CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitative way. In this paper, we propose a qualitative graphical representation of preferences that reflects conditional dependence and independence of preference statements under a ceteris paribus (all else being equal) interpretation. Such a representation is often compact and arguably quite natural in many circumstances. We provide a formal semantics for this model, and describe how the structure of the network can be exploited in several inference tasks, such as determining whether one outcome dominates (is preferred to) another, ordering a set outcomes according to the preference relation, and constructing the best outcome subject to available evidence

Double radiative pion capture on hydrogen and deuterium and the nucleon's pion cloud

We report measurements of double radiative capture in pionic hydrogen and pionic deuterium. The measurements were performed with the RMC spectrometer at the TRIUMF cyclotron by recording photon pairs from pion stops in liquid hydrogen and deuterium targets. We obtained absolute branching ratios of $(3.02 \pm 0.27 (stat.) \pm 0.31 (syst.)) \times 10^{-5}$ for hydrogen and $(1.42 \pm ^{0.09}_{0.12} (stat.) \pm 0.11 (syst.)) \times 10^{-5}$ for deuterium, and relative branching ratios of double radiative capture to single radiative capture of $(7.68 \pm 0.69(stat.) \pm 0.79(syst.)) \times 10^{-5}$ for hydrogen and $(5.44 \pm^{0.34}_{0.46}(stat.) \pm 0.42(syst.)) \times 10^{-5}$ for deuterium. For hydrogen, the measured branching ratio and photon energy-angle distributions are in fair agreement with a reaction mechanism involving the annihilation of the incident $\pi^-$ on the $\pi^+$ cloud of the target proton. For deuterium, the measured branching ratio and energy-angle distributions are qualitatively consistent with simple arguments for the expected role of the spectator neutron. A comparison between our hydrogen and deuterium data and earlier beryllium and carbon data reveals substantial changes in the relative branching ratios and the energy-angle distributions and is in agreement with the expected evolution of the reaction dynamics from an annihilation process in S-state capture to a bremsstrahlung process in P-state capture. Lastly, we comment on the relevance of the double radiative process to the investigation of the charged pion polarizability and the in-medium pion field.Comment: 44 pages, 7 tables, 13 figures, submitted to Phys. Rev.

Extracellular Matrix Aggregates from Differentiating Embryoid Bodies as a Scaffold to Support ESC Proliferation and Differentiation

Embryonic stem cells (ESCs) have emerged as potential cell sources for tissue engineering and regeneration owing to its virtually unlimited replicative capacity and the potential to differentiate into a variety of cell types. Current differentiation strategies primarily involve various growth factor/inducer/repressor concoctions with less emphasis on the substrate. Developing biomaterials to promote stem cell proliferation and differentiation could aid in the realization of this goal. Extracellular matrix (ECM) components are important physiological regulators, and can provide cues to direct ESC expansion and differentiation. ECM undergoes constant remodeling with surrounding cells to accommodate specific developmental event. In this study, using ESC derived aggregates called embryoid bodies (EB) as a model, we characterized the biological nature of ECM in EB after exposure to different treatments: spontaneously differentiated and retinoic acid treated (denoted as SPT and RA, respectively). Next, we extracted this treatment-specific ECM by detergent decellularization methods (Triton X-100, DOC and SDS are compared). The resulting EB ECM scaffolds were seeded with undifferentiated ESCs using a novel cell seeding strategy, and the behavior of ESCs was studied. Our results showed that the optimized protocol efficiently removes cells while retaining crucial ECM and biochemical components. Decellularized ECM from SPT EB gave rise to a more favorable microenvironment for promoting ESC attachment, proliferation, and early differentiation, compared to native EB and decellularized ECM from RA EB. These findings suggest that various treatment conditions allow the formulation of unique ESC-ECM derived scaffolds to enhance ESC bioactivities, including proliferation and differentiation for tissue regeneration applications. © 2013 Goh et al

Intelligent Cooperative Control Architecture: A Framework for Performance Improvement Using Safe Learning

Planning for multi-agent systems such as task assignment for teams of limited-fuel unmanned aerial vehicles (UAVs) is challenging due to uncertainties in the assumed models and the very large size of the planning space. Researchers have developed fast cooperative planners based on simple models (e.g., linear and deterministic dynamics), yet inaccuracies in assumed models will impact the resulting performance. Learning techniques are capable of adapting the model and providing better policies asymptotically compared to cooperative planners, yet they often violate the safety conditions of the system due to their exploratory nature. Moreover they frequently require an impractically large number of interactions to perform well. This paper introduces the intelligent Cooperative Control Architecture (iCCA) as a framework for combining cooperative planners and reinforcement learning techniques. iCCA improves the policy of the cooperative planner, while reduces the risk and sample complexity of the learner. Empirical results in gridworld and task assignment for fuel-limited UAV domains with problem sizes up to 9 billion state-action pairs verify the advantage of iCCA over pure learning and planning strategies

