Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach

The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively parallel system, has been chosen to minimize system production and operational costs. This paper presents a novel approach to expectation-driven low-level image segmentation, which can be mapped naturally onto mesh-connected massively parallel SIMD architectures capable of handling hierarchical data structures. The input image is assumed to contain a distorted version of a given template; a multiresolution stretching process is used to reshape the original template in accordance with the acquired image content, minimizing a potential function. The distorted template is the process output.Comment: See http://www.jair.org/ for any accompanying file

Low-Intensity Vibration Protects the Weight-Bearing Skeleton and Suppresses Fracture Incidence in Boys With Duchenne Muscular Dystrophy: A Prospective, Randomized, Double-Blind, Placebo-Controlled Clinical Trial

The ability of low-intensity vibration (LIV) to combat skeletal decline in Duchenne Muscular Dystrophy (DMD) was evaluated in a randomized controlled trial. Twenty DMD boys were enrolled, all ambulant and treated with glucocorticoids (mean age 7.6, height-adjusted Z-scores [HAZ] of hip bone mineral density [BMD] −2.3). Ten DMD boys were assigned to stand for 10 min/d on an active LIV platform (0.4 g at 30 Hz), while 10 stood on a placebo device. Baseline and 14-month bone mineral content (BMC) and BMD of spine, hip, and total body were measured with DXA, and trabecular bone density (TBD) of tibia with quantitative computed tomography (QCT). All children tolerated the LIV intervention well, with daily compliance averaging 78%. At 14 months, TBD in the proximal and distal tibia remained unchanged in placebo subjects (−1.0% and −0.2%), while rising 3.5% and 4.6% in LIV subjects. HAZ for hip BMD and BMC in the placebo group declined 22% and 13%, respectively, contrasting with no change from baseline (0.9% and 1.4%) in the LIV group. Fat mass in the leg increased 32% in the placebo group, contrasting with 21% in LIV subjects. Across the 14-month study, there were four incident fractures in three placebo patients (30%), with no new fractures identified in LIV subjects. Despite these encouraging results, a major limitation of the study is—despite randomized enrollment—that there was a significant difference in age between the two cohorts, with the LIV group being 2.8y older, and thus at greater severity of disease. In sum, these data suggest that noninvasive LIV can help protect the skeleton of DMD children against the disease progression, the consequences of diminished load bearing, and the complications of chronic steroid use. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research

PO-0940: Feasibility of planning CT to MVCT deformable registration for ìdose of the dayî calculation in helical Tomotherapy

Núm. a Art públic: 1135Digitalitzat per Tecnodo

Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis

© 2019 Elsevier Ltd Structural reliability analysis for rare failure events in the presence of hybrid uncertainties is a challenging task drawing increasing attentions in both academic and engineering fields. Based on the new imprecise stochastic simulation framework developed in the companion paper, this work aims at developing efficient methods to estimate the failure probability functions subjected to rare failure events with the hybrid uncertainties being characterized by imprecise probability models. The imprecise stochastic simulation methods are firstly improved by the active learning procedure so as to reduce the computational costs. For the more challenging rare failure events, two extended subset simulation based sampling methods are proposed to provide better performances in both local and global parameter spaces. The computational costs of both methods are the same with the classical subset simulation method. These two methods are also combined with the active learning procedure so as to further substantially reduce the computational costs. The estimation errors of all the methods are analyzed based on sensitivity indices and statistical properties of the developed estimators. All these new developments enrich the imprecise stochastic simulation framework. The feasibility and efficiency of the proposed methods are demonstrated with numerical and engineering test examples

Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation

© 2019 Elsevier Ltd Uncertainty propagation through the simulation models is critical for computational mechanics engineering to provide robust and reliable design in the presence of polymorphic uncertainty. This set of companion papers present a general framework, termed as non-intrusive imprecise stochastic simulation, for uncertainty propagation under the background of imprecise probability. This framework is composed of a set of methods developed for meeting different goals. In this paper, the performance estimation is concerned. The local extended Monte Carlo simulation (EMCS) is firstly reviewed, and then the global EMCS is devised to improve the global performance. Secondly, the cut-HDMR (High-Dimensional Model Representation) is introduced for decomposing the probabilistic response functions, and the local EMCS method is used for estimating the cut-HDMR component functions. Thirdly, the RS (Random Sampling)-HDMR is introduced to decompose the probabilistic response functions, and the global EMCS is applied for estimating the RS-HDMR component functions. The statistical errors of all estimators are derived, and the truncation errors are estimated by two global sensitivity indices, which can also be used for identifying the influential HDMR components. In the companion paper, the reliability and rare event analysis are treated. The effectiveness of the proposed methods are demonstrated by numerical and engineering examples

Practical Approach to the Diagnosis of the Vulvo-Vaginal Stromal Tumors: An Overview

Background: The category of the "stromal tumors of the lower female genital tract" encompasses a wide spectrum of lesions with variable heterogeneity, which can be nosologically classified on the basis of their morphologic and immunohistochemical profiles as deep (aggressive) angiomyxoma (DAM), cellular angiofibroma (CAF), angiomyofibroblastoma (AMFB) or myofibroblastoma (MFB). Despite the differential diagnosis between these entities being usually straightforward, their increasingly recognized unusual morphological variants, along with the overlapping morphological and immunohistochemical features among these tumours, may raise serious differential diagnostic problems. Methods and Results: The data presented in the present paper have been retrieved from the entire published literature on the PubMed website about DAM, CAF, AFMB and MFB from 1984 to 2021. The selected articles are mainly represented by small-series, and, more rarely, single-case reports with unusual clinicopathologic features. The present review focuses on the diagnostic clues of the stromal tumours of the lower female genital tract to achieve a correct classification. The main clinicopathologic features of each single entity, emphasizing their differential diagnostic clues, are discussed and summarized in tables. Representative illustrations, including the unusual morphological variants, of each single tumour are also provided. Conclusion: Awareness by pathologists of the wide morphological and immunohistochemical spectrum exhibited by these tumours is crucial to achieve correct diagnoses and to avoid confusion with reactive conditions or other benign or malignant entities

