Parallel Architectures for High Speed Multipliers

The authors compare various array multiplier architectures based on (p,q) counter circuits. The tradeoff in multiplier design is always between adding complexity and increasing speed. It is shown that by using a (2,2,3) counter cell it is possible to gain a significant increase in speed over a conventional full-adder, carry-save array based approach. The increase in complexity should be easily accommodated using modern emitter-coupled-logic processes.

The SV2A ligand levetiracetam inhibits presynaptic Ca2+ channels via an intracellular pathway

Levetiracetam (LEV) is a prominent antiepileptic drug (AED) which binds to neuronal synaptic vesicle glycoprotein 2A (SV2A) protein and has reported effects on ion channels, but retains a poorly-defined mechanism of action. Here, we investigate inhibition of voltage-dependent Ca2+ (CaV) channels as a potential mechanism by which LEV imparts effects on neuronal activity. We used electrophysiological methods to investigate the effects of LEV on cholinergic synaptic transmission and CaV channel activity in superior cervical ganglion neurons (SCGNs). In parallel, we investigated effects of the LEV ‘inactive’ R-enantiomer, UCB L060. Thus, LEV, but not UCB L060 (each 100 μM), inhibited synaptic transmission between SCGNs in long-term culture in a time-dependent manner, significantly reducing excitatory postsynaptic potentials (EPSP) following ≥30 min application. In isolated SCGNs, LEV pretreatment (≥1 h), but not acute (5 min) application, significantly inhibited whole-cell IBa amplitude. In current clamp recordings, LEV reduced the amplitude of the afterhyperpolarizing potential (AHP) in a Ca2+-dependent manner, but also increased action potential (AP) latency in a Ca2+-independent manner, suggesting further mechanisms associated with reduced excitability. Intracellular LEV application (4-5 min) caused a rapid inhibition of IBa amplitude to an extent comparable to that seen following extracellular LEV pretreatment ( ≥ 1 h). Neither pretreatment nor intracellular application of UCB L060 produced any inhibitory effects on IBa amplitude. These results identify a stereospecific intracellular pathway by which LEV inhibits presynaptic CaV channels; resultant reductions in neuronal excitability are proposed to contribute to the anticonvulsant effects of LEV.

Age related changes in speed and mechanism of adult skeletal muscle stem cell migration

Skeletal muscle undergoes a progressive age-related loss in mass and function. Preservation of muscle mass depends in part on satellite cells, the resident stem cells of skeletal muscle. Reduced satellite cell function may contribute to the age-associated decrease in muscle mass. Here we focused on characterising the effect of age on satellite cell migration. We report that aged satellite cells migrate at less than half the speed of young cells. In addition, aged cells show abnormal membrane extension and retraction characteristics required for amoeboid based cell migration. Aged satellite cells displayed low levels of integrin expression. By deploying a mathematical model approach to investigate mechanism of migration, we have found that young satellite cells move in a random ‘memoryless’ manner whereas old cells demonstrate superdiffusive tendencies. Most importantly, we show that nitric oxide, a key regulator of cell migration, reversed the loss in migration speed and reinstated the unbiased mechanism of movement in aged satellite cells. Finally we found that although Hepatocyte Growth Factor increased the rate of aged satellite cell movement it did not restore the memoryless migration characteristics displayed in young cells. Our study shows that satellite cell migration, a key component of skeletal muscle regeneration, is compromised during aging. However, we propose clinically approved drugs could be used to overcome these detrimental changes.

Assessing the microbial oxidative stress mechanism of ozone treatment through the responses of Escherichia coli mutants

Aims: To investigate the effect of the oxidative stress of ozone on the microbial inactivation, cell membrane integrity and permeability and morphology changes of Escherichia coli. Methods and Results: Escherichia coli BW 25113 and its isogenic mutants in soxR, soxS, oxyR, rpoS and dnaK genes were treated with ozone at a concentration of 6 lg ml)1 for a period up to 240 s. A significant effect of ozone exposure on microbial inactivation was observed. After ozonation, minor effects on the cell membrane integrity and permeability were observed, while scanning electron microscopy analysis showed slightly altered cell surface structure. Conclusions: The results of this study suggest that cell lysis was not the major mechanism of microbial inactivation. The deletion of oxidative stress–related genes resulted in increased susceptibility of E. coli cells to ozone treatment, implying that they play an important role for protection against the radicals produced by ozone. However, DnaK that has previously been shown to protect against oxidative stress did not protect against ozone treatment in this study. Furthermore, RpoS was important for the survival against ozone. Significance and Impact of the Study: This study provides important information about the role of oxidative stress in the responses of E. coli during ozonation.

Cyclic extrusion of a lava dome based on a stick-slip mechanism

Lava dome eruptions are sometimes characterised by large periodic fluctuations in extrusion rate over periods of hours that may be accompanied by Vulcanian explosions and pyroclastic flows. We consider a simple system of nonlinear equations describing a 1D flow of lava extrusion through a deep elastic dyke feeding a shallower cylindrical conduit in order to simulate this short-period cyclicity. Stick-slip conditions depending on a critical shear stress are assumed at the wall boundary of the cylindrical conduit. By analogy with the behaviour of industrial polymers in a plastic extruder, the elastic dyke acts like a barrel and the shallower cylindrical portion of the conduit as a die for the flow of magma acting as a polymer. When we applied the model to the Soufrière Hills Volcano, Montserrat, for which the key parameters have been evaluated from previous studies, cyclic extrusions with periods from 3 to 30 h were readily simulated, matching observations. The model also reproduces the reduced period of cycles observed when a major unloading event occurs due to lava dome collapse.

