1,381 research outputs found

    Performance Modeling of Parallel Applications on MPSoCs

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    In this paper we present a new technique for automatically measuring the performance of tasks, functions or arbitrary parts of a program on a multiprocessor embedded system. The technique instruments the tasks described by OpenMP, used to represent the task parallelism, while ad hoc pragmas in the source indicate other pieces of code to profile. The annotations and the instrumentation are completely target-independent, so the same code can be measured on different target architectures, on simulators or on prototypes. We validate the approach on a single and on a dual LEON 3 platform synthesized on FPGA, demonstrating a low instrumentation overhead. We show how the information obtained with this technique can be easily exploited in a hardware/software design space exploration tool, by estimating, with good accuracy, the speed-up of a parallel application given the profiling on the single processor prototype

    Performance Estimation for Task Graphs Combining Sequential Path Profiling and Control Dependence Regions

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    The speed-up estimation of parallelized code is crucial to efficiently compare different parallelization techniques or task graph transformations. Unfortunately, most of the time, during the parallelization of a specification, the information that can be extracted by profiling the corresponding sequential code (e.g. the most executed paths) are not properly taken into account. In particular, correlating sequential path profiling with the corresponding parallelized code can help in the identification of code hot spots, opening new possibilities for automatic parallelization. For this reason, starting from a well-known profiling technique, the Efficient Path Profiling, we propose a methodology that estimates the speed-up of a parallelized specification, just using the corresponding hierarchical task graph representation and the information coming from the dynamic profiling of the initial sequential specification. Experimental results show that the proposed solution outperforms existing approaches

    Towards a deep-learning-based methodology for supporting satire detection

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    This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers

    The inhomogeneous mechanical behaviour of Ascending Thoracic Aortic Aneurism (ATAA)

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    Surgical management of ascending thoracic aortic aneurysms (aTAAs) relies on maximum diameter, growth rate, and presence of connective tissue disorders. The surgical decision however is often not considering that dissection and rupture do occur in patients who do not meet criteria for surgical repair [1,2]. In this study the authors aim to investigate the mechanical properties of aTAAs to be implemented in computational biomechanics models for a preclinical risk evaluation. Additionally, in some recent studies, some data about the biomechanical properties of the aTAAs have been reported [3], but without any relation to bicuspidal or tricuspidal aTAA. The aim of this study was to investigate aTAA mechanical properties using a biaxial system to compare the circumferential and axial stress-strain relations for bicuspidal and tricuspidal aTAAs

    Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricular assist device implant: A machine learning approach

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    Background: Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms. Methods: Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute–right ventricular failure (N = 8, 11%) or chronic–right ventricular failure (N = 10, 14%). Logistic regression, penalized logistic regression, linear support vector machines, and naïve Bayes algorithms with leave-one-out validation were used to evaluate the efficiency of any combination of three collected variables in an “all-subsets” approach. Results: Michigan risk score combined with central venous pressure assessed invasively and apical longitudinal systolic strain of the right ventricular–free wall were the most significant predictors of acute–right ventricular failure (maximum receiver operating characteristic–area under the curve = 0.95, 95% confidence interval = 0.91–1.00, by the naïve Bayes), while the right ventricular–free wall systolic strain of the middle segment, right atrial strain (QRS-synced), and tricuspid annular plane systolic excursion were the most significant predictors of Chronic-RVF (receiver operating characteristic–area under the curve = 0.97, 95% confidence interval = 0.91–1.00, according to naïve Bayes). Conclusion: Apical right ventricular strain as well as right atrial strain provides complementary information, both critical to predict acute–right ventricular failure and chronic–right ventricular failure, respectively

    Somatic BRCA Mutation in a Cholangiocarcinoma Patient for HBOC Syndrome Detection

