Elaborazione del linguaggio naturale nell'IA e tecnologie moderne: Sentiment Analysis come caso di studio.

L'informatica e le sue tecnologie nella società moderna si riassumono spesso in un assioma fuorviante: essa, infatti, è comunemente legata al concetto che ciò che le tecnologie ci offrono può essere accessibile da tutti e sfruttato, all'interno della propria quotidianità, in modi più o meno semplici. Anche se quello appena descritto è un obiettivo fondamentale del mondo high-tech, occorre chiarire subito una questione: l'informatica non è semplicemente tutto ciò che le tecnologie ci offrono, perchè questo pensiero sommario fa presagire ad un'informatica "generalizzante"; l'informatica invece si divide tra molteplici ambiti, toccando diversi mondi inter-disciplinari. L'importanza di queste tecnologie nella società moderna deve spingerci a porre domande, riflessioni sul perchè l'informatica, in tutte le sue sfaccettature, negli ultimi decenni, ha portato una vera e propria rivoluzione nelle nostre vite, nelle nostre abitudini, e non di meno importanza, nel nostro contesto lavorativo e aziendale, e non ha alcuna intenzione (per fortuna) di fermare le proprie possibilità di sviluppo. In questo trattato ci occuperemo di definire una particolare tecnica moderna relativa a una parte di quel mondo complesso che viene definito come "Intelligenza Artificiale". L'intelligenza Artificiale (IA) è una scienza che si è sviluppata proprio con il progresso tecnologico e dei suoi potenti strumenti, che non sono solo informatici, ma soprattutto teorico-matematici (probabilistici) e anche inerenti l'ambito Elettronico-TLC (basti pensare alla Robotica): ecco l'interdisciplinarità. Concetto che è fondamentale per poi affrontare il nocciolo del percorso presentato nel secondo capitolo del documento proposto: i due approcci possibili, semantico e probabilistico, verso l'elaborazione del linguaggio naturale(NLP), branca fondamentale di IA. Per quanto darò un buono spazio nella tesi a come le tecniche di NLP semantiche e statistiche si siano sviluppate nel tempo, verrà prestata attenzione soprattutto ai concetti fondamentali di questi ambiti, perché, come già detto sopra, anche se è fondamentale farsi delle basi e conoscere l'evoluzione di queste tecnologie nel tempo, l'obiettivo è quello a un certo punto di staccarsi e studiare il livello tecnologico moderno inerenti a questo mondo, con uno sguardo anche al domani: in questo caso, la Sentiment Analysis (capitolo 3). Sentiment Analysis (SA) è una tecnica di NLP che si sta definendo proprio ai giorni nostri, tecnica che si è sviluppata soprattutto in relazione all'esplosione del fenomeno Social Network, che viviamo e "tocchiamo" costantemente. L'approfondimento centrale della tesi verterà sulla presentazione di alcuni esempi moderni e modelli di SA che riguardano entrambi gli approcci (statistico e semantico), con particolare attenzione a modelli di SA che sono stati proposti per Twitter in questi ultimi anni, valutando quali sono gli scenari che propone questa tecnica moderna, e a quali conseguenze contestuali (e non) potrebbe portare questa particolare tecnica.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

The Risk of Paradoxical Embolism (RoPE) Study: initial description of the completed database

