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Single photon source (SPS) is a key element for quantum spintronics and quantum photonics. It is known that several color centers such as silicon vacancy (VSi), divacancy (VSiVC), carbon antisite carbon vacancy pair (CSiVC), in silicon carbide (SiC) act as SPSs. Spin (S  =  3/2) in VSi in SiC can be manipulated even at room temperature and the intensity of its photoluminescence (PL) changes depending on the spin states (mS  =  ±3/2 or mS  =  ±1/2). Since PL from VSi is in the near infrared region (around 900 nm), it is expected that VSi is applied to quantum sensor especially for biological or medical applications. In this review, we discuss quantum sensing based on VSi in SiC. Also, we discuss energetic particle irradiation, especially proton beam writing (PBW), in which proton microbeams with MeV range are used, as a method to create VSi in SiC since PBW can create VSi in certain locations with micrometer accuracy and this is very useful to introduce VSi in electronic devices without the degradation of their electrical characteristics. [ABSTRACT FROM AUTHOR]

Aim. To study the profile of IL-6 in the early postoperative period after kidney transplantation and the factors that affect concentration of this cytokine. Methods and results. 28 kidney recipients were included in the study. It has been found that in most patients after surgery IL-6 was released, and the absence of such a reaction was a poor prognostic sign. Rate of increasing of the concentration and form of its curve within the first postoperative day depended on the length of preservation, warm ischemia time, type of donor, and differed in recipients with normal and delayed initial graft function. Conclusion. Further study of the role of circulating factors in kidney transplantation would improve patient outcomes.

Serial block-face scanning electron microscopy (SBEM) is quickly becoming an important imaging tool to explore three-dimensional biological structure across spatial scales. At probe-beam-electron energies of 2.0 keV or lower, the axial resolution should improve, because there is less primary electron penetration into the block face. More specifically, at these lower energies, the interaction volume is much smaller, and therefore, surface detail is more highly resolved. However, the backscattered electron yield for metal contrast agents and the backscattered electron detector sensitivity are both sub-optimal at these lower energies, thus negating the gain in axial resolution. We found that the application of a negative voltage (reversal potential) applied to a modified SBEM stage creates a tunable electric field at the sample. This field can be used to decrease the probe-beam-landing energy and, at the same time, alter the trajectory of the signal to increase the signal collected by the detector. With decelerated low landing-energy electrons, we observed that the probe-beam-electron-penetration depth was reduced to less than 30 nm in epoxy-embedded biological specimens. Concurrently, a large increase in recorded signal occurred due to the re-acceleration of BSEs in the bias field towards the objective pole piece where the detector is located. By tuning the bias field, we were able to manipulate the trajectories of the  primary and secondary electrons, enabling the spatial discrimination of these signals using an advanced ring-type BSE detector configuration or a standard monolithic BSE detector coupled with a blocking aperture.

The last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyber infrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remains a challenge because of issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate and/or hide these barriers to entry for computational neuroscientists. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines. It handles the running of jobs and data management and retrieval. This paper shares the early experiences in bringing up this gateway and describes the software architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. We also look at parallel scaling of some publicly available neuronal models and analyze the recent usage data of the neuroscience gateway.

The breadth of information resources available to researchers on the Internet continues to expand, particularly in light of recently implemented data-sharing policies required by funding agencies. However, the nature of dense, multifaceted neuroscience data and the design of contemporary search engine systems makes efficient, reliable and relevant discovery of such information a significant challenge. This challenge is specifically pertinent for online databases, whose dynamic content is 'hidden' from search engines. The Neuroscience Information Framework (NIF; http://www.neuinfo.org) was funded by the NIH Blueprint for Neuroscience Research to address the problem of finding and utilizing neuroscience-relevant resources such as software tools, data sets, experimental animals and antibodies across the Internet. From the outset, NIF sought to provide an accounting of available resources, whereas developing technical solutions to finding, accessing and utilizing them. The curators therefore, are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping the contents current. In the initial phases of the project, all aspects of the registration and curation processes were manual. However, as the number of resources grew, manual curation became impractical. This report describes our experiences and successes with developing automated resource discovery and semiautomated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. We also describe the DISCO framework, a suite of automated web services that significantly reduce manual curation efforts to periodically check for resource updates. Lastly, we discuss DOMEO, a semi-automated annotation tool that improves the discovery and curation of resources that are not necessarily website-based (i.e. reagents, software tools). Although the ultimate goal of automation was to reduce the workload of the curators, it has resulted in valuable analytic by-products that address accessibility, use and citation of resources that can now be shared with resource owners and the larger scientific community. DATABASE URL: http://neuinfo.org.

