A5104089834- Particle Detector Development and Performance
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Particle physics theoretical and experimental studies
- Galaxies: Formation, Evolution, Phenomena
- Astronomy and Astrophysical Research
- Astrophysics and Cosmic Phenomena
- Mosquito-borne diseases and control
- Cosmology and Gravitation Theories
- Energy Load and Power Forecasting
- Scientific Research and Discoveries
- Radiation Detection and Scintillator Technologies
- Stellar, planetary, and galactic studies
- CCD and CMOS Imaging Sensors
- Dengue and Mosquito Control Research
- Black Holes and Theoretical Physics
- Atomic and Subatomic Physics Research
- Forecasting Techniques and Applications
- Gamma-ray bursts and supernovae
- Smart Grid Energy Management
- Image and Signal Denoising Methods
- Muon and positron interactions and applications
- IoT Networks and Protocols
- Advanced Differential Geometry Research
- Gaussian Processes and Bayesian Inference
Universidad Nacional de Asunción
2020-2025
National University of Distance Education
2024
Fermi National Accelerator Laboratory
2023
Guyra Paraguay
2023
Universidad Nacional De Caaguazú
2022
Universidad Tecnológica del Perú
2022
National Institute for Space Research
2012-2018
Sorbonne Université
2017
Centre National de la Recherche Scientifique
2017
Institut d'Astrophysique de Paris
2017
Millicharged particles, proposed by various extensions of the standard model, can be created in pairs high-energy photons within nuclear reactors and interact electromagnetically with electrons matter. Recently, existence a plasmon peak interaction cross section silicon eV range was highlighted as promising approach to enhance low-energy sensitivities. The CONNIE Atucha-II reactor neutrino experiments utilize Skipper-CCD sensors, which enable detection interactions range. We present...
A bstract The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with aim of detecting coherent elastic scattering antineutrinos silicon nuclei using charge-coupled devices (CCDs). In 2019 experiment operated a hardware binning applied to readout stage, leading lower levels noise and improving detection threshold down 50 eV. results analysis are reported here, corresponding detector array 8 CCDs fiducial mass 36.2 g total exposure 2.2...
A bstract Oscura is a planned light-dark matter search experiment using Skipper-CCDs with total active mass of 10 kg. As part the detector development, collaboration plans to build Integration Test (OIT), an engineering test 10% mass. Here we discuss early science opportunities OIT for millicharged particles (mCPs) NuMI beam at Fermilab. mCPs would be produced low energies through photon-mediated processes from decays scalar, pseudoscalar, and vector mesons, or direct Drell-Yan productions....
We investigate the dependence of stellar population properties galaxies on group dynamical stage for a subsample Yang catalog. classify groups according to their galaxy velocity distribution into Gaussian (G) and Non-Gaussian (NG). Using two totally independent approaches we have shown that our measurement Gaussianity is robust reliable. Our sample covers Yang's in redshift range 0.03 $\leq$ z 0.1 having mass $\geq$ 10$^{14} \rm M_{\odot}$. The new method, Hellinger Distance (HD), determine...
Abstract Oscura is a proposed multi-kg skipper-CCD experiment designed for dark matter (DM) direct detection search that will reach unprecedented sensitivity to sub-GeV DM-electron interactions with its 10 kg detector array. planning operate at SNOLAB 2070 m overburden, and aims background goal of less than one event in each electron bin the 2–10 ionization-signal region full 30 kg-year exposure, radiation rate 0.01 dru.[1 dru (differential unit) corresponds 1 event/kg/day/keV.] In order...
 Fractures serve as highly conductive flow conduits in subsurface formations and thus have a significant impact on transport. The length of fractures can vary over several orders magnitude, with the largest potentially being comparable size to domain interest. This makes it impossible define representative elementary volume for extraction effective parameters. Furthermore, due high uncertainty fracture locations parameters, Monte Carlo (MC) study is typically needed accurately...
Introduction Dengue is transmitted by the Aedes aegypti mosquito as a vector, and recent outbreak was reported in several districts of Lima, Peru. We conducted modeling study to explain transmission dynamics dengue three these according demographics climatology. Methodology used weekly distribution cases Comas, Lurigancho, Puente Piedra districts, well temperature data investigate dynamics. maximum likelihood minimization human susceptible-infected-recovered vector susceptible-infected...
Abstract In this paper we address the problem of short-term electric energy prediction using a time series forecasting approach applied to data generated by Paraguayan electricity distribution provider. The dataset used in work contains collected over three-year period. This is first that these have been used; therefore, preprocessing phase was also performed. particular, propose comparative study various machine learning and statistical strategies with objective predicting consumption for...
