La-Ag-Co perovskites for the catalytic flameless combustion of methane

Ag represents an interesting dopant for the highly active LaCoO3 perovskites used for the catalytic flameless combustion (CFC) of methane, due to its ability to adsorb and activate oxygen and to the possibility of incorporation into the framework as Ag+ or Ag2+, with formation of oxygen vacancies. In the present work we compared the catalytic activity and resistance to sulphur poisoning of a series of LaCoO3, x%Ag/LaCoO3, La1-xAgxCoO3 samples (nominal composition), the latter two notations indicating post-synthesis Ag loading or direct incorporation during the synthesis, respectively. The samples were prepared by flame pyrolysis (FP) and by the sot-gel (SG) method, leading to different particle size and possibly to different incorporation degree of the dopant, quantified by Rietveld refinement of XRD patterns. Higher activity was observed, in general, with fresh catalysts synthesised by FP. The SG samples demonstrated a slightly better resistance to sulphur poisoning when considering the conversion decrease between the fresh and the poisoned samples, due to lower surface exposure. However, interesting data have been obtained with some of the Ag-doped poisoned FP samples, performing even better than the fresh SG-prepared ones. Ag addition led to a complex change of activity and resistance to poisoning. The activity of FP-prepared samples doped with a small amount of Ag (e.g. 5 mol%) was indeed lower than that of the undoped LaCoO3. By contrast, a further increase of Ag concentration led to increasing catalytic activity, mainly when big extra framework Ag particles were present. By contrast, for SG samples a low Ag amount was beneficial for activity, due to an increased reducibility of Co3+

Hot isostatic pressing and heat treatments of LPBFed CoCuFeMnNiTi0.13 high-entropy alloy: microstructure and mechanical properties

The present work explores the possibility of processing a CoCuFeMnNiTi0.13 high-entropy alloy by laser powder bed fusion (LPBF). The alloy, produced under optimised processing conditions, presents good densification but also hot cracks, caused by the liquation of an inter-dendritic Cu-rich phase. Microstructure of the as-built alloy is characterised by face centred cubic (FCC) columnar grains, containing Cu-poor dendrites and Cu-rich inter-dendritic areas. The alloy, which was designed to be strengthened by spinodal decomposition and precipitation, was subjected to different thermo-mechanical treatments to try and improve its properties. Direct ageing and solution treatment and ageing produced a strong but brittle material (tensile strength of 683 MPa and elongation to failure of 1.3%), whereas hot isostatic pressing followed by controlled cooling was able to heal pores and cracks while triggering the desired microstructural transformations (spinodal decomposition and precipitation). This resulted into a balanced set of mechanical properties (tensile strength of 473 MPa and elongation to failure of 7.6%). This work shows that proper post-processing can mitigate the issues typically affecting LPBF fabricated HEAs, producing tailored microstructures with satisfactory mechanical performances

Cool Core Clusters from Cosmological Simulations

We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non-cool-core systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and in observations. Furthermore, we also find that simulated cool-core clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic cool-core structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.Comment: 6 pages, 4 figures, accepted in ApJL, v2 contains some modifications on the text (results unchanged

Cardiac resynchronization therapy: a comparison among left ventricular bipolar, quadripolar and active fixation leads

We evaluated the performance of 3 different left ventricular leads (LV) for resynchronization therapy: bipolar (BL), quadripolar (QL) and active fixation leads (AFL). We enrolled 290 consecutive CRTD candidates implanted with BL (n = 136) or QL (n = 97) or AFL (n = 57). Over a minimum 10 months follow-up, we assessed: (a) composite technical endpoint (TE) (phrenic nerve stimulation at 8 [email protected] ms, safety margin between myocardial and phrenic threshold <2V, LV dislodgement and failure to achieve the target pacing site), (b) composite clinical endpoint (CE) (death, hospitalization for heart failure, heart transplantation, lead extraction for infection), (c) reverse remodeling (RR) (reduction of end systolic volume >15%). Baseline characteristics of the 3 groups were similar. At follow-up the incidence of TE was 36.3%, 14.3% and 19.9% in BL, AFL and QL, respectively (p < 0.01). Moreover, the incidence of RR was 56%, 64% and 68% in BL, AFL and QL respectively (p = 0.02). There were no significant differences in CE (p = 0.380). On a multivariable analysis, \u201cnon-BL leads\u201d was the single predictor of an improved clinical outcome. QL and AFL are superior to conventional BL by enhancing pacing of the target site: AFL through prevention of lead dislodgement while QL through improved management of phrenic nerve stimulation

Night blindness in cystic fibrosis : the key role of vitamin A in the digestive system

