Uso de processos químicos no controle do risco biológico de dejetos suínos.

bitstream/item/56395/1/publicacao-492.pdfProjeto/Plano de Ação: 02.07.06.007

Monitoramento da eficiência de remoção de nitrogênio no tratamento.

Projeto/Plano de Ação: 04.10.00.011

Harmful effects of mechanical ventilation on neurocognitive functions

Whether mechanical ventilation (MV) induces neurotoxicity that can trigger or accelerate chronic cognitive disorders is controversial [1, 2]. The relationship between MV and neurocognitive impairment—that persisted at hospital discharge and at 1-year follow up—was first reported in 1999 in MV-treated ARDS patients [3]. Since then, several preclinical and clinical studies have investigated the mechanisms, localization, and timing of brain damage induced by MVand possible preventive/therapeutic strategies

Matematica, Musica e Tecnologie: un trinomio possibile

ItIn questo lavoro descriviamo come le tecnologie dell'informazione e della computazione arricchiscono il classico rapporto tra Matematica e Musica, mettendo a disposizione dell'artista nuovi metodi e strumenti per la creativita' musicale. I nuovi modelli della Scienza legati ai frattali, ai sistemi dinamici, alla complessita' e al caos forniscono una grande quantita' di strutture matematiche che attraverso opportuni codici possono essere tradotti in suoni e musica. L'artista puo' usare questo contesto per le proprie produzioni, ed il matematico puo' trovare nelle produzioni musicali una semantica delle strutture matematiche astratte che intervengono nel corso dei suoi studi. In questo lavoro vengono esplorati i rapporti tra Spazi Matematici, Spazi Sonori e Spazi Musicali e come le strutture matematiche possono essere tradotte in musica attraverso opportuni codici

Stormwater Research Roadmap for Minnesota

The goal of the Stormwater Research Roadmap is to articulate major research needs to improve stormwater management in Minnesota. Multiple sources and approaches were used to identify stormwater research needs for Minnesota, including a review of relevant stormwater-related documents, and state-wide survey of stormwater managers, focus groups, and policy actor interviews. The Stormwater Research Roadmap for Minnesota identifies eight major areas that need additional research to improve stormwater management for communities, professionals, and agencies. Specific examples are included for each. Research in these areas can lead to more innovative management techniques and increased effectiveness and efficiency to prevent, minimize, and mitigate the effects of runoff from the built environment. The Roadmap also presents criteria to rank research needs. Data for the Roadmap was collected from 2017-2018 and was published in 2018.his work was supported with funds from the Minnesota Clean Water, Land, and Legacy Amendment allocated by the Minnesota Legislature through the Minnesota Pollution Control Agency

On Symbolic Ultrametrics, Cotree Representations, and Cograph Edge Decompositions and Partitions

Symbolic ultrametrics define edge-colored complete graphs K_n and yield a simple tree representation of K_n. We discuss, under which conditions this idea can be generalized to find a symbolic ultrametric that, in addition, distinguishes between edges and non-edges of arbitrary graphs G=(V,E) and thus, yielding a simple tree representation of G. We prove that such a symbolic ultrametric can only be defined for G if and only if G is a so-called cograph. A cograph is uniquely determined by a so-called cotree. As not all graphs are cographs, we ask, furthermore, what is the minimum number of cotrees needed to represent the topology of G. The latter problem is equivalent to find an optimal cograph edge k-decomposition {E_1,...,E_k} of E so that each subgraph (V,E_i) of G is a cograph. An upper bound for the integer k is derived and it is shown that determining whether a graph has a cograph 2-decomposition, resp., 2-partition is NP-complete

Mid-sagittal plane detection for advanced physiological measurements in brain scans

Objective: The process of diagnosing many neurodegenerative diseases, such as Parkinson's and progressive supranuclear palsy, involves the study of brain magnetic resonance imaging (MRI) scans in order to identify and locate morphological markers that can highlight the health status of the subject. A fundamental step in the pre-processing and analysis of MRI scans is the identification of the mid-sagittal plane, which corresponds to the mid-brain and allows a coordinate reference system for the whole MRI scan set. Approach: To improve the identification of the mid-sagittal plane we have developed an algorithm in Matlab® based on the k-means clustering function. The results have been compared with the evaluation of four experts who manually identified the mid-sagittal plane and whose performances have been combined with a cognitive decisional algorithm in order to define a gold standard. Main results: The comparison provided a mean percentage error of 1.84%. To further refine the automatic procedure we trained a machine learning system using the results from the proposed algorithm and the gold standard. We tested this machine learning system and obtained results comparable to medical raters with a mean absolute error of 1.86 slices. Significance: The system is promising and could be directly incorporated into broader diagnostic support systems