Microscopic expressions for the thermodynamic temperature

We show that arbitrary phase space vector fields can be used to generate phase functions whose ensemble averages give the thermodynamic temperature. We describe conditions for the validity of these functions in periodic boundary systems and the Molecular Dynamics (MD) ensemble, and test them with a short-ranged potential MD simulation.Comment: 21 pages, 2 figures, Revtex. Submitted to Phys. Rev.

Retrospective Evaluations of Sequences: Testing the Predictions of a Memory-based Analysis

Retrospective evaluation (RE) of event sequences are known to be biased in various ways. The present paper presents a series of studies that examined the suggestion that the moments that are the most accessible in memory at the point of RE contribute to these biases. As predicted by this memory-based analysis, Experiment 1 showed that pleasantness ratings of word lists were biased by the presentation position of a negative item and by how easy the negative information was to retrieve. Experiment 2 ruled out the hypothesis that these findings were due to the dual nature of the task called upon. Experiment 3 further manipulated the memorability of the negative items—and corresponding changes in RE were as predicted. Finally, Experiment 4 extended the findings to more complex stimuli involving event narratives. Overall, the results suggest that assessments were adjusted based on the retrieval of the most readily available information

Orientational Ordering in Spatially Disordered Dipolar Systems

This letter addresses basic questions concerning ferroelectric order in positionally disordered dipolar materials. Three models distinguished by dipole vectors which have one, two or three components are studied by computer simulation. Randomly frozen and dynamically disordered media are considered. It is shown that ferroelectric order is possible in spatially random systems, but that its existence is very sensitive to the dipole vector dimensionality and the motion of the medium. A physical analysis of our results provides significant insight into the nature of ferroelectric transitions.Comment: 4 pages twocolumn LATEX style. 4 POSTSCRIPT figures available from [email protected]

Ferroelectric and Dipolar Glass Phases of Non-Crystalline Systems

In a recent letter [Phys. Rev. Lett. {\bf 75}, 2360 (1996)] we briefly discussed the existence and nature of ferroelectric order in positionally disordered dipolar materials. Here we report further results and give a complete description of our work. Simulations of randomly frozen and dynamically disordered dipolar soft spheres are used to study ferroelectric ordering in non-crystalline systems. We also give a physical interpretation of the simulation results in terms of short- and long-range interactions. Cases where the dipole moment has 1, 2, and 3 components (Ising, XY and XYZ models, respectively) are considered. It is found that the Ising model displays ferroelectric phases in frozen amorphous systems, while the XY and XYZ models form dipolar glass phases at low temperatures. In the dynamically disordered model the equations of motion are decoupled such that particle translation is completely independent of the dipolar forces. These systems spontaneously develop long-range ferroelectric order at nonzero temperature despite the absence of any fined-tuned short-range spatial correlations favoring dipolar order. Furthermore, since this is a nonequilibrium model we find that the paraelectric to ferroelectric transition depends on the particle mass. For the XY and XYZ models, the critical temperatures extrapolate to zero as the mass of the particle becomes infinite, whereas, for the Ising model the critical temperature is almost independent of mass and coincides with the ferroelectric transition found for the randomly frozen system at the same density. Thus in the infinite mass limit the results of the frozen amorphous systems are recovered.Comment: 25 pages (LATEX, no macros). 11 POSTSCRIPT figures enclosed. Submitted to Phisical Review E. Contact: [email protected]

Curvature-coupling dependence of membrane protein diffusion coefficients

We consider the lateral diffusion of a protein interacting with the curvature of the membrane. The interaction energy is minimized if the particle is at a membrane position with a certain curvature that agrees with the spontaneous curvature of the particle. We employ stochastic simulations that take into account both the thermal fluctuations of the membrane and the diffusive behavior of the particle. In this study we neglect the influence of the particle on the membrane dynamics, thus the membrane dynamics agrees with that of a freely fluctuating membrane. Overall, we find that this curvature-coupling substantially enhances the diffusion coefficient. We compare the ratio of the projected or measured diffusion coefficient and the free intramembrane diffusion coefficient, which is a parameter of the simulations, with analytical results that rely on several approximations. We find that the simulations always lead to a somewhat smaller diffusion coefficient than our analytical approach. A detailed study of the correlations of the forces acting on the particle indicates that the diffusing inclusion tries to follow favorable positions on the membrane, such that forces along the trajectory are on average smaller than they would be for random particle positions.Comment: 16 pages, 8 figure

