The Prominin-1-Derived Peptide Improves Cardiac Function Following Ischemia

Myocardial infarction (MI) remains the leading cause of death in the western world. Despite advancements in interventional revascularization technologies, many patients are not candidates for them due to comorbidities or lack of local resources. Non-invasive approaches to accelerate revascularization within ischemic tissues through angiogenesis by providing Vascular Endothelial Growth Factor (VEGF) in protein or gene form has been effective in animal models but not in humans likely due to its short half-life and systemic toxicity. Here, we tested the hypothesis that PR1P, a small VEGF binding peptide that we developed, which stabilizes and upregulates endogenous VEGF, could be used to improve outcome from MI in rodents. To test this hypothesis, we induced MI in mice and rats via left coronary artery ligation and then treated animals with every other day intraperitoneal PR1P or scrambled peptide for 14 days. Hemodynamic monitoring and echocardiography in mice and echocardiography in rats at 14 days showed PR1P significantly improved multiple functional markers of heart function, including stroke volume and cardiac output. Furthermore, molecular biology and histological analyses of tissue samples showed that systemic PR1P targeted, stabilized and upregulated endogenous VEGF within ischemic myocardium. We conclude that PR1P is a potential non-invasive candidate therapeutic for MI.     

An Optimally Fair Coin Toss

We address one of the foundational problems in cryptography: the bias of coin-flipping protocols. Coin-flipping protocols allow mutually distrustful parties to generate a common unbiased random bit, guaranteeing that even if one of the parties is malicious, it cannot significantly bias the output of the honest party. A classical result by Cleve (Proceedings of the 18th annual ACM symposium on theory of computing, pp 364–369, 1986) showed that for any two-party \(r\)-round coin-flipping protocol there exists an efficient adversary that can bias the output of the honest party by \(\varOmega (1/r)\). However, the best previously known protocol only guarantees \(O(1/\sqrt{r})\) bias, and the question of whether Cleve’s bound is tight has remained open for more than 20 years. In this paper, we establish the optimal trade-off between the round complexity and the bias of two-party coin-flipping protocols. Under standard assumptions (the existence of oblivious transfer), we show that Cleve’s lower bound is tight: We construct an \(r\)-round protocol with bias \(O(1/r)\).     

Rational approach for the analysis of segmental reinforced soil walls based on kinematic constraints

The paper presents an analytical method for the solution of reinforced soil walls in which the wall facing has a structural role. The three-component (soil–reinforcement–wall) system is statically indeterminate, and hence cannot be solved by equilibrium equations alone. The paper follows up on the work of Baker and Klein [2004. An integrated limiting equilibrium approach for design of reinforced soil retaining structures part I – formulation. Geotextiles and Geomembranes 22, 119–150] where an interaction model, incorporating factors that divide forces between the reinforcement layers and the wall, was introduced to solve the statically indeterminate system. In the current work, the division factors are resolved such that the kinematic constraints of compatibility between the reinforcement layers and the wall are satisfied. This is achieved by solving an optimization problem in which the objective function includes the relative displacement between the reinforcement layers and the wall. The resultant system is fully coupled whereby upper reinforcement layers are affected by the behavior of lower layers. As such, the method overcomes the limitation of the original framework in which the top-down procedure omits such coupling. A non-dimensional parametric study was conducted on walls with 10 face blocks (9 reinforcement layers). Results are given in a normalized manner for cases in which the reinforcement pullout stiffness is uniform and linearly increasing with depth. Analysis results show that in cases where the wall is relatively stiff compared to the reinforcement, the upper reinforcement layers are clearly affected by the lower layers (this is a direct outcome of the fully coupled system). On the other hand, when the relative stiffness of the wall is low, the system behavior tends towards that of a hinged system, which is statically determinate. In this case the solution becomes independent of the reinforcement pullout stiffness. Analysis results indicate that current design codes, which do not explicitly consider the structural role of the facing in the calculation procedure, may be overconservative in certain cases. This result supports the argument for introducing the structural role of the facing into design procedures.     

The attentional white bear phenomenon: The mandatory allocation of attention to expected distractor locations.