BACKGROUND: Detecting a benefit from closure of patent foramen ovale in patients with cryptogenic stroke is hampered by low rates of stroke recurrence and uncertainty about the causal role of patent foramen ovale in the index event. A method to predict patent foramen ovale-attributable recurrence risk is needed. However, individual databases generally have too few stroke recurrences to support risk modeling. Prior studies of this population have been limited by low statistical power for examining factors related to recurrence. AIMS: The aim of this study was to develop a database to support modeling of patent foramen ovale-attributable recurrence risk by combining extant data sets. METHODS: We identified investigators with extant databases including subjects with cryptogenic stroke investigated for patent foramen ovale, determined the availability and characteristics of data in each database, collaboratively specified the variables to be included in the Risk of Paradoxical Embolism database, harmonized the variables across databases, and collected new primary data when necessary and feasible. RESULTS: The Risk of Paradoxical Embolism database has individual clinical, radiologic, and echocardiographic data from 12 component databases, including subjects with cryptogenic stroke both with (n = 1925) and without (n = 1749) patent foramen ovale. In the patent foramen ovale subjects, a total of 381 outcomes (stroke, transient ischemic attack, death) occurred (median follow-up 2·2 years). While there were substantial variations in data collection between studies, there was sufficient overlap to define a common set of variables suitable for risk modeling. CONCLUSION: While individual studies are inadequate for modeling patent foramen ovale-attributable recurrence risk, collaboration between investigators has yielded a database with sufficient power to identify those patients at highest risk for a patent foramen ovale-related stroke recurrence who may have the greatest potential benefit from patent foramen ovale closure.

Reduced Cerebral Blood Flow Within the Default-Mode Network and Within Total Gray Matter in Major Depression

The default-mode network (DMN) was shown to have aberrant blood oxygenation-level-dependent (BOLD) activity in major depressive disorder (MDD). While BOLD is a relative measure of neural activity, cerebral blood flow (CBF) is an absolute measure. Resting-state CBF alterations have been reported in MDD. However, the association of baseline CBF and CBF fluctuations is unclear in MDD. Therefore, the aim was to investigate the CBF within the DMN in MDD, applying a strictly data-driven approach. In 22 MDD patients and 22 matched healthy controls, CBF was acquired using arterial spin labeling (ASL) at rest. A concatenated independent component analysis was performed to identify the DMN within the ASL data. The perfusion of the DMN and its nodes was quantified and compared between groups. The DMN was identified in both groups with high spatial similarity. Absolute CBF values within the DMN were reduced in MDD patients (p<0.001). However, after controlling for whole-brain gray matter CBF and age, the group difference vanished. In patients, depression severity was correlated with reduced perfusion in the DMN in the posterior cingulate cortex and the right inferior parietal lobe. Hypoperfusion within the DMN in MDD is not specific to the DMN. Still, depression severity was linked to DMN node perfusion, supporting a role of the DMN in depression pathobiology. The finding has implications for the interpretation of BOLD functional magnetic resonance imaging data in MDD.

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.

The Role of Features and Context in Recognition of Novel Melodies

WE INVESTIGATED HOW WELL STRUCTURAL FEATURES such as note density or the relative number of changes in the melodic contour could predict success in implicit and explicit memory for unfamiliar melodies. We also analyzed which features are more likely to elicit increasingly confident judgments of "old" in a recognition memory task. An automated analysis program computed structural aspects of melodies, both independent of any context, and also with reference to the other melodies in the testset and the parent corpus of pop music. A few features predicted success in both memory tasks, which points to a shared memory component. However, motivic complexity compared to a large corpus of pop music had different effects on explicit and implicit memory. We also found that just a few features are associated with different rates of "old" judgments, whether the items were old or new. Rarer motives relative to the testset predicted hits and rarer motives relative to the corpus predicted false alarms. This data-driven analysis provides further support for both shared and separable mechanisms in implicit and explicit memory retrieval, as well as the role of distinctiveness in true and false judgments of familiarity.

Differential Expression with the Bioconductor Project

A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. We discuss different approaches to this task and illustrate how they can be applied using software from the Bioconductor Project. A central problem is the high dimensionality of gene expression space, which prohibits a comprehensive statistical analysis without focusing on particular aspects of the joint distribution of the genes expression levels. Possible strategies are to do univariate gene-by-gene analysis, and to perform data-driven nonspecific filtering of genes before the actual statistical analysis. However, more focused strategies that make use of biologically relevant knowledge are more likely to increase our understanding of the data.

