Substitution rate comparisons between grasses and palms: synonymous rate differences at the nuclear gene Adh parallel rate differences at the plastid gene rbcL.

A number of studies have noted that nucleotide substitution rates at the chloroplast-encoded rbcL locus violate the molecular clock principle. Substitution rate variation at this plastid gene is particularly pronounced between palms and grasses; for example, a previous study estimated that substitution rates in rbcL sequences are approximately 5-fold faster in grasses than in palms. To determine whether a proportionate change in substitution rates also occurs in plant nuclear genes, we characterized nucleotide substitution rates in palm and grass sequences for the nuclear gene Adh. In this article, we report that palm sequences evolve at a rate of 2.61 x 10(-9) substitution per synonymous site per year, a rate which is slower than most plant nuclear genes. Grass Adh sequences evolve approximately 2.5-fold faster than palms at synonymous sites. Thus, synonymous rates in nuclear Adh genes show a marked decrease in palms relative to grasses, paralleling the pattern found at the plastid rbcL locus. This shared pattern indicates that synonymous rates are correlated between a nuclear and a plastid gene. Remarkably, nonsynonymous rates do not show this correlation. Nonsynonymous rates vary between two duplicated grass Adh loci, and nonsynonymous rates at the palm Adh locus are not markedly reduced relative to grasses.

Studies of the lamin proteinase reveal multiple parallel biochemical pathways during apoptotic execution.

Although specific proteinases play a critical role in the active phase of apoptosis, their substrates are largely unknown. We previously identified poly(ADP-ribose) polymerase (PARP) as an apoptosis-associated substrate for proteinase(s) related to interleukin 1 beta-converting enzyme (ICE). Now we have used a cell-free system to characterize proteinase(s) that cleave the nuclear lamins during apoptosis. Lamin cleavage during apoptosis requires the action of a second ICE-like enyzme, which exhibits kinetics of cleavage and a profile of sensitivity to specific inhibitors that is distinct from the PARP proteinase. Thus, multiple ICE-like enzymes are required for apoptotic events in these cell-free extracts. Inhibition of the lamin proteinase with tosyllysine "chloromethyl ketone" blocks nuclear apoptosis prior to the packaging of condensed chromatin into apoptotic bodies. Under these conditions, the nuclear DNA is fully cleaved to a nucleosomal ladder. Our studies reveal that the lamin proteinase and the fragmentation nuclease function in independent parallel pathways during the final stages of apoptotic execution. Neither pathway alone is sufficient for completion of nuclear apoptosis. Instead, the various activities cooperate to drive the disassembly of the nucleus.

Microevolutionary responses in experimental populations of plants to CO2-enriched environments: parallel results from two model systems.

Despite the critical role that terrestrial vegetation plays in the Earth's carbon cycle, very little is known about the potential evolutionary responses of plants to anthropogenically induced increases in concentrations of atmospheric CO2. We present experimental evidence that rising CO2 concentration may have a direct impact on the genetic composition and diversity of plant populations but is unlikely to result in selection favoring genotypes that exhibit increased productivity in a CO2-enriched atmosphere. Experimental populations of an annual plant (Abutilon theophrasti, velvetleaf) and a temperate forest tree (Betula alleghaniensis, yellow birch) displayed responses to increased CO2 that were both strongly density-dependent and genotype-specific. In competitive stands, a higher concentration of CO2 resulted in pronounced shifts in genetic composition, even though overall CO2-induced productivity enhancements were small. For the annual species, quantitative estimates of response to selection under competition were 3 times higher at the elevated CO2 level. However, genotypes that displayed the highest growth responses to CO2 when grown in the absence of competition did not have the highest fitness in competitive stands. We suggest that increased CO2 intensified interplant competition and that selection favored genotypes with a greater ability to compete for resources other than CO2. Thus, while increased CO2 may enhance rates of selection in populations of competing plants, it is unlikely to result in the evolution of increased CO2 responsiveness or to operate as an important feedback in the global carbon cycle. However, the increased intensity of selection and drift driven by rising CO2 levels may have an impact on the genetic diversity in plant populations.

