Acquisizione, ricostruzione ed analisi di dati rotazionali da dispositivo mobile

Abbiamo analizzato il comportamento di dispositivi mobili allo scopo di acquisire, ricostruire ed analizzare dati rotazionali da veicoli in movimento. E' possibile ricostruire solo l'urto iniziale di un incidente tra automobili attraverso segnale GPS e accelerometri interni ai veicoli, non è possibile ricostruire l'intera dinamica dell'incidente poiché si perde la rotazione assunta dai mezzi di trasporto dopo l'urto. Per questo scopo abbiamo studiato il comportamento di un dispositivo mobile capace di percepire movimenti rotatori. Abbiamo creato un'architettura software per ricostruire graficamente ed analizzare le rotazioni di una piattaforma Arduino, ovvero un prototipo dotato di accelerometro e giroscopio. Per studiare le rotazioni è stata applicata la matematica dei quaternioni. Abbiamo trovato algoritmi che ricavano le rotazioni attraverso le velocità angolari fornite dalla piattaforma, ed anche attraverso componenti hardware specializzati in rotazioni. Entrambe le soluzioni riescono ad interpretare correttamente la rotazioni del dispositivo nell'intervallo di tempo in cui si può sviluppare un incidente.

A time-resolved fluorescence resonance energy transfer assay suitable for high-throughput screening for inhibitors of immunoglobulin E-receptor interactions

The interaction of immunoglobulin E (IgE) antibodies with the high-affinity receptor, FcεRI, plays a central role in initiating most allergic reactions. The IgE-receptor interaction has been targeted for treatment of allergic diseases, and many high-affinity macromolecular inhibitors have been identified. Small molecule inhibitors would offer significant advantages over current anti-IgE treatment, but no candidate compounds have been identified and fully validated. Here, we report the development of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay for monitoring the IgE-receptor interaction. The TR-FRET assay measures an increase in fluorescence intensity as a donor lanthanide fluorophore is recruited into complexes of site-specific Alexa Fluor 488-labeled IgE-Fc and His-tagged FcεRIα proteins. The assay can readily monitor classic competitive inhibitors that bind either IgE-Fc or FcεRIα in equilibrium competition binding experiments. Furthermore, the TR-FRET assay can also be used to follow the kinetics of IgE-Fc-FcεRIα dissociation and identify inhibitory ligands that accelerate the dissociation of preformed complexes, as demonstrated for an engineered DARPin (designed ankyrin repeat protein) inhibitor. The TR-FRET assay is suitable for high-throughput screening (HTS), as shown by performing a pilot screen of the National Institutes of Health (NIH) Clinical Collection Library in a 384-well plate format.

Get real in individual participant data (IPD) meta-analysis: a review of the methodology.

Individual participant data (IPD) meta-analysis is an increasingly used approach for synthesizing and investigating treatment effect estimates. Over the past few years, numerous methods for conducting an IPD meta-analysis (IPD-MA) have been proposed, often making different assumptions and modeling choices while addressing a similar research question. We conducted a literature review to provide an overview of methods for performing an IPD-MA using evidence from clinical trials or non-randomized studies when investigating treatment efficacy. With this review, we aim to assist researchers in choosing the appropriate methods and provide recommendations on their implementation when planning and conducting an IPD-MA. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Estimation of concentration-dependent diffusion coefficient in drying process from the space-averaged concentration versus time with experimental data

The estimation of a concentration-dependent diffusion coefficient in a drying process is known as an inverse coefficient problem. The solution is sought wherein the space-average concentration is known as function of time (mass loss monitoring). The problem is stated as the minimization of a functional and gradient-based algorithms are used to solve it. Many numerical and experimental examples that demonstrate the effectiveness of the proposed approach are presented. Thin slab drying was carried out in an isothermal drying chamber built in our laboratory. The diffusion coefficients of fructose obtained with the present method are compared with existing literature results.

Elements of natural philosophy. A text-book for high schools and academies.

Mode of access: Internet.

Analysis of HIV-1 expression level and sense of transcription by high-throughput sequencing of the infected cell.

Next-generation sequencing offers an unprecedented opportunity to jointly analyze cellular and viral transcriptional activity without prerequisite knowledge of the nature of the transcripts. SupT1 cells were infected with a vesicular stomatitis virus G envelope protein (VSV-G)-pseudotyped HIV vector. At 24 h postinfection, both cellular and viral transcriptomes were analyzed by serial analysis of gene expression followed by high-throughput sequencing (SAGE-Seq). Read mapping resulted in 33 to 44 million tags aligning with the human transcriptome and 0.23 to 0.25 million tags aligning with the genome of the HIV-1 vector. Thus, at peak infection, 1 transcript in 143 is of viral origin (0.7%), including a small component of antisense viral transcription. Of the detected cellular transcripts, 826 (2.3%) were differentially expressed between mock- and HIV-infected samples. The approach also assessed whether HIV-1 infection modulates the expression of repetitive elements or endogenous retroviruses. We observed very active transcription of these elements, with 1 transcript in 237 being of such origin, corresponding on average to 123,123 reads in mock-infected samples (0.40%) and 129,149 reads in HIV-1-infected samples (0.45%) mapping to the genomic Repbase repository. This analysis highlights key details in the generation and interpretation of high-throughput data in the setting of HIV-1 cellular infection.

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.

