Is there a close relationship between synonymous codon bias and codon-anticodon binding strength in human genes?

Synonymous codon bias has been examined in 78 human genes (19967 codons) and measured by relative synonymous codon usage (RSCU). Relative frequencies of all kinds of dinucleotides in 2,3 or 3,4 codon positions have been calculated, and codon-anticodon bin

The features of synonymous codon bias and GC-content relationship in human genes

728 human genes were divided to four groups according to the GC contents of their coding sequences (from GC<0.43 to GC>0.58). Examination of synonymous-codon bias in the 4 groups show that NTG (N represents any base of T, A, C, G) is most favored and NCG

Schizophrenia patients and their healthy siblings share disruption of white matter integrity in the left prefrontal cortex and the hippocampus but not the anterior cingulate cortex

Healthy siblings of schizophrenia patients have an almost 9-fold higher risk for developing the illness than the general population. Disruption of white matter (WM) integrity as indicated by reduced fractional anisotropy (FA) derived from diffusion tensor

Perceptual learning, roving and the unsupervised bias

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.

Statistical user simulation with a hidden agenda

Recent work in the area of probabilistic user simulation for training statistical dialogue managers has investigated a new agenda-based user model and presented preliminary experiments with a handcrafted model parameter set. Training the model on dialogue data is an important next step, but non-trivial since the user agenda states are not observable in data and the space of possible states and state transitions is intractably large. This paper presents a summary-space mapping which greatly reduces the number of state transitions and introduces a tree-based method for representing the space of possible agenda state sequences. Treating the user agenda as a hidden variable, the forward/backward algorithm can then be successfully applied to iteratively estimate the model parameters on dialogue data. © 2007 Association for Computational Linguistics.

User responses to the learning demands of consumer products

Designers are typically male, under 35 years old and unimpaired. Users can be of any age and currently over 15% will have some form of impairment. As a result a vast array of consumer products suit youthful males and in many cases exclude other demographics (e.g. Keates and Clarkson, 2004). In studying the way a range of users learn how to use new products, key cognitive difficulties are revealed and linked back to the areas of the product causing the problems. The trials were structured so each user had to complete a specific set of tasks and were consistent across the user spectrum. The tasks set aimed to represent both everyday usage and less familiar functions. Whilst the knowledge gained could provide designers with valuable guidelines for the specific products examined, a more general abstraction provides knowledge of the pitfalls to avoid in the design of other product families.

Parameter estimation for agenda-based user simulation

This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhibited by real users. The train-able part is formed by a set of random decision points that may be encountered during the process of receiving a system act and responding with a user act. A sample-based method is presented for using real user data to estimate the parameters that control these decisions. Evaluation results are given both in terms of statistics of generated user behaviour and the quality of policies trained with different simulators. Compared to a handcrafted simulator, the trained system provides a much better fit to corpus data and evaluations suggest that this better fit should result in improved dialogue performance. © 2010 Association for Computational Linguistics.

SNPNB: analyzing neighboring-nucleotide biases on single nucleotide polymorphisms (SNPs)

SNPNB is a user-friendly and platform-independent application for analyzing Single Nucleotide Polymorphism NeighBoring sequence context and nucleotide bias patterns, and subsequently evaluating the effective SNP size for the bias patterns observed from the whole data. It was implemented by Java and Perl. SNPNB can efficiently handle genome-wide or chromosome-wide SNP data analysis in a PC or a workstation. It provides visualizations of the bias patterns for SNPs or each type of SNPs.

Simulation in user-centred design: Helping designers to empathise with atypical users

Time and budget constraints frequently prevent designers from consulting with end-users while assessing the ease of use of the products they create. This has resulted in solutions that are difficult to use by a wide range of users, especially the growing older adult population and people with different types of impairments. To help designers with this problem, capability-loss simulators have been developed with the aim of temporarily representing users who are otherwise difficult to access. This paper questions the reliability of existing tools in providing designers with meaningful information about the users' capabilities. Consequently, a new capability-loss simulation toolkit is presented, followed by its empirical evaluation. The new toolkit proved to be significantly helpful for a group of designers identifying real usability problems with everyday devices. © 2012 Copyright Taylor and Francis Group, LLC.

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.

Designing inclusive interfaces through user modeling and simulation

Elderly and disabled people can be hugely benefited through the advancement of modern electronic devices, as those can help them to engage more fully with the world. However, existing design practices often isolate elderly or disabled users by considering them as users with special needs. This article presents a simulator that can reflect problems faced by elderly and disabled users while they use computer, television, and similar electronic devices. The simulator embodies both the internal state of an application and the perceptual, cognitive, and motor processes of its user. It can help interface designers to understand, visualize, and measure the effect of impairment on interaction with an interface. Initially a brief survey of different user modeling techniques is presented, and then the existing models are classified into different categories. In the context of existing modeling approaches the work on user modeling is presented for people with a wide range of abilities. A few applications of the simulator, which shows the predictions are accurate enough to make design choices and point out the implication and limitations of the work, are also discussed. © 2012 Copyright Taylor and Francis Group, LLC.