The spatiotemporal pattern of auditory cortical responses during verbal hallucinations

Functional magnetic resonance imaging (fMRI) studies can provide insight into the neural correlates of hallucinations. Commonly, such studies require self-reports about the timing of the hallucination events. While many studies have found activity in higher-order sensory cortical areas, only a few have demonstrated activity of the primary auditory cortex during auditory verbal hallucinations. In this case, using self-reports as a model of brain activity may not be sensitive enough to capture all neurophysiological signals related to hallucinations. We used spatial independent component analysis (sICA) to extract the activity patterns associated with auditory verbal hallucinations in six schizophrenia patients. SICA decomposes the functional data set into a set of spatial maps without the use of any input function. The resulting activity patterns from auditory and sensorimotor components were further analyzed in a single-subject fashion using a visualization tool that allows for easy inspection of the variability of regional brain responses. We found bilateral auditory cortex activity, including Heschl's gyrus, during hallucinations of one patient, and unilateral auditory cortex activity in two more patients. The associated time courses showed a large variability in the shape, amplitude, and time of onset relative to the self-reports. However, the average of the time courses during hallucinations showed a clear association with this clinical phenomenon. We suggest that detection of this activity may be facilitated by examining hallucination epochs of sufficient length, in combination with a data-driven approach.

Diazepam versus fentanyl for premedication during percutaneous coronary intervention: results from the Myocardial Protection by Fentanyl during Coronary Intervention (PROFIT) Trial

BACKGROUND: Sedation is a cornerstone in the premedication for percutaneous coronary intervention (PCI). Benzodiazepines and opioids are frequently used. Previous results suggest that opioids mimic the adaptation to ischemia during repeated balloon inflations and may provide direct myocardial protection in addition to their sedative effect. However, no comparative data exist. METHODS: We conducted a prospective, randomized, controlled, single-blind trial comparing diazepam and fentanyl in 276 patients undergoing elective PCI. Patients were randomized to either diazepam 5 mg sublingually or fentanyl 0.05 mg or 0.1 mg intravenously at least 5 minutes prior to the first balloon inflation. The primary end-point was the postprocedural elevation of myocardial markers of necrosis defined as an elevation of cardiac troponin T > or = 0.01 ng/ml. RESULTS: The three groups had similar baseline clinical, angiographic, and procedural characteristics, with no significant differences in lesion morphology, procedural complexity, or adjunctive medical treatment. No significant variation in the hemodynamic response to the study drugs was observed in the three groups. The rate of postprocedural troponin T elevation was 28% in the diazepam group, 20% in the fentanyl 0.05 mg group, and 30% in the fentanyl 0.1 mg group (P = 0.26). Rates of postprocedural myocardial infarction were 3%, 2%, and 2%, respectively (P = 0.84), with one case of in-hospital death in the diazepam group and no urgent TVR in the whole study population. CONCLUSION: Although providing a well-tolerated alternative to diazepam for sedation during PCI, fentanyl did not provide additional cardioprotection assessed through the postinterventional elevation of cardiac troponin T during elective coronary intervention.

Drug eluting and bare metal stents in people with and without diabetes: collaborative network meta-analysis

Objective To compare the effectiveness and safety of three types of stents (sirolimus eluting, paclitaxel eluting, and bare metal) in people with and without diabetes mellitus. Design Collaborative network meta-analysis. Data sources Electronic databases (Medline, Embase, the Cochrane Central Register of Controlled Trials), relevant websites, reference lists, conference abstracts, reviews, book chapters, and proceedings of advisory panels for the US Food and Drug Administration. Manufacturers and trialists provided additional data. Review methods Network meta-analysis with a mixed treatment comparison method to combine direct within trial comparisons between stents with indirect evidence from other trials while maintaining randomisation. Overall mortality was the primary safety end point, target lesion revascularisation the effectiveness end point. Results 35 trials in 3852 people with diabetes and 10 947 people without diabetes contributed to the analyses. Inconsistency of the network was substantial for overall mortality in people with diabetes and seemed to be related to the duration of dual antiplatelet therapy (P value for interaction 0.02). Restricting the analysis to trials with a duration of dual antiplatelet therapy of six months or more, inconsistency was reduced considerably and hazard ratios for overall mortality were near one for all comparisons in people with diabetes: sirolimus eluting stents compared with bare metal stents 0.88 (95% credibility interval 0.55 to 1.30), paclitaxel eluting stents compared with bare metal stents 0.91 (0.60 to 1.38), and sirolimus eluting stents compared with paclitaxel eluting stents 0.95 (0.63 to 1.43). In people without diabetes, hazard ratios were unaffected by the restriction. Both drug eluting stents were associated with a decrease in revascularisation rates compared with bare metal stents in people both with and without diabetes. Conclusion In trials that specified a duration of dual antiplatelet therapy of six months or more after stent implantation, drug eluting stents seemed safe and effective in people both with and without diabetes.

Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA

We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.

Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts

Prompted reports of recall of spontaneous, conscious experiences were collected in a no-input, no-task, no-response paradigm (30 random prompts to each of 13 healthy volunteers). The mentation reports were classified into visual imagery and abstract thought. Spontaneous 19-channel brain electric activity (EEG) was continuously recorded, viewed as series of momentary spatial distributions (maps) of the brain electric field and segmented into microstates, i.e. into time segments characterized by quasi-stable landscapes of potential distribution maps which showed varying durations in the sub-second range. Microstate segmentation used a data-driven strategy. Different microstates, i.e. different brain electric landscapes must have been generated by activity of different neural assemblies and therefore are hypothesized to constitute different functions. The two types of reported experiences were associated with significantly different microstates (mean duration 121 ms) immediately preceding the prompts; these microstates showed, across subjects, for abstract thought (compared to visual imagery) a shift of the electric gravity center to the left and a clockwise rotation of the field axis. Contrariwise, the microstates 2 s before the prompt did not differ between the two types of experiences. The results support the hypothesis that different microstates of the brain as recognized in its electric field implement different conscious, reportable mind states, i.e. different classes (types) of thoughts (mentations); thus, the microstates might be candidates for the `atoms of thought'.

Library Assessment Trends Report, 2010–2011

The field of library assessment continues to grow. The annual Library Assessment Trends Report provides a brief synopsis of the more important trends in library assessment. It is hoped these brief reports will facilitate the Dean of the Library’s understanding of assessment trends. These reports provide information that supports data driven decisions. Additionally, the reports are an outreach method that supports a greater institutional understanding of library assessment. Library assessment supports strategic planning, improved processes, and a greater understanding of our users’ needs.

CHARACTERIZING, ASSESSING AND IMPROVING HEALTHCARE REFERRAL COMMUNICATION

Similar to other health care processes, referrals are susceptible to breakdowns. These breakdowns in the referral process can lead to poor continuity of care, slow diagnostic processes, delays and repetition of tests, patient and provider dissatisfaction, and can lead to a loss of confidence in providers. These facts and the necessity for a deeper understanding of referrals in healthcare served as the motivation to conduct a comprehensive study of referrals. The research began with the real problem and need to understand referral communication as a mean to improve patient care. Despite previous efforts to explain referrals and the dynamics and interrelations of the variables that influence referrals there is not a common, contemporary, and accepted definition of what a referral is in the health care context. The research agenda was guided by the need to explore referrals as an abstract concept by: 1) developing a conceptual definition of referrals, and 2) developing a model of referrals, to finally propose a 3) comprehensive research framework. This dissertation has resulted in a standard conceptual definition of referrals and a model of referrals. In addition a mixed-method framework to evaluate referrals was proposed, and finally a data driven model was developed to predict whether a referral would be approved or denied by a specialty service. The three manuscripts included in this dissertation present the basis for studying and assessing referrals using a common framework that should allow an easier comparative research agenda to improve referrals taking into account the context where referrals occur.

Three decades of global methane sources and sinks

Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios � which differ in fossil fuel and microbial emissions � to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.