The number of available neuroscience resources (databases, tools, materials, and networks) available via the Web continues to expand, particularly in light of newly implemented data sharing policies required by funding agencies and journals. However, the nature of dense, multifaceted neuroscience data and the design of classic search engine systems make efficient, reliable, and relevant discovery of such resources a significant challenge. This challenge is especially pertinent for online databases, whose dynamic content is largely opaque to contemporary search engines. The Neuroscience Information Framework was initiated to address this problem of finding and utilizing neuroscience-relevant resources. Since its first production release in 2008, NIF has been surveying the resource landscape for the neurosciences, identifying relevant resources and working to make them easily discoverable by the neuroscience community. In this chapter, we provide a survey of the resource landscape for neuroscience: what types of resources are available, how many there are, what they contain, and most importantly, ways in which these resources can be utilized by the research community to advance neuroscience research., (Copyright © 2012 Elsevier Inc. All rights reserved.)

We report on progress of employing the Kepler workflow engine to prototype "end-to-end" application integration workflows that concern data coming from microscopes deployed at the National Center for Microscopy Imaging Research (NCMIR). This system is built upon the mature code base of the Cell Centered Database (CCDB) and integrated rule-oriented data system (IRODS) for distributed storage. It provides integration with external projects such as the Whole Brain Catalog (WBC) and Neuroscience Information Framework (NIF), which benefit from NCMIR data. We also report on specific workflows which spawn from main workflows and perform data fusion and orchestration of Web services specific for the NIF project. This "Brain data flow" presents a user with categorized information about sources that have information on various brain regions.

Objectives: Women with a sonographic short cervix in the mid-trimester are at increased risk for preterm delivery. This study was undertaken to determine the efficacy and safety of using micronized vaginal progesterone gel to reduce the risk of preterm birth and associated neonatal complications in women with a sonographic short cervix., Methods: This was a multicenter, randomized, double-blind, placebo-controlled trial that enrolled asymptomatic women with a singleton pregnancy and a sonographic short cervix (10-20 mm) at 19 + 0 to 23 + 6 weeks of gestation. Women were allocated randomly to receive vaginal progesterone gel or placebo daily starting from 20 to 23 + 6 weeks until 36 + 6 weeks, rupture of membranes or delivery, whichever occurred first. Randomization sequence was stratified by center and history of a previous preterm birth. The primary endpoint was preterm birth before 33 weeks of gestation. Analysis was by intention to treat., Results: Of 465 women randomized, seven were lost to follow-up and 458 (vaginal progesterone gel, n=235; placebo, n=223) were included in the analysis. Women allocated to receive vaginal progesterone had a lower rate of preterm birth before 33 weeks than did those allocated to placebo (8.9% (n=21) vs 16.1% (n=36); relative risk (RR), 0.55; 95% CI, 0.33-0.92; P=0.02). The effect remained significant after adjustment for covariables (adjusted RR, 0.52; 95% CI, 0.31-0.91; P=0.02). Vaginal progesterone was also associated with a significant reduction in the rate of preterm birth before 28 weeks (5.1% vs 10.3%; RR, 0.50; 95% CI, 0.25-0.97; P=0.04) and 35 weeks (14.5% vs 23.3%; RR, 0.62; 95% CI, 0.42-0.92; P=0.02), respiratory distress syndrome (3.0% vs 7.6%; RR, 0.39; 95% CI, 0.17-0.92; P=0.03), any neonatal morbidity or mortality event (7.7% vs 13.5%; RR, 0.57; 95% CI, 0.33-0.99; P=0.04) and birth weight < 1500 g (6.4% (15/234) vs 13.6% (30/220); RR, 0.47; 95% CI, 0.26-0.85; P=0.01). There were no differences in the incidence of treatment-related adverse events between the groups., Conclusions: The administration of vaginal progesterone gel to women with a sonographic short cervix in the mid-trimester is associated with a 45% reduction in the rate of preterm birth before 33 weeks of gestation and with improved neonatal outcome., (Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.)

The paper presents the results of the study of the sequences of bifurcation leading to the synchronization and amplitude death in a system of two dissipatively coupled self-sustained oscillators with inertial nonlinearity. Two types of synchronizations tongues have been identified. In one of them phase locking regions exist where the synchronization is achieved by the saddle-node bifurcation and regions where the transition to synchronization leads through Neimark-Sacker bifurcation. In the second type of the tongues there are only phase locking regions. It has been shown that for a weak non-identity of the system parameters, the first type tongues merge together. The transition between the synchronization tongues can occur without bifurcations, i.e., transition between the synchronized regimes with different periods of oscillations can occur gradually.

We consider phase multistability and phase synchronization phenomena in a chain of period-doubling oscillators. The synchronization in arrays of diffusively coupled self-sustained oscillators manifests itself as rotating wave regimes, which are characterized by equal amplitudes and phases in every site which are shifted by a constant value. The value of the phase shift is preserved while the shape of motion becomes more complex through a period-doubling cascade. The number of coexisting attractors increases drastically after the transition from period-one to period-two oscillations and then after every following period-doubling bifurcation. In the chaotic region, we observe a number of phase-synchronized modes with instantaneous phases locked in different values. The loss of phase synchronization with decreasing coupling is accompanied by intermittency between several synchronous regimes.

