The sensory pain of Dante's Inferno - Semantics of chronic pain in patients with narcolepsy.

To examine the semantics of chronic pain in narcolepsy and to compare with the poem Inferno, from Dante Alighieri. A cross-sectional study, in which type 1 (n=33) and type 2 (n=33) patients (hypocretin-1 quantification in cerebrospinal fluid), were studied at Departamento de Psicobiologia - Universidade Federal de São Paulo (Brazil). We assessed pain descriptors in the Present Rating Index (PRI) from McGill Pain Questionnaire. There was no significant difference in PRI between narcolepsy groups. In both groups, the most frequent words had a sensory dimension: throbbing, jumping, and tugging. Multiple correspondence analysis revealed the predominance of sensory descriptors and the deficiency of affective descriptors in these groups. A study that interpreted the poem Inferno, from Dante Alighieri, as McGill Pain Questionnaires descriptors suggested a contribution of the sensory dimension in pain of possibly narcolepsy patients, similar as in our results

Sleepiness comorbid to musculoskeletal pain is associated with worse quality of life and mood symptoms in a general population sample.

Musculoskeletal (MSK) pain and hypersomnolence (HPS) are very disabling conditions that may share some pathophysiological factors. This study aimed to evaluate the interaction between MSK pain and HPS and its association with mood symptoms, fatigue, quality of life, and both objective and subjective sleep quality. Cross-sectional study. General population based sample. 510 individuals from EPISONO cohort, São Paulo (Brazil). All participants completed questionnaires, had clinical assessment and underwent a full-night polysomnography. HPS was defined according to Epworth Sleepiness Scale while the presence of MSK pain was defined by structured questionnaire. The sample was allocated into 4 groups: control (CTRL, n=281), HPS (n=141), MSK (n=50), and both conditions (HPS+MSK, n=38). MSK pain and HPS by themselves were associated with worse mood symptoms and quality of life. However, individuals with both associated conditions (HPS+MSK) presented higher frequencies of moderate to severe depression (44.1%) and anxiety symptoms (45.7%), as well as an additional decrease in quality of life compared to the other groups. There were no differences between HPS+MSK and MSK groups in objective sleep pattern. With regard to subjective sleep, HPS+MSK presented a higher prevalence of sleep attacks and cataplexy compared to all other groups. The combination of MSK pain and HPS was associated with worse mood symptoms, quality of life and HPS-related features. This study suggests that sleepiness may be an important symptom to be investigated and treated in MSK pain-related conditions for a better quality of life

A feasibility cachaca type recognition using computer vision and pattern recognition

Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper.info:eu-repo/semantics/publishedVersio

Numerical convergence of the block-maxima approach to the Generalized Extreme Value distribution

In this paper we perform an analytical and numerical study of Extreme Value distributions in discrete dynamical systems. In this setting, recent works have shown how to get a statistics of extremes in agreement with the classical Extreme Value Theory. We pursue these investigations by giving analytical expressions of Extreme Value distribution parameters for maps that have an absolutely continuous invariant measure. We compare these analytical results with numerical experiments in which we study the convergence to limiting distributions using the so called block-maxima approach, pointing out in which cases we obtain robust estimation of parameters. In regular maps for which mixing properties do not hold, we show that the fitting procedure to the classical Extreme Value Distribution fails, as expected. However, we obtain an empirical distribution that can be explained starting from a different observable function for which Nicolis et al. [2006] have found analytical results.Comment: 34 pages, 7 figures; Journal of Statistical Physics 201