Abstract Gradient pattern analysis (GPA) is a well-established technique for measuring gradient bilateral asymmetries of square numerical lattice. This paper introduces an improved version GPA designed galaxy morphometry. We show the performance new method on selected sample 54 896 objects from SDSS-DR7 in common with Galaxy Zoo 1 catalogue. The results suggest that second moment, G2, has potential to dramatically improve over more conventional morphometric parameters. It separates early-...
While the density profiles (DPs) of $\Lambda$CDM haloes obey NFW law out to roughly one virial radius, $r_{\rm vir}$, structure their outer parts is still poorly understood, since 1-halo term describing halo itself dominated by 2-halo representing other picked up. Using a semi-analytical model, we measure real-space `1-halo' number DP groups $20\,r_{\rm vir}$ assigning each galaxy its nearest group with mass above $M_{\rm a}$, in units vir}$. If a}$ small (large), falls rapidly (slowly). We...
Dengue fever represents a public health problem and accurate forecasts can help governments take the best preventive actions. As volume of data provided continuously increases, machine learning deep (DL) models have become an attractive approach. However, it is difficult to perform predictions in areas with fewer cases. In this work, we compare traditional approaches such as LASSO Regression (LR), Random Forest (RF), Support Vector (SVR) vs DL based on long short-term memory (LSTM),...
Oscura is a proposed multi-kg skipper-CCD experiment designed for dark matter (DM) direct detection search that will reach unprecedented sensitivity to sub-GeV DM-electron interactions with its 10 kg detector array. planning operate at SNOLAB 2070 m overburden, and aims background goal of less than one event in each electron bin the 2-10 ionization-signal region full 30 kg-year exposure, radiation rate 0.01 dru. In order achieve this goal, must address potential source events, including...
We present results on the study of stellar population in Early-Type galaxies (ETGs) belonging to 151 Compact Groups (CGs). also selected a field sample composed 846 ETGs investigate environmental effects galaxy evolution. find that dependences mean ages, [Z/H] and [$α$/Fe] central velocity dispersion are similar, regardless where ETG resides, CGs or field. When compared centrals satellites from literature, we GCs behave similarly centrals, especially those embedded low-mass haloes ($M_{h}...
Oscura is a planned light-dark matter search experiment using Skipper-CCDs with total active mass of 10 kg. As part the detector development, collaboration plans to build Integration Test (OIT), an engineering test 10% mass. Here we discuss early science opportunities OIT for millicharged particles (mCPs) NuMI beam at Fermilab. mCPs would be produced low energies through photon-mediated processes from decays scalar, pseudoscalar, and vector mesons, or direct Drell-Yan productions. Estimates...
Short-term electricity demand forecasting represents a fundamental tool for decision-making by entities engaged in management since it allows the development of strategies to meet variations short periods.The accuracy predictive models is an important factor energy operations and scheduling generation sources at each instant.Intelligent based on Recurrent Neural Networks (RNN) require hyperparameter adjustment.These have several hyperparameters that substantially affect their performance.Our...
The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) aims to detect the coherent scattering (CE$\nu$NS) of reactor antineutrinos off silicon nuclei using thick fully-depleted high-resistivity CCDs. Two Skipper-CCD sensors with sub-electron readout noise capability were installed at experiment next Angra-2 in 2021, making CONNIE first employ Skipper-CCDs for neutrino detection. We report on performance Skipper-CCDs, new data processing and quality selection techniques event CE$\nu$NS...
Millicharged particles, proposed by various extensions of the standard model, can be created in pairs high-energy photons within nuclear reactors and interact electromagnetically with electrons matter. Recently, existence a plasmon peak interaction cross-section silicon eV range was highlighted as promising approach to enhance low-energy sensitivities. The CONNIE Atucha-II reactor neutrino experiments utilize Skipper-CCD sensors, which enable detection interactions range. We present...
CONNIE experiment installed 12 charge- coupled devices (CCDs) sensors near the Angra II nuclear reactor in dos Reis (Brazil) aiming to detect low energy antineutrinos produced core of reactor. For two years, these recorded particle images catching mainly muons and other particles such as electrons alphas that will be considered external radioactive background must removed. The were created from data taken every 3 hours, generating this way a vast catalog detected events on each CCD. In work...
This study aimed to develop accurate short-term air quality forecasting models for Asunción, Paraguay using machine learning algorithms. The dataset, which consisted of PM concentrations, indices, meteorological variables, and traffic information, spanned a duration 18 months. Two algorithms, Support Vector Regression (SVR) XGBoost, implemented window-based regression, were optimized grid search Bayesian optimization process. explored the impact look-back window <tex...