Discovering transcriptional modules by Bayesian data integration.

MOTIVATION: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets. RESULTS: We find that by working on a gene-by-gene basis, our model is able to extract clusters with greater functional coherence than existing methods. By combining gene expression and transcription factor binding (ChIP-chip) data in this way, we are better able to determine the groups of genes that are most likely to represent underlying TMs. AVAILABILITY: If interested in the code for the work presented in this article, please contact the authors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Opt-out options in new product co-development partnerships

We study three contractual arrangements—co-development, licensing, and co-development with opt-out options—for the joint development of new products between a small and financially constrained innovator firm and a large technology company, as in the case of a biotech innovator and a major pharma company. We formulate our arguments in the context of a two-stage model, characterized by technical risk and stochastically changing cost and revenue projections. The model captures the main disadvantages of traditional co-development and licensing arrangements: in co-development the small firm runs a risk of running out of capital as future costs rise, while licensing for milestone and royalty (M&R) payments, which eliminates the latter risk, introduces inefficiency, as profitable projects might be abandoned. Counter to intuition we show that the biotech's payoff in a licensing contract is not monotonically increasing in the M&R terms. We also show that an option clause in a co-development contract that gives the small firm the right but not the obligation to opt out of co-development and into a pre-agreed licensing arrangement avoids the problems associated with fully committed co-development or licensing: the probability that the small firm will run out of capital is greatly reduced or completely eliminated and profitable projects are never abandoned.

Paradoxical evidence integration in rapid decision processes

Decisions about noisy stimuli require evidence integration over time. Traditionally, evidence integration and decision making are described as a one-stage process: a decision is made when evidence for the presence of a stimulus crosses a threshold. Here, we show that one-stage models cannot explain psychophysical experiments on feature fusion, where two visual stimuli are presented in rapid succession. Paradoxically, the second stimulus biases decisions more strongly than the first one, contrary to predictions of one-stage models and intuition. We present a two-stage model where sensory information is integrated and buffered before it is fed into a drift diffusion process. The model is tested in a series of psychophysical experiments and explains both accuracy and reaction time distributions. © 2012 Rüter et al.

Slow peaking and low-gain designs for global stabilization of nonlinear systems

This paper presents an analysis of the slow-peaking phenomenon, a pitfall of low-gain designs that imposes basic limitations to large regions of attraction in nonlinear control systems. The phenomenon is best understood on a chain of integrators perturbed by a vector field up(x, u) that satisfies p(x, 0) = 0. Because small controls (or low-gain designs) are sufficient to stabilize the unperturbed chain of integrators, it may seem that smaller controls, which attenuate the perturbation up(x, u) in a large compact set, can be employed to achieve larger regions of attraction. This intuition is false, however, and peaking may cause a loss of global controllability unless severe growth restrictions are imposed on p(x, u). These growth restrictions are expressed as a higher order condition with respect to a particular weighted dilation related to the peaking exponents of the nominal system. When this higher order condition is satisfied, an explicit control law is derived that achieves global asymptotic stability of x = 0. This stabilization result is extended to more general cascade nonlinear systems in which the perturbation p(x, v) v, v = (ξ, u) T, contains the state ξ and the control u of a stabilizable subsystem ξ = a(ξ, u). As an illustration, a control law is derived that achieves global stabilization of the frictionless ball-and-beam model.

Neutronic optimization in high conversion Th-233U fuel assembly with simulated annealing

This paper reports on fuel design optimization of a PWR operating in a self sustainable Th-233U fuel cycle. Monte Carlo simulated annealing method was used in order to identify the fuel assembly configuration with the most attractive breeding performance. In previous studies, it was shown that breeding may be achieved by employing heterogeneous Seed-Blanket fuel geometry. The arrangement of seed and blanket pins within the assemblies may be determined by varying the designed parameters based on basic reactor physics phenomena which affect breeding. However, the amount of free parameters may still prove to be prohibitively large in order to systematically explore the design space for optimal solution. Therefore, the Monte Carlo annealing algorithm for neutronic optimization is applied in order to identify the most favorable design. The objective of simulated annealing optimization is to find a set of design parameters, which maximizes some given performance function (such as relative period of net breeding) under specified constraints (such as fuel cycle length). The first objective of the study was to demonstrate that the simulated annealing optimization algorithm will lead to the same fuel pins arrangement as was obtained in the previous studies which used only basic physics phenomena as guidance for optimization. In the second part of this work, the simulated annealing method was used to optimize fuel pins arrangement in much larger fuel assembly, where the basic physics intuition does not yield clearly optimal configuration. The simulated annealing method was found to be very efficient in selecting the optimal design in both cases. In the future, this method will be used for optimization of fuel assembly design with larger number of free parameters in order to determine the most favorable trade-off between the breeding performance and core average power density.

