Fiber Bragg Grating Sensor to Monitor Stress Kinetics in Drying Process of Commercial Latex Paints

In this paper, we report a study about the application of packaged fiber Bragg gratings used as strain sensors to monitor the stress kinetics during the drying process of commercial latex paints. Three stages of drying with distinct mechanical deformation and temporal behaviors were identified for the samples, with mechanical deformation from 15 μm to 21 μm in the longitudinal film dimension on time intervals from 370 to 600 minutes. Drying time tests based on human sense technique described by the Brazilian Technical Standards NBR 9558 were also done. The results obtained shows that human sense technique has a limited perception of the drying process and that the optical measurement system proposed can be used to characterize correctly the dry-through stage of paint. The influence of solvent (water) addition in the drying process was also investigated. The paint was diluted with four parts paint and one part water (80% paint), and one part paint and one part water (50% paint). It was observed that the increase of the water ratio mixed into the paint decreases both the mechanical deformation magnitude and the paint dry-through time. Contraction of 5.2 μm and 10.4 μm were measured for concentrations of 50% and 80% of paint in the mixture, respectively. For both diluted paints the dry-through time was approximately 170 minutes less than undiluted paint. The optical technique proposed in this work can contribute to the development of new standards to specify the drying time of paint coatings

Towards absolute scales of radii and masses of open clusters

Aims: In this paper we derive tidal radii and masses of open clusters in the nearest kiloparsecs around the Sun. Methods: For each cluster, the mass is estimated from tidal radii determined from a fitting of three-parametric King's profiles to the observed integrated density distribution. Different samples of members are investigated. Results: For 236 open clusters, all contained in the catalogue ASCC-2.5, we obtain core and tidal radii, as well as tidal masses. The distributions of the core and tidal radii peak at about 1.5 pc and 7 - 10 pc, respectively. A typical relative error of the core radius lies between 15% and 50%, whereas, for the majority of clusters, the tidal radius was determined with a relative accuracy better than 20%. Most of the clusters have tidal masses between 50 and 1000 $m_\odot$, and for about half of the clusters, the masses were obtained with a relative error better than 50%.Comment: 11 pages, 7 figures, accepted for publication in Astronomy & Astrophysic

Universality, limits and predictability of gold-medal performances at the Olympic Games

Inspired by the Games held in ancient Greece, modern Olympics represent the world's largest pageant of athletic skill and competitive spirit. Performances of athletes at the Olympic Games mirror, since 1896, human potentialities in sports, and thus provide an optimal source of information for studying the evolution of sport achievements and predicting the limits that athletes can reach. Unfortunately, the models introduced so far for the description of athlete performances at the Olympics are either sophisticated or unrealistic, and more importantly, do not provide a unified theory for sport performances. Here, we address this issue by showing that relative performance improvements of medal winners at the Olympics are normally distributed, implying that the evolution of performance values can be described in good approximation as an exponential approach to an a priori unknown limiting performance value. This law holds for all specialties in athletics-including running, jumping, and throwing-and swimming. We present a self-consistent method, based on normality hypothesis testing, able to predict limiting performance values in all specialties. We further quantify the most likely years in which athletes will breach challenging performance walls in running, jumping, throwing, and swimming events, as well as the probability that new world records will be established at the next edition of the Olympic Games.Comment: 8 pages, 3 figures, 1 table. Supporting information files and data are available at filrad.homelinux.or

Using Cepheids to determine the galactic abundance gradient I. The solar neighbourhood

A number of studies of abundance gradients in the galactic disk have been performed in recent years. The results obtained are rather disparate: from no detectable gradient to a rather significant slope of about -0.1 dex kpc -1. The present study concerns the abundance gradient based on the spectroscopic analysis of a sample of classical Cepheids. These stars enable one to obtain reliable abundances of a variety of chemical elements. Additionally, they have well determined distances which allow an accurate determination of abundance distributions in the galactic disc. Using 236 high resolution spectra of 77 galactic Cepheids, the radial elemental distribution in the galactic disc between galactocentric distances in the range 6-11 kpc has been investigated. Gradients for 25 chemical elements (from carbon to gadolinium) are derived...Comment: 28 pages, 14 postscript figures, LaTeX, uses Astronomy and Astrophysics macro aa.cls, graphicx package, to be published in Astronomy and Astrophysics (2002) also available at http://www.iagusp.usp.br/~maciel/index.htm

