Comparison of energy consumption and costs of different HEVs and PHEVs in European and American context

This paper will analyse on the one hand the potential of Plug in Hybrid electric Vehicles to significantly reduce fuel consumption and displace it torward various primary energies thanks to the electricity sector. On the other hand the total cost of ownership of two different PHEV architectures will be compared to a conventional cehicle and a HEV without external charging

La fonction conjonctionnelle de ga-, particule de phrase, dans la stratégie énonciative

Ga- serait l’héritier gotique d’une lointaine particule pronominale de l’indo-européen et serait étymologiquement et fonctionnellement lié au thème *ke/o. Ayant cette lointaine origine pronominale, il garderait le caractère anaphorique et déictique propre à celle-ci. Nous fondons ce que nous appelons la “fonction conjonctionnelle” de ga- sur ces données préliminaires, la logique articulatoire de ga- s’appuyant dès lors sur les fonctions d’anaphore et de cataphore propres aux déictiques. C’est ainsi que nous ne réduisons pas l’incidence de ga- au seul verbe qui la porte, ni non plus sa fonction au seul marquage de l’aspect “perfectif” du verbe. Ces recherches sont fondées sur une analyse de la traduction de la Bible par Wulfila

Tsallis entropy measure of noise-aided information transmission in a binary channel

Noise-aided information transmission via stochastic resonance is shown and analyzed in a binary channel by means of information measures based on the Tsallis entropy. The analysis extends the classic reference of binary information transmission based on the Shannon entropy, and also parallels a recent study based on the Rényi entropy. The conditions for a maximally pronounced stochastic resonance identify optimal Tsallis measures. The study involves a correspondence between Tsallis and Rényi information measures, specially relevant to the characterization of stochastic resonance, and establishing that for such effects identical properties are shared in common by both Tsallis and Rényi measures

Multifractality, sample entropy, and wavelet analyses for age-related changes in the peripheral cardiovascular system: Preliminary results

Using signal processing measures we evaluate the effect of aging on the peripheral cardiovascular system. Laser Doppler flowmetry (LDF) signals, reflecting the microvascular perfusion, are recorded on the forearm of 27 healthy subjects between 20–30, 40–50, or 60–70 years old. Wavelet-based representations, Hölder exponents, and sample entropy values are computed for each time series. The results indicate a possible modification of the peripheral cardiovascular system with aging. Thus, the endothelial-related metabolic activity decreases, but not significantly, with aging. Furthermore, LDF signals are more monofractal for elderly subjects than for young people for whom LDF signals are weakly multifractal: the average range of Hölder exponents computed with a parametric generalized quadratic variation based estimation method is 0.13 for subjects between 20 and 30 years old and 0.06 for subjects between 60 and 70 years old. Moreover, the average mean sample entropy value of LDF signals slightly decreases with age: it is 1.34 for subjects between 20 and 30 years old and 1.19 for subjects between 60 and 70 years old. Our results could assist in gaining knowledge on the relationship between microvascular system status and age and could also lead to a more accurate age-related nonlinear modeling

Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the gestational process. In this context, there is a clear need for segmentation techniques that are robust to variations in image contrast and to the spatial configuration of anatomical structures. In this work, we evaluate the potential of synthetic learning, a contrast-independent model trained using synthetic images generated from the ground truth labels of very few subjects.We base our experiments on the dataset released by the developmental Human Connectome Project, for which high-quality T1- and T2-weighted images are available for more than 700 babies aged between 26 and 45 weeks post-conception. First, we confirm the impressive performance of a standard Unet trained on a few T2-weighted volumes, but also confirm that such models learn intensity-related features specific to the training domain. We then evaluate the synthetic learning approach and confirm its robustness to variations in image contrast by reporting the capacity of such a model to segment both T1- and T2-weighted images from the same individuals. However, we observe a clear influence of the age of the baby on the predictions. We improve the performance of this model by enriching the synthetic training set with realistic motion artifacts and over-segmentation of the white matter. Based on extensive visual assessment, we argue that the better performance of the model trained on real T2w data may be due to systematic errors in the ground truth. We propose an original experiment combining two definitions of the ground truth allowing us to show that learning from real data will reproduce any systematic bias from the training set, while synthetic models can avoid this limitation. Overall, our experiments confirm that synthetic learning is an effective solution for segmenting neonatal brain MRI. Our adapted synthetic learning approach combines key features that will be instrumental for large multi-site studies and clinical applications

Exploiting the speckle noise for compressive imaging

An optical setup is proposed for the implementation of compressive sensing with coherent images. This setup specifically exploits the natural multiplicative action of speckle noise occurring with coherent light, in order to optically realize the essential step in compressive sensing which is the multiplication with known random patterns of the image to be acquired. In the test of the implementation, we specifically examine the impact of several departures, that exist in practice, from the ideal conditions of a pure multiplicative action of the speckle. In such practical realistic conditions, we assess the feasibility, performance and robustness of the optical scheme of compressive sensing. (C) 2011 Elsevier B.V. All rights reserved

log(TG)/HDL-C is related to both residual cardiometabolic risk and β-cell function loss in type 2 diabetes males

