. Differences between model-predictions and experimental observations at low pH suggest additional protonation-sites at the enzyme or substrates critical for enzymatic activity. The developed framework is a powerful tool to investigate enzyme reaction specifics and explore biological system behaviour in a wide range of experimental conditions