Allosteric mechanism controls traffic in the chaperone/usher pathway

Many virulence organelles of Gram-negative bacterial pathogens are assembled via the chaperone/ usher pathway. The chaperone transports organelle subunits across the periplasm to the outer membrane usher, where they are released and incorporated into growing fibers. Here, we elucidate the mechanism of the usher-targeting step in assembly of the Yersinia pestis F1 capsule at the atomic level. The usher interacts almost exclusively with the chaperone in the chaperone:subunit complex. In free chaperone, a pair of conserved proline residues at the beginning of the subunit-binding loop form a ‘‘proline lock’’ that occludes the usher-binding surface and blocks usher binding. Binding of the subunit to the chaperone rotates the proline lock away from the usher-binding surface, allowing the chaperone-subunit complex to bind to the usher. We show that the proline lock exists in other chaperone/usher systems and represents a general allosteric mechanism for selective targeting of chaperone:subunit complexes to the usher and for release and recycling of the free chaperone.

PMCRI: a parallel modular classification rule induction framework

In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction of Decision Trees (TDIDT) algorithm is a very widely used technology to predict the classification of newly recorded data. However alternative technologies have been derived that often produce better rules but do not scale well on large datasets. Such an alternative to TDIDT is the PrismTCS algorithm. PrismTCS performs particularly well on noisy data but does not scale well on large datasets. In this paper we introduce Prism and investigate its scaling behaviour. We describe how we improved the scalability of the serial version of Prism and investigate its limitations. We then describe our work to overcome these limitations by developing a framework to parallelise algorithms of the Prism family and similar algorithms. We also present the scale up results of a first prototype implementation.

Parallel induction of modular classification rules

The Distributed Rule Induction (DRI) project at the University of Portsmouth is concerned with distributed data mining algorithms for automatically generating rules of all kinds. In this paper we present a system architecture and its implementation for inducing modular classification rules in parallel in a local area network using a distributed blackboard system. We present initial results of a prototype implementation based on the Prism algorithm.

Parallel rule induction with information theoretic pre-pruning

In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to inducing classification rules, one is the divide and conquer approach, also known as the top down induction of decision trees; the other approach is called the separate and conquer approach. A considerable amount of work has been done on scaling up the divide and conquer approach. However, very little work has been conducted on scaling up the separate and conquer approach.In this work we describe a parallel framework that allows the parallelisation of a certain family of separate and conquer algorithms, the Prism family. Parallelisation helps the Prism family of algorithms to harvest additional computer resources in a network of computers in order to make the induction of classification rules scale better on large datasets. Our framework also incorporates a pre-pruning facility for parallel Prism algorithms.

Scaling up classification rule induction through parallel processing

The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelization in the field of classification rule induction.

Parallel random prism: a computationally efficient ensemble learner for classification

Generally classifiers tend to overfit if there is noise in the training data or there are missing values. Ensemble learning methods are often used to improve a classifier's classification accuracy. Most ensemble learning approaches aim to improve the classification accuracy of decision trees. However, alternative classifiers to decision trees exist. The recently developed Random Prism ensemble learner for classification aims to improve an alternative classification rule induction approach, the Prism family of algorithms, which addresses some of the limitations of decision trees. However, Random Prism suffers like any ensemble learner from a high computational overhead due to replication of the data and the induction of multiple base classifiers. Hence even modest sized datasets may impose a computational challenge to ensemble learners such as Random Prism. Parallelism is often used to scale up algorithms to deal with large datasets. This paper investigates parallelisation for Random Prism, implements a prototype and evaluates it empirically using a Hadoop computing cluster.

Suppression of a pro-apoptotic K+ channel as a mechanism for hepatitis C virus persistence

An estimated 3% of the global population are infected with hepatitis C virus (HCV), and the majority of these individuals will develop chronic liver disease. As with other chronic viruses, establishment of persistent infection requires that HCV-infected cells must be refractory to a range of pro-apoptotic stimuli. In response to oxidative stress, amplification of an outward K(+) current mediated by the Kv2.1 channel, precedes the onset of apoptosis. We show here that in human hepatoma cells either infected with HCV or harboring an HCV subgenomic replicon, oxidative stress failed to initiate apoptosis via Kv2.1. The HCV NS5A protein mediated this effect by inhibiting oxidative stress-induced p38 MAPK phosphorylation of Kv2.1. The inhibition of a host cell K(+) channel by a viral protein is a hitherto undescribed viral anti-apoptotic mechanism and represents a potential target for antiviral therapy.

A mechanism for Atlantic multidecadal variability in the Kiel Climate Model

Atlantic Multidecadal Variability (AMV) is investigated in a millennial control simulation with the Kiel Climate Model (KCM), a coupled atmosphere–ocean–sea ice model. An oscillatory mode with approximately 60 years period and characteristics similar to observations is identified with the aid of three-dimensional temperature and salinity joint empirical orthogonal function analysis. The mode explains 30 % of variability on centennial and shorter timescales in the upper 2,000 m of the North Atlantic. It is associated with changes in the Atlantic Meridional Overturning Circulation (AMOC) of ±1–2 Sv and Atlantic Sea Surface Temperature (SST) of ±0.2 °C. AMV in KCM results from an out-of-phase interaction between horizontal and vertical ocean circulation, coupled through Irminger Sea convection. Wintertime convection in this region is mainly controlled by salinity anomalies transported by the Subpolar Gyre (SPG). Increased (decreased) dense water formation in this region leads to a stronger (weaker) AMOC after 15 years, and this in turn leads to a weaker (stronger) SPG after another 15 years. The key role of salinity variations in the subpolar North Atlantic for AMV is confirmed in a 1,000 year long simulation with salinity restored to model climatology: No low frequency variations in convection are simulated, and the 60 year mode of variability is absent.