Josephson effects in MgB2 meta masked ion damage junctions

Ion beam damage combined with nanoscale focused ion beam direct milling was used to create manufacturable SNS type Josephson junctions in 100 nm thick MgB$_{2}$ with T$_{C}$ of 38 K. The junctions show non-hysteretic current - voltage characteristics between 36 and 4.2 K. Experimental evidence for the dc and ac Josephson effects in MgB$_{2}$ metal masked ion damage junctions are presented. This technique is particularly useful for prototyping devices due to its simplicity and flexibility of fabrication and has a great potential for high-density integration.Comment: 12 pages, 4 figures, RevTeX4, submitted to AP

Micro-manufacturing : research, technology outcomes and development issues

Besides continuing effort in developing MEMS-based manufacturing techniques, latest effort in Micro-manufacturing is also in Non-MEMS-based manufacturing. Research and technological development (RTD) in this field is encouraged by the increased demand on micro-components as well as promised development in the scaling down of the traditional macro-manufacturing processes for micro-length-scale manufacturing. This paper highlights some EU funded research activities in micro/nano-manufacturing, and gives examples of the latest development in micro-manufacturing methods/techniques, process chains, hybrid-processes, manufacturing equipment and supporting technologies/device, etc., which is followed by a summary of the achievements of the EU MASMICRO project. Finally, concluding remarks are given, which raise several issues concerning further development in micro-manufacturing

Long-Range Correlation in Synchronization and Syncopation Tapping: A Linear Phase Correction Model

We propose in this paper a model for accounting for the increase in long-range correlations observed in asynchrony series in syncopation tapping, as compared with synchronization tapping. Our model is an extension of the linear phase correction model for synchronization tapping. We suppose that the timekeeper represents a fractal source in the system, and that a process of estimation of the half-period of the metronome, obeying a random-walk dynamics, combines with the linear phase correction process. Comparing experimental and simulated series, we show that our model allows accounting for the experimentally observed pattern of serial dependence. This model complete previous modeling solutions proposed for self-paced and synchronization tapping, for a unifying framework of event-based timing

Measurement of the Negative Muon Anomalous Magnetic Moment to 0.7 ppm

The anomalous magnetic moment of the negative muon has been measured to a precision of 0.7 parts per million (ppm) at the Brookhaven Alternating Gradient Synchrotron. This result is based on data collected in 2001, and is over an order of magnitude more precise than the previous measurement of the negative muon. The result a_mu= 11 659 214(8)(3) \times 10^{-10} (0.7 ppm), where the first uncertainty is statistical and the second is sytematic, is consistend with previous measurements of the anomaly for the positive and negative muon. The average for the muon anomaly a_{mu}(exp) = 11 659 208(6) \times 10^{-10} (0.5ppm).Comment: 4 pages, 4 figures, submitted to Physical Review Letters, revised to reflect referee comments. Text further revised to reflect additional referee comments and a corrected Fig. 3 replaces the older versio

Autoimmune and autoinflammatory mechanisms in uveitis

The eye, as currently viewed, is neither immunologically ignorant nor sequestered from the systemic environment. The eye utilises distinct immunoregulatory mechanisms to preserve tissue and cellular function in the face of immune-mediated insult; clinically, inflammation following such an insult is termed uveitis. The intra-ocular inflammation in uveitis may be clinically obvious as a result of infection (e.g. toxoplasma, herpes), but in the main infection, if any, remains covert. We now recognise that healthy tissues including the retina have regulatory mechanisms imparted by control of myeloid cells through receptors (e.g. CD200R) and soluble inhibitory factors (e.g. alpha-MSH), regulation of the blood retinal barrier, and active immune surveillance. Once homoeostasis has been disrupted and inflammation ensues, the mechanisms to regulate inflammation, including T cell apoptosis, generation of Treg cells, and myeloid cell suppression in situ, are less successful. Why inflammation becomes persistent remains unknown, but extrapolating from animal models, possibilities include differential trafficking of T cells from the retina, residency of CD8(+) T cells, and alterations of myeloid cell phenotype and function. Translating lessons learned from animal models to humans has been helped by system biology approaches and informatics, which suggest that diseased animals and people share similar changes in T cell phenotypes and monocyte function to date. Together the data infer a possible cryptic infectious drive in uveitis that unlocks and drives persistent autoimmune responses, or promotes further innate immune responses. Thus there may be many mechanisms in common with those observed in autoinflammatory disorders

Prediction of protein structural classes for low-homology sequences based on predicted secondary structure

