First evidences of the effect of polyunsaturated fatty acids in fish neural activity and their implications in behaviour

Programa de doctorado: Acuicultura: producción controlada de animales acuáticos; Grupo de Investigación en Acuicultura (GIA)

Segmentazione di immagini mammografiche con convolutional neural networks

Il tumore al seno si colloca al primo posto per livello di mortalità tra le patologie tumorali che colpiscono la popolazione femminile mondiale. Diversi studi clinici hanno dimostrato come la diagnosi da parte del radiologo possa essere aiutata e migliorata dai sistemi di Computer Aided Detection (CAD). A causa della grande variabilità di forma e dimensioni delle masse tumorali e della somiglianza di queste con i tessuti che le ospitano, la loro ricerca automatizzata è un problema estremamente complicato. Un sistema di CAD è generalmente composto da due livelli di classificazione: la detection, responsabile dell’individuazione delle regioni sospette presenti sul mammogramma (ROI) e quindi dell’eliminazione preventiva delle zone non a rischio; la classificazione vera e propria (classification) delle ROI in masse e tessuto sano. Lo scopo principale di questa tesi è lo studio di nuove metodologie di detection che possano migliorare le prestazioni ottenute con le tecniche tradizionali. Si considera la detection come un problema di apprendimento supervisionato e lo si affronta mediante le Convolutional Neural Networks (CNN), un algoritmo appartenente al deep learning, nuova branca del machine learning. Le CNN si ispirano alle scoperte di Hubel e Wiesel riguardanti due tipi base di cellule identificate nella corteccia visiva dei gatti: le cellule semplici (S), che rispondono a stimoli simili ai bordi, e le cellule complesse (C) che sono localmente invarianti all’esatta posizione dello stimolo. In analogia con la corteccia visiva, le CNN utilizzano un’architettura profonda caratterizzata da strati che eseguono sulle immagini, alternativamente, operazioni di convoluzione e subsampling. Le CNN, che hanno un input bidimensionale, vengono solitamente usate per problemi di classificazione e riconoscimento automatico di immagini quali oggetti, facce e loghi o per l’analisi di documenti.

Integrating wireless sensor networks and internet of things: A coap-based approach

L'obiettivo su cui è stata basata questa Tesi di Laurea è stato quello di integrare la tecnologia delle Wireless Sensor Networks (WSN) al contesto dell'Internet delle cose (IoT). Per poter raggiungere questo obiettivo, il primo passo è stato quello di approfondire il concetto dell'Internet delle cose, in modo tale da comprendere se effettivamente fosse stato possibile applicarlo anche alle WSNs. Quindi è stata analizzata l'architettura delle WSNs e successivamente è stata fatta una ricerca per capire quali fossero stati i vari tipi di sistemi operativi e protocolli di comunicazione supportati da queste reti. Infine sono state studiate alcune IoT software platforms. Il secondo passo è stato quindi di implementare uno stack software che abilitasse la comunicazione tra WSNs e una IoT platform. Come protocollo applicativo da utilizzare per la comunicazione con le WSNs è stato usato CoAP. Lo sviluppo di questo stack ha consentito di estendere la piattaforma SensibleThings e il linguaggio di programmazione utilizzato è stato Java. Come terzo passo è stata effettuata una ricerca per comprendere a quale scenario di applicazione reale, lo stack software progettato potesse essere applicato. Successivamente, al fine di testare il corretto funzionamento dello stack CoAP, è stata sviluppata una proof of concept application che simulasse un sistema per la rilevazione di incendi. Questo scenario era caratterizzato da due WSNs che inviavano la temperatura rilevata da sensori termici ad un terzo nodo che fungeva da control center, il cui compito era quello di capire se i valori ricevuti erano al di sopra di una certa soglia e quindi attivare un allarme. Infine, l'ultimo passo di questo lavoro di tesi è stato quello di valutare le performance del sistema sviluppato. I parametri usati per effettuare queste valutazioni sono stati: tempi di durata delle richieste CoAP, overhead introdotto dallo stack CoAP alla piattaforma Sensible Things e la scalabilità di un particolare componente dello stack. I risultati di questi test hanno mostrato che la soluzione sviluppata in questa tesi ha introdotto un overheadmolto limitato alla piattaforma preesistente e inoltre che non tutte le richieste hanno la stessa durata, in quanto essa dipende dal tipo della richiesta inviata verso una WSN. Tuttavia, le performance del sistema potrebbero essere ulteriormente migliorate, ad esempio sviluppando un algoritmo che consenta la gestione concorrente di richieste CoAP multiple inviate da uno stesso nodo. Inoltre, poichè in questo lavoro di tesi non è stato considerato il problema della sicurezza, una possibile estensione al lavoro svolto potrebbe essere quello di implementare delle politiche per una comunicazione sicura tra Sensible Things e le WSNs.

Reticulate eruptions. Part 1: Vascular networks and physiology

Reticulate pattern is one of the most important dermatological signs of a pathological process involving the superficial vascular networks. Vascular malformations, such as cutis marmorata congenita telangiectasia and benign forms of livedo reticularis, and sinister conditions, such as meningococcal meningitis or Sneddon's syndrome, can all present with a reticulate pattern. The clinical presentation and morphology is determined by the nature and extent of the underlying pathology and the involvement of a particular vascular network. This review has been divided into four instalments. In the present paper, we discuss the anatomy and physiology of the complex network of vascular structures that support the function of the skin and subcutis.

