Information methods for predicting risk and outcome of stroke

Stroke is a major cause of disability and mortality in most economically developed countries. It is the second leading cause of death worldwide (after cancer and heart disease) [55.1, 2] and a major cause of disability in adults in developed countries [55.3]. Personalized modeling is an emerging effective computational approach, which has been applied to various disciplines, such as in personalized drug design, ecology, business, and crime prevention; it has recently become more prominent in biomedical applications. Biomedical data on stroke risk factors and prognostic data are available in a large volume, but the data are complex and often difficult to apply to a specific person. Individualizing stroke risk prediction and prognosis will allow patients to focus on risk factors specific to them, thereby reducing their stroke risk and managing stroke outcomes more effectively. This chapter reviews various methods–conventional statistical methods and computational intelligent modeling methods for predicting risk and outcome of stroke

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage

Reduced magnetic braking and the magnetic capture model for the formation of ultra-compact binaries

A binary in which a slightly evolved star starts mass transfer to a neutron star can evolve towards ultra-short orbital periods under the influence of magnetic braking. This is called magnetic capture. In a previous paper we showed that ultra-short periods are only reached for an extremely small range of initial binary parameters, in particular orbital period and donor mass. Our conclusion was based on one specific choice for the law of magnetic braking, and for the loss of mass and angular momentum during mass transfer. In this paper we show that for less efficient magnetic braking it is impossible to evolve to ultra-short periods, independent of the amount of mass and associated angular momentum lost from the binary.Comment: 7 pages, 7 figures, accepted for publication in Astronomy and Astrophysics. See http://www.astro.uu.nl/~sluys/PhD

Detection of a period decrease in NN Ser with ULTRACAM: evidence for strong magnetic braking or an unseen companion?

We present results of high time resolution photometry of the eclipsing pre-cataclysmic variable NN Ser. We observed 13 primary eclipses of NN Ser using the high-speed CCD camera ULTRACAM and derived times of mid-eclipse, from fitting of light curve models, with uncertainties as low as 0.06 s. The observed rates of period change appear difficult to reconcile with any models of orbital period change. If the observed period change reflects an angular momentum loss, the average loss rate is consistent with the loss rates (via magnetic stellar wind braking) used in standard models of close binary evolution, which were derived from observations of much more massive cool stars. Observations of low-mass stars such as NN Ser's secondary predict rates of ~100 times lower than we observe. We show that magnetic activity-driven changes in the quadrupole moment of the secondary star (Applegate, 1992) fail to explain the period change by an order of magnitude on energetic grounds, but that a light travel time effect caused by the presence of a third body in a long (~ decades) orbit around the binary could account for the observed changes in the timings of NN Ser's mid-eclipses. We conclude that we have either observed a genuine angular momentum loss for NN Ser, in which case our observations pose serious difficulties for the theory of close binary evolution, or we have detected a previously unseen low-mass companion to the binary.Comment: 10 pages, 6 figures. Accepted for publication in MNRA

Reducing recurrent stroke: methodology of the motivational interviewing in stroke (MIST) randomized clinical trial

Recurrent stroke is prevalent in both developed and developing countries, contributing significantly to disability and death. Recurrent stroke rates can be reduced by adequate risk factor management. However, adherence to prescribed medications and lifestyle changes recommended by physicians at discharge after stroke is poor, leading to a large number of preventable recurrent strokes. Using behavior change methods such as Motivational Interviewing early after stroke occurrence has the potential to prevent recurrent stroke

Dynamical model for spindown of solar-type stars

After their formation, stars slow down their rotation rates by the removal of angular momentum from their surfaces, e.g., via stellar winds. Explaining how this rotation of solar-type stars evolves in time is currently an interesting but difficult problem in astrophysics. Despite the complexity of the processes involved, a traditional model, where the removal of angular momentum by magnetic fields is prescribed, has provided a useful framework to understand observational relations between stellar rotation, age, and magnetic field strength. Here, for the first time, a spindown model is proposed where loss of angular momentum by magnetic fields evolves dynamically, instead of being prescibed kinematically. To this end, we evolve the stellar rotation and magnetic field simultaneously over stellar evolution time by extending our previous work on a dynamo model which incorporates nonlinear feedback mechanisms on rotation and magnetic fields. We show that our extended model reproduces key observations and is capable of explaining the presence of the two branches of (fast and slow rotating) stars which have different relations between rotation rate Ω versus time (age), magnetic field strength $| B|$ versus rotation rate, and frequency of magnetic field ${\omega }_{\mathrm{cyc}}$ versus rotation rate. For fast rotating stars we find that: (i) there is an exponential spindown ${\rm{\Omega }}\propto {e}^{-1.35t}$, with t measured in Gyr; (ii) magnetic activity saturates for higher rotation rate; (iii) ${\omega }_{\mathrm{cyc}}\propto {{\rm{\Omega }}}^{0.83}$. For slow rotating stars we find: (i) a power-law spindown ${\rm{\Omega }}\propto {t}^{-0.52}$; (ii) that magnetic activity scales roughly linearly with rotation rate; (iii) ${\omega }_{\mathrm{cyc}}\propto {{\rm{\Omega }}}^{1.16}$. The results obtained from our investigations are in good agreement with observations. The Vaughan–Preston gap is consistently explained in our model by the shortest spindown timescale in this transition from fast to slow rotators. Our results highlight the importance of self-regulation of magnetic fields and rotation by direct and indirect interactions involving nonlinear feedback in stellar evolution