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

Imagination is the critical point in developing of realistic intelligence (AI) systems. One way to approach imagination would be simulation of its properties and operations. We developed two models "Brain Network Hierarchy of Languages," and "Semantical Holographic Calculus" and simulation system ScriptWriter that emulate the process of imagination through an automatic animation of English texts. The purpose of this paper is to demonstrate the model and present "ScriptWriter" system http://nvo.sdsc.edu/NVO/JCSG/get&#95;SRB&#95;mime&#95;file2.cgi//home/tamara.sdsc/test/demo.zip?F=/home/tamara.sdsc/test/demo.zip&M=application/x-gtar for simulation of the imagination.

The overarching goal of the NIF (Neuroscience Information Framework) project is to be a one-stop-shop for Neuroscience. This paper provides a technical overview of how the system is designed. The technical goal of the first version of the NIF system was to develop an information system that a neuroscientist can use to locate relevant information from a wide variety of information sources by simple keyword queries. Although the user would provide only keywords to retrieve information, the NIF system is designed to treat them as concepts whose meanings are interpreted by the system. Thus, a search for term should find a record containing synonyms of the term. The system is targeted to find information from web pages, publications, databases, web sites built upon databases, XML documents and any other modality in which such information may be published. We have designed a system to achieve this functionality. A central element in the system is an ontology called NIFSTD (for NIF Standard) constructed by amalgamating a number of known and newly developed ontologies. NIFSTD is used by our ontology management module, called OntoQuest to perform ontology-based search over data sources. The NIF architecture currently provides three different mechanisms for searching heterogeneous data sources including relational databases, web sites, XML documents and full text of publications. Version 1.0 of the NIF system is currently in beta test and may be accessed through http://nif.nih.gov.

Neutral pion transverse momentum spectra were measured in p+C and p+Pb collisions at sqrt[S{NN}]=17.4 GeV at midrapidity (2.3 less than or approximately equal eta{lab} less than or approximately equal 3.0) over the range 0.7 less than or approximately equal p{T} less than or approximately equal 3.5 GeV/c. The spectra are compared to pi{0} spectra measured in Pb+Pb collisions at sqrt[S{NN}]=17.3 GeV in the same experiment. For a wide range of Pb+Pb centralities (N{part} less than or approximately equal 300), the yield of pi{0}'s with p{T} greater than or approximately equal 2 GeV/c is larger than or consistent with the p+C or p+Pb yields scaled with the number of nucleon-nucleon collisions (N{coll}), while for central Pb+Pb collisions with N{part}greater than or approximately equal 350, the pi{0} yield is suppressed.

Prediction of peptides binding to HLA (human leukocyte antigen) finds application in peptide vaccine design. A number of statistical and structural models have been developed in recent years for HLA binding peptide prediction. However, a Bayesian Network (BNT) model is not available. In this study we describe a BNT model for HLA-A2 binding peptide prediction. It has been demonstrated that the BNT model allows up to 99 % accurate identification of the HLA-A2 binding peptides and provides similar prediction accuracy compared to HMM (Hidden Markov Model) and ANN (Artificial Neural Network). At the same time, it has been shown that the BNT has that advantage that it allows more accurate performance for smaller sets of empirical data compared to the HMM and the ANN methods. When the size of the training set has been reduced to 40% from the original data, the identification of the HLA-A2 binding peptides by the BNT, ANN and HMM methods produced ARoc (area under receiver operating characteristic) values 0.88, 0.85, 0.85 respectively. The results of the work demonstrate certain advantages of using the Bayesian Networks in predicting the HLA binding peptides using smaller datasets.

We use an index of chaotic synchronization based on the averaged coherence function for the quantitative analysis of the process of the complete synchronization loss in unidirectionally coupled oscillators and maps. We demonstrate that this value manifests different stages of the synchronization breaking. It is invariant to time delay and insensitive to small noise and distortions, which can influence the accessible signals at measurements. Peculiarities of the synchronization destruction in maps and oscillators are investigated.

Two-particle correlations of direct photons were measured in central 208Pb+208Pb collisions at 158A GeV. The invariant interferometric radii were extracted for 100

Based on an information theory approach we suggest a quantitative characteristic for evaluating the degree of chaotic synchronization. The proposed characteristic is tested for the cases of complete and phase synchronization of chaos. It is shown that this characteristic is stable with respect to the influence of small noise and nonlinear signal distortion.

We investigate phenomena of multistability and complete chaos synchronization in coupled Hénon maps, which is an invertible system. Multiparametric analysis of a selected family of periodic orbits for coupled Henon maps shows that a single bifurcational mechanism describes both a loss of chaos synchronization and multistability formation. The process of bubbling transition and riddle basins, and the multistability formation in invertible systems are described in detail.

Three-particle correlations have been measured for identified pi(-) from central 158A GeV Pb+Pb collisions by the WA98 experiment at CERN. A substantial contribution of the genuine three-body correlation has been found as expected for a mainly chaotic and symmetric source.