The authors devised a prestimulus-probe method to assess the allocation of attention as a function of participants' top-down expectancies concerning distractor and target locations. Participants performed the flanker task, and distractor locations remained fixed. On some trials, instead of the flanker display, either 2 simultaneous dots or a horizontal line appeared. The dot in the expected distractor location was perceived to occur before the dot in the expected empty location, and the line appeared to extend from the expected distractor location to the expected empty location, suggesting that attention is allocated to expected distractor locations prior to stimulus onset. The authors propose that a process-all mechanism guides attention to expected locations of all stimuli regardless of task demands and that this constitutes a major cause for failures of selective attention. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Feature‐Preserving Surface Completion Using Four Points

We present a user‐guided, semi‐automatic approach to completing large holes in a mesh. The reconstruction of the missing features in such holes is usually ambiguous. Thus, unsupervised methods may produce unsatisfactory results. To overcome this problem, we let the user indicate constraints by providing merely four points per important feature curve on the mesh. Our algorithm regards this input as an indication of an important broken feature curve. Our completion is formulated as a global energy minimization problem, with user‐defined spatial‐coherence constraints, allows for completion that adheres to the existing features. We demonstrate the method on example problems that are not handled satisfactorily by fully automatic methods.     

A second-order maximum principle for discrete-time bilinear control systems with applications to discrete-time linear switched systems

A powerful approach for analyzing the stability of continuous-time switched systems is based on using optimal control theory to characterize the “most unstable” switching law. This reduces the problem of determining stability under arbitrary switching to analyzing stability for the specific “most unstable” switching law. For discrete-time switched systems, the variational approach received considerably less attention. This approach is based on using a first-order necessary optimality condition in the form of a maximum principle (MP), and typically this is not enough to completely characterize the “most unstable” switching law. In this paper, we provide a simple and self-contained derivation of a second-order necessary optimality condition for discrete-time bilinear control systems. This provides new information that cannot be derived using the first-order MP. We demonstrate several applications of this second-order MP to the stability analysis of discrete-time linear switched systems.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

On the Sequential Accumulation of Evidence

In this paper, we introduce a method for sequentially accumulating evidence as it pertains to an active observer seeking to identify an object in a known environment. We develop a probabilistic framework, based on a generalized inverse theory, where assertions are represented by conditional probability density functions. This leads to a sequential recognition strategy in which evidence is accumulated over successive viewpoints using Bayesian chaining until a definitive assertion can be made. To illustrate the theory we show how the characteristics of belief distributions can be exploited in a model-based recognition problem, where the task is to identify an unknown model from a database of known objects on the basis of parameter estimates. We illustrate the robustness of the algorithm through recognition experiments in two very different contexts: (1) a highly structured recognition context where 3-D parametric models can be estimated directly from range data, (2) a complex environment, where the relationship between the data and the model is learned through an appearance-based strategy. Specifically, the flow fields computed through the object's motion are used as structural signatures for recognition.     

Adding precise nanoliter volume capabilities to liquid-handling automation for compound screening experimentation

Miniaturizing experimental sample volumes to the nanoliter volume range is one of the most economical ways to perform mid- and high-throughput compound screening experiments. Existing automation platforms for nanoliter fluid handling can be bulky, expensive, and require periodic calibration to provide consistent liquid dispensing. In addition, even with frequent calibration, significant instrument-to-instrument variation in low-volume dispensing can occur between different instrument platforms. Many of these issues can be addressed by the use of PocketTips. PocketTips are tips with a defined internal pocket designed to hold specific nanoliter volumes of compound dissolved in dimethylsulfoxide. Although the overall liquid-handling process with PocketTips uses the aspirate/dispense features of the specific liquid-handling device being used, the dispensed nanoliter volume is solely based on the dimensions of the pocket of the PocketTip and thus, the liquid-handling device itself need not have nanoliter dispensing capabilities. In this report, we demonstrate the performance of PocketTips on different automation platforms. In addition, we used a cell-based ?-lactamase reporter assay system to demonstrate that compound delivery by PocketTips compares favorably with a standard compound addition technique.