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    BRCA-associated hereditary breast and ovarian cancer syndrome (HBOC) is characterized by an increased risk of developing other malignancies including cholangiocarcinoma (CCA). Somatic BRCA mutations have been reported in CCA, but they have yet to be utilized in a proband case to identify HBOC in families. Two healthy daughters of a deceased female patient who had had metachronous breast cancer and CCA received genetic counseling to assess their cancer risk. Somatic BRCA1/2 mutation analysis was performed by next-generation sequencing on the DNA extracted from a formalin-fixed, paraffin-embedded CCA biopsy specimen of their mother. A pathogenic variant was identified (c.6468_6469delTC in a BRCA2 gene mutation). Germline BRCA mutation analysis of the two daughters detected the same pathogenic variant in one of them. For the first time, a CCA somatic BRCA mutation has been used to identify a family with HBOC

    Family as a health promotion setting: A scoping review of conceptual models of the health-promoting family

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    Background The family is a key setting for health promotion. Contemporary health promoting family models can establish scaffolds for shaping health behaviors and can be useful tools for education and health promotion. Objectives The objective of this scoping review is to provide details as to how conceptual and theoretical models of the health promoting potential of the family are being used in health promotion contexts. Design Guided by PRISMA ScR guidelines, we used a three-step search strategy to find relevant papers. This included key-word searching electronic databases (Medline, PSycINFO, Embase, and CINAHL), searching the reference lists of included studies, and intentionally searching for grey literature (in textbooks, dissertations, thesis manuscripts and reports.) Results After applying inclusion and exclusion criteria, the overall search generated 113 included manuscripts/chapters with 118 unique models. Through our analysis of these models, three main themes were apparent: 1) ecological factors are central components to most models or conceptual frameworks; 2) models were attentive to cultural and other diversities, allowing room for a wide range of differences across family types, and for different and ever-expanding social norms and roles; and 3) the role of the child as a passive recipient of their health journey rather than as an active agent in promoting their own family health was highlighted as an important gap in many of the identified models. Conclusions This review contributes a synthesis of contemporary literature in this area and supports the priority of ecological frameworks and diversity of family contexts. It encourages researchers, practitioners and family stakeholders to recognize the value of the child as an active agent in shaping the health promoting potential of their family context.Brock Library Open Access Publishing Fun

    Patient-specific analysis of ascending thoracic aortic aneurysm with the living heart human model

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    In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs

    Regional biomechanical characterization of human ascending aortic aneurysms: Microstructure and biaxial mechanical response

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    : The ascending thoracic aortic aneurysm (ATAA) is a permanent dilatation of the vessel with a high risk of adverse events, and shows heterogeneous properties. To investigate regional differences in the biomechanical properties of ATAAs, tissue samples were collected from 10 patients with tricuspid aortic valve phenotype and specimens from minor, anterior, major, and posterior regions were subjected to multi-ratio planar biaxial extension tests and second-harmonic generation (SHG) imaging. Using the data, parameters of a microstructure-motivated constitutive model were obtained considering fiber dispersion. SHG imaging showed disruptions in the organization of the layers. Structural and material parameters did not differ significantly between regions. The non-symmetric fiber dispersion model proposed by Holzapfel et al. [25] was used to fit the data. The mean angle of collagen fibers was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. The experimental data collected in this study contribute to the biomechanical data available in the literature on human ATAAs. Region-specific parameters for the constitutive models are fundamental to improve the current risk stratification strategies, which are mainly based on aortic size. Such investigations can facilitate the development of more advanced finite element models capable of capturing the regional heterogeneity of pathological tissues. STATEMENT OF SIGNIFICANCE: Tissue samples of human ascending thoracic aortic aneurysms (ATAA) were collected. Samples from four regions underwent multi-ratio planar biaxial extension tests and second-harmonic generation imaging. Region-specific parameters of a microstructure-motivated model considering fiber dispersion were obtained. Structural and material parameters did not differ significantly between regions, however, the mean fiber angle was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. This study provides a unique set of mechanical and structural data, supporting the microstructural influence on the tissue response. It may facilitate the development of better finite element models capable of capturing the regional tissue heterogeneity
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