Optimization on manifolds: Methods and applications

This paper provides an introduction to the topic of optimization on manifolds. The approach taken uses the language of differential geometry, however,we choose to emphasise the intuition of the concepts and the structures that are important in generating practical numerical algorithms rather than the technical details of the formulation. There are a number of algorithms that can be applied to solve such problems and we discuss the steepest descent and Newton's method in some detail as well as referencing the more important of the other approaches.There are a wide range of potential applications that we are aware of, and we briefly discuss these applications, as well as explaining one or two in more detail. © 2010 Springer -Verlag Berlin Heidelberg.

Heterogeneity in structurally arrested hard spheres

When cooled or compressed sufficiently rapidly, a liquid vitrifies into a glassy amorphous state. Vitrification in a dense liquid is associated with jamming of the particles. For hard spheres, the density and degree of order in the final structure depend on the compression rate: simple intuition suggests, and previous computer simulation demonstrates, that slower compression results in states that are both denser and more ordered. In this work, we use the Lubachevsky-Stillinger algorithm to generate a sequence of structurally arrested hard-sphere states by varying the compression rate.

对Allen的时间理论的某些改进

Ａｌｌｅｎ的时间理论因直观、易懂而倍受推崇，但它存在不能处理连续变化事件等缺欠。本文提出更为一般的时间理论框架，以扩展Ａｌｌｅｎ的理论，本框架的特点为：（ｌ）将Ａｌｌｅｎ的理论纳入其中；（２）可由时间点构造时区，并可处理时区和时间点；（３）以时间元素集的２Ｄ图形表示为基础的约束传播算法，既高效又可视化。

获取无意识结构知识的机制:主观熟悉感与刺激重复结构在人工语法学习中的作用

The nature of the distinction between conscious and unconscious knowledge is a core issue in the implicit learning field. Furthermore, the phenomenological experience associated with having knowledge is central to the conscious or unconscious status of that knowledge. Consistently, Dienes and Scott (2005) measured the conscious or unconscious status of structure knowledge using subjective measures. Believing that one is purely guessing when in fact one knows indicates unconscious knowledge. But unconscious structural knowledge can also be associated with feelings of intuition or familiarity. In this thesis, we explored whether phenomenological feelings, like familiarity, associated with unconscious structural knowledge could be used, paradoxically, to exert conscious control over the use of the knowledge, and whether people could obtain repetition structure knowledge. We also investigated the neural correlates of awareness of knowing, as measured phenomenologically. In study one, subjects were trained on two grammars and then asked to endorse strings from only one of the grammars. Subjects also rated how familiar each string they felt and reported whether or not they used familiarity to make their grammaticality judgment. We found subjects could endorse the strings of just one grammar and ignore the strings from the other. Importantly, when subjects said they were using familiarity, the rated familiarity for test strings consistent with their chosen grammar was greater than that for strings from the other grammar. Familiarity, subjectively defined, is sensitive to intentions and can play a key role in strategic control. In study two, we manipulated the structural characteristic of stings and explored whether participants could learn repetition structures in the grammatical strings. We measured phenomenology again and also ERPs. Deviant letters of ungrammatical strings violating the repetition structure elicited the N2 component; we took this to be an indication of knowledge, whether conscious or not. Strings which were attributed to conscious categories (rules and recollection) rather than phenomenology associated with unconscious structural knowledge (guessing, intuition and familiarity) elicited the P300 component. Different waveforms provided evidence for the neural correlates of different phenomenologies associated with knowledge of an artificial grammar.

