Linearizing Toda and SVD flows on large phase spaces of matrices with real spectrum

We consider different phase spaces for the Toda flows and the less familiar SVD flows. For the Toda flow, we handle symmetric and non-symmetric matrices with real simple eigenvalues, possibly with a given profile. Profiles encode, for example, band matrices and Hessenberg matrices. For the SVD flow, we assume simplicity of the singular values. In all cases, an open cover is constructed, as are corresponding charts to Euclidean space. The charts linearize the flows, converting it into a linear differential system with constant coefficients and diagonal matrix. A variant construction transform the flows into uniform straight line motion. Since limit points belong to the phase space, asymptotic behavior becomes a local issue. The constructions rely only on basic facts of linear algebra, making no use of symplectic geometry.Comment: 25 pages, 2 figure

A semi-supervised learning algorithm for relevance feedback and collaborative image retrieval

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The interaction of users with search services has been recognized as an important mechanism for expressing and handling user information needs. One traditional approach for supporting such interactive search relies on exploiting relevance feedbacks (RF) in the searching process. For large-scale multimedia collections, however, the user efforts required in RF search sessions is considerable. In this paper, we address this issue by proposing a novel semi-supervised approach for implementing RF-based search services. In our approach, supervised learning is performed taking advantage of relevance labels provided by users. Later, an unsupervised learning step is performed with the objective of extracting useful information from the intrinsic dataset structure. Furthermore, our hybrid learning approach considers feedbacks of different users, in collaborative image retrieval (CIR) scenarios. In these scenarios, the relationships among the feedbacks provided by different users are exploited, further reducing the collective efforts. Conducted experiments involving shape, color, and texture datasets demonstrate the effectiveness of the proposed approach. Similar results are also observed in experiments considering multimodal image retrieval tasks.The interaction of users with search services has been recognized as an important mechanism for expressing and handling user information needs. One traditional approach for supporting such interactive search relies on exploiting relevance feedbacks (RF) i2015FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [2013/08645-0, 2013/50169-1]CNPq [306580/2012-8, 484254/2012-0]2013/08645-0; 2013/50169-1306580/2012-8;484254/2012-0SEM INFORMAÇÃ

Meso-microscale coupling for wind resource assessment using averaged atmospheric stability conditions

This research was supported by a grant from The Norwegian Research Council, project number 271080. We acknowledge Botnia-Atlantica, an EU-programme financing cross border cooperation projects in Sweden, Finland and Norway, for their support of this work through the WindCoE project. We would like to thank the High Performance Computing Center North (HPC2N) for providing the computer resources needed to perform the numerical experiments presented in this paper. We would also like to thank the two anonymous reviewers for their useful comments.Peer reviewedPublisher PD

The Usage of Skeletal Muscle Oxygenation and Heart Rate Variability as Predictors of Aerobic Fitness.

Heart rate variability (HRV) is used to assess the autonomic nervous system’s (ANS) activity on the heart, while skeletal muscle oxygenation (SmO2) measures how well muscles uptake oxygen from the blood. Both measurements have demonstrated strong associations with cardiorespiratory fitness and are altered with increased exercise workloads. Both have been used to assess athletic performance. While the gold standard for assessing cardiorespiratory fitness is VO2 max testing, several situations preclude the usage of a true VO2 max. Purpose: To determine if HRV and SmO2 possess predictive qualities to accurately assess cardiorespiratory fitness levels. Methods: Thirty-six healthy fit individuals (n = 22 men; n = 14 women; age 37.6 + 12.4 yr; BF% 19.2 + 7.1%; VO2max 41.8 + 7.4 ml/kg/min) completed a single VO2 max ramp protocol treadmill test while wearing an infrared oxyhemoglobin (MOXY) Sensor to assess SmO2 while HRV was assessed via Polar (Bluetooth monitor (Polar H7)) heart rate (HR) monitor. The MOXY Sensor was placed on the lateral-posterior belly of the gastrocnemius while the Polar HR monitor was placed on the distal third of the sternum using an elastic belt. The data was analyzed using a Pearson Correlation to compare SmO2, HRV indices, and VO2max associations. In addition, a multiple linear regression analysis was performed to examine the relationship between HRV indices and SmO2 to VO2 max. All analyses were performed using SPSS (v. 28.0.1.1). Results: There was a significant correlation between VO2 max, mean of RR intervals (mRR) (r = 0.440, p = 0.007), and THb Max (r = 0.509, p = 0.002). mRR and THb Max were able to significantly predictive (r2 = 0.365, p = 0.001) VO2 max outcomes. Conclusion: The combination of SmO2 measurements and HRV can assist in predicting VO2 max levels, but further research is needed to determine the accuracy at which it will predict. This can be a useful and simple method for predicting cardiorespiratory fitness when a VO2 max test is unavailable, or an individual is unfit to perform one. This can aid in better exercise prescription for chronic diseased individuals

