Coefficient of thermal expansion of nanostructured tungsten based coatings assessed by thermally induced substrate curvature method

The in plane coefficient of thermal expansion (CTE) and the residual stress of nanostructured W based coatings are extensively investigated. The CTE and the residual stresses are derived by means of an optimized ad-hoc developed experimental setup based on the detection of the substrate curvature by a laser system. The nanostructured coatings are deposited by Pulsed Laser Deposition. Thanks to its versatility, nanocrystalline W metallic coatings, ultra-nano-crystalline pure W and W-Tantalum coatings and amorphous-like W coatings are obtained. The correlation between the nanostructure, the residual stress and the CTE of the coatings are thus elucidated. We find that all the samples show a compressive state of stress that decreases as the structure goes from columnar nanocrystalline to amorphous-like. The CTE of all the coatings is higher than the one of the corresponding bulk W form. In particular, as the grain size shrinks, the CTE increases from 5.1 10$^{-6}$ K$^{-1}$ for nanocrystalline W to 6.6 10$^{-6}$ K$^{-1}$ in the ultra-nano-crystalline region. When dealing with amorphous W, the further increase of the CTE is attributed to a higher porosity degree of the samples. The CTE trend is also investigated as function of materials stiffness. In this case, as W coatings become softer, the easier they thermally expand.Comment: The research leading to these results has also received funding from the European Research Council Consolidator Grant ENSURE (ERC-2014-CoG No. 647554

Biochemical parameter estimation vs. benchmark functions: A comparative study of optimization performance and representation design

© 2019 Elsevier B.V. Computational Intelligence methods, which include Evolutionary Computation and Swarm Intelligence, can efficiently and effectively identify optimal solutions to complex optimization problems by exploiting the cooperative and competitive interplay among their individuals. The exploration and exploitation capabilities of these meta-heuristics are typically assessed by considering well-known suites of benchmark functions, specifically designed for numerical global optimization purposes. However, their performances could drastically change in the case of real-world optimization problems. In this paper, we investigate this issue by considering the Parameter Estimation (PE) of biochemical systems, a common computational problem in the field of Systems Biology. In order to evaluate the effectiveness of various meta-heuristics in solving the PE problem, we compare their performance by considering a set of benchmark functions and a set of synthetic biochemical models characterized by a search space with an increasing number of dimensions. Our results show that some state-of-the-art optimization methods – able to largely outperform the other meta-heuristics on benchmark functions – are characterized by considerably poor performances when applied to the PE problem. We also show that a limiting factor of these optimization methods concerns the representation of the solutions: indeed, by means of a simple semantic transformation, it is possible to turn these algorithms into competitive alternatives. We corroborate this finding by performing the PE of a model of metabolic pathways in red blood cells. Overall, in this work we state that classic benchmark functions cannot be fully representative of all the features that make real-world optimization problems hard to solve. This is the case, in particular, of the PE of biochemical systems. We also show that optimization problems must be carefully analyzed to select an appropriate representation, in order to actually obtain the performance promised by benchmark results

MedGA: A novel evolutionary method for image enhancement in medical imaging systems

Medical imaging systems often require the application of image enhancement techniques to help physicians in anomaly/abnormality detection and diagnosis, as well as to improve the quality of images that undergo automated image processing. In this work we introduce MedGA, a novel image enhancement method based on Genetic Algorithms that is able to improve the appearance and the visual quality of images characterized by a bimodal gray level intensity histogram, by strengthening their two underlying sub-distributions. MedGA can be exploited as a pre-processing step for the enhancement of images with a nearly bimodal histogram distribution, to improve the results achieved by downstream image processing techniques. As a case study, we use MedGA as a clinical expert system for contrast-enhanced Magnetic Resonance image analysis, considering Magnetic Resonance guided Focused Ultrasound Surgery for uterine fibroids. The performances of MedGA are quantitatively evaluated by means of various image enhancement metrics, and compared against the conventional state-of-the-art image enhancement techniques, namely, histogram equalization, bi-histogram equalization, encoding and decoding Gamma transformations, and sigmoid transformations. We show that MedGA considerably outperforms the other approaches in terms of signal and perceived image quality, while preserving the input mean brightness. MedGA may have a significant impact in real healthcare environments, representing an intelligent solution for Clinical Decision Support Systems in radiology practice for image enhancement, to visually assist physicians during their interactive decision-making tasks, as well as for the improvement of downstream automated processing pipelines in clinically useful measurements

Host range of mammalian orthoreovirus type 3 widening to alpine chamois

Mammalian orthoreoviruses (MRV) type 3 have been recently identified in human and several animal hosts, highlighting the apparent lack of species barriers. Here we report the identification and genetic characterization of MRVs strains in alpine chamois, one of the most abundant wild ungulate in the Alps. Serological survey was also performed by MRV neutralization test in chamois population during five consecutive years (2008-2012). Three novel MRVs were isolated on cell culture from chamois lung tissues. No respiratory or other clinical symptoms neither lung macroscopic lesions were observed in the chamois population. MRV strains were classified as MRV-3 within the lineage III, based on S1 phylogeny, and were closely related to Italian strains identified in dog, bat and diarrheic pig. The full genome sequence was obtained by next-generation sequencing and phylogenetic analyses showed that other segments were more similar to MRVs of different geographic locations, serotypes and hosts, including human, highlighting genome reassortment and lack of host specific barriers. By using serum neutralization test, a high prevalence of MRV-3 antibodies was observed in chamois population throughout the monitored period, showing an endemic level of infection and suggesting a self-maintenance of MRV and/or a continuous spill-over of infection from other animal species

