313 research outputs found
Development and Evaluation of a Borohydride-palladium System for Selective Reduction of the C=C Bond of α,β-unsaturated Carbonyl Compounds
Selective reduction of the carbon-carbon double bond of α,β-unsaturated carbonyl compounds is most commonly and reliably effected using a palladium metal catalyst together with molecular hydrogen from a pressurized tank. Sodium borohydride, like other hydrides, is ordinarily associated with reduction of the more polarized carbonyl of such compounds. However, we have developed an alternative means of employing sodium borohydride in combination with palladium metal to selectively reduce the carbon-carbon double bonds of these compounds. In this survey study, we introduce sodium borohydride as an alternative hydrogen source for such selective, palladium-catalyzed reductions. We also compare the results of this new, heterogeneous borohydride-palladium method with that of traditional palladium-catalyzed hydrogenation. A third method using only sodium borohydride with no palladium is included for comparison.Faculty Sponsor: Dr. David B. Corde
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Implicit equal-weights particle filter
Filter degeneracy is the main obstacle for the implementation of particle filter in non-linear high-dimensional models.
A new scheme, the implicit equal-weights particle filter (IEWPF), is introduced. In this scheme samples are drawn implicitly from proposal densities with a different covariance for each particle, such that all particle weights are equal by construction.
We test and explore the properties of the new scheme using a 1,000-dimensional simple linear model, and the 1,000-dimensional non-linear Lorenz96 model, and compare the performance of the scheme to a Local Ensemble Kalman Filter.
The experiments show that the new scheme can easily be implemented in high-dimensional systems and is never degenerate, with good convergence properties in both systems
Use of the stock market simulator in the Faculty of Administrative and Social Sciences of the UV as a tool to support the learning of students
El objetivo de este artículo es exponer la manera en que se ha implementado la simulación en los estudiantes que cursan la experiencia educativa Finanzas Internacionales de la carrera de Administración de Negocios Internacionales, así como los beneficios que ha aportado en su formación. Por lo que en primera instancia, se presenta una revisión de literatura sobre el uso de los simuladores educativos a través del tiempo, posteriormente se aborda la metodología empleada en el curso iniciando como base del conocimiento la parte teórica, para luego aplicarlos en el uso del simulador bursátil donde éste favorece significativamente en el aprendizaje, pues los acerca al mundo real de una manera fácil, en seguida se muestran los resultados obtenidos los cuales revelan que los simuladores son una herramienta única para crear un entorno de enseñanza-aprendizaje efectivo, ya que proporcionan una visión integral de los saberes teóricos y prácticos, finalizando con las conclusiones.The objective of this article is to expose the way in which simulation has been implemented in students who are studying the International Finance educational experience of the International Business Administration career, as well as the benefits it has provided in their training. Therefore, in the first instance, a review of the literature on the use of educational simulators over time is presented, later the methodology used in the course is addressed, starting as a basis of knowledge the theoretical part, and then applying them in the use of the Stock market simulator where it significantly favors learning, as it brings them closer to the real world in an easy way, then the results obtained are shown which reveal that simulators are a unique tool to create an effective teaching-learning environment, since provides a comprehensive view of the theoretical and practical knowledge ending with the conclusions
Analyzing the turbulent planetary boundary layer by remote sensing systems: the Doppler wind lidar, aerosol elastic lidar and microwave radiometer
he planetary boundary layer (PBL) is the lowermost
region of troposphere and is endowed with turbulent
characteristics, which can have mechanical and/or thermodynamic
origins. This behavior gives this layer great importance,
mainly in studies about pollutant dispersion and
weather forecasting. However, the instruments usually applied
in studies of turbulence in the PBL have limitations
in spatial resolution (anemometer towers) or temporal resolution
(instrumentation aboard an aircraft). Ground-based
remote sensing, both active and passive, offers an alternative
for studying the PBL. In this study we show the capabilities
of combining different remote sensing systems (microwave
radiometer – MWR, Doppler lidar – DL – and elastic lidar
– EL) for retrieving a detailed picture on the PBL turbulent
features. The statistical moments of the high frequency distributions
of the vertical wind velocity, derived from DL,
and of the backscattered coefficient, derived from EL, are
corrected by two methodologies, namely first lag correction