The Influence of Age and Cardiorespiratory Fitness on Cardiac Autonomic Modulation. A Pilot Study.

Maximal rate of oxygen consumption (VO2max) is traditionally viewed as the gold standard of determining cardiorespiratory fitness (CF) in healthy and diseased populations. CF has a significant influence on the improvement of cardiac autonomic modulation (CAM) and the risk of morbidity and mortality rates. Heart rate variability (HRV) is a non-invasive way to assess CAM. Age is another factor that influences CAM and CF in healthy and diseased populations. However, what is not fully elucidated, is if CF is maintained at a high level throughout adulthood, will CAM remain relatively unchanged. PURPOSE: To determine if age and CF are significantly correlated to variables of HRV to determine CAM in healthy fit individuals. METHODS: Twenty-two healthy individuals (n = 14 male; n = 8 female, Age 33.2 ± 11.8 years, %BF 18.3 ± 6.0, VO2max 42.0 ± 6.2 ml/ /kg/min) completed a single health assessment to quantify CF and HRV. HRV was measured for 5 mins in the supine position and during a standard VO2max test using an elastic belt and Bluetooth monitor (Polar H7). CardioMood software was used to process HRV variables high frequency (HF), low frequency (LF), total power (TP) were assessed for frequency domain, and standard deviation of all NN intervals (SDNN) and the square root of the mean of the squares of successive R-R interval differences (RMSSD) for the time domain. Pearson correlation was used to check associations between age and CF, and CAM. Multiple regression was implemented to determine if there were any differences in HRV variables in relation to age and VO2max. A paired sample t-test was used to determine changes in HRV variables from rest to VO2max. All analyses were performed using SAS (v.9.3). RESULTS: HRV variables were significantly altered from rest to VO2max (p \u3c 0.05). HRV time and frequency domain variables were not significantly correlated to age and CF level (p \u3e 0.05). The multiple regression analysis indicated that the only significance was max heart rate is 0.642 bpm lower during exercise for each 1-year increase in age (p = 0.035). CONCLUSION: The analysis of pilot data focused on determining the impact of CF and age on CAM appears not to be significantly correlated when utilizing HRV. However, due to the project\u27s continuation and further data collection, significant outcomes may still be observed

Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks

Plant phenology studies rely on long-term monitoring of life cycles of plants. High-resolution unmanned aerial vehicles (UAVs) and near-surface technologies have been used for plant monitoring, demanding the creation of methods capable of locating, and identifying plant species through time and space. However, this is a challenging task given the high volume of data, the constant data missing from temporal dataset, the heterogeneity of temporal profiles, the variety of plant visual patterns, and the unclear definition of individuals' boundaries in plant communities. In this letter, we propose a novel method, suitable for phenological monitoring, based on convolutional networks (ConvNets) to perform spatio-temporal vegetation pixel classification on high-resolution images. We conducted a systematic evaluation using high-resolution vegetation image datasets associated with the Brazilian Cerrado biome. Experimental results show that the proposed approach is effective, overcoming other spatio-temporal pixel-classification strategies