Analisi della suscettività da frane rapide nell'Appennino Bolognese

Nel presente lavoro di tesi, partendo dall’Inventario del Dissesto della Regione Emilia – Romagna sono stati individuati i fenomeni di colata rapida di detrito che hanno interessato l’Appennino Bolognese negli ultimi anni. Si tratta di fenomeni rapidi, altamente pericolosi e ancora poco studiati. Ad ogni evento individuato è stata associata la precipitazione di innesco, caratterizzandola in termini di durata (D) e intensità (I) al fine di confrontarla con le soglie probabilistiche bayesiane proposte da Berti et al. (2012). Nella maggior parte dei casi è stato verificato che gli eventi considerati ricadono al di sopra delle soglie considerate come limite accettabile. Successivamente è stato applicato il metodo fisicamente basato SHALSTAB (SHALlow STABility model. Montgomery & Dietricht, 1994) al fine di valutarne la capacità previsionale al variare dei dati di input. Ne è emerso che tale metodo risulta fortemente influenzato dalla topografia. Dai dati esaminati, è stato dedotto che i fenomeni di colata rapida si sono innescati in seguito a eventi di pioggia fortemente transitori, pertanto l’applicazione del metodo SHALSTAB, che presuppone flusso allo stato stazionario mal si adatta a riprodurre questi casi.

Flipped classroom ed apprendimento: un'esperienza di attività propedeutica nella scuola secondaria di primo grado

La Flipped Classroom è una metodologia didattica innovativa che prevede una inversione dei momenti classici delle didattica: la lezione frontale a scuola e lo studio individuale a casa. L’idea alla base della Flipped Classroom è utilizzare la tecnologia moderna per diffondere i contenuti fuori dall’orario scolastico così da concentrare poi le ore di lezione sull’elaborazione dei contenuti stessi. In questo modo si riporta l’attenzione didattica sull’elaborazione dei contenuti piuttosto che sul loro ascolto passivo. A seguito dello studio teorico del metodo Flipped ho fatto una esperienza di tirocinio presso una classe terza della Scuola secondaria di primo grado "`Il Guercino"' dell'IC9, in collaborazione con la professoressa Leone, per applicare questa metodologia didattica. Una volta in classe, io e la professoressa, abbiamo considerato più efficace e utile, per gli studenti con cui lavoravamo, fare propedeutica piuttosto che Flipped Classroom. L’esperienza di tirocinio è stata conclusa con un questionario per valutare l’utilizzo, da parte dei nostri studenti, della piattaforma didattica Moodle, in uso nella scuola. I risultati dell’analisi delle risposte è stato conforme a quanto da noi atteso: data l’età i nostri studenti non avevano il giusto grado di autonomia per lavorare con la metodologia della Flipped Classroom.

Risposta delle comunità bentoniche della zona intertidale di coste sabbiose a un evento estremo di mareggiata: il caso di Cesenatico

L’aumento della frequenza di accadimento e dell’intensità di eventi di tempesta rappresenta una seria minaccia per gli ambienti costieri, in particolare per quelli dominati da spiagge sabbiose. Nel seguente lavoro di tesi si è voluto approfittare di un evento di flooding che ha interessato la spiaggia di Cesenatico (Febbraio 2015), provocando un lieve arretramento della linea di riva, per valutare la risposta del comparto macrobentonico a uno shift da zona intertidale a quella di primo subtidale. I dati relativi al periodo post-disturbo (after), mostrano variazioni sia dal punto di vista dell’ambiente fisico che delle comunità bentoniche ad esso associate; per quanto riguarda i campioni del 2015, si è osservata una diminuzione della media granulometrica e un aumento della materia organica rispetto al 2011 (before). Si evidenziano differenze anche tra le comunità bentoniche before e after l’evento, con valori di abbondanza, numero di taxa e diversità maggiori in after, nonché dell’intera struttura di comunità in cui si osservano variazioni di dominanza di particolari specie e l’insediamento di specie non presenti prima dell’evento. In before c’è una dominanza di S. squamata, un polichete fossatorio tipico dell’intertidale. In after è risultato che molte più specie concorrono nel determinare i pattern osservati, ed emerge una netta dominanza di L. mediterraneum e dei tanaidacei del genere Apseudes. I valori delle variabili ambientali e biotiche sono stati utilizzati per costruire un modello previsionale FNB (fuzzy naive Bayes) che è stato utilizzato con i dati abiotici relativi all’after per prevedere i pattern di comunità. Dalle simulazioni si osserva che i pattern spaziali del macrobenthos seguono l’evoluzione dell’intero sistema, confermando uno shift da intertidale a primo subtidale e può essere usato come base per comprendere gli effetti di un flooding costiero su sistemi vulnerabili qual è la spiaggia di Cesenatico.

POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Multiple Testing With an Empirical Alternative Hypothesis

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for use of an empirical alternative hypothesis to increase by 50% or more the number of true positives identified at a given significance level.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.

ASSESSING THE UNRELIABILITY OF THE MEDICAL LITERATURE: A RESPONSE TO "WHY MOST PUBLISHED RESEARCH FINDINGS ARE FALSE"

A recent article in this journal (Ioannidis JP (2005) Why most published research findings are false. PLoS Med 2: e124) argued that more than half of published research findings in the medical literature are false. In this commentary, we examine the structure of that argument, and show that it has three basic components: 1)An assumption that the prior probability of most hypotheses explored in medical research is below 50%. 2)Dichotomization of P-values at the 0.05 level and introduction of a “bias” factor (produced by significance-seeking), the combination of which severely weakens the evidence provided by every design. 3)Use of Bayes theorem to show that, in the face of weak evidence, hypotheses with low prior probabilities cannot have posterior probabilities over 50%. Thus, the claim is based on a priori assumptions that most tested hypotheses are likely to be false, and then the inferential model used makes it impossible for evidence from any study to overcome this handicap. We focus largely on step (2), explaining how the combination of dichotomization and “bias” dilutes experimental evidence, and showing how this dilution leads inevitably to the stated conclusion. We also demonstrate a fallacy in another important component of the argument –that papers in “hot” fields are more likely to produce false findings. We agree with the paper’s conclusions and recommendations that many medical research findings are less definitive than readers suspect, that P-values are widely misinterpreted, that bias of various forms is widespread, that multiple approaches are needed to prevent the literature from being systematically biased and the need for more data on the prevalence of false claims. But calculating the unreliability of the medical research literature, in whole or in part, requires more empirical evidence and different inferential models than were used. The claim that “most research findings are false for most research designs and for most fields” must be considered as yet unproven.

MODIFIED TEST STATISTICS BY INTER-VOXEL VARIANCE SHRINKAGE WITH AN APPLICATION TO fMRI

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

Aggressive vs. conservative phototherapy for infants with extremely low birth weight.

BACKGROUND: It is unclear whether aggressive phototherapy to prevent neurotoxic effects of bilirubin benefits or harms infants with extremely low birth weight (1000 g or less). METHODS: We randomly assigned 1974 infants with extremely low birth weight at 12 to 36 hours of age to undergo either aggressive or conservative phototherapy. The primary outcome was a composite of death or neurodevelopmental impairment determined for 91% of the infants by investigators who were unaware of the treatment assignments. RESULTS: Aggressive phototherapy, as compared with conservative phototherapy, significantly reduced the mean peak serum bilirubin level (7.0 vs. 9.8 mg per deciliter [120 vs. 168 micromol per liter], P<0.01) but not the rate of the primary outcome (52% vs. 55%; relative risk, 0.94; 95% confidence interval [CI], 0.87 to 1.02; P=0.15). Aggressive phototherapy did reduce rates of neurodevelopmental impairment (26%, vs. 30% for conservative phototherapy; relative risk, 0.86; 95% CI, 0.74 to 0.99). Rates of death in the aggressive-phototherapy and conservative-phototherapy groups were 24% and 23%, respectively (relative risk, 1.05; 95% CI, 0.90 to 1.22). In preplanned subgroup analyses, the rates of death were 13% with aggressive phototherapy and 14% with conservative phototherapy for infants with a birth weight of 751 to 1000 g and 39% and 34%, respectively (relative risk, 1.13; 95% CI, 0.96 to 1.34), for infants with a birth weight of 501 to 750 g. CONCLUSIONS: Aggressive phototherapy did not significantly reduce the rate of death or neurodevelopmental impairment. The rate of neurodevelopmental impairment alone was significantly reduced with aggressive phototherapy. This reduction may be offset by an increase in mortality among infants weighing 501 to 750 g at birth. (ClinicalTrials.gov number, NCT00114543.)