Vitamin A is a fundamental micronutrient that regulates various cellular patterns. Vitamin A deficiency (VAT) is a worldwide problem and the primary cause of nocturnal blindness especially in low income countries. Cystic fibrosis (CF) is a known risk factor of VAD because of liposoluble vitamin malabsorption due to pancreatic insufficiency. We describe a case of a 9-year-old girl who experienced recurrent episodes of nocturnal blindness due to profound VAD. This little girl is paradigmatic for the explanation of the key role of the gut\u2013liver axis in vitamin A metabolism. She presents with meconium ileus at birth, requiring intestinal resection that led to a transient intestinal failure with parenteral nutrition need. In addition, she suffered from cholestatic liver disease due to CF and intestinal failure-associated liver disease. The interaction of pancreatic function, intestinal absorption and liver storage is fundamental for the correct metabolism of vitamin A

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of pathology-driven anatomical remodeling is a crucial step for the diagnosis and treatment of many conditions. Deep learning approaches have recently achieved wide success in the analysis of medical images, but they lack interpretability in the feature extraction and decision processes. In this work, we propose a new interpretable deep learning model for shape analysis. In particular, we exploit deep generative networks to model a population of anatomical segmentations through a hierarchy of conditional latent variables. At the highest level of this hierarchy, a two-dimensional latent space is simultaneously optimised to discriminate distinct clinical conditions, enabling the direct visualisation of the classification space. Moreover, the anatomical variability encoded by this discriminative latent space can be visualised in the segmentation space thanks to the generative properties of the model, making the classification task transparent. This approach yielded high accuracy in the categorisation of healthy and remodelled left ventricles when tested on unseen segmentations from our own multi-centre dataset as well as in an external validation set, and on hippocampi from healthy controls and patients with Alzheimer's disease when tested on ADNI data. More importantly, it enabled the visualisation in three-dimensions of both global and regional anatomical features which better discriminate between the conditions under exam. The proposed approach scales effectively to large populations, facilitating high-throughput analysis of normal anatomy and pathology in large-scale studies of volumetric imaging

3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders

Accurate segmentation of heart structures imaged by cardiac MR is key for the quantitative analysis of pathology. High-resolution 3D MR sequences enable whole-heart structural imaging but are time-consuming, expensive to acquire and they often require long breath holds that are not suitable for patients. Consequently, multiplanar breath-hold 2D cines sequences are standard practice but are disadvantaged by lack of whole-heart coverage and low through-plane resolution. To address this, we propose a conditional variational autoencoder architecture able to learn a generative model of 3D high-resolution left ventricular (LV) segmentations which is conditioned on three 2D LV segmentations of one short-axis and two long-axis images. By only employing these three 2D segmentations, our model can efficiently reconstruct the 3D high-resolution LV segmentation of a subject. When evaluated on 400 unseen healthy volunteers, our model yielded an average Dice score of 87.92 ± 0.15 and outperformed competing architectures (TL-net, Dice score = 82.60 ± 0.23, p = 2.2 · 10 -16 )

Microstructure and preliminary fatigue analysis on AlSi10Mg samples manufactured by SLM

Nowadays, selective laser melting (SLM) is considered as the most challenging technology for manufacturing complex components in different industrial fields, such as biomedical, aerospace and racing. It is well-known that SLM may yield to microstructures significantly different from those obtained by conventional casting, thus affecting the mechanical properties of the component. In the present paper, microstructural and mechanical tests were carried out on AlSi10Mg samples manufactured by SLM technique in the XY building configuration. Homogeneous composition and typical microstructures were achieved for all the investigated samples. The mechanical properties were assessed through a tensile test and through the Impulse Excitation Technique (IET). The feasibility of ultrasonic Very High Cycle Fatigue (VHCF) tests with Gaussian specimens characterized by large loaded volumes (risk-volumes) was also experimentally verified in the paper. A Gaussian specimen was designed and manufactured. A preliminary ultrasonic test was then carried out on the manufactured specimen and the fracture surface was finally investigated

Design for the Damping of a Railway Collector Based on the Application of Shape Memory Alloys

A new design of a Cu based SMA/GFRP lateral horn of a railway collector is proposed. Synergistic contribution of the performance parameters associated with the SMA, including specific damping, specific stiffness, and volume fraction, as well as those associated with the host composite such as flexural rigidity, SMA through-the-thickness location, and SMA-host interfacial strength, is taken into account. The aim is to increase the structural damping of the first flexural mode of the horn without significantly changing its flexural stiffness and weight. The focus of this work also applies to manufacturability and the cost effectiveness of the component for future industrial production