Irreversibility and Biased Ensembles in Active Matter: Insights from Stochastic Thermodynamics

Active systems evade the rules of equilibrium thermodynamics by constantly dissipating energy at the level of their microscopic components. This energy flux stems from the conversion of a fuel, present in the environment, into sustained individual motion. It can lead to collective effects without any equilibrium equivalent, some of which can be rationalized by using equilibrium tools to recapitulate nonequilibrium transitions. An important challenge is then to delineate systematically to what extent the character of these active transitions is genuinely distinct from equilibrium analogs. We review recent works that use stochastic thermodynamics tools to identify, for active systems, a measure of irreversibility comprising a coarse-grained or informatic entropy production. We describe how this relates to the underlying energy dissipation or thermodynamic entropy production, and how it is influenced by collective behavior. Then, we review the possibility of constructing thermodynamic ensembles out-of-equilibrium, where trajectories are biased toward atypical values of nonequilibrium observables. We show that this is a generic route to discovering unexpected phase transitions in active matter systems, which can also inform their design. Expected final online publication date for the Annual Review of Condensed Matter Physics, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Black Sigatoka Classification Using Convolutional Neural Networks

In this paper we present a methodology for the automatic recognition of black Sigatoka in commercial banana crops. This method uses a LeNet convolutional neural network to detect the progress of infection by the disease in different regions of a leaf image; using this information, we trained a decision tree in order to classify the level of infection severity. The methodology was validated with an annotated database, which was built in the process of this work and which can be compared with other state-of-the-art alternatives. The results show that the method is robust against atypical values and photometric variations.

The Frequency of Atypical and Extreme Values for Pharyngeal Phase Swallowing Measures in Mild Parkinson Disease Compared to Healthy Aging

Purpose Dysphagia is thought to be prevalent and a leading cause of morbidity and mortality in people with Parkinson disease (PwPD). The aim of this study was to compare the frequencies of atypical and extreme values for measures of swallowing physiology in PwPD and in an age- and sex-matched cohort of healthy adults. Atypical and extreme values were defined, respectively, as values falling in the 25% and 5% tails of the reference distribution for healthy adults under age 60 years. Method A standard videofluoroscopy (VF) protocol was performed in 17 adults with mild PD and 17 age- and sex-matched healthy adults using 20% w/v liquid barium ranging from thin to extremely thick consistency. Blinded VF analysis was performed according to the Analysis of Swallowing Physiology: Events, Kinematics and Timing Method. Frequencies for atypical and extreme values were tabulated by cohort and compared using odds ratios. Results Increased frequencies of atypical values (> 25%) were seen in the PwPD for prolonged swallow reaction time, prolonged time-to-laryngeal-vestibule-closure (LVC), and poor pharyngeal constriction. However, these findings were also observed in the healthy controls. The PwPD showed significantly higher odds of atypical values for narrow upper esophageal sphincter (UES) diameter on thin liquids, a short hyoid-burst-to-UES-opening interval on extremely thick liquids, and prolonged time-to-LVC, LVC duration, and UES opening duration on multiple consistencies. The frequencies of extreme values failed to show any significant cohort differences for any parameter. Conclusions In this study, a group of people with mild PD did not show clear evidence of swallowing impairments distinct from the changes seen in a healthy age-matched control group when odds ratios were used to compare the frequencies of atypical values between PwPD and the control group; only a few parameters showed significant differences. These were findings of significantly higher frequencies in PwPD of prolonged LVC and UES opening duration. Supplemental Material https://doi.org/10.23641/asha.15032241

Evaluation of bone mineral density through radiographic optical densitometry in 42 canine femures

This study evaluates the bone mineral density of 42 canine femurs using radiographic optical densitometry and validates radiographic optical densitometry as a parameter to standardize bone tissue samples used in biomechanical tests, contributing to the diagnosis of osteoporosis in dogs. The ImageJ 1.46r® program was used for the radiographic optical densitometry. After selecting the aluminum steps and the area of interest in the femur, the data obtained were stored in a table and converted into mm/Al using the MS Excel® trend function. Statistical analysis demonstrated the absence of atypical values (outiliers) in the samples analyzed. The samples evaluated were homogeneous and the densitometric data obtained may contribute to reducing the scarcity of densitometric references in the veterinary literature. Ex vivo biomechanical studies may benefit from the method used in this study to standardize their sample when evaluating bone mineral density, validating their respective projects

Use patterns of educational videos: a quantitative study among university students

<p>This paper analyzes the perception, on the part of Grade students, of the availability of videos complementary to classroom teaching, as well as the moment of visualization of the same, with the aim of identifying their use pattern and perceived usefulness, an initial step towards future flip-teaching interventions. The analysis has been carried out in three groups, one of the Business Administration degree, and two of the double degree of Business Administration and Law, during the academic year 2018-19, in a quantitative subject (Quantitative Models), the content of which is necessary for subsequent subjects, including Operations Management, in the third year of the grade. The use pattern of the videos, which received a total of 7281 views, was analysed using the Box-Jenkins methodology, adjusting an ARIMA model and identifying the atypical values in the series. The results indcate that the students perceive these videos as useful, although more as a tool to help in the preparation of exams than as an instrument to review the contents. All authors have participated in the idea, study design, collection and/or analysis and interpretation of the data, in the draft of the paper and in the critical review of their intellectual content.</p>

