915 resultados para Automated estimator
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Cryopreservation of sperm is important to preserve the gerrnplasm from animals of genetic value, which can die unexpectedly. This study compares conventional and automated methods of cryopreservation of spermatozoa obtained from the epididymis of bulls post-mortem. Twenty-two epididymides were obtained from a commercial slaughterhouse. Spermatozoa were collected from the tail of the epididymis using the retrograde flow technique. Thus, the samples, which were diluted in 10 ml of extender without glycerol (Botubov (R) I, Botupharma, Botucatu, SP, Brazil), were evaluated on motility, sperm vigor, structural and functional (swelling hypoosmotic test) membrane integrity, mitochondrial activity, sperm viability and ADN fragmentation. The samples were divided into two aliquots and diluted in extender with glycerol (Botubov (R) II, Botupharma, Botucatu, SP, Brazil) at a concentration of 50x10(6) motile sperm/0.5 French straws. One sample was frozen by the conventional method (4 hours at 5 degrees C, in a refrigerator and 20 min in nitrogen vapor) and the other by the automated method (Cryogen (R) Dualflex, Neovet, Uberaba, MG, Brazil). The parameters were higher in all the tests of fresh sperm samples, with the exception of the swelling hypoosmotic test, which showed no significant difference when the results were compared with sperm frozen by the conventional method. The average motility of fresh spermatozoa was 74%, and conventional and automated averages were 29 and 25%, respectively. Therefore, although cryopreservation techniques reduce sperm quality parameters, the viability of the sperm is maintained, and these methods can be used to preserve sperm.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The development of self-adaptive software (SaS) has specific characteristics compared to traditional one, since it allows that changes to be incorporated at runtime. Automated processes have been used as a feasible solution to conduct the software adaptation at runtime. In parallel, reference model has been used to aggregate knowledge and architectural artifacts, since capture the systems essence of specific domains. However, there is currently no reference model based on reflection for the development of SaS. Thus, the main contribution of this paper is to present a reference model based on reflection for development of SaS that have a need to adapt at runtime. To present the applicability of this model, a case study was conducted and good perspective to efficiently contribute to the area of SaS has been obtained.
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Insulin resistance is a common risk factor in chronic kidney disease patients contributing to the high cardiovascular burden, even in the absence of diabetes. Glucose-based peritoneal dialysis (PD) solutions are thought to intensify insulin resistance due to the continuous glucose absorption from the peritoneal cavity. The aim of our study was to analyse the effect of the substitution of glucose for icodextrin on insulin resistance in non-diabetic PD patients in a multicentric randomized clinical trial. This was a multicenter, open-label study with balanced randomization (1:1) and two parallel-groups. Inclusion criteria were non-diabetic adult patients on automated peritoneal dialysis (APD) for at least 3 months on therapy prior to randomization. Patients assigned to the intervention group were treated with 2L of icodextrin 7.5%, and the control group with glucose 2.5% during the long dwell and, at night in the cycler, with a prescription of standard glucose-based PD solution only in both groups. The primary end-point was the change in insulin resistance measured by homeostatic model assessment (HOMA) index at 90 days. Sixty patients were included in the intervention (n = 33) or the control (n = 27) groups. There was no difference between groups at baseline. After adjustment for pre-intervention HOMA index levels, the group treated with icodextrin had the lower post-intervention levels at 90 days in both intention to treat [1.49 (95% CI: 1.23-1.74) versus 1.89 (95% CI: 1.62-2.17)], (F = 4.643, P = 0.03, partial η(2) = 0.078); and the treated analysis [1.47 (95% CI: 1.01-1.84) versus 2.18 (95% CI: 1.81-2.55)], (F = 7.488, P = 0.01, partial η(2) = 0.195). The substitution of glucose for icodextrin for the long dwell improved insulin resistance measured by HOMA index in non-diabetic APD patients.
