936 resultados para errors-in-variables model


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Increasing in resolution of numerical weather prediction models has allowed more and more realistic forecasts of atmospheric parameters. Due to the growing variability into predicted fields the traditional verification methods are not always able to describe the model ability because they are based on a grid-point-by-grid-point matching between observation and prediction. Recently, new spatial verification methods have been developed with the aim of show the benefit associated to the high resolution forecast. Nested in among of the MesoVICT international project, the initially aim of this work is to compare the newly tecniques remarking advantages and disadvantages. First of all, the MesoVICT basic examples, represented by synthetic precipitation fields, have been examined. Giving an error evaluation in terms of structure, amplitude and localization of the precipitation fields, the SAL method has been studied more thoroughly respect to the others approaches with its implementation in the core cases of the project. The verification procedure has concerned precipitation fields over central Europe: comparisons between the forecasts performed by the 00z COSMO-2 model and the VERA (Vienna Enhanced Resolution Analysis) have been done. The study of these cases has shown some weaknesses of the methodology examined; in particular has been highlighted the presence of a correlation between the optimal domain size and the extention of the precipitation systems. In order to increase ability of SAL, a subdivision of the original domain in three subdomains has been done and the method has been applied again. Some limits have been found in cases in which at least one of the two domains does not show precipitation. The overall results for the subdomains have been summarized on scatter plots. With the aim to identify systematic errors of the model the variability of the three parameters has been studied for each subdomain.

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The interactions between host individual, host population, and environmental factors modulate parasite abundance in a given host population. Since adult exophilic ticks are highly aggregated in red deer (Cervus elaphus) and this ungulate exhibits significant sexual size dimorphism, life history traits and segregation, we hypothesized that tick parasitism on males and hinds would be differentially influenced by each of these factors. To test the hypothesis, ticks from 306 red deer-182 males and 124 females-were collected during 7 years in a red deer population in south-central Spain. By using generalized linear models, with a negative binomial error distribution and a logarithmic link function, we modeled tick abundance on deer with 20 potential predictors. Three models were developed: one for red deer males, another for hinds, and one combining data for males and females and including "sex" as factor. Our rationale was that if tick burdens on males and hinds relate to the explanatory factors in a differential way, it is not possible to precisely and accurately predict the tick burden on one sex using the model fitted on the other sex, or with the model that combines data from both sexes. Our results showed that deer males were the primary target for ticks, the weight of each factor differed between sexes, and each sex specific model was not able to accurately predict burdens on the animals of the other sex. That is, results support for sex-biased differences. The higher weight of host individual and population factors in the model for males show that intrinsic deer factors more strongly explain tick burden than environmental host-seeking tick abundance. In contrast, environmental variables predominated in the models explaining tick burdens in hinds.

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Assessment processes are essential to guarantee quality and continuous improvement of software in healthcare, as they measure software attributes in their lifecycle, verify the degree of alignment between the software and its objectives and identify unpredicted events. This article analyses the use of an assessment model based on software metrics for three healthcare information systems from a public hospital that provides secondary and tertiary care in the region of Ribeirão Preto. Compliance with the metrics was investigated using questionnaires in guided interviews of the system analysts responsible for the applications. The outcomes indicate that most of the procedures specified in the model can be adopted to assess the systems that serves the organization, particularly in the attributes of compatibility, reliability, safety, portability and usability.

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Purpose: This was a retrospective cohort study designed to evaluate the clinical performance of ceramicveneered zirconia frameworks. Materials and Methods: Patients were recruited according to defined inclusion criteria. All patients were checked every 4 months from the time of definitive rehabilitation. At the end of 2013, all patients were rescheduled and rechecked for study purposes. The restorative procedures assessment was performed by previously established methods. The primary outcomes were the survival and success rates of the prosthesis. Descriptive statistics were used for the patient's demographics, implant distribution, and occurrence of complications. To study the survival and success of the prostheses, a Cox Regression analysis was used with a model constructed in a forward conditional stepwise mode. Predictive variables were included in the model, and adjusted survival curves were obtained for each outcome. Results: From 2008 to 2013, 75 patients were rehabilitated with 92 implant-supported, screw-retained, full-arch ceramic-veneered zirconia framework rehabilitations. The range of follow-up was between 6 months and 5 years. From the 92 full implant-supported screw-retained full-arch rehabilitations, Cox regression analysis indicated that within a 5-year time frame, the probability of framework fracture, major chipping, minor chipping, or any of the former combined to occur was 17.6%, 46.5%, 69.2%, and 90.5%, respectively. Conclusion: Results suggest zirconia as a suitable material for framework structure in implant-supported, full-arch rehabilitations. However, it experiences a high incidence of technical complications, mainly due to ceramic chipping. Further clinical studies should aim to ascertain the effects of clinical features and manufacturing procedures on the survival rates of these prostheses. © 2016 by Quintessence Publishing Co Inc.

