Rough volatility via the Lamperti transform

We study the roughness of the log-volatility process by testing the self-similarity of the process obtained by the de-Lampertized realized volatility. The value added of our analysis rests on the application of a distribution-based estimator providing results which are more robust with respect to those deduced by the scaling of the individual moments of the process. Our findings confirm the roughness of the log-volatility process

3D-Hog Embedding Frameworks for Single and Multi-Viewpoints Action Recognition Based on Human Silhouettes

This paper has been presented at : 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Given the high demand for automated systems for human action recognition, great efforts have been undertaken in recent decades to progress the field. In this paper, we present frameworks for single and multi-viewpoints action recognition based on Space-Time Volume (STV) of human silhouettes and 3D-Histogram of Oriented Gradient (3D-HOG) embedding. We exploit fast-computational approaches involving Principal Component Analysis (PCA) over the local feature spaces for compactly describing actions as combinations of local gestures and L 2 -Regularized Logistic Regression (L 2 -RLR) for learning the action model from local features. Outperforming results on Weizmann and i3DPost datasets confirm efficacy of the proposed approaches as compared to the baseline method and other works, in terms of accuracy and robustness to appearance changes

Archaeology and virtual acoustics. A pan flute from ancient Egypt

This paper presents the early developments of a recently started research project, aimed at studying from a multidisciplinary perspective an exceptionally well preserved ancient pan flute. A brief discussion of the history and iconography of pan flutes is provided, with a focus on Classical Greece. Then a set of non-invasive analyses are presented, which are based on 3D scanning andmaterials chemistry, and are the starting point to inspect the geometry, construction, age and geographical origin of the instrument. Based on the available measurements, a preliminary analysis of the instrument tuning is provided, which is also informed with elements of theory of ancient Greek music. Finally, the paper presents current work aimed at realizing an interactive museum installation that recreates a virtual flute and allows intuitive access to all these research facets

Evidence of a cyclotron feature in the spectrum of the anomalous X-ray pulsar 1RXS J170849-400910

We report the results of a long observation of the anomalous X-ray pulsar 1RXS J170849-400910 obtained with the BeppoSAX satellite in August 2001. The best-fit phase-averaged spectrum was an absorbed power law plus blackbody model, with photon index Gamma~2.4 and a blackbody temperature of kT_bb~0.4 keV. We confirm the presence of significant spectral variations with the rotational phase of the pulsar. In the spectrum corresponding to the rising part of the pulse we found an absorption-like feature at ~8.1 keV (a significance of 4 sigma), most likely due to cyclotron resonant scattering. The centroid energy converts to a magnetic field of 9x10^11 G and 1.6x10^15 G in the case of electrons and protons, respectively. If confirmed, this would be the first detection of a cyclotron feature in the spectrum of an anomalous X-ray pulsar.Comment: 5 pages, 5 figures. Accepted for publication on ApJ Letter

Exploring chitosan-shelled nanobubbles to improve HER2 + immunotherapy via dendritic cell targeting

Immunotherapy is a valuable approach to cancer treatment as it is able to activate the immune system. However, the curative methods currently in clinical practice, including immune checkpoint inhibitors, present some limitations. Dendritic cell vaccination has been investigated as an immunotherapeutic strategy, and nanotechnology-based delivery systems have emerged as powerful tools for improving immunotherapy and vaccine development. A number of nanodelivery systems have therefore been proposed to promote cancer immunotherapy. This work aims to design a novel immunotherapy nanoplatform for the treatment of HER2 + breast cancer, and specially tailored chitosan-shelled nanobubbles (NBs) have been developed for the delivery of a DNA vaccine. The NBs have been functionalized with anti-CD1a antibodies to target dendritic cells (DCs). The NB formulations possess dimensions of approximately 300 nm and positive surface charge, and also show good physical stability up to 6 months under storage at 4 °C. In vitro characterization has confirmed that these NBs are capable of loading DNA with good encapsulation efficiency (82%). The antiCD1a-functionalized NBs are designed to target DCs, and demonstrated the ability to induce DC activation in both human and mouse cell models, and also elicited a specific immune response that was capable of slowing tumor growth in mice in vivo. These findings are the proof of concept that loading a tumor vaccine into DC-targeted chitosan nanobubbles may become an attractive nanotechnology approach for the future immunotherapeutic treatment of cancer. GRAPHICAL ABSTRACT: [Image: see text

Renal function and physical fitness after 12-mo supervised training in kidney transplant recipients