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The impact of peritoneal dialysis modality on patient survival and peritonitis rates is not fully understood, and no large-scale randomized clinical trial (RCT) is available. In the absence of a RCT, the use of an advanced matching procedure to reduce selection bias in large cohort studies may be the best approach. The aim of this study is to compare automated peritoneal dialysis (APD) and continuous ambulatory peritoneal dialysis (CAPD) according to peritonitis risk, technique failure and patient survival in a large nation-wide PD cohort. This is a prospective cohort study that included all incident PD patients with at least 90 days of PD recruited in the BRAZPD study. All patients who were treated exclusively with either APD or CAPD were matched for 15 different covariates using a propensity score calculated with the nearest neighbor method. Clinical outcomes analyzed were overall mortality, technique failure and time to first peritonitis. For all analysis we also adjusted the curves for the presence of competing risks with the Fine and Gray analysis. After the matching procedure, 2,890 patients were included in the analysis (1,445 in each group). Baseline characteristics were similar for all covariates including: age, diabetes, BMI, Center-experience, coronary artery disease, cancer, literacy, hypertension, race, previous HD, gender, pre-dialysis care, family income, peripheral artery disease and year of starting PD. Mortality rate was higher in CAPD patients (SHR1.44 CI95%1.21-1.71) compared to APD, but no difference was observed for technique failure (SHR0.83 CI95%0.69-1.02) nor for time till the first peritonitis episode (SHR0.96 CI95%0.93-1.11). In the first large PD cohort study with groups balanced for several covariates using propensity score matching, PD modality was not associated with differences in neither time to first peritonitis nor in technique failure. Nevertheless, patient survival was significantly better in APD patients.
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Traditional abduction imposes as a precondition the restriction that the background information may not derive the goal data. In first-order logic such precondition is, in general, undecidable. To avoid such problem, we present a first-order cut-based abduction method, which has KE-tableaux as its underlying inference system. This inference system allows for the automation of non-analytic proofs in a tableau setting, which permits a generalization of traditional abduction that avoids the undecidable precondition problem. After demonstrating the correctness of the method, we show how this method can be dynamically iterated in a process that leads to the construction of non-analytic first-order proofs and, in some terminating cases, to refutations as well.
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A sensitive, selective, and reproducible in-tube solid-phase microextraction and liquid chromatographic (in-tube SPME/LC-UV) method for determination of lidocaine and its metabolite monoethylglycinexylidide (MEGX) in human plasma has been developed, validated, and further applied to pharmacokinetic study in pregnant women with gestational diabetes mellitus (GDM) subjected to epidural anesthesia. Important factors in the optimization of in-tube SPME performance are discussed, including the draw/eject sample volume, draw/eject cycle number, draw/eject flow rate, sample pH, and influence of plasma proteins. The limits of quantification of the in-tube SPME/LC method were 50 ng/mL for both metabolite and lidocaine. The interday and intraday precision had coefficients of variation lower than 8%, and accuracy ranged from 95 to 117%. The response of the in-tube SPME/LC method for analytes was linear over a dynamic range from 50 to 5000 ng/mL, with correlation coefficients higher than 0.9976. The developed in-tube SPME/LC method was successfully used to analyze lidocaine and its metabolite in plasma samples from pregnant women with GDM subjected to epidural anesthesia for pharmacokinetic study.
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Purpose: Automated weaning modes are available in some mechanical ventilators, but no studies compared them hitherto. We compared the performance of 3 automated modes under standard and challenging situations. Methods: We used a lung simulator to compare 3 automated modes, adaptive support ventilation (ASV), mandatory rate ventilation (MRV), and Smartcare, in 6 situations, weaning success, weaning failure, weaning success with extreme anxiety, weaning success with Cheyne-Stokes, weaning success with irregular breathing, and weaning failure with ineffective efforts. Results: The 3 modes correctly recognized the situations of weaning success and failure, even when anxiety or irregular breathing were present but incorrectly recognized weaning success with Cheyne-Stokes. MRV incorrectly recognized weaning failure with ineffective efforts. Time to pressure support (PS) stabilization was shorter for ASV (1-2 minutes for all situations) and MRV (1-7 minutes) than for Smartcare (8-78 minutes). ASV had higher rates of PS oscillations per 5 minutes (4-15), compared with Smartcare (0-1) and MRV (0-12), except when extreme anxiety was present. Conclusions: Smartcare, ASV, and MRV were equally able to recognize weaning success and failure, despite the presence of anxiety or irregular breathing but performed incorrectly in the presence of Cheyne-Stokes. PS behavior over the time differs among modes, with ASV showing larger and more frequent PS oscillations over the time. Clinical studies are needed to confirm our results. (C) 2012 Elsevier Inc. All rights reserved.
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The autoregressive (AR) estimator, a non-parametric method, is used to analyze functional magnetic resonance imaging (fMRI) data. The same method has been used, with success, in several other time series data analysis. It uses exclusively the available experimental data points to estimate the most plausible power spectra compatible with the experimental data and there is no need to make any assumption about non-measured points. The time series, obtained from fMRI block paradigm data, is analyzed by the AR method to determine the brain active regions involved in the processing of a given stimulus. This method is considerably more reliable than the fast Fourier transform or the parametric methods. The time series corresponding to each image pixel is analyzed using the AR estimator and the corresponding poles are obtained. The pole distribution gives the shape of power spectra, and the pixels with poles at the stimulation frequency are considered as the active regions. The method was applied in simulated and real data, its superiority is shown by the receiver operating characteristic curves which were obtained using the simulated data.