and -2=3 law correction. The corrected profiles, obtained
from DL data, present small differences when compared with
the uncorrected profiles, showing the low influence of noise
and the viability of the proposed methodology. Concerning
EL, in addition to analyzing the influence of noise, we explore
the use of different wavelengths that usually include
EL systems operated in extended networks, like the European
Aerosol Research Lidar Network (EARLINET),This work was supported by the Andalusia
Regional Government through project P12-RNM-2409 and by the
Spanish Agencia Estatal de Investigación (AEI) through projects
CGL2016-81092-R and CGL2017-90884-REDT. We acknowledge
the financial support by the European Union’s Horizon 2020
research and innovation program through project ACTRIS-2 (grant
agreement no. 654109)
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The value of adding black carbon to community monitoring of particulate matter
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Ensemble clustering in deterministic ensemble Kalman filters
Ensemble clustering (EC) can arise in data assimilation with ensemble square root filters (EnSRFs) using non-linear models: an M-member ensemble splits into a single outlier and a cluster of M−1 members. The stochastic Ensemble Kalman Filter does not present this problem. Modifications to the EnSRFs by a periodic resampling of the ensemble through random rotations have been proposed to address it. We introduce a metric to quantify the presence of EC and present evidence to dispel the notion that EC leads to filter failure. Starting from a univariate model, we show that EC is not a permanent but transient phenomenon; it occurs intermittently in non-linear models. We perform a series of data assimilation experiments using a standard EnSRF and a modified EnSRF by a resampling though random rotations. The modified EnSRF thus alleviates issues associated with EC at the cost of traceability of individual ensemble trajectories and cannot use some of algorithms that enhance performance of standard EnSRF. In the non-linear regimes of low-dimensional models, the analysis root mean square error of the standard EnSRF slowly grows with ensemble size if the size is larger than the dimension of the model state. However, we do not observe this problem in a more complex model that uses an ensemble size much smaller than the dimension of the model state, along with inflation and localisation. Overall, we find that transient EC does not handicap the performance of the standard EnSRF
Remote System for Detection of Low-Levels of Methane Based on Photonic Crystal Fibres and Wavelength Modulation Spectroscopy
In this work we described an optical fibre sensing system for detecting low levels of methane. The properties of hollow-core photonic crystal fibres are explored to have a sensing head with favourable characteristics for gas sensing, particularly in what concerns intrinsic readout sensitivity and gas diffusion time in the sensing structure. The sensor interrogation was performed applying the Wavelength Modulation Spectroscopy technique, and a portable measurement unit was developed with performance suitable for remote detection of low levels of methane. This portable system has the capacity to simultaneously interrogate four remote photonic crystal fibre sensing heads
Extreme, wintertime Saharan dust intrusion in the Iberian Peninsula: Lidar monitoring and evaluation of dust forecast models during the February 2017 event
The research leading to these results has received funding from the H2020 program from the European Union (grant agreement no. 654109, 778349) and also from the Spanish Ministry of Industry, Economy and Competitiviness (MINECO, ref. CGL2013-45410-R, CGL2016-81092-R, CGL2017-85344-R, TEC2015-63832-P), the Spanish Ministry of Science, Innovation and Universities (ref. CGL2017-90884-REDT); the CommSensLab "Maria de Maeztu" Unity of Excellence (ref. MDM-2016-0600) financed by the Spanish Agencia Estatal de Investigación. Co-funding was also provided by the European Union through the European Regional Development Fund (ref. POCI-01-0145-FEDER-007690, ALT20-03-0145-FEDER-000004, ALT20-03-0145-FEDER-000011); by the Andalusia Regional Government (ref. P12-RNM-2409); by the Madrid Regional Government (projects TIGAS-CM, ref. Y2018/EMT-5177 and AIRTEC-CM, ref. P2018/EMT4329); by the University of Granada through “Plan Propio. Programa 9 Convocatoria 2013” and by the Portuguese Foundation for Science and Technology and national funding (ref. SFRH/BSAB/143164/2019). The BSC-DREAM8b and NNMB/BSC-Dust (now NMMB-MONARCH) model simulations were performed by the Mare Nostrum supercomputer hosted by the Barcelona Supercomputer Center (BSC). S. Basart acknowledges the AXA Research Fund for supporting aerosol research at the BSC through the AXA Chair on Sand and Dust Storms Fund, as well as the InDust project (COST Action CA16202). The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website (http://www.ready.noaa.gov) used in this publication.An unprecedented extreme Saharan dust event was registered in winter time from 20 to 23 February 2017 over the Iberian Peninsula (IP). We report