Hot Streaks in Artistic, Cultural, and Scientific Careers

The hot streak, loosely defined as winning begets more winnings, highlights a specific period during which an individual's performance is substantially higher than her typical performance. While widely debated in sports, gambling, and financial markets over the past several decades, little is known if hot streaks apply to individual careers. Here, building on rich literature on lifecycle of creativity, we collected large-scale career histories of individual artists, movie directors and scientists, tracing the artworks, movies, and scientific publications they produced. We find that, across all three domains, hit works within a career show a high degree of temporal regularity, each career being characterized by bursts of high-impact works occurring in sequence. We demonstrate that these observations can be explained by a simple hot-streak model we developed, allowing us to probe quantitatively the hot streak phenomenon governing individual careers, which we find to be remarkably universal across diverse domains we analyzed: The hot streaks are ubiquitous yet unique across different careers. While the vast majority of individuals have at least one hot streak, hot streaks are most likely to occur only once. The hot streak emerges randomly within an individual's sequence of works, is temporally localized, and is unassociated with any detectable change in productivity. We show that, since works produced during hot streaks garner significantly more impact, the uncovered hot streaks fundamentally drives the collective impact of an individual, ignoring which leads us to systematically over- or under-estimate the future impact of a career. These results not only deepen our quantitative understanding of patterns governing individual ingenuity and success, they may also have implications for decisions and policies involving predicting and nurturing individuals with lasting impact

Examining a staging model for anorexia nervosa: empirical exploration of a four stage model of severity.

Background: An illness staging model for anorexia nervosa (AN) has received increasing attention, but assessing the merits of this concept is dependent on empirically examining a model in clinical samples. Building on preliminary findings regarding the reliability and validity of the Clinician Administered Staging Instrument for Anorexia Nervosa (CASIAN), the current study explores operationalising CASIAN severity scores into stages and assesses their relationship with other clinical features. Method: In women with DSM-IV-R AN and sub-threshold AN (all met AN criteria using DSM 5), receiver operating curve (ROC) analysis (n = 67) assessed the relationship between the sensitivity and specificity of each stage of the CASIAN. Thereafter chi-square and post-hoc adjusted residual analysis provided a preliminary assessment of the validity of the stages comparing the relationship between stage and treatment intensity and AN sub-types, and explored movement between stages after six months (Time 3) in a larger cohort (n = 171). Results: The CASIAN significantly distinguished between milder stages of illness (Stage 1 and 2) versus more severe stages of illness (Stages 3 and 4), and approached statistical significance in distinguishing each of the four stages from one other. CASIAN Stages were significantly associated with treatment modality and primary diagnosis, and CASIAN Stage at Time 1 was significantly associated with Stage at 6 month follow-up. Conclusions: Provisional support is provided for a staging model in AN. Larger studies with longer follow-up of cases are now needed to replicate and extend these findings and evaluate the overall utility of staging as well as optimal staging models

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

ALL-1/MLL1, a homologue of Drosophila TRITHORAX, modifies chromatin and is directly involved in infant acute leukaemia

Rearrangements of the ALL-1/MLL1 gene underlie the majority of infant acute leukaemias, as well as of therapy-related leukaemias developing in cancer patients treated with inhibitors of topoisomerase II, such as VP16 and doxorubicin. The rearrangements fuse ALL-1 to any of \u3e50 partner genes or to itself. Here, we describe the unique features of ALL-1-associated leukaemias, and recent progress in understanding molecular mechanisms involved in the activity of the ALL-1 protein and of its Drosophila homologue TRITHORAX