The Effect Of Misleading Prior Information On The Subjective Visual Vertical

When tilted sideways participants misperceive the visual vertical assessed by means of a luminous line in otherwise complete dark- ness. A recent modeling approach (De Vrijer et al., 2009) claimed that these typical patterns of errors (known as A- and E-effects) could be explained by as- suming that participants behave in a Bayes optimal manner. In this study, we experimentally manipulate participants’ prior information about body-in-space orientation and measure the effect of this manipulation on the subjective visual vertical (SVV). Specifically, we explore the effects of veridical and misleading instructions about body tilt orientations on the SVV. We used a psychophys- ical 2AFC SVV task at roll tilt angles of 0 degrees, 16 degrees and 4 degrees CW and CCW. Participants were tilted to 4 degrees under different instruction conditions: in one condition, participants received veridical instructions as to their tilt angle, whereas in another condition, participants received the mis- leading instruction that their body position was perfectly upright. Our results indicate systematic differences between the instruction conditions at 4 degrees CW and CCW. Participants did not simply use an ego-centric reference frame in the misleading condition; instead, participants’ estimates of the SVV seem to lie between their head’s Z-axis and the estimate of the SVV as measured in the veridical condition. All participants displayed A-effects at roll tilt an- gles of 16 degrees CW and CCW. We discuss our results in the context of the Bayesian model by De Vrijer et al. (2009), and claim that this pattern of re- sults is consistent with a manipulation of precision of a prior distribution over body-in-space orientations. Furthermore, we introduce a Bayesian Generalized Linear Model for estimating parameters of participants’ psychometric function, which allows us to jointly estimate group level and individual level parameters under all experimental conditions simultaneously, rather than relying on the traditional two-step approach to obtaining group level parameter estimates.

Validität und Reliabilität bei der visuellen okklusalen Kariesdiagnostik mit ICDAS unter der Verwendung von unterschiedlichen dentalen Vergrösserungshilfen