Comparative Study of Informal Health Care Networks and Elderly Health Status in Argentina and Cuba

The objective of this study is to evaluate the impact of informal care support networks on the health status, life satisfaction, happiness and anxiety of elderly individuals in Argentina and Cuba. Recent economic changes, demographic changes, the structure of families and changes in women?s labor participation have affected the availability of informal care. Additionally, the growing number of elderly as a percentage of total population has significant implications for both formal and informal care in Argentina and Cuba. Methods: The SABE - Survey on Health, Well-Being, and Aging in Latin America and the Caribbean, 2000 was used as the data source. The survey has a sample of 10,656 individuals aged 60 years and older residing in private households occupied by permanent dwellers in 7 cities in the Latin American and Caribbean region. My study will focus on the Buenos Aires and Havana samples in which there were 1043 individuals and 1905 individuals respectively. General sampling design was used to establish comparability between countries. Individuals requiring assistance are surveyed on their source of help and the relative impact of informal versus paid help is measured for this group. Other measures of social support (number of living children, companionship and number of individuals living in the same dwelling) are used to measure networks for the full sample. Multivariate probit regression analyses were run separately for Cuba and for Argentina to evaluate the marginal impacts of the types of social support on health status, life satisfaction, happiness and anxiety. Results: For Argentina, almost all of the family help variables positively impact good health. Getting help from most other members of the family negatively impacts satisfaction with life. Happiness is affected differently by each of the family help variables but community support increases the likelihood of being happy. Although none of the family or community help variables show statistical significance, most negatively affect anxiety levels. In Cuba, all of the social support variables have a positive marginal impact on the health status of the elderly. In this case, some of the family and community help variables have a negative marginal impact on life satisfaction; however, it appears that having those closest to the elderly, children, spouse, or other family, positively impacts life satisfaction. Most of the support variables negatively impact happiness. Receiving help from a child, spouse or parent is associated with a marginal increase in anxiety, whereas receiving help from a grandchild, another family member or a friend actually reduces anxiety. Discussion: The study highlights the necessity for enhancing the coordination of various care networks in order to provide adequate care and reduce the burdens of old age on the individual, family and society and the need for consistent support for the caregivers. More qualitative work should be done to identify how support is given and what comprises the support. The constant change and advancement of the world, and the growth of the Latin American and Caribbean region, suggests that more updates studies need to be done.

COMPARATIVE STUDY OF INFORMAL HEALTH CARE NETWORKS AND ELDERLY HEALTH STATUS IN ARGENTINA AND CUBA

This study will explore familial and friend support networks and living arrangements among elderly individuals in Latin America and the impact that this type of support has on the health of the elderly individuals in the countries of interest. Using data from the Survey on Health and Well-Being of Elders (SABE) from 1999-2000, I will explore which type of support has a larger impact on overall health. I will also measure differences in unmet needs for certain health services. This topic is particularly interesting because it will help to uncover what policies are best for aiding in the healthcare of the elderly in aging population. Lastly, the investigation of this topic will allow me to draw conclusions about the most effective means of social and public policy for the elderly community and provide me with information about the role of both informal provisions of support from family and friends, and formal provisions of support from the government. My primary focus will be on Argentina, using Buenos Aires as the sample city, and Cuba, using Havana as the sample city. These two countries have increasingly aging populations, poorer resources and vast inequalities, but, extremely different political, economic and cultural situations. Comparing the two countries will further allow me to determine correlations between health and the existence of support networks, as well as provide me with information to make more general claims that may be of use in the United States. Argentina is particularly interesting to me because of my abroad experience and homestay experience with an older Argentine woman who lived alone but depended upon her family for many healthcare needs, doctors’ visits and general well-being. In Argentina, I experienced a different form of living than I am used to in the United States, where many older individuals or couples live in nursing homes or assisted living facilities rather than alone or with family. The changing economic climate of the two countries coupled with labor patterns of women returning to work at rapid rates indicates that policies cannot just rely on either the formal or informal sector but require a combination of the two sectors working together.This paper will first give background on the difference in the economies and the health care systems in Argentina and Cuba and will show why it interesting to study and compare these two countries. I will then discuss the health status of the elderly in each population as well as discuss the informal care networks and the role of family in each country. This section will then be followed by a description of the data and methods used. I will end by drawing conclusions about the study and the outcomes, and then I will attempt to make suggestions about effective health care policies for the elderly.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Dissociated lateralization of transient and sustained blood oxygen level-dependent signal components in human primary auditory cortex

Among other auditory operations, the analysis of different sound levels received at both ears is fundamental for the localization of a sound source. These so-called interaural level differences, in animals, are coded by excitatory-inhibitory neurons yielding asymmetric hemispheric activity patterns with acoustic stimuli having maximal interaural level differences. In human auditory cortex, the temporal blood oxygen level-dependent (BOLD) response to auditory inputs, as measured by functional magnetic resonance imaging (fMRI), consists of at least two independent components: an initial transient and a subsequent sustained signal, which, on a different time scale, are consistent with electrophysiological human and animal response patterns. However, their specific functional role remains unclear. Animal studies suggest these temporal components being based on different neural networks and having specific roles in representing the external acoustic environment. Here we hypothesized that the transient and sustained response constituents are differentially involved in coding interaural level differences and therefore play different roles in spatial information processing. Healthy subjects underwent monaural and binaural acoustic stimulation and BOLD responses were measured using high signal-to-noise-ratio fMRI. In the anatomically segmented Heschl's gyrus the transient response was bilaterally balanced, independent of the side of stimulation, while in opposite the sustained response was contralateralized. This dissociation suggests a differential role at these two independent temporal response components, with an initial bilateral transient signal subserving rapid sound detection and a subsequent lateralized sustained signal subserving detailed sound characterization.