<p>Abstract</p> <p>Background</p> <p>T2DM is associated with atherogenic dyslipidemia (AD), defined as decreased HDL-C plus raised triglycerides (TG). AD confers increased risk for CAD, even when LDL-C is at target. AD is rarely assessed due to lack of screening methods consensus.</p> <p>Aim</p> <p>To establish the prevalence and severity of AD from <it>log</it>(TG)/HDL-C in T2DM males, and to determine how it relates to cardiometabolic phenotype, glucose homeostasis, micro- and macrovascular complications, and 10-year <it>UKPDS </it>CV risk.</p> <p>Methods</p> <p>585 T2DM males divided according to quintiles (Q) of <it>log</it>(TG)/HDL-C. AD prevalence defined as HDL-C <40 mg.dL^-1plus TG ≥150 mg.dL^-1. β-cell function assessed with HOMA.</p> <p>Results</p> <p>Mean HDL-C and TG were 44 (13) and 204 (155) mg.dL^-1. AD prevalence was 35%. AD correlated with lower β-cell function, with accelerated loss of insulin secretion, and with poorer HbA_1clevels. AD was related to a high prevalence of CAD, and also to 10-year absolute CAD risk.</p> <p>Conclusions</p> <p><it>log</it>(TG)/HDL-C is a simple means to estimate AD and the residual CV risk it confers in T2DM. AD closely associates with major cardiometabolic and glucose homeostasis determinants and poorer metabolic control. The ratio also relates to macroangiopathy prevalence and ranks future CAD risk, and is well-suited to capture non-LDL-related macrovascular residual risk and major glycemic determinants.</p

Peran Desentralisasi Fiskal Terhadap Kinerja Ekonomi Di Kabupaten/kota Provinsi Jawa Tengah

This research is intended to examine the influence of fiscal decentralization on economic growth, poverty, employment, and welfare at regencies/municipalities level in Central Java Province. Research population consist of 29 regencies and 6 municipalities, employing secondary data from Central Bureau of Statistic of Central Java Province and regencies/municipalities level in Central Java Province within the period of 2001 up to 2005. Data analysis is conducted by using path analysis with AMOS program software. The results of this study indicate that, first fiscal decentralization has a positive and significant effect on economic growth. Second, economic growth has a positive and significant effect on employment rate. Third, economic growth has a negative and significant effect on poverty. Forth, economic growth has a positive and significant effect on welfare. Fifth, employment rate has a negative and significant effect on welfare. Sixth, poverty has a negative and significant effect on welfare at regencies/municipalities level in Central Java Province

PERC rule to exclude the diagnosis of pulmonary embolism in emergency low-risk patients: study protocol for the PROPER randomized controlled study.

BACKGROUND: The diagnosis of Pulmonary Embolism (PE) in the emergency department (ED) is crucial. As emergency physicians fear missing this potential life-threatening condition, PE tends to be over-investigated, exposing patients to unnecessary risks and uncertain benefit in terms of outcome. The Pulmonary Embolism Rule-out Criteria (PERC) is an eight-item block of clinical criteria that can identify patients who can safely be discharged from the ED without further investigation for PE. The endorsement of this rule could markedly reduce the number of irradiative imaging studies, ED length of stay, and rate of adverse events resulting from both diagnostic and therapeutic interventions. Several retrospective and prospective studies have shown the safety and benefits of the PERC rule for PE diagnosis in low-risk patients, but the validity of this rule is still controversial. We hypothesize that in European patients with a low gestalt clinical probability and who are PERC-negative, PE can be safely ruled out and the patient discharged without further testing. METHODS/DESIGN: This is a controlled, cluster randomized trial, in 15 centers in France. Each center will be randomized for the sequence of intervention periods: a 6-month intervention period (PERC-based strategy) followed by a 6-month control period (usual care), or in reverse order, with 2 months of "wash-out" between the 2 periods. Adult patients presenting to the ED with a suspicion of PE and a low pre test probability estimated by clinical gestalt will be eligible. The primary outcome is the percentage of failure resulting from the diagnostic strategy, defined as diagnosed venous thromboembolic events at 3-month follow-up, among patients for whom PE has been initially ruled out. DISCUSSION: The PERC rule has the potential to decrease the number of irradiative imaging studies in the ED, and is reported to be safe. However, no randomized study has ever validated the safety of PERC. Furthermore, some studies have challenged the safety of a PERC-based strategy to rule-out PE, especially in Europe where the prevalence of PE diagnosed in the ED is high. The PROPER study should provide high-quality evidence to settle this issue. If it confirms the safety of the PERC rule, physicians will be able to reduce the number of investigations, associated subsequent adverse events, costs, and ED length of stay for patients with a low clinical probability of PE. TRIAL REGISTRATION: NCT02375919