To evaluate the effect of a 12-mo supervised aerobic and resistance training, on renal function and exercise capacity compared to usual care recommendations

The Swift X-ray flaring afterglow of GRB 050607

The unique capability of the Swift satellite to perform a prompt and autonomous slew to a newly detected Gamma-Ray Burst (GRB) has yielded the discovery of interesting new properties of GRB X-ray afterglows, such as the steep early lightcurve decay and the frequent presence of flares detected up to a few hours after the GRB trigger. We present observations of GRB 050607, the fourth case of a GRB discovered by Swift with flares superimposed on the overall fading X-ray afterglow. The flares of GRB 050607 were not symmetric as in previously reported cases, showing a very steep rise and a shallower decay, similar to the Fast Rise, Exponential Decay that are frequently observed in the gamma-ray prompt emission. The brighter flare had a flux increase by a factor of approximately 25,peaking for 30 seconds at a count rate of approximately 30 counts s-1, and it presented hints of addition short time scale activity during the decay phase. There is evidence of spectral evolution during the flares. In particular, at the onset of the flares the observed emission was harder, with a gradual softening as each flare decayed. The very short time scale and the spectral variability during the flaring activity are indicators of possible extended periods of energy emission by the GRB central engine. The flares were followed by a phase of shallow decay, during which the forward shock was being refreshed by a long-lived central engine or by shells of lower Lorentz factors, and by a steepening after approximately 12 ks to a decay slope considered typical of X-ray afterglows.Comment: 23 pages, 5 figures, Accepted by the Astrophysical Journa

Machine learning in space and time for modelling soil organic carbon change

Spatially resolved estimates of change in soil organic carbon (SOC) stocks are necessary for supporting national and international policies aimed at achieving land degradation neutrality and climate change mitigation. In this work we report on the development, implementation and application of a data-driven, statistical method for mapping SOC stocks in space and time, using Argentina as a pilot. We used quantile regression forest machine learning to predict annual SOC stock at 0–30 cm depth at 250 m resolution for Argentina between 1982 and 2017. The model was calibrated using over 5,000 SOC stock values from the 36-year time period and 35 environmental covariates. We preprocessed normalized difference vegetation index (NDVI) dynamic covariates using a temporal low-pass filter to allow the SOC stock for a given year to depend on the NDVI of the current as well as preceding years. Predictions had modest temporal variation, with an average decrease for the entire country from 2.55 to 2.48 kg C m−2 over the 36-year period (equivalent to a decline of 211 Gg C, 3.0% of the total 0–30 cm SOC stock in Argentina). The Pampa region had a larger estimated SOC stock decrease from 4.62 to 4.34 kg C m−2 (5.9%) during the same period. For the 2001–2015 period, predicted temporal variation was seven-fold larger than that obtained using the Tier 1 approach of the Intergovernmental Panel on Climate Change and United Nations Convention to Combat Desertification. Prediction uncertainties turned out to be substantial, mainly due to the limited number and poor spatial and static, whereas SOC is dynamic and SOC dynamics are of particular interest to carbon sequestration and land degradation studies. Thus, there is a clear need to extend spatial SOC mapping to space–time SOC mapping. temporal distribution of the calibration data, and the limited explanatory power of the covariates. Cross-validation confirmed that SOC stock prediction accuracy was limited, with a mean error of 0.03 kg C m−2 and a root mean squared error of 2.04 kg C m−2. In spite of the large uncertainties, this work showed that machine learning methods can be used for space–time SOC mapping and may yield valuable information to land managers and policymakers, provided that SOC observation density in space and time is sufficiently large.Fil: Heuvelink, Gerard B.M. ISRIC - World soil information; Holanda. Wageningen University. Soil Geography and Landscape Group; HolandaFil: Angelici, Marcos E. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Poggio, Laura ISRIC - World soil information, Wageningen; HolandaFil: Bai, Zhanguo ISRIC - World soil information, Wageningen, The NetherlandsFil: Batjes, Niels H. ISRIC - World soil information, Wageningen, The NetherlandsFil: an den Bosch, Rik ISRIC - World soil information, Wageningen, The NetherlandsFil: Bossio, Deborah The Nature Conservancy; Estados UnidosFil: Estella, Sergio Vizzuality; EspañaFil: Lehmann, Jhoannes. Cornell University. Soil and Crop Sciences; Estados UnidosFil: Olmedo, Guillermo F. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; ArgentinaFil: Sandermann, Jonathan. Woods Hole Research Center; Estados Unido