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Although errors might foster learning, they can also be perceived as something to avoid if they are associated with negative consequences (e.g., receiving a bad grade or being mocked by classmates). Such adverse perceptions may trigger negative emotions and error-avoidance attitudes, limiting the possibility to use errors for learning. These students’ reactions may be influenced by relational and cultural aspects of errors that characterise the learning environment. Accordingly, the main aim of this research was to investigate whether relational and cultural characteristics associated with errors affect psychological mechanisms triggered by making mistakes. In the theoretical part, we described the role of errors in learning using an integrated multilevel (i.e., psychological, relational, and cultural levels of analysis) approach. Then, we presented three studies that analysed how cultural and relational error-related variables affect psychological aspects. The studies adopted a specific empirical methodology (i.e., qualitative, experimental, and correlational) and investigated different samples (i.e., teachers, primary school pupils and middle school students). Findings of study one (cultural level) highlighted errors acquire different meanings that are associated with different teachers’ error-handling strategies (e.g., supporting or penalising errors). Study two (relational level) demonstrated that teachers’ supportive error-handling strategies promote students’ perceptions of being in a positive error climate. Findings of study three (relational and psychological level) showed that positive error climate foster students’ adaptive reactions towards errors and learning outcomes. Overall, our findings indicated that different variables influence students’ learning from errors process and teachers play an important role in conveying specific meanings of errors during learning activities, dealing with students’ mistakes supportively, and establishing an error-friendly classroom environment.

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Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with no curative pharmacological treatment. Animal models play an essential role in revealing molecular mechanisms involved in the pathogenesis of the disease. Bleomycin (BLM)-induced lung fibrosis is the most widely used and characterized model for anti-fibrotic drugs screening. However, several issues have been reported, such as the identification of an optimal BLM dose and administration scheme as well as gender-specificity. Moreover, the balance between disease resolution, an appropriate time window for therapeutic intervention and animal welfare remains critical aspects yet to be fully elucidated. In this thesis, Micro CT imaging has been used as a tool to identify the ideal BLM dose regimen to induce sustained lung fibrosis in mice as well as to assess the anti-fibrotic effect of Nintedanib (NINT) treatment upon this BLM administration regimen. In order to select the optimal BLM dose scheme, C57bl/6 male mice were treated with BLM via oropharyngeal aspiration (OA), following either double or triple BLM administration. The triple BLM administration resulted in the most promising scheme, able to balance disease resolution, appropriate time-window for therapeutic intervention and animal welfare. The fibrosis progression was longitudinally assessed by micro-CT every 7 days for 5 weeks after BLM administration and 5 animals were sacrificed at each timepoint for the BALF and histological evaluation. The antifibrotic effect of NINT was assessed following different treatment regimens in this model. Herein, we have developed an optimized mouse model of pulmonary fibrosis, enabling three weeks of the therapeutic window to screen putative anti-fibrotic drugs. micro-CT scanning, allowed us to monitor the progression of lung fibrosis and the therapeutical response longitudinally in the same subject, drastically reducing the number of animals involved in the experiment.

