Superconductivity as a probe of magnetic switching and ferromagnetic stability in Nb/Ni multilayers

The temperature and field dependences of the AC and DC magnetic moment of superconducting and ferromagnetic Nb/Ni multilayers were measured using a SQUID magnetometer with magnetic field applied parallel to the multilayer plane. Periodic kinks in the superconducting upper critical field are evidence for nucleation of a hierarchy of Abrikosov vortex lattices aligned parallel to the multilayer. Small cusps in the low-field, isothermal DC magnetization are evidence that supercurrents are sensitive to extremely small changes in the Ni layer magnetization. Smooth ferromagnetic hysteresis is observed in the normal state, but is supplanted below the superconducting transition by two reproducible discontinuities that indicate magnetic switching of the Ni layers is tightly coupled to the supercurrents. The discontinuities are attributed to the non-dipole character of the moment near switching fields and, therefore, cannot be analyzed by standard magnetometer software. Ferromagnetic resonance spectra were measured in parallel and perpendicular DC magnetic fields at room temperature and 4.2 K, and resulting data suggest that Ni layers interact magnetically in the superconducting state

Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics\ud

Objective: To investigate the impact of upper extremity deficit in subjects with tetraplegia.\ud \ud Setting: The United Kingdom and The Netherlands.\ud \ud Study design: Survey among the members of the Dutch and UK Spinal Cord Injury (SCI) Associations.\ud \ud Main outcome parameter: Indication of expected improvement in quality of life (QOL) on a 5-point scale in relation to improvement in hand function and seven other SCI-related impairments.\ud \ud Results: In all, 565 subjects with tetraplegia returned the questionnaire (overall response of 42%). Results in the Dutch and the UK group were comparable. A total of 77% of the tetraplegics expected an important or very important improvement in QOL if their hand function improved. This is comparable to their expectations with regard to improvement in bladder and bowel function. All other items were scored lower.\ud \ud Conclusion: This is the first study in which the impact of upper extremity impairment has been assessed in a large sample of tetraplegic subjects and compared to other SCI-related impairments that have a major impact on the life of subjects with SCI. The present study indicates a high impact as well as a high priority for improvement in hand function in tetraplegics.\ud \u

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

What are the living conditions and health status of those who don't report their migration status? a population-based study in Chile

BACKGROUND: Undocumented immigrants are likely to be missing from population databases, making it impossible to identify an accurate sampling frame in migration research. No population-based data has been collected in Chile regarding the living conditions and health status of undocumented immigrants. However, the CASEN survey (Caracterizacion Socio- Economica Nacional) asked about migration status in Chile for the first time in 2006 and provides an opportunity to set the base for future analysis of available migration data. We explored the living conditions and health of self-reported immigrants and respondents who preferred not to report their migration status in this survey. METHODS: Cross-sectional secondary analysis of CASEN survey in Chile in 2006. Outcomes: any disability, illness/accident, hospitalization/surgery, cancer/chronic condition (all binary variables); and the number of medical/emergency attentions received (count variables). Covariates: Demographics (age, sex, marital status, urban/rural, ethnicity), socioeconomic status (education level, employment status and household income), and material standard of living (overcrowding, sanitation, housing quality). Weighted regression models were estimated for each health outcome, crude and adjusted by sets of covariates, in STATA 10.0. RESULTS: About 1% of the total sample reported being immigrants and 0.7% preferred not to report their migration status (Migration Status - Missing Values; MS-MV). The MS-MV lived in more deprived conditions and reported a higher rate of health problems than immigrants. Some gender differences were observed by health status among immigrants and the MS-MV but they were not statistically significant. Regressions indicated that age, sex, SES and material factors consistently affected MS-MVs’ chance of presenting poor health and these patterns were different to those found among immigrants. Great heterogeneity in both the MS-MV and the immigrants, as indicated by wide confidence intervals, prevented the identification of other significantly associated covariates. CONCLUSION: This is the first study to look at the living conditions and health of those that preferred not to respond their migration status in Chile. Respondents that do not report their migration status are vulnerable to poor health and may represent undocumented immigrants. Surveys that fail to identify these people are likely to misrepresent the experiences of immigrants and further quantitative and qualitative research is urgently required

