Polyamide Nanocomposites for Selective Laser Sintering

Current polyamide 11 and 12 are lacking in fire retardancy and high strength/high heat resistance characteristics for a plethora of finished parts that are desired and required for performance driven applications. It is anticipated that nanomodification of polyamide 11 and 12 will result in enhanced polymer performance, i.e., fire retardancy, high strength and high heat resistance for polyamide 11 and 12. It is expected that these findings will expand the market opportunities for polyamide 11 and 12 resin manufacturers. The objective of this research is to develop improved polyamide 11 and 12 polymers with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into the polyamide 11 and 12 via twin screw extrusion to provide improved material properties of the polymer blends. Arkema RILSAN® polyamide 11 molding polymer pellets and Degussa VESTAMID® L1670 polyamide 12 were examined with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, surface modified nanosilica, and carbon nanofibers (CNFs) to create polyamide 11 and 12 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Injection molded test specimens were fabricated for physical, thermal, mechanical properties, and flammability tests. Thermal stability of these polyamide 11 and 12 nanocomposites was examined by TGA. Mechanical properties such as tensile, flexural, and elongation at break were measured. Flammability properties were also obtained using the Cone Calorimeter at an external heat flux of 50 kW/m2. TEM micrographs, physical, mechanical, and flammability properties are included in the paper. Polyamide 11 and 12 nanocomposites properties are compared with polyamide 11 and 12 baseline polymers. Based on flammability and mechanical material performance, selective polymers including polyamide 11 nanocomposites and control polyamide 11 were cryogenically ground into fine powders and fabricated into SLS parts.Mechanical Engineerin

Performance Modeling of Parallel Applications on MPSoCs

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

Innovative Selective Laser Sintering Rapid Manufacturing using Nanotechnology

The objective of this research is to develop an improved nylon 11 (polyamide 11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into nylon 11 via twin screw extrusion to provide improved material properties of the polymer blends. Atofina (now known as Arkema) RILSAN® nylon 11 injection molding polymer pellets was used with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, nanosilica, and carbon nanofibers (CNF) to create nylon 11 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Fifteen nylon 11 nanocomposites and control nylon 11 were fabricated by injection molding. Flammability properties (using a cone calorimeter with a radiant flux of 50 kW/m2 ) and mechanical properties such as tensile strength and modulus, flexural modulus, elongation at break were determined for the nylon 11 nanocomposites and compared with the baseline nylon 11. Based on flammability and mechanical material performance, five polymers including four nylon 11 nanocomposites and a control nylon 11 were cryogenically ground into fine powders for SLS RM. SLS specimens were fabricated for flammability, mechanical, and thermal properties characterization. Nylon 11-CNF nanocomposites exhibited the best overall properties for this study.Mechanical Engineerin

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

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

Polyamide 11-Carbon Nanotubes Nanocomposites: Preliminary Investigation

The objective of this research is to develop an improved polyamide 11 (PA11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing. In the present study, a nanophase was introduced into polyamide 11 via twin screw extrusion. Arkema Rilsan® polyamide 11 molding polymer pellets were used with 1, 3, 5, and 7 wt% loadings of Arkema’s GraphistrengthTM multi-wall carbon nanotubes (MWNTs) to create a family of PA11-MWNT nanocomposites. Transmission electron microscopy and scanning electron microscopy were used to determine the degree and uniformity of dispersion. Injection molded test specimens were fabricated for physical, thermal, mechanical properties, and flammability measurements. Thermal stability of these polyamide 11-MWNT nanocomposites was examined by TGA. Mechanical properties such as ultimate tensile strength, rupture tensile strength, and elongation at rupture were measured. Flammability properties were also obtained using the UL 94 test method. All these different methods and subsequent polymer characteristics are discussed in this paper.Mechanical Engineerin

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

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

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

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

Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms

Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta

Transcatheter heart valve implantation in bicuspid patients with self-expanding device

Bicuspid aortic valve (BAV) patients are conventionally not treated by transcathether aortic valve implantation (TAVI) because of anatomic constraint with unfavorable outcome. Patient-specific numerical simulation of TAVI in BAV may predict important clinical insights to assess the con-formability of the transcathether heart valves (THV) implanted on the aortic root of members of this challenging patient population. We aimed to develop a computational approach and virtually simulate TAVI in a group of n.6 stenotic BAV patients using the self-expanding Evolut Pro THV. Specif-ically, the structural mechanics were evaluated by a finite-element model to estimate the deformed THV configuration in the oval bicuspid anatomy. Then, a fluid–solid interaction analysis based on the smoothed-particle hydrodynamics (SPH) technique was adopted to quantify the blood-flow patterns as well as the regions at high risk of paravalvular leakage (PVL). Simulations demonstrated a slight asymmetric and elliptical expansion of the THV stent frame in the BAV anatomy. The contact pressure between the luminal aortic root surface and the THV stent frame was determined to quantify the device anchoring force at the level of the aortic annulus and mid-ascending aorta. At late diastole, PVL was found in the gap between the aortic wall and THV stent frame. Though the modeling framework was not validated by clinical data, this study could be considered a further step towards the use of numerical simulations for the assessment of TAVI in BAV, aiming at understanding patients not suitable for device implantation on an anatomic basis

Somatic BRCA Mutation in a Cholangiocarcinoma Patient for HBOC Syndrome Detection

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