Inverse Spectral Methods in Acoustic Normal Mode Velocimetry of High Reynolds Number Spherical Couette Flows

Experimental geophysical fluid dynamics often examines regimes of fluid flow infeasible for computer simulations. Velocimetry of zonal flows present in these regimes brings many challenges when the fluid is opaque and vigorously rotating; spherical Couette flows with molten metals are one such example. The fine structure of the acoustic spectrum can be related to the fluid’s velocity field, and inverse spectral methods can be used to predict and, with sufficient acoustic data, mathematically reconstruct the velocity field. The methods are to some extent inherited from helioseismology. This work develops a Finite Element Method suitable to matching the geometries of experimental setups, as well as modelling the acoustics based on that geometry and zonal flows therein. As an application, this work uses the 60-cm setup Dynamo 3.5 at the University of Maryland Nonlinear Dynamics Laboratory. Additionally, results obtained using a small acoustic data set from recent experiments in air are provided.

Distance and overcurrent relay coordination considering non standardized inverse time curves

Protective relaying comprehends several procedures and techniques focused on maintaining the power system working safely during and after undesired and abnormal network conditions, mostly caused by faulty events. Overcurrent relay is one of the oldest protective relays, its operation principle is straightforward: when the measured current is greater than a specified magnitude the protection trips; less variables are required from the system in comparison with other protections, causing the overcurrent relay to be the simplest and also the most difficult protection to coordinate; its simplicity is reflected in low implementation, operation, and maintenance cost. The counterpart consists in the increased tripping times offered by this kind of relays mostly before faults located far from their location; this problem can be particularly accentuated when standardized inverse-time curves are used or when only maximum faults are considered to carry out relay coordination. These limitations have caused overcurrent relay to be slowly relegated and replaced by more sophisticated protection principles, it is still widely applied in subtransmission, distribution, and industrial systems. In this work, the use of non standardized inverse-time curves, the model and implementation of optimization algorithms capable to carry out the coordination process, the use of different levels of short circuit currents, and the inclusion of distance relays to replace insensitive overcurrent ones are proposed methodologies focused on the overcurrent relay performance improvement. These techniques may transform the typical overcurrent relay into a more sophisticated one without changing its fundamental principles and advantages. Consequently a more secure and still economical alternative can be obtained, increasing its implementation area

STUDY OF A DIRECT SAMPLING METHOD FOR THE INVERSE MEDIUM SCATTERING PROBLEM

Direct sampling methods are increasingly being used to solve the inverse medium scattering problem to estimate the shape of the scattering object. A simple direct method using one incident wave and multiple measurements was proposed by Ito, Jin and Zou. In this report, we performed some analytic and numerical studies of the direct sampling method. The method was found to be effective in general. However, there are a few exceptions exposed in the investigation. Analytic solutions in different situations were studied to verify the viability of the method while numerical tests were used to validate the effectiveness of the method.

Minor and major consolidations in inverse DEA:definition and determination

Many production systems have acquisition and merge operations to increase productivity. This paper proposes a novel method to anticipate whether a merger in a market is generating a major or a minor consolidation, using InvDEA model. A merger between two or more decision making units (DMUs) producing a single merged DMU that affects the efficiency frontier, defined by the pre-consolidation market conditions, is called a major consolidation. The corresponding alternative case is called a minor consolidation. A necessary and sufficient condition to distinguish the two types of consolidations is proven and two numerical illustrations in banking and supply chain management are discussed. The crucial importance of anticipating the magnitude of a consolidation in a market is outlined.

A methodological approach for the performance optimization of transient seepage models through inverse analysis

The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

A dive into the inverse Galois problem

Il problema inverso di Galois classico consiste nel chiedersi se, dato un gruppo finito G, esista una estensione di Galois del campo dei numeri razionali che abbia come gruppo di Galois il gruppo G. Una volta verificata l'esistenza di una tale estensione poi, si cercano polinomi a coefficienti razionali il cui gruppo di Galois sia G stesso. Noto dall'inizio del diciannovesimo secolo, il problema è tuttora in generale irrisolto, nonostante nel corso degli anni siano stati fatti notevoli progressi. In questa tesi il problema viene affrontato e risolto in alcuni casi particolari: viene mostrata la realizzazione dei gruppi ciclici, dei gruppi abeliani e dei gruppi simmetrici come gruppi di Galois sul campo dei razionali, e vengono dati alcuni esempi di polinomi con tali gruppi di Galois.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Association Of Single Nucleotide Polymorphisms In The Gene Encoding Glut1 And Diabetic Nephropathy In Brazilian Patients With Type 1 Diabetes Mellitus.

Mesangial cells subject to high extracellular glucose concentrations, as occur in hyperglycaemic states, are unable to down regulate glucose influx, resulting in intracellular activation of deleterious biochemical pathways. A high expression of GLUT1 participates in the development of diabetic glomerulopathy. Variants in the gene encoding GLUT1 (SLC2A1) have been associated to this diabetic complication. The aim of this study was to test whether polymorphisms in SLC2A1 confer susceptibility to diabetic nephropathy (DN) in Brazilian type 1 diabetes patients. Four polymorphisms (rs3820589, rs1385129, rs841847 and rs841848) were genotyped in a Brazilian cohort comprised of 452 patients. A prospective analysis was performed in 155 patients. Mean duration of follow-up was 5.6±2.4years and the incidence of renal events was 18.0%. The rs3820589 presented an inverse association with the prevalence of incipient DN (OR: 0.36, 95% CI: 0.16 - 0.80, p=0.01) and with progression to renal events (HR: 0.20; 95% CI: 0.03 - 0.70; p=0.009). AGGT and AGAC haplotypes were associated with the prevalence of incipient DN and the AGAC haplotype was also associated with the prevalence of established/advanced DN. In conclusion, rs3820589 in the SLC2A1 gene modulates the risk to DN in Brazilian patients with inadequate type 1 diabetes control.