Individualized Prediction of Drug Resistance in People with Post-Stroke Epilepsy: A Retrospective Study

Background: The study aimed to develop a model and build a nomogram to predict the probability of drug resistance in people with post-stroke epilepsy (PSE). Methods: Subjects with epilepsy secondary to ischemic stroke or spontaneous intracerebral hemorrhage were included. The study outcome was the occurrence of drug-resistant epilepsy defined according to International League Against Epilepsy criteria. Results: One hundred and sixty-four subjects with PSE were included and 32 (19.5%) were found to be drug-resistant. Five variables were identified as independent predictors of drug resistance and were included in the nomogram: age at stroke onset (odds ratio (OR): 0.941, 95% confidence interval (CI) 0.907–0.977), intracerebral hemorrhage (OR: 6.292, 95% CI 1.957–20.233), severe stroke (OR: 4.727, 95% CI 1.573–14.203), latency of PSE (>12 months, reference; 7–12 months, OR: 4.509, 95% CI 1.335–15.228; 0–6 months, OR: 99.099, 95% CI 14.873–660.272), and status epilepticus at epilepsy onset (OR: 14.127, 95% CI 2.540–78.564). The area under the receiver operating characteristic curve of the nomogram was 0.893 (95% CI: 0.832–0.956). Conclusions: Great variability exists in the risk of drug resistance in people with PSE. A nomogram based on a set of readily available clinical variables may represent a practical tool for an individualized prediction of drug-resistant PSE

The Bhattacharyya distance: Enriching the P-box in stochastic sensitivity analysis

© 2019 Elsevier Ltd The tendency of uncertainty analysis has promoted the transformation of sensitivity analysis from the deterministic sense to the stochastic sense. This work proposes a stochastic sensitivity analysis framework using the Bhattacharyya distance as a novel uncertainty quantification metric. The Bhattacharyya distance is utilised to provide a quantitative description of the P-box in a two-level procedure for both aleatory and epistemic uncertainties. In the first level, the aleatory uncertainty is quantified by a Monte Carlo process within the probability space of the cumulative distribution function. For each sample of the Monte Carlo simulation, the second level is performed to propagate the epistemic uncertainty by solving an optimisation problem. Subsequently, three sensitivity indices are defined based on the Bhattacharyya distance, making it possible to rank the significance of the parameters according to the reduction and dispersion of the uncertainty space of the system outputs. A tutorial case study is provided in the first part of the example to give a clear understanding of the principle of the approach with reproducible results. The second case study is the NASA Langley challenge problem, which demonstrates the feasibility of the proposed approach, as well as the Bhattacharyya distance metric, in solving such a large-scale, strong-nonlinear, and complex problem

The wide morphological spectrum of deep (Aggressive) angiomyxoma of the vulvo-vaginal region: A clinicopathologic study of 36 cases, including recurrent tumors

Background: Deep angiomyxoma (DAM) is currently included in the category of "specific stromal tumors of the lower female genital tract", along with angiomyofibroblastoma, cellular angiofibroma and myofibroblastoma. Given the high rate of local recurrences, it is crucial to recognize DAM from other tumors that possess indolent behaviour. In the present paper, we analyzed the morphological and immunohistochemical features of 42 surgically-resected vulvo-vaginal DAMs (36 primary and 6 recurrent lesions) in order to widen the morphological spectrum of this uncommon tumor. Methods: A series of 36 cases of surgically-resected primary vulvo-vaginal DAMs were retrospectively collected. Locally recurrent tumors were also available for six of these cases. Results: Out of the primary tumors, 25 out of 36 exhibited the classic-type morphology of DAM. In the remaining cases (11/36 cases), the following uncommon features, which sometimes coexist with one another, were observed: (i) alternating myxoid and collagenized/fibrous areas; (ii) hypercellular areas; (iii) neurofibroma-like appearance; (iv) perivascular hyalinization; (v) microcystic/reticular stromal changes; (vi) "microvascular growth pattern"; (vii) perivascular cuffing; (viii) nodular leiomyomatous differentiation; (ix) hypocellular and fibro-sclerotic stroma. Among the six locally recurrent tumors the following features were observed: (i) classic-type morphology; (ii) hypocellular fibro-sclerotic stroma; (iii) extensive perivascular hyalinization, lumen obliteration and formation of confluent nodular sclerotic masses; (iv) hypercellularity. Immunohistochemically, the neoplastic cells of classic-type DAM in both primary and recurrent tumors were diffusely stained with desmin, suggesting a myofibroblastic nature; in contrast, the neoplastic cells showing elongated fibroblastic-like morphology and set in collagenized/fibrosclerotic stroma in both primary and recurrent tumors were negative or only focally stained with desmin, which is consistent with a fibroblastic profile. Conclusion: Although diagnosis of DAM is usually straightforward if typical morphology is encountered, diagnostic problems may arise when a pathologist is dealing with unusual morphological features, especially hypercellularity, extensive collagenous/fibrosclerotic stroma or neurofibroma-like appearance