Zielsetzung: Diese Studie untersuchte die Validität und Reliabilität von verschiedenen visuellen dentalen Vergrösserungshilfen in Bezug auf die okklusale Kariesdiagnostik mit Hilfe des International Caries Detection and Assessment System (ICDAS). Material und Methode: Die Okklusalflächen von 100 extrahierten Zähnen wurde an einer zuvor bestimmten Stelle von 10 Studenten (5 Studenten des 3. Jahreskurses (Bachelor-Studenten) und 5 Studenten des 4. Jahreskurses (Master-Studenten) der Zahnmedizinischen Kliniken der Universität Bern) und 4 Zahnärzten visuell untersucht und nach ICDAS auf das Vorhandensein und die Tiefe einer kariösen Läsion beurteilt. Die Beurteilung der Zähne erfolgte je zwei Mal von blossem Auge, mit einem Galilei-Lupensystem (2.5x Vergrösserung), mit einem Kepler-Lupensystem (4.5x Vergrösserung) und mit dem Operationsmikroskop (10x Vergrösserung) mit mindestens 24 Stunden Abstand zwischen den jeweiligen Untersuchungen. Als Goldstandard diente die Histologie. Die statistische Auswertung der Untersuchungen erfolgte mit der Berechnung der Kappa-Koeffizienten für die Intra- und Inter-Untersucher Reliabilität sowie einer Bayes-Analyse durch Ermittlung von Sensitivität, Spezifität und der Fläche unter der Receiver Operating Characteristic Kurve (AUC). Ergebnisse: Bei den Untersuchungsdurchläufen, welche mit dentalen Vergrösserungshilfen für die Diagnostik der okklusalen Zahnoberflächen durchgeführt wurden, sank die Anzahl der mit einem ICDAS-Code 0 (gesunde Zahnoberfläche) beurteilten Zähne, während die Quantität des Codes 3 (Schmelzeinbruch) mit höheren Vergrösserungen drastisch zunahm. Mit steigendem Vergrösserungsfaktor liessen sich sowohl mehr Schmelzkaries als auch Dentinkaries richtig erkennen (bessere Sensitivität), im Gegenzug sanken aber die Werte der Spezifität auf ein klinisch unakzeptables Niveau. Während der Abfall der Spezifität und AUC-Werte bei der Beurteilung von Schmelzkaries unter Verwendung von kleinen Vergrösserungen lediglich einen Trend darstellte, waren die Verschlechterungen in der Diagnostik bei der Dentinkaries unter der Zuhilfenahme von höheren Vergrösserungen häufig signifikant. So stiegen zum Beispiel bei den Zahnärzten die Werte der Sensitivität (Bandbreite) auf dem D3-Diagnostikniveau von 0.47 (0.17-0.79) bei dem Durchlauf von Auge auf 0.91 (0.83-1.00) bei der Benutzung des Operationsmikroskopes an, während jedoch die Spezifitätswerte (Bandbreite) von 0.78 (0.58-0.95) auf 0.30 (0.07-0.55) sanken. Ebenfalls einen negativen Einfluss von optischen Hilfsmitteln zeigte sich bei der Inter-Untersucher Reliabilität, während die Intra-Untersucher Reliabilität unbeeinflusst blieb. Die persönliche klinische Erfahrung scheint sowohl in Bezug auf das Mass der Übereinstimmung visueller Kariesdiagnostik als auch auf die Präferenz bei der Vergabe der ICDAS-Codes und somit auf die Werte der Validität einen wesentlichen Faktor auszumachen. Die Studenten erreichten die besten Werte der Sensitivität, indes die Zahnärzte dies bei der Spezifität erzielten. Schlussfolgerung: Insgesamt zeigte sich, dass ICDAS nicht für den zusätzlichen Gebrauch von optischen Vergrösserungen konzipiert wurde. Da es auf Grund von der Zuhilfenahme von dentalen Vergrösserungen zu mehr und unnötigen invasiven Behandlungsentscheidungen kommen könnte, ist von der Zuhilfenahme derselben für die okklusale Kariesdiagnostik mit ICDAS abzuraten.

Automated counting of bacterial colony forming units on agar plates.

Manual counting of bacterial colony forming units (CFUs) on agar plates is laborious and error-prone. We therefore implemented a colony counting system with a novel segmentation algorithm to discriminate bacterial colonies from blood and other agar plates.A colony counter hardware was designed and a novel segmentation algorithm was written in MATLAB. In brief, pre-processing with Top-Hat-filtering to obtain a uniform background was followed by the segmentation step, during which the colony images were extracted from the blood agar and individual colonies were separated. A Bayes classifier was then applied to count the final number of bacterial colonies as some of the colonies could still be concatenated to form larger groups. To assess accuracy and performance of the colony counter, we tested automated colony counting of different agar plates with known CFU numbers of S. pneumoniae, P. aeruginosa and M. catarrhalis and showed excellent performance.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes’ theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.