1,720,979 research outputs found
Study and Design of Deep Learning Computer-Aided Diagnosis Systems Based on Biomedical Images and Signals
No full textThis Ph.D. thesis aims to describe the research works conducted for the design, the development and the evaluation of innovative Computer-Aided Diagnosis (CAD) systems based on machine learning and deep learning techniques. Several CAD solutions were developed in different medical applications trying to ensure, when possible, three main CAD requirements: improve clinicians performance, reduce or at least not increase clinicians time and integrate the CAD solution in standard procedures. The proposed applications involved images and signals processing; the firsts required the use of different deep learning models to face classification, detection and segmentation problems, while the latter allowed to investigate machine learning as signal processing technique for movement disorder analysis and for a more speculative research in the rehabilitation field. In order to properly validate the proposed algorithms, all the methodologies were applied on real data provided by clinicians, public datasets or specific acquisitions.
Potentialities, challenges and drawbacks about deep learning for medical imaging analysis are discussed in two medical fields, digital pathology and radiology, and complete pipelines are proposed to accomplish three clinical practices: global glomerulosclerosis analysis for Chronic Kidney Disease evaluation, kidneys volume analysis for Autosomal Dominant Polycystic Kidney Disease evaluation and organs segmentation for generic volume quantification. Each study case aims to identify and overcome the limitation of classical image processing techniques, and paves the way towards the clinical use of CAD systems based on deep learning. A second part of this thesis focuses on machine learning and deep learning for signals processing; deep neural networks were investigated for movement disorders analysis and a particular neural model for surface electromyography analysis has been proposed for the evaluation of complex muscle activation patterns, useful in the rehabilitation field. The developed solutions for signals and images processing, were compared with literature standards and, if possible, a personalised classical pipelines has been proposed and customised to face each clinical challenge.
The thesis is divided into six chapters. The first chapter provides an introduction about the reference context. The following chapter two describes the state of the art about traditional CAD systems based on conventional machine learning algorithms, and the novelty that deep learning techniques bring to CADs and medical practices; description of the main convolutional neural network models and autoencoders, and literature about the application of deep learning and machine learning to the concerned medical fields are reported. Chapters three, four and five report the original contribution about the application of deep learning and machine learning techniques to the two types of medical data: images and signals; in detail, chapter three reports the applications in the clinical areas of digital pathology and radiology, focusing on the development of full pipelines based on image analysis; chapter four shows a more speculative research work for signal processing, focusing on the application of undercomplete autoencoders for surface electromyography analysis; chapter five reports the applications of deep neural networks for diseases assessment and grading in subjects affected by movement disorders. The analysed study cases and the contributions reported in this thesis were compared with standard processing techniques ad-hoc developed. Finally, the conclusions about the research works and proposals for future researches are reported in chapter six
Biogenic extracellular synthesis of gold and silver nanoparticles by Trichoderma harzianum and Trichoderma longibrachiatum and their effectiveness against seed-borne fungal pathogens.
No full textNanoparticles present a multifunctional platform for a diverse range of applications in the modern agricultural concept of precision farming due to their small size, high surface to volume ratio and unique optical properties. Antimicrobial nano-materials, pathogen detection by the use of nano-sensors, spray-induced gene silencing (SIGS) are only some of the potentialities of the nanotechnology in crop protection. The biosynthesis of gold and silver nanoparticles (AuNPs and AgNPs) by
Trichoderma harzianum and T. longibrachiatum was evaluated. Fungi were isolated from deep-sterilized tissues of Cupressus sempervirens and Gladiolus cv. ‘Red Balance’, respectively, and were molecularly identified using ITS and tef-1alfa sequences analyzed by TrichOKEY and TrichoBLAST. Cell-free extracts of the fungi were challenged with 1 mM silver nitrate and 0.5 mM tetracholoroauric acid solutions. The formed nanoparticles were characterized by means of spectroscopic and microscopic analyses including UV-VIS spectroscopy, TEM and XRD, EDAX and FT-IR analyses. Antifungal activity using a microdilution assay in 96-well microtiter plates against Colletotrichum lupini, Fusarium oxysporum f. sp. basilici and Botrytis cinerea was assessed. The results were transformed to percentage of controls and the IC50 and IC90 values were graphically obtained from the dose-response curves. The AgNPs of T. harzianum and T. longibrachiatum strongly reduced the growth rate of all tested pathogens (85-100%) and only the AuNPs of T. longibrachiatum gave rise to a reduction of growth between 18 and 56% depending on the pathogen tested. The promising results obtained open up opportunities for further research on effective and
ecofriendly solutions for the control of seed-borne diseases
A comparative study of Neogymnomyces virgineus, a new keratinolytic species from dung, and its relationships with the Onygenales
No full textIsolations of onygenalean fungi were made recently from different dung samples from Italy.. A striking snow-white species with gymnothecial ascomata, developed in damp chamber on dormouse dung collected in a cave, was subjected to keratinolytic tests and morphological, cultural, and phylogenetic studies. The keratinolytic ability of this species, associated with a Chrysosporium anamorph and a sexual state of appendiculate reticuloperidia and oblate ascospores, allows it to be accomodated in Onygenaceae. White ascomata, blunt or subcapitate peridial appendages, pitted ascospores, and tuberculate conidia suggest it to be a new Neogymnomyces, and this was confirmed by parsimony analyses of LSU and ITS nrDNA sequences. Following recent phylogenetic analyses, the morphological and physiological features of order Onygenales and its families are re–examined and discussed. After the introduction of a new species, Neogymnomyces is reviewed and compared with all other genera in Onygenaceae. The Chrysosporium imperfect state of Neogymnomyces virgineus is described and compared to the anamorph of N. demonbreunii. It is also compared to the atypical Chrysosporium merdarium and to several other Chrysosporium species with echinulate to verrucose–tuberculate conidia, isolated from guano, dung, and nitrogen–rich soils in caves. The onygenalean fungi isolated from any kind of dung are discussed and their facultative coprophily ascribed to variable faecal contents of keratin or other degradable substances. A key to the families and genera of the Onygenales is provided
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Innovative Approaches for Crop Improvement and Sustainable Management of Plant Disease in the Post-Genomic Era
Full text linkSafeguarding food supply in a world environment subject to sudden climate change, reducing the use of anthropogenic sources of pollution as much as possible, and using crops that must necessarily be increasingly resilient to biotic and abiotic stresses is a mandatory and ambitious necessity for the foreseeable future [...
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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