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

Autophagy in antigen-presenting cells results in presentation of citrullinated peptides to CD4 T cells

Citrullinated peptide presentation by DCs and macrophages is constitutive, whereas B cells present modified peptides only with autophagy induced by serum starvation or BCR ligation

The Nordic back pain subpopulation program: Can low back pain patterns be predicted from the first consultation with a chiropractor? A longitudinal pilot study

<p>Abstract</p> <p>Background</p> <p>It is widely believed that non-specific low back pain (LBP) consists of a number of subgroups which should be identified in order to improve treatment effects. In order to identify subgroups, patient characteristics that relate to different outcomes are searched for. However, LBP is often fluctuating or recurring rather than clearly limited in time. Therefore it would be relevant to consider outcome after completed treatment from a longitudinal perspective (describing "course patterns") instead of defining it from an arbitrarily selected end-point.</p> <p>Aims</p> <p>The objectives of this pilot study were to investigate the interobserver reliability of a diagnostic classification system and to evaluate whether diagnostic classes or other baseline characteristics are associated with the LBP course pattern over a period of 18 weeks.</p> <p>Methods</p> <p>Patients visiting one of 7 chiropractors because of LBP were classified according to a diagnostic classification system, which includes end-range loading, SI-joint pain provocation tests, neurological examination and tests for muscle tenderness and abnormal nerve tension. In addition, age, gender, duration of pain and presence of leg pain were registered in the patient's file. By weekly SMS-messages on their mobile phones, patients were asked how many days they had LBP the preceding week, and these answers were transformed into pain course patterns and the total number of LBP days.</p> <p>Results</p> <p>A total of 110 patients were included and 76 (69%) completed follow-up. Thirty-five patients were examined by two chiropractors. The agreement regarding diagnostic classes was 83% (95% CI: 70 - 96). The diagnostic classes were associated with the pain course patterns and number of LBP days. Patients with disc pain had the highest number of LBP days and patients with muscular pain reported the fewest (35 vs. 12 days, p < 0.01). Men had better outcome than women (17 vs. 29 days, p < 0.01) and patients without leg pain tended to have fewer LBP days than those with leg pain (21 vs.31 days, p = 0.06). Duration of LBP at the first visit was not associated with outcome.</p> <p>Conclusions</p> <p>The study indicated that there is a clinically meaningful relationship between diagnostic classes and the course of LBP. This should be evaluated in more depth.</p

Machine learning for comprehensive forecasting of Alzheimer's Disease progression

Most approaches to machine learning from electronic health data can only predict a single endpoint. The ability to simultaneously simulate dozens of patient characteristics is a crucial step towards personalized medicine for Alzheimer’s Disease. Here, we use an unsupervised machine learning model called a Conditional Restricted Boltzmann Machine (CRBM) to simulate detailed patient trajectories. We use data comprising 18-month trajectories of 44 clinical variables from 1909 patients with Mild Cognitive Impairment or Alzheimer’s Disease to train a model for personalized forecasting of disease progression. We simulate synthetic patient data including the evolution of each sub-component of cognitive exams, laboratory tests, and their associations with baseline clinical characteristics. Synthetic patient data generated by the CRBM accurately reflect the means, standard deviations, and correlations of each variable over time to the extent that synthetic data cannot be distinguished from actual data by a logistic regression. Moreover, our unsupervised model predicts changes in total ADAS-Cog scores with the same accuracy as specifically trained supervised models, additionally capturing the correlation structure in the components of ADAS-Cog, and identifies sub-components associated with word recall as predictive of progression

Measurement of the Branching Fraction for B- --> D0 K*-

We present a measurement of the branching fraction for the decay B- --> D0 K*- using a sample of approximately 86 million BBbar pairs collected by the BaBar detector from e+e- collisions near the Y(4S) resonance. The D0 is detected through its decays to K- pi+, K- pi+ pi0 and K- pi+ pi- pi+, and the K*- through its decay to K0S pi-. We measure the branching fraction to be B.F.(B- --> D0 K*-)= (6.3 +/- 0.7(stat.) +/- 0.5(syst.)) x 10^{-4}.Comment: 7 pages, 1 postscript figure, submitted to Phys. Rev. D (Rapid Communications