Classificação não-supervisionada de dados hiperespectrais usando análise em componentes independentes

No passado recente foram desenvolvidas v árias t écnicas para classi ca ção de dados hiperspectrais. Uma abordagem tí pica consiste em considerar que cada pixel e uma mistura linear das reflectancias espectrais dos elementos presentes na c élula de resolu ção, adicionada de ru ído. Para classifi car e estimar os elementos presentes numa imagem hiperespectral, v ários problemas se colocam: Dimensionalidade dos dados, desconhecimento dos elementos presentes e a variabilidade da reflectância destes. Recentemente foi proposta a An álise em Componentes Independentes,para separa ção de misturas lineares. Nesta comunica ção apresenta-se uma metodologia baseada na An álise em Componentes Independentes para detec ção dos elementos presentes em imagens hiperespectrais e estima ção das suas quantidades. Apresentam-se resultados desta metodologia com dados simulados e com dados hiperespectrais reais, ilustrando a potencialidade da t écnica

Disponibilização de Cursos EaD para Programador Web a partir da Abordagem de Cursos Privados e Centrada ao Aluno

Distance learning evolution demands for studies to continuous improvement ofteaching and learning, making the student aware and present in this process. This article deals with the case study of a course that uses approaches Small Private Online Course (SPOC) and student-centered teaching. Thus, we seek to verify the applicability of these concepts as a tool with the Moodle platform, and as a case study of web programming course. Keywords: virtual environment, teacher, task, automation

Predicting functional impairment trajectories in amyotrophic lateral sclerosis: a probabilistic, multifactorial model of disease progression.

To employ Artificial Intelligence to model, predict and simulate the amyotrophic lateral sclerosis (ALS) progression over time in terms of variable interactions, functional impairments, and survival. We employed demographic and clinical variables, including functional scores and the utilisation of support interventions, of 3940 ALS patients from four Italian and two Israeli registers to develop a new approach based on Dynamic Bayesian Networks (DBNs) that models the ALS evolution over time, in two distinct scenarios of variable availability. The method allows to simulate patients' disease trajectories and predict the probability of functional impairment and survival at different time points. DBNs explicitly represent the relationships between the variables and the pathways along which they influence the disease progression. Several notable inter-dependencies were identified and validated by comparison with literature. Moreover, the implemented tool allows the assessment of the effect of different markers on the disease course, reproducing the probabilistically expected clinical progressions. The tool shows high concordance in terms of predicted and real prognosis, assessed as time to functional impairments and survival (integral of the AU-ROC in the first 36 months between 0.80-0.93 and 0.84-0.89 for the two scenarios, respectively). Provided only with measurements commonly collected during the first visit, our models can predict time to the loss of independence in walking, breathing, swallowing, communicating, and survival and it can be used to generate in silico patient cohorts with specific characteristics. Our tool provides a comprehensive framework to support physicians in treatment planning and clinical decision-making. [Abstract copyright: © 2022. The Author(s).

Mortality and morbidity among people living close to incinerators: a cohort study based on dispersion modeling for exposure assessment

<p>Abstract</p> <p>Background</p> <p>Several studies have been conducted on the possible health effects for people living close to incinerators and well-conducted reviews are available. Nevertheless, several uncertainties limit the overall interpretation of the findings. We evaluated the health effects of emissions from two incinerators in a pilot cohort study.</p> <p>Methods</p> <p>The study area was defined as the 3.5 km radius around two incinerators located near Forlì (Italy). People who were residents in 1/1/1990, or subsequently became residents up to 31/12/2003, were enrolled in a longitudinal study (31,347 individuals). All the addresses were geocoded. Follow-up continued until 31/12/2003 by linking the mortality register, cancer registry and hospital admissions databases. Atmospheric Dispersion Model System (ADMS) software was used for exposure assessment; modelled concentration maps of heavy metals (annual average) were considered the indicators of exposure to atmospheric pollution from the incinerators, while concentration maps of nitrogen dioxide (NO₂) were considered for exposure to other pollution sources. Age and area-based socioeconomic status adjusted rate ratios and 95% Confidence Intervals were estimated with Poisson regression, using the lowest exposure category to heavy metals as reference.</p> <p>Results</p> <p>The mortality and morbidity experience of the whole cohort did not differ from the regional population. In the internal analysis, no association between pollution exposure from the incinerators and all-cause and cause-specific mortality outcomes was observed in men, with the exception of colon cancer. Exposure to the incinerators was associated with cancer mortality among women, in particular for all cancer sites (RR for the highest exposure level = 1.47, 95% CI: 1.09, 1.99), stomach, colon, liver and breast cancer. No clear trend was detected for cancer incidence. No association was found for hospitalizations related to major diseases. NO₂levels, as a proxy from other pollution sources (traffic in particular), did not exert an important confounding role.</p> <p>Conclusions</p> <p>No increased risk of mortality and morbidity was found in the entire area. The internal analysis of the cohort based on dispersion modeling found excesses of mortality for some cancer types in the highest exposure categories, especially in women. The interpretation of the findings is limited given the pilot nature of the study.</p

