Programmable nanowire circuits for nanoprocessors

A nanoprocessor constructed from intrinsically nanometre-scale building blocks is an essential component for controlling memory, nanosensors and other functions proposed for nanosystems assembled from the bottom up. Important steps towards this goal over the past fifteen years include the realization of simple logic gates with individually assembled semiconductor nanowires and carbon nanotubes, but with only 16 devices or fewer and a single function for each circuit. Recently, logic circuits also have been demonstrated that use two or three elements of a one-dimensional memristor array, although such passive devices without gain are difficult to cascade. These circuits fall short of the requirements for a scalable, multifunctional nanoprocessor owing to challenges in materials, assembly and architecture on the nanoscale. Here we describe the design, fabrication and use of programmable and scalable logic tiles for nanoprocessors that surmount these hurdles. The tiles were built from programmable, non-volatile nanowire transistor arrays. Ge/Si core/shell nanowires coupled to designed dielectric shells yielded single-nanowire, non-volatile field-effect transistors (FETs) with uniform, programmable threshold voltages and the capability to drive cascaded elements. We developed an architecture to integrate the programmable nanowire FETs and define a logic tile consisting of two interconnected arrays with 496 functional configurable FET nodes in an area of ～960 μm(2). The logic tile was programmed and operated first as a full adder with a maximal voltage gain of ten and input-output voltage matching. Then we showed that the same logic tile can be reprogrammed and used to demonstrate full-subtractor, multiplexer, demultiplexer and clocked D-latch functions. These results represent a significant advance in the complexity and functionality of nanoelectronic circuits built from the bottom up with a tiled architecture that could be cascaded to realize fully integrated nanoprocessors with computing, memory and addressing capabilities.     

Highly stretchable and tough hydrogels

Hydrogels are used as scaffolds for tissue engineering, vehicles for drug delivery, actuators for optics and fluidics, and model extracellular matrices for biological studies. The scope of hydrogel applications, however, is often severely limited by their mechanical behaviour. Most hydrogels do not exhibit high stretchability; for example, an alginate hydrogel ruptures when stretched to about 1.2 times its original length. Some synthetic elastic hydrogels have achieved stretches in the range 10-20, but these values are markedly reduced in samples containing notches. Most hydrogels are brittle, with fracture energies of about 10?J?m(-2) (ref. 8), as compared with ～1,000?J?m(-2) for cartilage and ～10,000?J?m(-2) for natural rubbers. Intense efforts are devoted to synthesizing hydrogels with improved mechanical properties; certain synthetic gels have reached fracture energies of 100-1,000?J?m(-2) (refs 11, 14, 17). Here we report the synthesis of hydrogels from polymers forming ionically and covalently crosslinked networks. Although such gels contain ～90% water, they can be stretched beyond 20 times their initial length, and have fracture energies of ～9,000?J?m(-2). Even for samples containing notches, a stretch of 17 is demonstrated. We attribute the gels' toughness to the synergy of two mechanisms: crack bridging by the network of covalent crosslinks, and hysteresis by unzipping the network of ionic crosslinks. Furthermore, the network of covalent crosslinks preserves the memory of the initial state, so that much of the large deformation is removed on unloading. The unzipped ionic crosslinks cause internal damage, which heals by re-zipping. These gels may serve as model systems to explore mechanisms of deformation and energy dissipation, and expand the scope of hydrogel applications.     

A first phylogenomic hypothesis for Eulophidae (Hymenoptera,Chalcidoidea)

ABSTRACT

Eulophidae is a hyper-diverse family of chalcidoid wasps with 324 genera, about 5300 described species and probably thousands of others to be described. Until now, the absence of unequivocal morphological apomorphies and the low resolution provided by the handful of Sanger sequenced genes have hampered the reconstruction of phylogenetic relationships within the family. Here, we used ultra-conserved elements and their flanking regions to resolve relationships among 84 species of eulophids included in 63 genera representing all subfamilies and most tribes, plus 15 outgroups. Our analyses recover all traditional Eulophidae subfamilies and tribes with high support and globally agree with the traditional classification of the family. Our results confirm that Eulophinae + Tetrastichinae is the sister group of (Opheliminae + Entiinae) + Entedoninae. At the generic level, our analyses provide high support for intergeneric relationships for which morphology and Sanger markers previously failed to provide resolution. Our results also confirm that Trisecodes does not group with Eulophidae and may not belong to this family; however, its correct classification still awaits a large-scale phylogenomic hypothesis for Chalcidoidea. This work opens new avenues towards a better understanding of the evolutionary history, biogeography and evolution of host–parasitoid associations in this hyper-diverse family of chalcidoid wasps.     