保险推销员自我效能感及其工作模型

The research studied self-efficacy and job mechanism of insurance salesmen in China by the methods of in-depth interview, focus-group, semi-open questionnaire, standard questionnaire. There were about 1300 samples surveyed. The way of data analysis such as factor analysis, correlation analysis, regreesion analysis and structure equation was used. Four following conclusions were drawn: First, self-efficacy of inssurance salesmen in China consists of eight factorswhich are interview skills, manner, persistence, control of emotion, plans and comments, master of knowledge, intuition and judgement, preparation. Second, the relationship between self-efficacy and other job variables such as achievement motivation, work incentive, coping strategy, view of ability, performance, goalsetting, colleague relationship, the way of feedback from leader, job satisfaction and exertion were tested and all the correlations were significant. Third, regression analysis was used to test the relationship between self-efficacy and the antecedent variables. The result was that four antecedent varialbes enter equation (p<.05). They are self-oriented achievement motivation, stability of emotion, performance and colleague relationship.. Finally, vertified by path-analysis, the research posits a comprehensive model about job for insurance salesmen, in which self-efficacy was the most important factor. On the one hand, self-efficacy has dominant effects on the consequent variables, such as mastery goal, performance- approach goal, job satisfaction, exertion, coping strategy, on the another hand, self-efficacy was found as mediator of the relationship between the antecedent variables and consequent variables.

弈棋问题解决启发式的元策略模型

Problem solving is one of the basic processes of human cognition and heuristic strategy is the key to human problem solving, hence, the studies on heuristic strategy is of great importance in cognitive psychology. Current studies on heuristics in problem solving may be summarized as follows: nature and structure of heuristics, problem structure and representation, expert knowledge and expert intuition, nature and role of image, social cognition and social learning. The present study deals with the nature and structure of heuristics. The Solitaire problem was used in our the experiments. Both traditional experimental method and computer simulation were used to study the nature and structure of heuristics. Through a series of experiments, the knowledge of Solitaire problem solving was summed up, its metastrategy is worked out, and then the the metastrategy by computer simulation and experimental verification are tested.

Taxonomic Syntax for First-Order Inference

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.

Generating Good Degree Distributions for Sparse Parity Check Codes using Oracles

Fast forward error correction codes are becoming an important component in bulk content delivery. They fit in naturally with multicast scenarios as a way to deal with losses and are now seeing use in peer to peer networks as a basis for distributing load. In particular, new irregular sparse parity check codes have been developed with provable average linear time performance, a significant improvement over previous codes. In this paper, we present a new heuristic for generating codes with similar performance based on observing a server with an oracle for client state. This heuristic is easy to implement and provides further intuition into the need for an irregular heavy tailed distribution.

Extracting Location from Contact Traces

Localization is essential feature for many mobile wireless applications. Data collected from applications such as environmental monitoring, package tracking or position tracking has no meaning without knowing the location of this data. Other applications have location information as a building block for example, geographic routing protocols, data dissemination protocols and location-based services such as sensing coverage. Many of the techniques have the trade-off among many features such as deployment of special hardware, level of accuracy and computation power. In this paper, we present an algorithm that extracts location constraints from the connectivity information. Our solution, which does not require any special hardware and a small number of landmark nodes, uses two types of location constraints. The spatial constraints derive the estimated locations observing which nodes are within communication range of each other. The temporal constraints refine the areas, computed by the spatial constraints, using properties of time and space extracted from a contact trace. The intuition of the temporal constraints is to limit the possible locations that a node can be using its previous and future locations. To quantify this intuitive improvement in refine the nodes estimated areas adding temporal information, we performed simulations using synthetic and real contact traces. The results show this improvement and also the difficulties of using real traces.

Implications of Selfish Neighbor Selection in Overlay Networks

In a typical overlay network for routing or content sharing, each node must select a fixed number of immediate overlay neighbors for routing traffic or content queries. A selfish node entering such a network would select neighbors so as to minimize the weighted sum of expected access costs to all its destinations. Previous work on selfish neighbor selection has built intuition with simple models where edges are undirected, access costs are modeled by hop-counts, and nodes have potentially unbounded degrees. However, in practice, important constraints not captured by these models lead to richer games with substantively and fundamentally different outcomes. Our work models neighbor selection as a game involving directed links, constraints on the number of allowed neighbors, and costs reflecting both network latency and node preference. We express a node's "best response" wiring strategy as a k-median problem on asymmetric distance, and use this formulation to obtain pure Nash equilibria. We experimentally examine the properties of such stable wirings on synthetic topologies, as well as on real topologies and maps constructed from PlanetLab and AS-level Internet measurements. Our results indicate that selfish nodes can reap substantial performance benefits when connecting to overlay networks composed of non-selfish nodes. On the other hand, in overlays that are dominated by selfish nodes, the resulting stable wirings are optimized to such great extent that even non-selfish newcomers can extract near-optimal performance through naive wiring strategies.