Electron Spin for Classical Information Processing: A Brief Survey of Spin-Based Logic Devices, Gates and Circuits

In electronics, information has been traditionally stored, processed and communicated using an electron's charge. This paradigm is increasingly turning out to be energy-inefficient, because movement of charge within an information-processing device invariably causes current flow and an associated dissipation. Replacing charge with the "spin" of an electron to encode information may eliminate much of this dissipation and lead to more energy-efficient "green electronics". This realization has spurred significant research in spintronic devices and circuits where spin either directly acts as the physical variable for hosting information or augments the role of charge. In this review article, we discuss and elucidate some of these ideas, and highlight their strengths and weaknesses. Many of them can potentially reduce energy dissipation significantly, but unfortunately are error-prone and unreliable. Moreover, there are serious obstacles to their technological implementation that may be difficult to overcome in the near term. This review addresses three constructs: (1) single devices or binary switches that can be constituents of Boolean logic gates for digital information processing, (2) complete gates that are capable of performing specific Boolean logic operations, and (3) combinational circuits or architectures (equivalent to many gates working in unison) that are capable of performing universal computation.Comment: Topical Revie

Comparative analysis of prototype two-component systems with either bifunctional or monofunctional sensors: differences in molecular structure and physiological function

Signal transduction by a traditional two-component system involves a sensor protein that recognizes a physiological signal, autophosphorylates and transfers its phosphate, and a response regulator protein that receives the phosphate, alters its affinity toward specific target proteins or DNA sequences and causes change in metabolic activity or gene expression. In some cases the sensor protein, when unphosphorylated, has a positive effect upon the rate of dephosphorylation of the regulator protein (bifunctional sensor), whereas in other cases it has no such effect (monofunctional sensor). In this work we identify structural and functional differences between these two designs. In the first part of the paper we use sequence data for two-component systems from several organisms and homology modelling techniques to determine structural features for response regulators and for sensors. Our results indicate that each type of reference sensor (bifunctional and monofunctional) has a distinctive structural feature, which we use to make predictions regarding the functionality of other sensors. In the second part of the paper we use mathematical models to analyse and compare the physiological function of systems that differ in the type of sensor and are otherwise equivalent. Our results show that a bifunctional sensor is better than a monofunctional sensor both at amplifying changes in the phosphorylation level of the regulator caused by signals from the sensor and at attenuating changes caused by signals from small phosphodonors. Cross-talk to or from other two-component systems is better suppressed if the transmitting sensor is monofunctional, which is the more appropriate design when such cross-talk represents pathological noise. Cross-talk to or from other two-component systems is better amplified if the transmitting sensor is bifunctional, which is the more appropriate design when such cross-talk represents a physiological signal. These results provide a functional rationale for the selection of each design that is consistent with available experimental evidence for several two-component systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74871/1/j.1365-2958.2003.03344.x.pd

Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Comparative Structural Analysis of Human DEAD-Box RNA Helicases

DEAD-box RNA helicases play various, often critical, roles in all processes where RNAs are involved. Members of this family of proteins are linked to human disease, including cancer and viral infections. DEAD-box proteins contain two conserved domains that both contribute to RNA and ATP binding. Despite recent advances the molecular details of how these enzymes convert chemical energy into RNA remodeling is unknown. We present crystal structures of the isolated DEAD-domains of human DDX2A/eIF4A1, DDX2B/eIF4A2, DDX5, DDX10/DBP4, DDX18/myc-regulated DEAD-box protein, DDX20, DDX47, DDX52/ROK1, and DDX53/CAGE, and of the helicase domains of DDX25 and DDX41. Together with prior knowledge this enables a family-wide comparative structural analysis. We propose a general mechanism for opening of the RNA binding site. This analysis also provides insights into the diversity of DExD/H- proteins, with implications for understanding the functions of individual family members

Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

<p>Abstract</p> <p>Background</p> <p>Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged <it>in vivo </it>with <it>S. aureus</it>, <it>E. coli</it>, and <it>S. uberis</it>, samples from goats challenged <it>in vivo </it>with <it>S. aureus</it>, as well as cattle macrophages and ovine dendritic cells infected <it>in vitro </it>with <it>S. aureus</it>. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific.</p> <p>Results</p> <p>Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including <it>XBP1 </it>and <it>SREBF1</it>.</p> <p>The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of <it>E. coli </it>and <it>S. aureus </it>infections in cattle <it>in vivo </it>revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that <it>E. coli </it>caused a stronger host response.</p> <p>Conclusions</p> <p>This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.</p