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Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.
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Objective: To review the clinical characteristics of patients with neuromyelitis optica (NMO) and to compare their visual outcome with those of patients with optic neuritis (ON) and multiple sclerosis (MS). Methods: Thirty-three patients with NMO underwent neuro-ophthalmic evaluation, including automated perimetry along with 30 patients with MS. Visual function in both groups was compared overall and specifically for eyes after a single episode of ON. Results: Visual function and average visual field (VF) mean deviation were significantly worse in eyes of patients with NMO. After a single episode of ON, the VF was normal in only 2 of 36 eyes of patients with NMO compared to 17 of 35 eyes with MS (P < 0.001). The statistical analysis indicated that after a single episode of ON, the odds ratio for having NMO was 6.0 (confidence interval [CI]: 1.6-21.9) when VF mean deviation was worse than -20.0 dB while the odds ratio for having MS was 16.0 (CI: 3.6-68.7) when better than -3.0 dB. Conclusion: Visual outcome was significantly worse in NMO than in MS. After a single episode of ON, suspicion of NMO should be raised in the presence of severe residual VF deficit with automated perimetry and lowered in the case of complete VF recovery.
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Purpose: To evaluate the relationship between glaucomatous structural damage assessed by the Cirrus Spectral Domain OCT (SDOCT) and functional loss as measured by standard automated perimetry (SAP). Methods: Four hundred twenty-two eyes (78 healthy, 210 suspects, 134 glaucomatous) of 250 patients were recruited from the longitudinal Diagnostic Innovations in Glaucoma Study and from the African Descent and Glaucoma Evaluation Study. All eyes underwent testing with the Cirrus SDOCT and SAP within a 6-month period. The relationship between parapapillary retinal nerve fiber layer thickness (RNFL) sectors and corresponding topographic SAP locations was evaluated using locally weighted scatterplot smoothing and regression analysis. SAP sensitivity values were evaluated using both linear as well as logarithmic scales. We also tested the fit of a model (Hood) for structure-function relationship in glaucoma. Results: Structure was significantly related to function for all but the nasal thickness sector. The relationship was strongest for superotemporal RNFL thickness and inferonasal sensitivity (R(2) = 0.314, P < 0.001). The Hood model fitted the data relatively well with 88% of the eyes inside the 95% confidence interval predicted by the model. Conclusions: RNFL thinning measured by the Cirrus SDOCT was associated with correspondent visual field loss in glaucoma.
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This work proposes the development of an Adaptive Neuro-fuzzy Inference System (ANFIS) estimator applied to speed control in a three-phase induction motor sensorless drive. Usually, ANFIS is used to replace the traditional PI controller in induction motor drives. The evaluation of the estimation capability of the ANFIS in a sensorless drive is one of the contributions of this work. The ANFIS speed estimator is validated in a magnetizing flux oriented control scheme, consisting in one more contribution. As an open-loop estimator, it is applied to moderate performance drives and it is not the proposal of this work to solve the low and zero speed estimation problems. Simulations to evaluate the performance of the estimator considering the vector drive system were done from the Matlab/Simulink(R) software. To determine the benefits of the proposed model, a practical system was implemented using a voltage source inverter (VSI) to drive the motor and the vector control including the ANFIS estimator, which is carried out by the Real Time Toolbox from Matlab/Simulink(R) software and a data acquisition card from National Instruments.
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Among the ongoing attempts to enhance cognitive performance, an emergent and yet underrepresented venue is brought by hemoencefalographic neurofeedback (HEG). This paper presents three related advances in HEG neurofeedback for cognitive enhancement: a) a new HEG protocol for cognitive enhancement, as well as b) the results of independent measures of biological efficacy (EEG brain maps) extracted in three phases, during a one year follow up case study; c) the results of the first controlled clinical trial of HEG, designed to assess the efficacy of the technique for cognitive enhancement of an adult and neurologically intact population. The new protocol was developed in the environment of a software that organizes digital signal algorithms in a flowchart format. Brain maps were produced through 10 brain recordings. The clinical trial used a working memory test as its independent measure of achievement. The main conclusion of this study is that the technique appears to be clinically promising. Approaches to cognitive performance from a metabolic viewpoint should be explored further. However, it is particularly important to note that, to our knowledge, this is the world's first controlled clinical study on the matter and it is still early for an ultimate evaluation of the technique.