β-Carotene transport in human lipoproteins. Comparisons with a-tocopherol

The purpose of this study was to investigate the temporal relationships of the transport of β-carotene in human lipoproteins. We administered 60 mg β-carotene with breakfast to nine fasting subjects, then blood samples were collected at intervals of up to 75 h, lipoproteins were isolated, and β-carotene was quantitated. β-Carotene concentrations in chylomicrons and very low density lipoproteins (VLDL) peaked at 6 and 9 h, respectively. Nonetheless, at all time points the majority of plasma β-carotene was contained in low density lipoproteins (LDL), while high density lipoproteins (HDL) carried a smaller portion (at 24 h, 73±8% in LDL as compared with 23±5% in HDL). In three subjects, transport of β-carotene was compred with the results of earlier studies on the transport of stereoisomers of α-tocopherol. Unlike plasmaRRR-α-tocopherol concentrations, which are maintained by the preferential incorporation ofRRR-α-tocopherol into VLDL by the liver, β-carotene increased and decreased in VLDL similarly toSRR-α-tocopherol, a stereoisomer whose concentrations are not maintained in plasma. In conclusion, β-carotene is primarily transported in the plasma in LDL, but its incorporation by the liver into lipoproteins does not appear to be enhanced.     

Performance analysis challenges and framework for high-performance reconfigurable computing

Reconfigurable computing (RC) applications employing both microprocessors and FPGAs have potential for large speedup when compared with traditional (software) parallel applications. However, this potential is marred by the additional complexity of these dual-paradigm systems, making it difficult to identify performance bottlenecks and achieve desired performance. Performance analysis concepts and tools are well researched and widely available for traditional parallel applications but are lacking in RC, despite being of great importance due to the applications’ increased complexity. In this paper, we explore challenges and present new techniques in automated instrumentation, runtime measurement, and visualization of RC application behavior. We also present ideas for integration with conventional performance analysis tools to create a unified tool for RC applications as well as our initial framework for FPGA instrumentation and measurement. Results from a case study are provided using a prototype of this new tool.     

Multi-input optical parallel logic processing with the shadow-casting technique

The lensless shadow-casting technique for coded pattern processing usually accommodates two inputs at a time to perform desired logical operations in parallel. A method of binary encoding is proposed that can accommodate multiple input patterns for simultaneous processing. With the proposed multiple-input encoding a carry-look-ahead technique of binary addition is developed that requires fewer processing steps than the conventional ripple-carry method. Experimental results for a few logic-processing operations are included to establish the validity of the proposed technique.     

An n‐material thresholding method for improving integerness of solutions in topology optimization

It is common in solving topology optimization problems to replace an integer‐valued characteristic function design field with the material volume fraction field, a real‐valued approximation of the design field that permits ‘fictitious’ mixtures of materials during intermediate iterations in the optimization process. This is reasonable so long as one can interpolate properties for such materials and so long as the final design is integer valued. For this purpose, we present a method for smoothly thresholding the volume fractions of an arbitrary number of material phases which specify the design. This method is trivial for two‐material design problems, for example, the canonical topology design problem of specifying the presence or absence of a single material within a domain, but it becomes more complex when three or more materials are used, as often occurs in material design problems. We take advantage of the similarity in properties between the volume fractions and the barycentric coordinates on a simplex to derive a thresholding, method which is applicable to an arbitrary number of materials. As we show in a sensitivity analysis, this method has smooth derivatives, allowing it to be used in gradient‐based optimization algorithms. We present results, which show synergistic effects when used with Solid Isotropic Material with Penalty and Rational Approximation of Material Properties material interpolation functions, popular methods of ensuring integerness of solutions. Copyright © 2016 John Wiley & Sons, Ltd.     