Advantages and Challenges of Tailored Regimens for Drug-Resistant Tuberculosis : A {StopTB} Italia Look into the Future

The emerge of drug-resistant tuberculosis (TB) strain in recent decades is hampering the efforts of the international community to eliminate the disease worldwide. The World Health Organization (WHO) has drafted many strategies to achieve this ambitious goal. In the very beginning, the aim was to standardize inadequate regimens used in many countries and, thereafter, evolved to tackle the social determinants which hinder TB elimination. However, following the path of narrowing the clinical vision to deal with TB, there is an increased need to personalize the treatment considering both patients and pathogen unique characteristics. In our narrative review, we report the advantages and the backwards in developing a method to implement the concept of precision medicine to the treatment of TB. In this dissertation, we highlight the importance to address different aspects of the diseases encompassing the host and pathogen features, as well as the needs to further implement an adequate follow-up based on the available resources. Nevertheless, many things may hamper the vision of precision medicine in TB, such as the complexity and the costs to develop novel compounds and the costs related to global-scale implementation of patient-centered follow-up. To achieve the ambitious goal of TB elimination, a radical change in TB treatment is needed in order to give a more comprehensive approach based both on patients\u2019 peculiarities and driven by drug susceptibility tests and whole-genome sequencing

Computational Intelligence for Life Sciences

Computational Intelligence (CI) is a computer science discipline encompassing the theory, design, development and application of biologically and linguistically derived computational paradigms. Traditionally, the main elements of CI are Evolutionary Computation, Swarm Intelligence, Fuzzy Logic, and Neural Networks. CI aims at proposing new algorithms able to solve complex computational problems by taking inspiration from natural phenomena. In an intriguing turn of events, these nature-inspired methods have been widely adopted to investigate a plethora of problems related to nature itself. In this paper we present a variety of CI methods applied to three problems in life sciences, highlighting their effectiveness: we describe how protein folding can be faced by exploiting Genetic Programming, the inference of haplotypes can be tackled using Genetic Algorithms, and the estimation of biochemical kinetic parameters can be performed by means of Swarm Intelligence. We show that CI methods can generate very high quality solutions, providing a sound methodology to solve complex optimization problems in life sciences

Control Words of String Rewriting P Systems

P systems with controlled computations have been introduced and investigated in the recent past, by assigning labels to the rules in the regions of the P system and guiding the computations by control words. Here we consider string rewriting cell-like transition P system with label assigned rules working in acceptor mode and compare the obtained family of languages of control words over the rule labels with certain well-known language families. An application to chain code picture generation is also pointed out

Macroglobulinemia de Waldeström

Esta enfermedad que fue descrita por primera vez por Waldestróm, en 1944, es una afección que está íntimamente emparentada con el mieloma múltiple y es una alteración irreversible de las proteínas con el carácter de una paraproteinemia. Waldestróm señaló como signos característicos: a) La presencia en el plasma de una macroglobulina, es decir, una globulina de peso molecular muv elevado, con constante de sedimentación S20 en cantidad mayor del 15 % de las globulinas. b) La infiltración y proliferación en la médula ósea y demás órganos del SRE, de un tipo de células de estirpe reticular, pero que en su morfología recuerda a la serie linfocítica y a la plasmocítica, es decir, sería una reticulosis plasmo-linfocitaria. Dichas células elaboran un exceso de inmunoglobulinas o fragmentos de las mismas que en 1940 fueron denominadas por Apitz de “paraproteínas” consideradas por este autor como afines aunque diferentes de las gammaolobulinas normales.Facultad de Ciencias Médica

Macroglobulinemia de Waldeström

Esta enfermedad que fue descrita por primera vez por Waldestróm, en 1944, es una afección que está íntimamente emparentada con el mieloma múltiple y es una alteración irreversible de las proteínas con el carácter de una paraproteinemia. Waldestróm señaló como signos característicos: a) La presencia en el plasma de una macroglobulina, es decir, una globulina de peso molecular muv elevado, con constante de sedimentación S20 en cantidad mayor del 15 % de las globulinas. b) La infiltración y proliferación en la médula ósea y demás órganos del SRE, de un tipo de células de estirpe reticular, pero que en su morfología recuerda a la serie linfocítica y a la plasmocítica, es decir, sería una reticulosis plasmo-linfocitaria. Dichas células elaboran un exceso de inmunoglobulinas o fragmentos de las mismas que en 1940 fueron denominadas por Apitz de “paraproteínas” consideradas por este autor como afines aunque diferentes de las gammaolobulinas normales.Facultad de Ciencias Médica