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Primary myelofibrosis is a clonal hematopoietic disorder characterized by marked degrees of systemic inflammation. The release of pro-inflammatory factors by clonal hematopoietic cell populations cause the remodeling of a specialized microenvironment, defined niche, in which the hematopoietic stem cells reside. The main source of pro-inflammatory cytokines is represented by malignant megakaryocytes. The bone marrow and spleen from myelofibrosis patients, as well as those from the Gata1low mouse model of the disease, contain increased number of abnormal megakaryocytes. These cells express on their surface high levels of the adhesion receptor P-selectin that, by triggering a pathological megakaryocyte-neutrophil emperipolesis, lead to increased bioavailability of TGF-β1 in the microenvironment and disease progression. Gata1low mice develop with age a phenotype similar to that of patients with myelofibrosis. We previously demonstrated that deletion of the P-selectin gene in Gata1low mice prevented the development of the myelofibrotic phenotype in these mice. In the current study, we tested the hypothesis that pharmacological inhibition of P-selectin may rescue the fibrotic phenotype of Gata1low mice. To test this hypothesis, we have investigated the phenotype expressed by old Gata1low mice treated with the anti-mouse monoclonal antibody against P-selectin RB40.34, alone or in combination with the JAK2 inhibitor Ruxolitinib. The results showed that the combined therapy normalized the phenotype of Gata1low mice with limited toxicity by reducing fibrosis, TGF-β1 and CXCL1 content in the BM and spleen and by restoring hematopoiesis in the bone marrow and the normal architecture of the spleen. In conclusion, pharmacological inhibition of P-selectin was effective in targeting malignant megakaryocytes and the microenvironmental abnormalities that affect the hematopoietic stem cell compartment in this model. These results suggest that P-selectin and JAK1/2 inhibitors in combination may represent a valid therapeutic option for patients with myelofibrosis.

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Day by day, machine learning is changing our lives in ways we could not have imagined just 5 years ago. ML expertise is more and more requested and needed, though just a limited number of ML engineers are available on the job market, and their knowledge is always limited by an inherent characteristic of theirs: they are humans. This thesis explores the possibilities offered by meta-learning, a new field in ML that takes learning a level higher: models are trained on other models' training data, starting from features of the dataset they were trained on, inference times, obtained performances, to try to understand the relationship between a good model and the way it was obtained. The so-called metamodel was trained on data collected by OpenML, the largest ML metadata platform that's publicly available today. Datasets were analyzed to obtain meta-features that describe them, which were then tied to model performances in a regression task. The obtained metamodel predicts the expected performances of a given model type (e.g., a random forest) on a given ML task (e.g., classification on the UCI census dataset). This research was then integrated into a custom-made AutoML framework, to show how meta-learning is not an end in itself, but it can be used to further progress our ML research. Encoding ML engineering expertise in a model allows better, faster, and more impactful ML applications across the whole world, while reducing the cost that is inevitably tied to human engineers.

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Combinatorial decision and optimization problems belong to numerous applications, such as logistics and scheduling, and can be solved with various approaches. Boolean Satisfiability and Constraint Programming solvers are some of the most used ones and their performance is significantly influenced by the model chosen to represent a given problem. This has led to the study of model reformulation methods, one of which is tabulation, that consists in rewriting the expression of a constraint in terms of a table constraint. To apply it, one should identify which constraints can help and which can hinder the solving process. So far this has been performed by hand, for example in MiniZinc, or automatically with manually designed heuristics, in Savile Row. Though, it has been shown that the performances of these heuristics differ across problems and solvers, in some cases helping and in others hindering the solving procedure. However, recent works in the field of combinatorial optimization have shown that Machine Learning (ML) can be increasingly useful in the model reformulation steps. This thesis aims to design a ML approach to identify the instances for which Savile Row’s heuristics should be activated. Additionally, it is possible that the heuristics miss some good tabulation opportunities, so we perform an exploratory analysis for the creation of a ML classifier able to predict whether or not a constraint should be tabulated. The results reached towards the first goal show that a random forest classifier leads to an increase in the performances of 4 different solvers. The experimental results in the second task show that a ML approach could improve the performance of a solver for some problem classes.

