922 resultados para Signal detection Mathematical models
Theoretical approaches to forensic entomology: I. Mathematical model of postfeeding larval dispersal
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An overall theoretical approach to model phenomena of interest for forensic entomology is advanced. Efforts are concentrated in identifying biological attributes at the individual, population and community of the arthropod fauna associated with decomposing human corpses and then incorporating these attributes into mathematical models. In particular in this paper a diffusion model of dispersal of post feeding larvae is described for blowflies, which are the most common insects associated with corpses.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This work presents major results from a novel dynamic model intended to deterministically represent the complex relation between HIV-1 and the human immune system. The novel structure of the model extends previous work by representing different host anatomic compartments under a more in-depth cellular and molecular immunological phenomenology. Recently identified mechanisms related to HIV-1 infection as well as other well known relevant mechanisms typically ignored in mathematical models of HIV-1 pathogenesis and immunology, such as cell-cell transmission, are also addressed. (C) 2011 Elsevier Ltd. All rights reserved.
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The emergency of infection by highly pathogenic avian influenza virus (HPAI) subtype H5N1 has focused the attention of the world scientific community, requiring the prompt provision of effective control systems for early detection of the circulation of low pathogenic influenza H5 viruses (LPAI) in populations of wild birds to prevent outbreaks of highly pathogenic (HPAI) in populations of domestic birds with possible transmission to humans. The project stems from the aim to provide, through a preliminary analysis of data obtained from surveillance in Italy and Europe, a preliminary study about the virus detection rates and the development of mathematical models, an objective assessment of the effectiveness of avian influenza surveillance systems in wild bird populations, and to point out guidelines to support the planning process of the sampling activities. The results obtained from the statistical processing quantify the sampling effort in terms of time and sample size required, and simulating different epidemiological scenarios identify active surveillance as the most suitable for endemic LPAI infection monitoring in wild waterfowl, and passive surveillance as the only really effective tool in early detecting HPAI H5N1 circulation in wild populations. Given the lack of relevant information on H5N1 epidemiology, and the actual finantial and logistic constraints, an approach that makes use of statistical tools to evaluate and predict monitoring activities effectiveness proves to be of primary importance to direct decision-making and make the best use of available resources.
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Die regionale Bestimmung der Durchblutung (Perfusion) ermöglicht differenzierte Aussagen über den Gesundheitszustand und die Funktionalität der Lunge. Durch neue Messverfahren ermöglicht die Magnetresonanztomographie (MRT) eine nicht-invasive und strahlungsfreie Untersuchung der Perfusion. Obwohl die Machbarkeit qualitativer MRT-Durchblutungsmessungen bereits gezeigt wurde, fehlt bisher eine validierte quantitative Methode. Ziel dieser Arbeit war eine Optimierung der bestehenden Messprotokolle und mathematischen Modelle zur Absolutquantifizierung der Lungenperfusion mit Magnetresonanztomographie. Weiterhin sollte die Methodik durch Vergleich mit einem etablierten Referenzverfahren validiert werden. Durch Simulationen und Phantommessungen konnten optimale MRT-Messparameter und ein standardisiertes Protokoll festgelegt werden. Des Weiteren wurde eine verallgemeinerte Bestimmung der Kontrastmittelkonzentration aus den gemessenen Signalintensitäten vorgestellt, diskutiert und durch Probandenmessungen validiert. Auf der Basis dieser Entwicklungen wurde die MRT-Durchblutungsmessung der Lunge tierexperimentell mit der Positronenemissionstomographie (PET) intraindividuell verglichen und validiert. Die Ergebnisse zeigten nur kleine Abweichungen und eine statistisch hochsignifikante, stark lineare Korrelation. Zusammenfassend war es durch die Entwicklungen der vorgestellten Arbeit möglich, die kontrastmittelgestützte MRT-Durchblutungsmessung der Lunge zu optimieren und erstmals zu validieren.
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In this work I tried to explore many aspects of cognitive visual science, each one based on different academic fields, proposing mathematical models capable to reproduce both neuro-physiological and phenomenological results that were described in the recent literature. The structure of my thesis is mainly composed of three chapters, corresponding to the three main areas of research on which I focused my work. The results of each work put the basis for the following, and their ensemble form an homogeneous and large-scale survey on the spatio-temporal properties of the architecture of the visual cortex of mammals.