on aerosol optical properties observed under this extreme dust intrusion through passive and active remote sensing techniques. For that, AERONET (AErosol RObotic NETwork) and EARLINET (European Aerosol Research LIdar NETwork) databases are used. The sites considered are: Barcelona (41.38°N, 2.17°E), Burjassot (39.51°N, 0.42°W), Cabo da Roca (38.78°N, 9.50°W), Évora (38.57°N, 7.91°W), Granada (37.16°N, 3.61°W) and Madrid (40.45°N, 3.72°W). Large aerosol optical depths (AOD) and low Ångström exponents (AE) are observed. An AOD of 2.0 at 675 nm is reached in several stations. A maximum peak of 2.5 is registered in Évora. During and around the peak of AOD, AEs close to 0 and even slightly negative are measured. With regard to vertically-resolved aerosol optical properties, particle backscatter coefficients as high as 15 Mm−1 sr−1 at 355 nm are recorded at the lidar stations. Layer-mean lidar ratios are found in the range 40–55 sr at 355 nm and 34–61 sr at 532 nm during the event. The particle depolarization ratios are found to be constant inside the dust layer, and consistent from one site to another. Layer-mean values vary in the range 0.19–0.31. Another remarkable aspect of the event is the limited vertical distribution of the dust plume which never exceeds 5 km. The extreme aspect of the event also presented a nice case for testing the ability of two dust forecast models, BSC-DREAM8b and NMMB/BSC-Dust, to reproduce the arrival, the vertical distribution and the intensity of the dust plume over a long-range transport region. In the particular case of the February 2017 dust event, we found a large underestimation in the forecast of the extinction coefficient provided by BSC-DREAM8b at all heights independently of the site. In contrast NMMB/BSC-Dust forecasts presented a better agreement with the observations, especially in southwestern part of the IP. With regard to the forecast skill as a function of lead time, no clear degradation of the prognostic is appreciated at 24, 48 and 72 h for Évora and Granada stations (South). However the prognostic does degrade (bias increases and/or correlation decreases) for Barcelona (North), which is attributed to the fact that Barcelona is at a greater distance from the source region and to the singularity of the event.Funding from the H2020 program from the European Union (grant agreement no. 654109, 778349)Spanish Ministry of Industry, Economy and Competitiviness (MINECO, ref. CGL2013-45410-R, CGL2016-81092-R, CGL2017-85344-R, TEC2015-63832-P)Spanish Ministry of Science, Innovation and Universities (ref. CGL2017-90884-REDT)CommSensLab "Maria de Maeztu" Unity of Excellence (ref. MDM-2016-0600) financed by the Spanish Agencia Estatal de InvestigaciónCo-funding was also provided by the European Union through the European Regional Development Fund (ref. POCI-01-0145-FEDER-007690, ALT20-03-0145-FEDER-000004, ALT20-03-0145-FEDER-000011)Andalusia Regional Government (ref. P12-RNM-2409); by the Madrid Regional Government (projects TIGAS-CM, ref. Y2018/EMT-5177 and AIRTEC-CM, ref. P2018/EMT4329)Portuguese Foundation for Science and Technology and national funding (ref. SFRH/BSAB/143164/2019
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An international initiative of predicting the Sars-Cov-2 pandemic using ensemble data assimilation
This work demonstrates the efficiency of using iterative ensemble smoothers to estimate the parameters of an SEIR model. We have extended a standard SEIR model with age-classes and compartments of sick, hospitalized, and dead. The data conditioned on are the daily numbers of accumulated deaths and the number of hospitalized. Also, it is possible to condition the model on the number of cases obtained from testing. We start from a wide prior distribution for the model parameters; then, the ensemble conditioning leads to a posterior ensemble of estimated parameters yielding model predictions in close agreement with the observations. The updated ensemble of model simulations has predictive capabilities and include uncertainty estimates. In
particular, we estimate the effective reproductive number as a function of time, and we can assess the impact of different intervention measures. By starting from the updated set of model parameters, we can make accurate short-term predictions of the epidemic development assuming
knowledge of the future effective reproductive number. Also, the model system allows for the computation of long-term scenarios of the epidemic under different assumptions. We have applied the model system on data sets from several countries, i.e., the four European countries Norway, England, The Netherlands, and France; the province of Quebec in Canada; the South American countries Argentina and Brazil; and the four US states Alabama, North Carolina, California, and New York. These countries and states all have vastly different developments of the epidemic, and we could accurately model the SARS-CoV-2 outbreak in all of them. We realize that more complex models, e.g., with regional compartments, may be desirable, and we suggest that the approach used here should be applicable also for these models
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