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Beta cell destruction in type 1 diabetes (TID) is associated with cellular oxidative stress and mitochondrial pathway of cell death. The aim of this study was to determine whether oxidative stress and mitochondrial dysfunction are present in T1D model (non-obese diabetic mouse, NOD) and if they are related to the stages of disease development. NOD mice were studied at three stages: non-diabetic, pre-diabetic, and diabetic and compared with age-matched Balb/c mice. Mitochondria respiration rates measured at phosphorylating and resting states in liver and soleus biopsies and in isolated liver mitochondria were similar in NOD and Balb/c mice at the three disease stages. However, NOD liver mitochondria were more susceptible to calcium-induced mitochondrial permeability transition as determined by cyclosporine-A-sensitive swelling and by decreased calcium retention capacity in all three stages of diabetes development. Mitochondria H2O2 production rate was higher in non-diabetic, but unaltered in pre-diabetic and diabetic NOD mice. The global cell reactive oxygen species (ROS), but not specific mitochondria ROS production, was significantly increased in NOD lymphomononuclear and stem cells in all disease stages. In addition, marked elevated rates of 2',7'-dichlorodihydrofluorescein (H2DCF) oxidation were observed in pancreatic islets from non-diabetic NOD mice. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) and lipidomic approach, we identified oxidized lipid markers in NOD liver mitochondria for each disease stage, most of them being derivatives of diacylglycerols and phospholipids. These results suggest that the cellular oxidative stress precedes the establishment of diabetes and may be the cause of mitochondrial dysfunction that is involved in beta cell death.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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PURPOSE: Evaluate the bone tissue recovery following transplantation of ovine mesenchymal stem cells (MSC) from bone marrow and human immature dental-pulp stem cells (hIDPSC) in ovine model of induced osteonecrosis of femoral head (ONFH). METHODS: Eight sheep were divided in three experimental groups. First group was composed by four animals with ONFH induced by ethanol through central decompression (CD), for control group without any treatment. The second and third group were compose by two animals, six weeks after ONFH induction received transplantation of heterologous ovine MSC (CD + oMSC), and hIDPSC (CD + hIDPSC), respectively. In both experiments the cells were transplanted without application of any type of immunosupression protocol. RESULTS: Our data indicate that both cell types used in experiments were able to proliferate within injured site providing bone tissue recovery. The histological results obtained from CD+hIDPSC suggested that the bone regeneration in such animals was better than that observed in CD animals. CONCLUSION: Mesenchymal stem cell transplant in induced ovine osteonecrosis of femoral head by central decompression technique is safe, and apparently favors bone regeneration of damaged tissues.

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Malignant brain tumor experimental models tend to employ cells that are immunologically compatible with the receptor animal. In this study, we have proposed an experimental model of encephalic tumor development by injecting C6 cells into athymic Rowett rats, aiming at reaching a model which more closely resembles to the human glioma tumor. In our model, we observed micro-infiltration of tumor cell clusters in the vicinity of the main tumor mass, and of more distal isolated tumor cells immersed in normal encephalic parenchyma. This degree of infiltration is superior to that usually observed in other C6 models.

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We evaluated the impact of a lifestyle intervention on the cardiometabolic risk profile of women participating in the Study on Diabetes and Associated Diseases in the Japanese-Brazilian Population in Bauru. This was a non-controlled experimental study including clinical and laboratory values at baseline and after a 1-year intervention period. 401 Japanese-Brazilian women were examined (age 60.8±11.7 years), and 365 classified for metabolic syndrome (prevalence = 50.6%). Subjects with metabolic syndrome were older than those without (63.0±10.0 vs. 56.7±11.6 years, p < 0.01). After intervention, improvements in variables were found, except for C-reactive protein. Body mass index and waist circumference decreased, but adiposity reduction was more pronounced in the abdominal region (87.0±9.7 to 84.5±11.2cm, p < 0.001). Intervention-induced differences in total cholesterol, LDL, and post-challenge glucose were significant; women who lost more than 5% body weight showed a better profile than those who did not. The lifestyle intervention in Japanese-Brazilian women at high cardiometabolic risk improved anthropometric and laboratory parameters, but it is not known whether such benefits will persist and result in long-term reduction in cardiovascular events.

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OBJETIVO: analisar a insegurança alimentar e o vínculo inadequado mãe-filho como dois potenciais determinantes da desnutrição em crianças de quatro a seis anos de idade. MÉTODOS: estudo de caso-controle desenvolvido em Escolas Municipais de Educação Infantil (EMEIs) no Jardim Jaqueline, área de alta vulnerabilidade social do município de São Paulo, Brasil. Foram aplicados a Escala Brasileira de Insegurança Alimentar e o Protocolo de Avaliação do Vínculo Mãe-filho, além de coletadas informações biológicas e socio-econômicas. Para verificação dos efeitos de cada variável independente e controle dos efeitos das demais variáveis incluídas no modelo, foi utilizado o modelo de regressão logística múltipla. RESULTADOS: verificou-se que tanto a insegurança alimentar familiar (OR=3,6) como o vínculo inadequado mãe-filho (OR=9,4) estiveram associados com a desnutrição infantil (p<0,05), mesmo após o controle para o peso ao nascimento da criança e idade, estado conjugal e trabalho maternos. CONCLUSÕES: tanto a insegurança alimentar familiar (OR=3,6) como o vínculo mãe-filho inadequado (OR=9,4) mostraram-se fatores determinantes da ocorrência da desnutrição na população estudada.