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This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.
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The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.
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Das aus wissenschaftlicher und ökonomischer Sicht wichtigste Pflanzenpathogen M. oryzae entwickelte im Laufe der Evolution konservierte aber auch einzigartige Mechanismen zur Signaltransduktion. Das Erforschen dieser Mechanismen und Prozesse ist essenziell für das Verständnis von Differenzierungsprozessen bei der Pathogen-Wirt-Interaktion.rnIm ersten Teil der vorliegenden Arbeit wurde der Signalweg zur Osmoregulation, der „High Osmolarity Glycerol“ (HOG)-Signalweg, erstmals anhand physiologischer Experimente in entsprechenden Mutantenstämmen in M. oryzae untersucht. Dabei konnten klare Unter-schiede zum HOG-Signalweg von S. cerevisiae aufgezeigt werden. rnDas in M. oryzae bisher noch nicht beschriebene Gen MoYPD1, welches das Phosphotransferprotein MoYpd1p kodiert, wurde erfolgreich inaktiviert. Diese Inaktivierung ist in S. cerevisiae und vielen anderen Pilzen letal und resultierte bei M. oryzae in einer apathoge¬nen Albinomutante, deren Konidiogenese gestört ist. Insbesondere die Funktion des Phosphotransferproteins MoYpd1p, sowohl im Phosphorelaysystem des HOG-Signal¬wegs als auch im Wirkmechanismus des Fungizids Fludioxonil, konnte eindeutig mittels Y2H- und Western Blot-Analysen nachgewiesen werden.rnEs wurden entscheidende Fortschritte für das Verständnis des Aufbaus und der Funktion des HOG-Signalwegs sowohl als physiologisches Regulationssystem für Umweltreize als auch als Fungizidtarget im Pflanzenschutz erzielt. Dabei konnte gezeigt werden, dass die Zweikompo-nenten-Hybrid-Histidinkinase (HIK) MoSln1p als Signalsensor für Salzstress und MoHik1p als Signalsensor für Zuckerstress fungiert. Die Beteiligung der Histidinkinasen MoHik5p und MoHik9p als Sensorproteine für Hypoxie im HOG-Signalweg ist durchaus denk¬bar und wurde durch erste Ergebnisse bekräftigt. rnSo konnte der HOG-Signalweg in mehreren Modellen dargestellt werden. Die Modelle der Signalerkennung und –transduktion von osmotischem Stress, von Hypoxie und der Wirkmecha¬nismus von Fludioxonil wurden erstmals in diesem Umfang für M. oryzae ausgearbei¬tet.rnDer zweite Teil dieser Arbeit repräsentiert die erste umfassende Untersuchung aller zehn HIK-codierender Gensequenzen, die im Genom von M. oryzae identifiziert werden konnten. Diese Signalproteine waren bisher noch nicht Gegenstand wissenschaftlicher Studien. Die Untersuchung beginnt mit einer phylogenetischen Einordnung aller untersuchten Proteinsequen¬zen in die verschiedenen Gruppen von Histidinkinasen in Pilzen. Eine ausführli-che phänotypische Charakterisierung aller HIK-codierender Gene folgt und wurde anhand von Mutanten durchgeführt, in denen diese Gene einzeln inaktiviert wurden.rnDie Beteiligung von MoHik5p und MoHik9p als mögliche Sauerstoffsensoren im HOG-Signal-weg konnte dokumentiert werden und die anschließenden Western Blot-Analysen bestätig¬ten erstmals die Aktivierung des HOG-Signalwegs bei hypoxieähnlichen Zuständen.rnDes Weiteren wurden mit MoHik5p und MoHik8p zwei neue Pathogenitätsfaktoren in M. oryzae identifiziert. Die apathogenen Mutantenstämme ΔMohik5 und ΔMohik8 sind in der Konidiogenese gestört und nicht in der Lage Appressorien zu differenzieren. Der Einsatz dieser Proteine als Fungizidtarget im protektiven Pflanzenschutz in der Zukunft ist somit denk-bar.rn
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In this study, the effect of time derivatives of flow rate and rotational speed was investigated on the mathematical modeling of a rotary blood pump (RBP). The basic model estimates the pressure head of the pump as a dependent variable using measured flow and speed as predictive variables. Performance of the model was evaluated by adding time derivative terms for flow and speed. First, to create a realistic working condition, the Levitronix CentriMag RBP was implanted in a sheep. All parameters from the model were physically measured and digitally acquired over a wide range of conditions, including pulsatile speed. Second, a statistical analysis of the different variables (flow, speed, and their time derivatives) based on multiple regression analysis was performed to determine the significant variables for pressure head estimation. Finally, different mathematical models were used to show the effect of time derivative terms on the performance of the models. In order to evaluate how well the estimated pressure head using different models fits the measured pressure head, root mean square error and correlation coefficient were used. The results indicate that inclusion of time derivatives of flow and speed can improve model accuracy, but only minimally.