Creationism and Intelligent Design

Until recently, little attention has been paid in the school classroom to creationism and almost none to intelligent design. However, creationism and intelligent design appear to be on the increase and there are indications that there are more countries in which schools are becoming battlegrounds over them. I begin by examining whether creationism and intelligent design are controversial issues, drawing on Robert Dearden’s epistemic criterion of the controversial and more recent responses to and defences of this. I then examine whether the notion of ‘worldviews’ in the context of creationism is a useful one by considering the film March of the Penguins. I conclude that the ‘worldviews’ perspective on creationism is useful for two reasons: first, it indicates the difficulty of using the criterion of reason to decide whether an issue is controversial or not; secondly, it suggests that standard ways of addressing the diversity of student views in a science classroom may be inadequate. I close by examining the implications of this view for teaching in science lessons and elsewhere, for example in religious education lessons and at primary level where subject divisions cannot be made in so clear-cut a manner

A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin

The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5–Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response

CAR-T cell. the long and winding road to solid tumors

Adoptive cell therapy of solid tumors with reprogrammed T cells can be considered the "next generation" of cancer hallmarks. CAR-T cells fail to be as effective as in liquid tumors for the inability to reach and survive in the microenvironment surrounding the neoplastic foci. The intricate net of cross-interactions occurring between tumor components, stromal and immune cells leads to an ineffective anergic status favoring the evasion from the host's defenses. Our goal is hereby to trace the road imposed by solid tumors to CAR-T cells, highlighting pitfalls and strategies to be developed and refined to possibly overcome these hurdles

Dynamical R-parity Breaking at the LHC

In a class of extensions of the minimal supersymmetric standard model with (B-L)/left-right symmetry that explains the neutrino masses, breaking R-parity symmetry is an essential and dynamical requirement for successful gauge symmetry breaking. Two consequences of these models are: (i) a new kind of R-parity breaking interaction that protects proton stability but adds new contributions to neutrinoless double beta decay and (ii) an upper bound on the extra gauge and parity symmetry breaking scale which is within the large hadron collider (LHC) energy range. We point out that an important prediction of such theories is a potentially large mixing between the right-handed charged lepton ($e^c$) and the superpartner of the right-handed gauge boson ($\widetilde W_R^+$), which leads to a brand new class of R-parity violating interactions of type $\widetilde{\mu^c}^\dagger\nu_\mu^c e^c$ and \widetilde{d^c}^\dagger\u^c e^c. We analyze the relevant constraints on the sparticle mass spectrum and the LHC signatures for the case with smuon/stau NLSP and gravitino LSP. We note the "smoking gun" signals for such models to be lepton flavor/number violating processes: $pp\to \mu^\pm\mu^\pm e^+e^-jj$ (or $\tau^\pm\tau^\pm e^+e^-jj$) and $pp\to\mu^\pm e^\pm b \bar{b} jj$ (or $\tau^\pm e^\pm b \bar{b} jj$) without significant missing energy. The predicted multi-lepton final states and the flavor structure make the model be distinguishable even in the early running of the LHC.Comment: 30 pages, 13 figures, 6 tables, reference adde

High-performance predictor for critical unstable generators based on scalable parallelized neural networks

A high-performance predictor for critical unstable generators (CUGs) of power systems is presented in this paper. The predictor is driven by the MapReduce based parallelized neural networks. Specifically, a group of back propagation neural networks (BPNNs), fed by massive response trajectories data, are efficiently organized and concurrently trained in Hadoop to identify dynamic behaviour of individual generator. Rather than simply classifying global stability of power systems, the presented approach is able to distinguish unstable generators accurately with a few cycles of synchronized trajectories after fault clearing, enabling more in-depth emergency awareness based on wide-area implementation. In addition, the technique is of rich scalability due to Hadoop framework, which can be deployed in the control centers as a high-performance computing infrastructure for real-time instability alert. Numerical examples are studied using NPCC 48 machines test system and a realistic power system of China

Matched sizes of activating and inhibitory receptor/ligand pairs are required for optimal signal integration by human Natural Killer cells

It has been suggested that receptor-ligand complexes segregate or co-localise within immune synapses according to their size, and this is important for receptor signaling. Here, we set out to test the importance of receptor-ligand complex dimensions for immune surveillance of target cells by human Natural Killer (NK) cells. NK cell activation is regulated by integrating signals from activating receptors, such as NKG2D, and inhibitory receptors, such as KIR2DL1. Elongating the NKG2D ligand MICA reduced its ability to trigger NK cell activation. Conversely, elongation of KIR2DL1 ligand HLA-C reduced its ability to inhibit NK cells. Whereas normal-sized HLA-C was most effective at inhibiting activation by normal-length MICA, only elongated HLA-C could inhibit activation by elongated MICA. Moreover, HLA-C and MICA that were matched in size co-localised, whereas HLA-C and MICA that were different in size were segregated. These results demonstrate that receptor-ligand dimensions are important in NK cell recognition, and suggest that optimal integration of activating and inhibitory receptor signals requires the receptor-ligand complexes to have similar dimensions