Genome size rather than content might affect call properties in toads of three ploidy levels (Anura: Bufonidae: Bufo viridis subgroup).

In vertebrates, genome size has been shown to correlate with nuclear and cell sizes, and influences phenotypic features, such as brain complexity. In three different anuran families, advertisement calls of polyploids exhibit longer notes and intervals than diploids, and difference in cellular dimensions have been hypothesized to cause these modifications. We investigated this phenomenon in green toads (Bufo viridis subgroup) of three ploidy levels, in a different call type (release calls) that may evolve independently from advertisement calls, examining 1205 calls, from ten species, subspecies, and hybrid forms. Significant differences between pulse rates of six diploid and four polyploid (3n, 4n) green toad forms across a range of temperatures from 7 to 27 °C were found. Laboratory data supported differences in pulse rates of triploids vs. tetraploids, but failed to reach significance when including field recordings. This study supports the idea that genome size, irrespective of call type, phylogenetic context, and geographical background, might affect call properties in anurans and suggests a common principle governing this relationship. The nuclear-cell size ratio, affected by genome size, seems the most plausible explanation. However, we cannot rule out hypotheses under which call-influencing genes from an unexamined diploid ancestral species might also affect call properties in the hybrid-origin polyploids.

Ascending aorta measurements as assessed by ECG-gated multi-detector computed tomography : a pilot study to etablish normative values for transcatheters therapies

Rapport de synthèse : Mesures de l'aorte ascendante par scanner synchronisé au rythme cardiaque: une étude pilote pour établir des valeurs normatives dans le cadre des futures thérapies par transcathéter. Objectif : L'objectif de cette étude est d'établir les valeurs morphométriques normatives de l'aorte ascendante à l'aide de l'angiographie par scanner synchronisé au rythme cardiaque, afin d'aider au développement des futurs traitements par transcathéter. Matériels et méthodes : Chez soixante-dix-sept patients (âgé de 22 à 83 ans, âge moyen: 54,7 ans), une angiographie par scanner synchronisé au rythme cardiaque a été réalisée pour évaluation des vaisseaux coronaires. Les examens ont été revus afin d'étudier l'anatomie de la chambre de chasse du ventricule gauche jusqu'au tronc brachio-céphalique droit. A l'aide de programmes de reconstructions multiplanaires et de segmentation automatique, différents diamètres et longueurs considérés comme importants pour les futurs traitements par transcathéter ont été mesurés. Les valeurs sont exprimées en moyennes, médianes, maximums, minimums, écart-types et en coefficients de variation. Les variations de diamètre de l'aorte ascendante durant le cycle cardiaque ont été aussi considérées. Résultats : Le diamètre moyen de la chambre de chasse du ventricule gauche était de 20.3+/-3.4 mm. Au niveau du sinus coronaire de l'aorte, il était de 34.2+/-4.1 mm et au niveau de la jonction sinotubulaire il était de 29.7+/-3.4 mm. Le diamètre moyen de l'aorte ascendante était de 32.7+/-3.8 mm. Le coefficient de variation de ces mesures variait de 12 à 17%. La distance moyenne entre l'insertion proximale des valvules aortiques et le départ du tronc brachio-céphalique droit était de 92.6+/-11.8 mm. La distance moyenne entre l'insertion proximale des valvules aortiques et l'origine de l'artère coronaire proximale était de 12.1+/-3.7 mm avec un coefficient de variation de 31%. La distance moyenne entre les deux ostia coronaires était de 7.2+/-3.1 mm avec un coefficient de variation de 43%. La longueur moyenne du petit arc de l'aorte ascendante entre l'artère coronaire gauche et le tronc brachio-céphalique droit était de 52.9+/-9.5 mm. La longueur moyenne de la continuité fibreuse entre la valve aortique et la valvule mitrale antérieure était de 14.6+/-3.3 mm avec un coefficient de variation de 23%. L'aire moyenne de la valve aortique était de 582.0+/-131.9 mm2. La variation du diamètre antéro-postérieur et transverse de l'aorte ascendante était respectivement de 8.4% et de 7.3%. Conclusion Il existe d'importantes variations inter-individuelles dans les mesures de l'aorte ascendante avec cependant des variations intra-individuelles faibles durant le cycle cardiaque. De ce fait, une approche personnalisée pour chaque patient est recommandée dans la confection des futures endoprothèses de l'aorte ascendante. Le scanner synchronisé au rythme cardiaque jouera un rôle prépondérant dans le bilan préthérapeutique. Abstract : The aim of this study was to provide an insight into normative values of the ascending aorta in regards to novel endovascular procedures using ECG-gated multi-detector CT angiography. Seventy-seven adult patients without ascending aortic abnormalities were evaluated. Measurements at relevant levels of the aortic root and ascending aorta were obtained. Diameter variations of the ascending aorta during cardiac cycle were also considered. Mean diameters (mm) were as follows: LV outflow tract 20.3+/-3.4, coronary sinus 34.2+/-4.1, sinotubular junction 29.7+-3.4 and mid ascending aorta 32.7+/-3.8 with coefficients of variation (CV) ranging from 12 to 17%. Mean distances (mm) were: from the plane passing through the proximal insertions of the aortic valve cusps to the right brachio-cephalic artery (BCA) 92.6111.8, from the plane passing through the proximal insertions of the aortic valve cusps to the proximal coronary ostium 12.1+/-3.7, and between both coronary ostia 7.2+/-3.1, minimal arc of the ascending aorta from left coronary ostium to right BCA 52.9 X9.5, and the fibrous continuity between the aortic valve and the anterior leaflet of the mitral valve 14.óf3.3, CV 13-43%. Mean aortic valve area was 582+-131.9 mm2. The variations of the antero-posterior and transverse diameters of the ascending aorta during the cardiac cycle were 8.4% and 7.3%, respectively. Results showed large inter-individual variations in diameters and distances but with limited intra-individual variations during the cardiac cycle. A personalized approach for planning endovascular devices must be considered.