Rambo: a robust, reconfigurable atomic memory service for dynamic networks

In this paper, we present Rambo, an algorithm for emulating a read/write distributed shared memory in a dynamic, rapidly changing environment. Rambo provides a highly reliable, highly available service, even as participants join, leave, and fail. In fact, the entire set of participants may change during an execution, as the initial devices depart and are replaced by a new set of devices. Even so, Rambo ensures that data stored in the distributed shared memory remains available and consistent. There are two basic techniques used by Rambo to tolerate dynamic changes. Over short intervals of time, replication suffices to provide fault-tolerance. While some devices may fail and leave, the data remains available at other replicas. Over longer intervals of time, Rambo copes with changing participants via reconfiguration, which incorporates newly joined devices while excluding devices that have departed or failed. The main novelty of Rambo lies in the combination of an efficient reconfiguration mechanism with a quorum-based replication strategy for read/write shared memory. The Rambo algorithm can tolerate a wide variety of aberrant behavior, including lost and delayed messages, participants with unsynchronized clocks, and, more generally, arbitrary asynchrony. Despite such behavior, Rambo guarantees that its data is stored consistency. We analyze the performance of Rambo during periods when the system is relatively well-behaved: messages are delivered in a timely fashion, reconfiguration is not too frequent, etc. We show that in these circumstances, read and write operations are efficient, completing in at most eight message delays.     

Reconfigurable distributed storage for dynamic networks

This paper presents a new algorithm for implementing a reconfigurable distributed shared memory in an asynchronous dynamic network. The algorithm guarantees atomic consistency (linearizability) in all executions in the presence of arbitrary crash failures of the processing nodes, message delays, and message loss. The algorithm incorporates a classic quorum-based algorithm for read/write operations, and an optimized consensus protocol, based on Fast Paxos for reconfiguration, and achieves the design goals of: (i) allowing read and write operations to complete rapidly and (ii) providing long-term fault-tolerance through reconfiguration, a process that evolves the quorum configurations used by the read and write operations. The resulting algorithm tolerates dynamism. We formally prove our algorithm to be correct, we present its performance and compare it to existing reconfigurable memories, and we evaluate experimentally the cost of its reconfiguration mechanism.     

Maintaining strong mutual visibility of an evader moving over the reduced visibility graph

In this paper, we address the problem of determining whether a mobile robot, called the pursuer, is able to maintain strong mutual visibility (a visibility notion between regions over a convex partition of the environment) of an antagonist agent, called the evader. We frame the problem as a non cooperative game. We consider the case in which the pursuer and the evader move at bounded speed, traveling in a known polygonal environment with or without holes, and in which there are no restrictions as to the distance that might separate the agents. Unlike our previous efforts (Murrieta-Cid et al. in Int J Robot Res 26:233–253, 2007), we give special attention to the combinatorial problem that arises when searching for a solution through visiting several locations in an environment with obstacles. In this paper we take a step further, namely, we assume an antagonistic evader who moves continuously and unpredictably, but with a constraint over its set of admissible motion policies, as the evader moves in the shortest-path roadmap, also called the reduced visibility graph (RVG). The pursuer does not know which among the possible paths over the RVG the evader will choose, but the pursuer is free to move within all the environment. We provide a constructive method to solve the decision problem of determining whether or not the pursuer is able to maintain strong mutual visibility of the evader. This method is based on an algorithm that computes the safe areas (areas that keep evader surveillance) at all times. We prove decidability of this problem, and provide a complexity measure to this evader surveillance game; both contributions hold for any general polygonal environment that might or not contain holes. All our algorithms have been implemented and we show simulation results.     

A short note on simultaneous splitting

We show that for any alphabet there is a setL ^* such that ifC is any infinite co-infinite context-free language over , thenL splitsC (i.e., each ofL C,L , C, and is infinite).Preparation of this paper was supported in part by the National Science Foundation under Grant No. MCS77-11360.     

Strictly positive-definite spike train kernels for point-process divergences

Exploratory tools that are sensitive to arbitrary statistical variations in spike train observations open up the possibility of novel neuroscientific discoveries. Developing such tools, however, is difficult due to the lack of Euclidean structure of the spike train space, and an experimenter usually prefers simpler tools that capture only limited statistical features of the spike train, such as mean spike count or mean firing rate. We explore strictly positive-definite kernels on the space of spike trains to offer both a structural representation of this space and a platform for developing statistical measures that explore features beyond count or rate. We apply these kernels to construct measures of divergence between two point processes and use them for hypothesis testing, that is, to observe if two sets of spike trains originate from the same underlying probability law. Although there exist positive-definite spike train kernels in the literature, we establish that these kernels are not strictly definite and thus do not induce measures of divergence. We discuss the properties of both of these existing nonstrict kernels and the novel strict kernels in terms of their computational complexity, choice of free parameters, and performance on both synthetic and real data through kernel principal component analysis and hypothesis testing.