Usefulness and reliability of cell free fetal DNA screening for main trisomies in case of atypical profile on first trimester maternal serum screening

Background Patients with atypical values of HCG and/or PAPP-A are at higher risk of chromosomal abnormality and vascular complications of pregnancy. The performance of cfDNA in this particular population has not yet been evaluated. Objectives The primary objective was to evaluate the usefulness and reliability of cfDNA in screening for trisomy 21, 18 and 13 for patients with HCG < 0.25 multiple of median (MoM), HCG > 5.0 MoM and/or PAPP-A < 0.25 MoM, PAPP-A > 2.5 MoM. The secondary objective was to evaluate the contribution of cfDNA assay for the prediction of pregnancy’s vascular complications. Method Between June 2016 and July 2017, we analysed a women cohort from all over France who had at least one first trimester serum biomarker outside of normal range, in a retrospective, observational and multicentre study. Patients were included if they had a single pregnancy, normal first trimester ultrasound examination, whatever the result of the combined first trimester screening test was. The cfDNA was analysed by massive parallel sequencing technique. The accuracy of cfDNA assay was evaluated by calculation of sensitivity and specificity, and multivariate regression analysis was used to search for predictive factors for pregnancy’s vascular complications. Results Among the 498 patients who underwent a cfDNA assay in this context, twenty-one (4.2%) were excluded because of loss to follow-up. Out of 477, test failure occurred for four patients initially, reduced to two patients (0.4%) after redrawn. CfDNA was positive for Trisomy 21 (n = 19), Trisomy 18 (n = 6) and Trisomy 13 (n = 1) and negative in 449. The sensitivity of cfDNA assay for trisomy 21 screening was 100% (19/19) (IC 95% 82.4–100) and specificity 100% (458/458) (IC 95% 99.2–100). Among the 447 patients included for prediction of vascular complications, there were four cases of pregnancy induced hypertension and 10 cases of preeclampsia, for which no predictive factor was identified. Intra Uterine growth restriction under 5th percentile (n = 44, 9.8%) was significantly associated with a low fetal fraction (OR = 0.87, IC 95% 0.79–0.96, p = 0.006). Conclusion cfDNA assay is an effective and reliable tool for women with atypical profile of first trimester serum biomarkers.

Tuning of conic parameters using Tikhonov regularization and L-Curve simulation

In this article, a method to infer the parameters of a conic given a set of rectangular coordinates that belong to the geometric entity is shown. The methodology consists of solving a Tikhonov regulation problem where the unregulated term introduces the non-linear nature of the conical body and the regulated the restriction associated to the discriminant of the quadratic equation, then the solution is computed minimizing the resulting cost function where the Regularization parameter is tuned using the L-Curve technique. The model was validated with synthetic and real data from digital images, as well as subject to comparison against other state of the art alternatives. The results show that the method is robust against atypical values and the phenomenon of occlusion present in the data.

A distribuição Lindley potência inversa: diferentes métodos de estimação

The identification of outliers plays an important role in the statistical analysis, since such observations may contain important information regarding the hypotheses of the study. If classical statistical models are blindly applied to data containing atypical values, the results may be misleading and mistaken decisions can be made. Moreover, in practical situations, the outliers themselves are often the special points of interest and their identification may be the main objective of the investigation. In this way, it was proposed to propose a technique of detection of multivariate outliers, based on cluster analysis and to compare this technique with the method of identification of outliers via Mahalanobis Distance. For data generation, Monte Carlo method simulation and the mixed multivariate normal distribution technique were used. The results presented in the simulations showed that the proposed method was superior to the Mahalanobis method for both sensitivity and specificity, that is, it presented greater ability to correctly diagnose outliers and non-outliers individuals. In addition, the proposed methodology was illustrated with an application in real data from the health area.

Explanatory Business Analytics in OLAP

In this paper the authors describe a method to integrate explanatory business analytics in OLAP information systems. This method supports the discovery of exceptional values in OLAP data and the explanation of such values by giving their underlying causes. OLAP applications offer a support tool for business analysts and accountants in analyzing financial data because of the availability of different views and managerial reporting facilities. The purpose of the methods and algorithms presented here, is to extend OLAP applications with more powerful analysis and reporting functions. The authors describe how exceptional values at any level in the data, can be automatically detected by statistical models. Secondly, a generic model for diagnosis of atypical values is realized in the OLAP context. By applying it, a full explanation tree of causes at successive levels can be generated. If the tree is too large, the analyst can use appropriate filtering measures to prune the tree to a manageable size. This methodology has a wide range of applications such as interfirm comparison, analysis of sales data and the analysis of any other data that possess a multi-dimensional hierarchical structure. The method is demonstrated in a case study on financial data.