Convergent and parallel activation of low-conductance potassium channels by calcium and cAMP-dependent protein kinase.

K+ channels, which have been linked to regulation of electrogenic solute transport as well as Ca2+ influx, represent a locus in hepatocytes for the concerted actions of hormones that employ Ca2+ and cAMP as intracellular messengers. Despite considerable study, the single-channel basis for synergistic effects of Ca2+ and cAMP on hepatocellular K+ conductance is not well understood. To address this question, patch-clamp recording techniques were applied to a model liver cell line, HTC hepatoma cells. Increasing the cytosolic Ca2+ concentration ([Ca2+]i) in HTC cells, either by activation of purinergic receptors with ATP or by inhibition of intracellular Ca2+ sequestration with thapsigargin, activated low-conductance (9-pS) K+ channels. Studies with excised membrane patches suggested that these channels were directly activated by Ca2+. Exposure of HTC cells to a permeant cAMP analog, 8-(4-chlorophenylthio)-cAMP, also activated 9-pS K+ channels but did not change [Ca2+]i. In excised membrane patches, cAMP-dependent protein kinase (the downstream effector of cAMP) activated K+ channels with conductance and selectivity identical to those of channels activated by Ca2+. In addition, cAMP-dependent protein kinase activated a distinct K+ channel type (5 pS). These data represent the differential regulation of low-conductance K+ channels by signaling pathways mediated by Ca2+ and cAMP. Moreover, since low-conductance Ca(2+)-activated K+ channels have been identified in a variety of cell types, these findings suggest that differential regulation of K+ channels by hormones with distinct signaling pathways may provide a mechanism for hormonal control of solute transport and Ca(2+)-dependent cellular functions in the liver as well as other nonexcitable tissues.

Neurosecretory habituation in PC12 cells: modulation during parallel habituation.

PC12 cells habituate during repetitive stimulation with acetylcholine, bradykinin, or high potassium. Interspersing these stimulants did not affect the rate of habituation of the others, but it could modulate the amplitude of the norepinephrine secretion each could achieve. Stimulation with acetylcholine inhibited norepinephrine secretion caused by high potassium and bradykinin stimulation, while high potassium had no effect on acetylcholine or bradykinin, and bradykinin increased secretion caused by acetylcholine. Changes in norepinephrine secretion resulting from any of these stimulants correlated with changes in internal calcium levels. Cyclic AMP-, protein kinase C-, and calmodulin-dependent second messenger pathways all modulated norepinephrine secretion caused by acetylcholine and high potassium and showed a distinct hierarchy in their effectiveness. These data demonstrate that different receptor pathways can change the norepinephrine response of one another while not changing the levels of the molecules responsible for habituation.

Reconfigurable computing for Monte Carlo simulations: results and prospects of the Janus project

We describe Janus, a massively parallel FPGA-based computer optimized for the simulation of spin glasses, theoretical models for the behavior of glassy materials. FPGAs (as compared to GPUs or many-core processors) provide a complementary approach to massively parallel computing. In particular, our model problem is formulated in terms of binary variables, and floating-point operations can be (almost) completely avoided. The FPGA architecture allows us to run many independent threads with almost no latencies in memory access, thus updating up to 1024 spins per cycle. We describe Janus in detail and we summarize the physics results obtained in four years of operation of this machine; we discuss two types of physics applications: long simulations on very large systems (which try to mimic and provide understanding about the experimental non equilibrium dynamics), and low-temperature equilibrium simulations using an artificial parallel tempering dynamics. The time scale of our non-equilibrium simulations spans eleven orders of magnitude (from picoseconds to a tenth of a second). On the other hand, our equilibrium simulations are unprecedented both because of the low temperatures reached and for the large systems that we have brought to equilibrium. A finite-time scaling ansatz emerges from the detailed comparison of the two sets of simulations. Janus has made it possible to perform spin glass simulations that would take several decades on more conventional architectures. The paper ends with an assessment of the potential of possible future versions of the Janus architecture, based on state-of-the-art technology.