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BACKGROUND Partner notification is essential to the comprehensive case management of sexually transmitted infections. Systematic reviews and mathematical modelling can be used to synthesise information about the effects of new interventions to enhance the outcomes of partner notification. OBJECTIVE To study the effectiveness and cost-effectiveness of traditional and new partner notification technologies for curable sexually transmitted infections (STIs). DESIGN Secondary data analysis of clinical audit data; systematic reviews of randomised controlled trials (MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials) published from 1 January 1966 to 31 August 2012 and of studies of health-related quality of life (HRQL) [MEDLINE, EMBASE, ISI Web of Knowledge, NHS Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA)] published from 1 January 1980 to 31 December 2011; static models of clinical effectiveness and cost-effectiveness; and dynamic modelling studies to improve parameter estimation and examine effectiveness. SETTING General population and genitourinary medicine clinic attenders. PARTICIPANTS Heterosexual women and men. INTERVENTIONS Traditional partner notification by patient or provider referral, and new partner notification by expedited partner therapy (EPT) or its UK equivalent, accelerated partner therapy (APT). MAIN OUTCOME MEASURES Population prevalence; index case reinfection; and partners treated per index case. RESULTS Enhanced partner therapy reduced reinfection in index cases with curable STIs more than simple patient referral [risk ratio (RR) 0.71; 95% confidence interval (CI) 0.56 to 0.89]. There are no randomised trials of APT. The median number of partners treated for chlamydia per index case in UK clinics was 0.60. The number of partners needed to treat to interrupt transmission of chlamydia was lower for casual than for regular partners. In dynamic model simulations, > 10% of partners are chlamydia positive with look-back periods of up to 18 months. In the presence of a chlamydia screening programme that reduces population prevalence, treatment of current partners achieves most of the additional reduction in prevalence attributable to partner notification. Dynamic model simulations show that cotesting and treatment for chlamydia and gonorrhoea reduce the prevalence of both STIs. APT has a limited additional effect on prevalence but reduces the rate of index case reinfection. Published quality-adjusted life-year (QALY) weights were of insufficient quality to be used in a cost-effectiveness study of partner notification in this project. Using an intermediate outcome of cost per infection diagnosed, doubling the efficacy of partner notification from 0.4 to 0.8 partners treated per index case was more cost-effective than increasing chlamydia screening coverage. CONCLUSIONS There is evidence to support the improved clinical effectiveness of EPT in reducing index case reinfection. In a general heterosexual population, partner notification identifies new infected cases but the impact on chlamydia prevalence is limited. Partner notification to notify casual partners might have a greater impact than for regular partners in genitourinary clinic populations. Recommendations for future research are (1) to conduct randomised controlled trials using biological outcomes of the effectiveness of APT and of methods to increase testing for human immunodeficiency virus (HIV) and STIs after APT; (2) collection of HRQL data should be a priority to determine QALYs associated with the sequelae of curable STIs; and (3) standardised parameter sets for curable STIs should be developed for mathematical models of STI transmission that are used for policy-making. FUNDING The National Institute for Health Research Health Technology Assessment programme.
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Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.
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The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.
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In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.
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Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.