Real time prediction of irregular periodic time series data

By means of a novel time-dependent cumulated variation penalty function, a new class of real-time prediction methods is developed to improve the prediction accuracy of time series exhibiting irregular periodic patterns: in particular, the breathing motion data of the patients during robotic radiation therapy. It is illustrated that for both simulated and empirical data involving changes in mean, trend, and amplitude, the proposed methods outperform existing forecasting methods based on support vector machines and artificial neural network in terms of prediction accuracy. Moreover, the proposed methods are designed so that real-time updates can be done efficiently with O(1) computational complexity upon the arrival of a new signal without scanning the old data repeatedly.     

Wallerian demyelination: chronicle of a cellular cataclysm

Wallerian demyelination is characteristic of peripheral nerve degeneration after traumatic injury. After axonal degeneration, the myelinated Schwann cell undergoes a stereotypical cellular program that results in the disintegration of the myelin sheath, a process termed demyelination. In this review, we chronologically describe this program starting from the late and visible features of myelin destruction and going backward to the initial molecular steps that trigger the nuclear reprogramming few hours after injury. Wallerian demyelination is a wonderful model for myelin degeneration occurring in the diverse forms of demyelinating peripheral neuropathies that plague human beings.     

SPIN90 dephosphorylation is required for cofilin-mediated actin depolymerization in NMDA-stimulated hippocampal neurons

Actin plays a fundamental role in the regulation of spine morphology (both shrinkage and enlargement) upon synaptic activation. In particular, actin depolymerization is crucial for the spine shrinkage in NMDAR-mediated synaptic depression. Here, we define the role of SPIN90 phosphorylation/dephosphorylation in regulating actin depolymerization via modulation of cofilin activity. When neurons were treated with NMDA, SPIN90 was dephosphorylated by STEP61 (striatal-enriched protein tyrosine phosphatase) and translocated from the spines to the dendritic shafts. In addition, phosphorylated SPIN90 bound cofilin and then inhibited cofilin activity, suggesting that SPIN90 dephosphorylation is a prerequisite step for releasing cofilin so that cofilin can adequately sever actin filaments into monomeric form. We found that SPIN90 YE, a phosphomimetic mutant, remained in the spines after NMDAR activation where it bound cofilin, thereby effectively preventing actin depolymerization. This led to inhibition of the activity-dependent redistribution of cortactin and drebrin A, as well as of the morphological changes in the spines that underlie synaptic plasticity. These findings indicate that NMDA-induced SPIN90 dephosphorylation and translocation initiates cofilin-mediated actin dynamics and spine shrinkage within dendritic spines, thereby modulating synaptic activity.     

Forecasting changes in UK interest rates

Making accurate forecasts of the future direction of interest rates is a vital element when making economic decisions. The focus on central banks as they make decisions about the future direction of interest rates requires the forecaster to assess the likely outcome of committee decisions based on new information since the previous meeting. We characterize this process as a dynamic ordered probit process that uses information to decide between three possible outcomes for interest rates: an increase, decrease or no change. When we analyse the predictive ability of two information sets, we find that the approach has predictive ability both in‐sample and out‐of‐sample that helps forecast the direction of future rates. Copyright © 2008 John wiley & Sons, Ltd.     

基于VaR模型的信用担保定价方法

随着金融市场的日渐完善，信用担保的使用日趋频繁，目前信用担保定价方法主要采用经验定价法和期权定价法。分析这两种方法在实际使用当中的局限，结合国际通行的VaR风险模型，给出了能根据信用担保风险确定担保价格的定价方法，使用该定价方法，担保机构可以在一定置信水平下至少获得无风险收益。