<p>Abstract</p> <p>Background</p> <p>Prediction of protein structural classes (<it>α</it>, <it>β</it>, <it>α </it>+ <it>β </it>and <it>α</it>/<it>β</it>) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulation and interactions. Many methods have been developed for high-homology protein sequences, and the prediction accuracies can achieve up to 90%. However, for low-homology sequences whose average pairwise sequence identity lies between 20% and 40%, they perform relatively poorly, yielding the prediction accuracy often below 60%.</p> <p>Results</p> <p>We propose a new method to predict protein structural classes on the basis of features extracted from the predicted secondary structures of proteins rather than directly from their amino acid sequences. It first uses PSIPRED to predict the secondary structure for each protein sequence. Then, the <it>chaos game representation </it>is employed to represent the predicted secondary structure as two time series, from which we generate a comprehensive set of 24 features using <it>recurrence quantification analysis</it>, <it>K-string based information entropy </it>and <it>segment-based analysis</it>. The resulting feature vectors are finally fed into a simple yet powerful Fisher's discriminant algorithm for the prediction of protein structural classes. We tested the proposed method on three benchmark datasets in low homology and achieved the overall prediction accuracies of 82.9%, 83.1% and 81.3%, respectively. Comparisons with ten existing methods showed that our method consistently performs better for all the tested datasets and the overall accuracy improvements range from 2.3% to 27.5%. A web server that implements the proposed method is freely available at <url>http://www1.spms.ntu.edu.sg/~chenxin/RKS_PPSC/</url>.</p> <p>Conclusion</p> <p>The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the predicted secondary structure sequences, which is capable of characterizing the sequence order information, local interactions of the secondary structural elements, and spacial arrangements of <it>α </it>helices and <it>β </it>strands. Thus, it is a valuable method to predict protein structural classes particularly for low-homology amino acid sequences.</p

Measurement of the proton form factor by studying e+e−→ppˉe^{+} e^{-}\rightarrow p\bar{p}

Using data samples collected with the BESIII detector at the BEPCII collider, we measure the Born cross section of $e^{+}e^{-}\rightarrow p\bar{p}$ at 12 center-of-mass energies from 2232.4 to 3671.0 MeV. The corresponding effective electromagnetic form factor of the proton is deduced under the assumption that the electric and magnetic form factors are equal $(|G_{E}|= |G_{M}|)$. In addition, the ratio of electric to magnetic form factors, $|G_{E}/G_{M}|$, and $|G_{M}|$ are extracted by fitting the polar angle distribution of the proton for the data samples with larger statistics, namely at $\sqrt{s}=$ 2232.4 and 2400.0 MeV and a combined sample at $\sqrt{s}$ = 3050.0, 3060.0 and 3080.0 MeV, respectively. The measured cross sections are in agreement with recent results from BaBar, improving the overall uncertainty by about 30\%. The $|G_{E}/G_{M}|$ ratios are close to unity and consistent with BaBar results in the same $q^{2}$ region, which indicates the data are consistent with the assumption that $|G_{E}|=|G_{M}|$ within uncertainties.Comment: 13 pages, 24 figure

Hepatitis C Virus Sensitizes Host Cells to TRAIL-Induced Apoptosis by Up-Regulating DR4 and DR5 via a MEK1-Dependent Pathway

BACKGROUND: Hepatitis C virus (HCV) is the leading cause of liver fibrosis, cirrhosis and hepatocellular carcinoma. It is believed that continuous liver cell apoptosis contributes to HCV pathogenesis. Recent studies have shown that HCV infection can sensitize host cells to TNF-related apoptosis-inducing ligand (TRAIL) induced apoptosis, but the mechanism by which HCV regulates the TRAIL pathway remains unclear. METHODS AND RESULTS: Using a sub-genomic replicon and full length virus, JFH-1, we demonstrate that HCV can sensitize host cells to TRAIL-induced apoptosis by up-regulating two TRAIL receptors, death receptor 4 (DR4) and death receptor 5 (DR5). Furthermore, the HCV replicon enhanced transcription of DR5 via Sp1, and the HCV-mediated up-regulation of DR4 and DR5 required MEK1 activity. HCV infection also stimulated the activity of MEK1, and the inhibition of MEK1 activity or the knockdown of MEK1 increased the replication of HCV. CONCLUSIONS: Our studies demonstrate that HCV replication sensitizes host cells to TRAIL-induced apoptosis by up-regulating DR4 and DR5 via a MEK1 dependent pathway. These findings may help to further understand the pathogenesis of HCV infection and provide a therapeutic target