Multiplex network analysis with application to biological high-throughput data

In questa tesi vengono studiate alcune caratteristiche dei network a multiplex; in particolare l'analisi verte sulla quantificazione delle differenze fra i layer del multiplex. Le dissimilarita sono valutate sia osservando le connessioni di singoli nodi in layer diversi, sia stimando le diverse partizioni dei layer. Sono quindi introdotte alcune importanti misure per la caratterizzazione dei multiplex, che vengono poi usate per la costruzione di metodi di community detection . La quantificazione delle differenze tra le partizioni di due layer viene stimata utilizzando una misura di mutua informazione. Viene inoltre approfondito l'uso del test dell'ipergeometrica per la determinazione di nodi sovra-rappresentati in un layer, mostrando l'efficacia del test in funzione della similarita dei layer. Questi metodi per la caratterizzazione delle proprieta dei network a multiplex vengono applicati a dati biologici reali. I dati utilizzati sono stati raccolti dallo studio DILGOM con l'obiettivo di determinare le implicazioni genetiche, trascrittomiche e metaboliche dell'obesita e della sindrome metabolica. Questi dati sono utilizzati dal progetto Mimomics per la determinazione di relazioni fra diverse omiche. Nella tesi sono analizzati i dati metabolici utilizzando un approccio a multiplex network per verificare la presenza di differenze fra le relazioni di composti sanguigni di persone obese e normopeso.

Sviluppo di un modulo di acquisizione dati ad elevato throughput da amplificatori per elettrofisiologia

Lo scopo dell'elaborato di tesi è la progettazione e lo sviluppo di alcuni moduli di un software per la lettura ad elevato throughput di dati da particolari dispositivi per elettrofisiologia sviluppati dall'azienda Elements s.r.l. Elements produce amplificatori ad alta precisione per elettrofisiologia, in grado di misurare correnti a bassa intensità prodotte dai canali ionici. Dato il grande sviluppo che l'azienda sta avendo, e vista la previsione di introdurre sul mercato nuovi dispositivi con precisione e funzionalità sempre migliori, Elements ha espresso l'esigenza di un sistema software che fosse in grado di supportare al meglio i dispositivi già prodotti, e, soprattutto, prevedere il supporto dei nuovi, con prestazioni molto migliori del software già sviluppato da loro per la lettura dei dati. Il software richiesto deve fornire una interfaccia grafica che, comunicando con il dispositivo tramite USB per leggere dati da questo, provvede a mostrarli a schermo e permette di registrarli ed effettuare basilari operazioni di analisi. In questa tesi verranno esposte analisi, progettazione e sviluppo dei moduli di software che si interfacciano direttamente con il dispositivo, quindi dei moduli di rilevamento, connessione, acquisizione ed elaborazione dati.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

Real-time fieldbus communications using Profibus networks

This paper provides a comprehensive study on how to use Profibus fieldbus networks to support real-time industrial communications, that is, on how to ensure the transmission of real-time messages within a maximum bound time. Profibus is base on a simplified timed token (TT) protocol, which is a well-proved solution for real-time communication systems. However, Profibus differs with respect to the TT protocol, thus preventing the application of the usual TT protocol real-time analysis. In fact, real-time solutions for networks based on the TT protocol rely on the possibility of allocating specific bandwidth for the real-time traffic. This means that a minimum amount of time is always available, at each token visit, to transmit real-time messages, transversely, with the Profibus protocol, in the worst case, only one real-time message is processed per token visit. The authors propose two approaches to guarantee the real-time behavior of the Profibus protocol: (1) an unconstrained low-priority traffic profile; and (2) a constrained low-priority traffic profile. The proposed analysis shows that the first profile is a suitable approach for more responsive systems (tighter deadlines), while the second allows for increased nonreal-time traffic throughput

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.

Validation of real-time methylation-specific PCR to determine O6-methylguanine-DNA methyltransferase gene promoter methylation in glioma.

Epigenetic silencing of the DNA repair protein O(6)-methylguanine-DNA methyltransferase (MGMT) by promoter methylation predicts successful alkylating agent therapy, such as with temozolomide, in glioblastoma patients. Stratified therapy assignment of patients in prospective clinical trials according to tumor MGMT status requires a standardized diagnostic test, suitable for high-throughput analysis of small amounts of formalin-fixed, paraffin-embedded tumor tissue. A direct, real-time methylation-specific PCR (MSP) assay was developed to determine methylation status of the MGMT gene promoter. Assay specificity was obtained by selective amplification of methylated DNA sequences of sodium bisulfite-modified DNA. The copy number of the methylated MGMT promoter, normalized to the beta-actin gene, provides a quantitative test result. We analyzed 134 clinical glioma samples, comparing the new test with the previously validated nested gel-based MSP assay, which yields a binary readout. A cut-off value for the MGMT methylation status was suggested by fitting a bimodal normal mixture model to the real-time results, supporting the hypothesis that there are two distinct populations within the test samples. Comparison of the tests showed high concordance of the results (82/91 [90%]; Cohen's kappa = 0.80; 95% confidence interval, 0.82-0.95). The direct, real-time MSP assay was highly reproducible (Pearson correlation 0.996) and showed valid test results for 93% (125/134) of samples compared with 75% (94/125) for the nested, gel-based MSP assay. This high-throughput test provides an important pharmacogenomic tool for individualized management of alkylating agent chemotherapy.