Association Between Parity, Pre-pregnancy Body Mass Index And Gestational Weight Gain.

To analyze the relationship between parity, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG). This observational controlled study was conducted from November 2013 to April 2014, with postpartum women who started antenatal care up to 14 weeks and had full-term births. Data were collected from medical records and antenatal cards. Descriptive and bivariate analyses were performed. The significance level was 5%. Data were collected from 130 primiparous and 160 multiparous women. At the beginning of prenatal care, 54.62% of the primiparous were eutrophic, while the majority of multiparous were overweight or obese (62.51%). Multiparas are two times more likely to be obese at the beginning of their pregnancies, when compared to primiparas. The average pre-pregnancy weight and final pregnancy weight was significantly higher in multiparous, however, the mean GWG was higher among primiparous. We found an inverse correlation between parity and the total GWG, but initial BMI was significantly higher in multiparas. Nevertheless, monitoring of the GWG through actions that promote a healthier lifestyle is needed, regardless of parity and nutritional status, in order to prevent excessive GWG and postpartum weight retention and consequently inadequate pre-pregnancy nutritional status in future pregnancies.

Correlation Between The Friedman Staging System And The Upper Airway Volume In Patients With Obstructive Sleep Apnea.

This study was designed to evaluate the correlation between computed tomography findings and data from the physical examination and the Friedman Staging System (FSS) in patients with obstructive sleep apnea (OSA). We performed a retrospective evaluation by reviewing the medical records of 33 patients (19 male and 14 female patients) with a mean body mass index of 30.38 kg/m(2) and mean age of 49.35 years. Among these patients, 14 presented with severe OSA, 7 had moderate OSA, 7 had mild OSA, and 5 were healthy. The patients were divided into 2 groups according to the FSS: Group A comprised patients with FSS stage I or II, and group B comprised patients with FSS stage III. By use of the Fisher exact test, a positive relationship between the FSS stage and apnea-hypopnea index (P = .011) and between the FSS stage and body mass index (P = .012) was found. There was no correlation between age (P = .55) and gender (P = .53) with the FSS stage. The analysis of variance test comparing the upper airway volume between the 2 groups showed P = .018. In this sample the FSS and upper airway volume showed an inverse correlation and were useful in analyzing the mechanisms of airway collapse in patients with OSA.

Levantamento e características ecológicas de orchidacea e da mata ciliar do rio dourados, Dourados-MS

The Orchidaceae is one of the largest flowering plants family and with a great importance to conservation. However, no survey on orchid flowers can be found in Mato Grosso do Sul. Thus, the objective of this work was to make a survey of the Orchidaceae species and of its ecology features in a riparian forest in a fragment of Floresta Estacional Semi-Decidual that belongs to the riparian forest of the Dourados River. The inventory was made by using a sweeping method for collection, and in addition to this the vertical and horizontal position of epiphytes were assessed on the hosts. For characterization of microclimate, it was used a thermohygrometer and luximeter. It was identified 17 species of 13 genera. Of the listed genera, the most abundant ones were: Acianthera, Macradenia and Capanemia. It was also noted a vertical and horizontal distribution of the Orchidaceae in relation to inverse gradient of water and light availability. Some species tended to be sensitive to height level categorization, whereas others seemed to occur with similar frequency along the host. In relation to the cardinal orientation, the apparent preferential response for south and east directions was associated to the low sampling effort and lower water availability, which could occur because the north face is opposed to the water body.

Variação na cobertura vegetal nativa em São Paulo: um panorama do conhecimento atual

Studies in several countries have shown the occurrence of forest transition, when forest cover increase overcomes the loss by deforestation. In Brazil, although deforestation is still higher than afforestation, this relationship may be inverse in some regions. Recent assessments suggest the tendency of the state of São Paulo towards forest transition. Aiming to analyze forest transition evidence and facilitate the use of existing information, we review data on native vegetation cover variation in São Paulo from four data sources (Instituto Florestal, SOS MataAtlântica/INPE, IBGE and CATI/IEA). Our results indicate that discrepancies among these assessments may be accounted by differences in methodologies and objectives. We highlight their common grounds and discuss possibilities to harmonize their information.

Association of insulin resistance and GLP-2 secretion in obesity: a pilot study

OBJECTIVE: The objective of this pilot study was to determine whether glugagon-like peptide 2 (GLP-2) secretion relates to insulin sensitivity (IS) in obese subjects. SUBJECTS AND METHODS: Twenty four obese subjects [body mass index (BMI) 40.0 ± 3.0 kg/m² (mean ± standard deviation)] were included, nine of which were male, age 43 ± 8 years. Twelve subjects had type 2 diabetes, all treated with oral anti-diabetic agents only. The subjects were submitted to standard meal tolerance test (MTT) for dosage of the curves: glucose, insulin, and GLP-2. Insulin sensitivity was measured by HOMA-IR, and OGIS was derived from the MTT. Spearman linear correlations and partial correlations were obtained. RESULTS: There was an inverse relationship between the GLP-2 secretion and IS: HOMA-IR correlated with GLP-2 AUC (R = 0.504; p = 0.012), and OGIS correlated with GLP-2 incremental AUC (R = -0.54; p = 0.054). The correlation persisted after controlling for BMI. CONCLUSION: We found an association of GLP-2 secretion and insulin resistance (IR). The understanding of the underlying mechanisms may provide future directions in the pharmacological manipulation of incretins, and in the treatment of obesity and related metabolic disorders.