Ianus: an adaptive FPGA computer

Dedicated machines designed for specific computational algorithms can outperform conventional computers by several orders of magnitude. In this note we describe Ianus, a new generation FPGA based machine and its basic features: hardware integration and wide reprogrammability. Our goal is to build a machine that can fully exploit the performance potential of new generation FPGA devices. We also plan a software platform which simplifies its programming, in order to extend its intended range of application to a wide class of interesting and computationally demanding problems. The decision to develop a dedicated processor is a complex one, involving careful assessment of its performance lead, during its expected lifetime, over traditional computers, taking into account their performance increase, as predicted by Moore’s law. We discuss this point in detail.

Interfaz software/hardware entre Raspberry Pi y FPGA Spartan-6 y su aplicación a simulación dirigida por eventos

Hoy día vivimos en la sociedad de la tecnología, en la que la mayoría de las cosas cuentan con uno o varios procesadores y es necesario realizar cómputos para hacer más agradable la vida del ser humano. Esta necesidad nos ha brindado la posibilidad de asistir en la historia a un acontecimiento sin precedentes, en el que la cantidad de transistores era duplicada cada dos años, y con ello, mejorada la velocidad de cómputo (Moore, 1965). Tal acontecimiento nos ha llevado a la situación actual, en la que encontramos placas con la capacidad de los computadores de hace años, consumiendo muchísima menos energía y ocupando muchísimo menos espacio, aunque tales prestaciones quedan un poco escasas para lo que se requiere hoy día. De ahí surge la idea de comunicar placas que se complementan en aspectos en las que ambas se ven limitadas. En nuestro proyecto desarrollaremos una interfaz s oftware/hardware para facilitar la comunicación entre dos placas con distintas prestaciones, a saber, una Raspberry Pi modelo A 2012 y una FPGA Spartan XSA3S1000 con placa extendida XStend Board V3.0. Dicha comunicación se basará en el envío y recepción de bits en serie, y será la Raspberry Pi quien marque las fases de la comunicación. El proyecto se divide en dos partes: La primera parte consiste en el desarrollo de un módulo para el kernel de Linux, que se encarga de gestionar las entradas y salidas de datos de la Raspberry Pi cuando se realizan las pertinentes llamadas de write o read. Mediante el control de los GPIO y la gestión de las distintas señales, se realiza la primera fase de la comunicación. La segunda parte consiste en el desarrollo de un diseño en VHDL para la FPGA, mediante el cual se pueda gestionar la recepción, cómputo y posterior envío de bits, de forma que la Raspberry Pi pueda disponer de los datos una vez hayan sido calculados. Ambas partes han sido desarrolladas bajo licencias libres (GPL) para que estén disponibles a cualquier persona interesada en el desarrollo y que deseen su reutilización.

An hybrid parallel algorithm for solving tridiagonal linear systems versus the Wang’s method in a Cray T3D BSP computer

In this paper we describe an hybrid algorithm for an even number of processors based on an algorithm for two processors and the Overlapping Partition Method for tridiagonal systems. Moreover, we compare this hybrid method with the Partition Wang’s method in a BSP computer. Finally, we compare the theoretical computation cost of both methods for a Cray T3D computer, using the cost model that BSP model provides.

Sequential and parallel synchronous alternating iterative methods

The so-called parallel multisplitting nonstationary iterative Model A was introduced by Bru, Elsner, and Neumann [Linear Algebra and its Applications 103:175-192 (1988)] for solving a nonsingular linear system Ax = b using a weak nonnegative multisplitting of the first type. In this paper new results are introduced when A is a monotone matrix using a weak nonnegative multisplitting of the second type and when A is a symmetric positive definite matrix using a P -regular multisplitting. Also, nonstationary alternating iterative methods are studied. Finally, combining Model A and alternating iterative methods, two new models of parallel multisplitting nonstationary iterations are introduced. When matrix A is monotone and the multisplittings are weak nonnegative of the first or of the second type, both models lead to convergent schemes. Also, when matrix A is symmetric positive definite and the multisplittings are P -regular, the schemes are also convergent.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external NLP solver implemented in Matlab®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.