2018 Robotic Scene Segmentation Challenge

In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models. However, the limited background variation and simple motion rendered the dataset uninformative in learning about which techniques would be suitable for segmentation in real surgery. In 2017, at the same workshop in Quebec we introduced the robotic instrument segmentation dataset with 10 teams participating in the challenge to perform binary, articulating parts and type segmentation of da Vinci instruments. This challenge included realistic instrument motion and more complex porcine tissue as background and was widely addressed with modifications on U-Nets and other popular CNN architectures. In 2018 we added to the complexity by introducing a set of anatomical objects and medical devices to the segmented classes. To avoid over-complicating the challenge, we continued with porcine data which is dramatically simpler than human tissue due to the lack of fatty tissue occluding many organs

Compulsive buying and branding phenomena

The purpose of this paper was to explore the impact of brand variables such as brand awareness, brand loyalty, brand attachment, and perceived brand quality on compulsive buying behavior. A self-administered questionnaire, containing demographic items and items related to compulsive buying, brand awareness, brand loyalty, brand attachment and perceived quality, was used to collect data. Participants were 269 US university students at a large mid-western university (138 men, 131 women; mean age = 21.96). Data were analyzed using descriptive statistics, t-test and MANOVA/ANOVA. Reliability of all scales was acceptable. In the current study, 18% of the participants were classified as compulsive buyers. Women showed higher compulsive buying tendency than men. Participants with greater compulsive buying tendency scored higher on brand attachment and brand loyalty and lower on brand awareness; there was no difference in scores on perceived brand quality. Results support that brand variables such as brand awareness, brand loyalty, and brand attachment are related to compulsive buying behavior. New perceptions and implications for both academicians and practitioners are provided

Biomonitoring of complex occupational exposures to carcinogens: The case of sewage workers in Paris

<p>Abstract</p> <p>Background</p> <p>Sewage workers provide an essential service in the protection of public and environmental health. However, they are exposed to varied mixtures of chemicals; some are known or suspected to be genotoxics or carcinogens. Thus, trying to relate adverse outcomes to single toxicant is inappropriate. We aim to investigate if sewage workers are at increased carcinogenic risk as evaluated by biomarkers of exposure and early biological effects.</p> <p>Methods/design</p> <p>This cross sectional study will compare exposed sewage workers to non-exposed office workers. Both are voluntaries from Paris municipality, males, aged (20–60) years, non-smokers since at least six months, with no history of chronic or recent illness, and have similar socioeconomic status. After at least 3 days of consecutive work, blood sample and a 24-hour urine will be collected. A caffeine test will be performed, by administering coffee and collecting urines three hours after. Subjects will fill in self-administered questionnaires; one covering the professional and lifestyle habits while the a second one is alimentary. The blood sample will be used to assess DNA adducts in peripheral lymphocytes. The 24-hour urine to assess urinary 8-oxo-7, 8-dihydro-2'-deoxy-Guanosine (8-oxo-dG), and the in vitro genotoxicity tests (comet and micronucleus) using HeLa S3 or HepG2 cells. In parallel, occupational air sampling will be conducted for some Polycyclic Aromatic Hydrocarbons and Volatile Organic Compounds. A weekly sampling chronology at the offices of occupational medicine in Paris city during the regular medical visits will be followed. This protocol has been accepted by the French Est III Ethical Comitee with the number 2007-A00685-48.</p> <p>Discussion</p> <p>Biomarkers of exposure and of early biological effects may help overcome the limitations of environmental exposure assessment in very complex occupational or environmental settings.</p