Distinguishing general concepts from individuals: an automatic coarse-grained classifier

Named entity recognizers are unable to distinguish if a term is a general concept as "scientist" or an individual as "Einstein". In this paper we explore the possibility to reach this goal combining two basic approaches: (i) Super Sense Tagging (SST) and (ii) YAGO. Thanks to these two powerful tools we could automatically create a corpus set in order to train the SuperSense Tagger. The general F1 is over 76% and the model is publicly available.

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.

Automatic recognition of postural allocations.

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.

The automatic selection of ventilation parameters during the initial phase of mechanical ventilation.

OBJECTIVE: To test a method that allows automatic set-up of the ventilator controls at the onset of ventilation. DESIGN: Prospective randomized crossover study. SETTING: ICUs in one adult and one children's hospital in Switzerland. PATIENTS: Thirty intubated stable, critically ill patients (20 adults and 10 children). INTERVENTIONS: The patients were ventilated during two 20-min periods using a modified Hamilton AMADEUS ventilator. During the control period the ventilator settings were chosen immediately prior to the study. During the other period individual settings were automatically determined by the ventilatior (AutoInit). MEASUREMENTS AND RESULTS: Pressure, flow, and instantaneous CO2 concentration were measured at the airway opening. From these measurements, series dead space (V(DS)), expiratory time constant (RC), tidal volume (VT, total respiratory frequency (f(tot), minute ventilation (MV), and maximal and mean airway pressure (Paw, max and Paw, mean) were calculated. Arterial blood gases were analyzed at the end of each period. Paw, max was significantly less with the AutoInit ventilator settings while f(tot) was significantly greater (P < 0.05). The other values were not statistically significant. CONCLUSIONS: The AutoInit ventilator settings, which were automatically derived, were acceptable for all patients for a period of 20 min and were not found to be inferior to the control ventilator settings. This makes the AutoInit method potentially useful as an automatic start-up procedure for mechanical ventilation.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.