Value Iteration for Simple Stochastic Games: Stopping Criterion and Learning Algorithm

Simple stochastic games can be solved by value iteration (VI), which yields a sequence of under-approximations of the value of the game. This sequence is guaranteed to converge to the value only in the limit. Since no stopping criterion is known, this technique does not provide any guarantees on its results. We provide the first stopping criterion for VI on simple stochastic games. It is achieved by additionally computing a convergent sequence of over-approximations of the value, relying on an analysis of the game graph. Consequently, VI becomes an anytime algorithm returning the approximation of the value and the current error bound. As another consequence, we can provide a simulation-based asynchronous VI algorithm, which yields the same guarantees, but without necessarily exploring the whole game graph.Comment: CAV201

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

Extracellular matrix interactions have essential roles in normal physiology and many pathological processes. Although the importance of extracellular matrix interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel-screening platform capable of measuring phenotypic responses to combinations of extracellular matrix molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the extracellular matrix-dependent adhesion of tumour-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumour lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8 or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified extracellular matrix and integrin interactions that could serve as therapeutic targets.National Institutes of Health (U.S.) (Grant K99-CA151968)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service AwardStand Up To Cancer (SU2C/AACR)David H. Koch Institute for Integrative Cancer Research at MIT (CTC Project)Harvard Stem Cell Institute (SG-0046-08-00)National Cancer Center (Postdoctoral Fellowship)National Cancer Institute (U.S.) (U54CA126515)National Cancer Institute (U.S.) (U54CA112967)Howard Hughes Medical InstituteMassachusetts Institute of Technology. Ludwig Center for Molecular Oncolog

Special Agents Can Promote Cooperation in the Population

Cooperation is ubiquitous in our real life but everyone would like to maximize her own profits. How does cooperation occur in the group of self-interested agents without centralized control? Furthermore, in a hostile scenario, for example, cooperation is unlikely to emerge. Is there any mechanism to promote cooperation if populations are given and play rules are not allowed to change? In this paper, numerical experiments show that complete population interaction is unfriendly to cooperation in the finite but end-unknown Repeated Prisoner's Dilemma (RPD). Then a mechanism called soft control is proposed to promote cooperation. According to the basic idea of soft control, a number of special agents are introduced to intervene in the evolution of cooperation. They comply with play rules in the original group so that they are always treated as normal agents. For our purpose, these special agents have their own strategies and share knowledge. The capability of the mechanism is studied under different settings. We find that soft control can promote cooperation and is robust to noise. Meanwhile simulation results demonstrate the applicability of the mechanism in other scenarios. Besides, the analytical proof also illustrates the effectiveness of soft control and validates simulation results. As a way of intervention in collective behaviors, soft control provides a possible direction for the study of reciprocal behaviors

F-Spondin/spon1b Expression Patterns in Developing and Adult Zebrafish

F-spondin, an extracellular matrix protein, is an important player in embryonic morphogenesis and CNS development, but its presence and role later in life remains largely unknown. We generated a transgenic zebrafish in which GFP is expressed under the control of the F-spondin (spon1b) promoter, and used it in combination with complementary techniques to undertake a detailed characterization of the expression patterns of F-spondin in developing and adult brain and periphery. We found that F-spondin is often associated with structures forming long neuronal tracts, including retinal ganglion cells, the olfactory bulb, the habenula, and the nucleus of the medial longitudinal fasciculus (nMLF). F-spondin expression coincides with zones of adult neurogenesis and is abundant in CSF-contacting secretory neurons, especially those in the hypothalamus. Use of this new transgenic model also revealed F-spondin expression patterns in the peripheral CNS, notably in enteric neurons, and in peripheral tissues involved in active patterning or proliferation in adults, including the endoskeleton of zebrafish fins and the continuously regenerating pharyngeal teeth. Moreover, patterning of the regenerating caudal fin following fin amputation in adult zebrafish was associated with F-spondin expression in the blastema, a proliferative region critical for tissue reconstitution. Together, these findings suggest major roles for F-spondin in the CNS and periphery of the developing and adult vertebrate