Conceptual frameworks and empirical approaches used to assess the impact of health research: an overview of reviews

<p>Abstract</p> <p>Background</p> <p>How to assess the impact of research is of growing interest to funders, policy makers and researchers mainly to understand the value of investments and to increase accountability. Broadly speaking the term "research impact" refers to the contribution of research activities to achieve desired societal outcomes. The aim of this overview is to identify the most common approaches to research impact assessment, categories of impact and their respective indicators.</p> <p>Methods</p> <p>We systematically searched the relevant literature (PubMed, The Cochrane Library (1990-2009)) and funding agency websites. We included systematic reviews, theoretical and methodological papers, and empirical case-studies on how to evaluate research impact. We qualitatively summarised the included reports, as well the conceptual frameworks.</p> <p>Results</p> <p>We identified twenty-two reports belonging to four systematic reviews and 14 primary studies. These publications reported several theoretical frameworks and methodological approaches (bibliometrics, econometrics, ad hoc case studies). The "payback model" emerged as the most frequently used. Five broad categories of impact were identified: a) advancing knowledge, b) capacity building, c) informing decision-making, d) health benefits, e) broad socio-economic benefits. For each proposed category of impact we summarized a set of indicators whose pros and cons are presented and briefly discussed.</p> <p>Conclusions</p> <p>This overview is a comprehensive, yet descriptive, contribution to summarize the conceptual framework and taxonomy of an heterogeneous and evolving area of research. A shared and comprehensive conceptual framework does not seem to be available yet and its single components (epidemiologic, economic, and social) are often valued differently in different models.</p

The characteristics and activities of child and adolescent mental health services in Italy: a regional survey

<p>Abstract</p> <p>Background</p> <p>To date, no studies have assessed in detail the characteristics, organisation, and functioning of Child and Adolescent Mental Health Services (CAMHS). This information gap represents a major limitation for researchers and clinicians because most mental disorders have their onset in childhood or adolescence, and effective interventions can therefore represent a major factor in avoiding chronicity. Interventions and mental health care are delivered by and through services, and not by individual, private clinicians, and drawbacks or limitations of services generally translate in inappropriateness and ineffectiveness of treatments and interventions: therefore information about services is essential to improve the quality of care and ultimately the course and outcome of mental disorders in childhood and adolescence.</p> <p>The present paper reports the results of the first study aimed at providing detailed, updated and comprehensive data on CAMHS of a densely populated Italian region (over 4 million inhabitants) with a target population of 633,725 subjects aged 0-17 years.</p> <p>Methods</p> <p>Unit Chiefs of all the CAMHS filled in a structured 'Facility Form', with activity data referring to 2008 (data for inpatient facilities referred to 2009), which were then analysed in detail.</p> <p>Results</p> <p>Eleven CAMHS were operative, including 110 outpatient units, with a ratio of approximately 20 child psychiatrists and 23 psychologists per 100,000 inhabitants aged 0-17 years. All outpatient units were well equipped and organized and all granted free service access. In 2008, approximately 6% of the target population was in contact with outpatient CAMHS, showing substantial homogeneity across the eleven areas thereby. Most patients in contact in 2008 received a language disorder- or learning disability diagnosis (41%). First-ever contacts accounted for 30% of annual visits across all units. Hospital bed availability was 5 per 100,000 inhabitants aged 0-17 years.</p> <p>Conclusion</p> <p>The percentage of young people in contact with CAMHS for mental disorders is in line with those observed in previous epidemiological studies. The overall number of child psychiatrists per 100,000 inhabitants is one of the highest in Europe and it is comparable with the most well equipped areas in the US. This comparison should be interpreted with caution, however, because in Italy, child psychiatrists also treat neurological disorders. Critical areas requiring improvement are: the uneven utilisation of standardised assessment procedures and the limited availability of dedicated emergency services during non-office hours (e.g., nights and holidays).</p