1,720 research outputs found
Quantitative weighted estimates for Rubio de Francia's Littlewood--Paley square function
We consider the Rubio de Francia's Littlewood--Paley square function
associated with an arbitrary family of intervals in with finite
overlapping. Quantitative weighted estimates are obtained for this operator.
The linear dependence on the characteristic of the weight turns
out to be sharp for , whereas the sharpness in the range
remains as an open question. Weighted weak-type estimates in the endpoint
are also provided. The results arise as a consequence of a sparse domination
shown for these operators, obtained by suitably adapting the ideas coming from
Benea (2015) and Culiuc et al. (2016).Comment: 18 pages. Revised versio
Feasibility analysis of design for remanufacturing in bearing using hybrid fuzzy-topsis and taguchi optimization
The tremendous advancement in technology, productivity and improved standard of living has come at the cost of environmental deterioration, increased energy and raw material consumption. In this regard, remanufacturing is viable option to reduce energy usage, carbon footprint and raw material usage. In this manuscript, using computational intelligence techniques we try to determine the feasibility of remanufacturing in case of roller bearings. We collected used N308 bearings from 5 different Indian cities. Using Fuzzy-TOPSIS, we found that the roundness, surface roughness and weight play a vital role in design for remanufacturing of roller bearings. Change in diameter, change in thickness and change in width showed minimal influence. We also used Taguchi analysis to reassess the problem. The roundness of inner and outer race was found to be the most influential parameters in deciding the selection of bearing for remanufacturing. The results suggest the bearing designer to design the bearing in such a way that roundness of both races will be taken cared while manufacturing a bearing. However, using Taguchi the weight of the rollers was found to be of least influence. Overall, the predictions of Taguchi analysis were found to be similar to Fuzzy-TOPSIS analysis
Quantitative weighted estimates for Rubio de Francia's Littlewood--Paley square function
We consider the Rubio de Francia's Littlewood--Paley square function associated with an arbitrary family of intervals in with finite overlapping.
Quantitative weighted estimates are obtained for this operator. The linear dependence on the characteristic of the weight turns out to be sharp for , whereas the sharpness in the range remains as an open question. Weighted weak-type estimates in the endpoint are also provided. The results arise as a consequence of a sparse domination shown for these operators, obtained by suitably adapting the ideas coming from Benea [2015] and Culiuc et al. [2018].2017 Leonardo grant for Researchers and Cultural Creators, BBVA Foundatio
Invariant Random Approximation in Nonconvex Domain
Random fixed point results in the setup of compact and weakly compact domain of Banach spaces which is not necessary starshaped have been obtained in the present work. Invariant random approximation results have also been determined asits application. In this way, random version of invariant approximation results due toMukherjee and Som [13] and Singh [17] have been given.DOI : http://dx.doi.org/10.22342/jims.15.2.45.69-7
Simple Analytical Particle and Kinetic Energy Densities for a Dilute Fermionic Gas in a d-Dimensional Harmonic Trap
We derive simple analytical expressions for the particle density
and the kinetic energy density for a system of noninteracting
fermions in a dimensional isotropic harmonic oscillator potential. We test
the Thomas-Fermi (TF, or local-density) approximation for the functional
relation using the exact and show that it locally
reproduces the exact kinetic energy density , {\it including the shell
oscillations,} surprisingly well everywhere except near the classical turning
point. For the special case of two dimensions (2D), we obtain the unexpected
analytical result that the integral of yields the {\it
exact} total kinetic energy.Comment: 4 pages, 4 figures; corrected versio
Modeling regional aerosol variability over California and its sensitivity to emissions and long-range transport during the 2010 CalNex and CARES campaigns
Abstract. The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The extensive meteorological, trace gas, and aerosol measurements collected at surface sites and along aircraft and ship transects during CalNex and CARES were combined with operational monitoring network measurements to create a single dataset that was used to evaluate the one configuration of the model. Simulations were performed that examined the sensitivity of regional variations in aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally-driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. However, sub-grid scale variability in the meteorology and emissions as well as uncertainties in the treatment of secondary organic aerosol chemistry likely contribute to errors at a primary surface sampling site located at the edge of the Los Angeles basin. Differences among the sensitivity simulations demonstrate that the aerosol layers over the central valley detected by lidar measurements likely resulted from lofting and recirculation of local anthropogenic emissions along the Sierra Nevada. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. The model performance for some aerosol species was not uniform over the region, and we found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics regarding the differences between observed and simulated quantities. Comparisons with lidar and in-situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of two that offset the under-predictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during "clean" conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES datasets are an ideal testbed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes
Open-Retrieval Conversational Question Answering
Conversational search is one of the ultimate goals of information retrieval.
Recent research approaches conversational search by simplified settings of
response ranking and conversational question answering, where an answer is
either selected from a given candidate set or extracted from a given passage.
These simplifications neglect the fundamental role of retrieval in
conversational search. To address this limitation, we introduce an
open-retrieval conversational question answering (ORConvQA) setting, where we
learn to retrieve evidence from a large collection before extracting answers,
as a further step towards building functional conversational search systems. We
create a dataset, OR-QuAC, to facilitate research on ORConvQA. We build an
end-to-end system for ORConvQA, featuring a retriever, a reranker, and a reader
that are all based on Transformers. Our extensive experiments on OR-QuAC
demonstrate that a learnable retriever is crucial for ORConvQA. We further show
that our system can make a substantial improvement when we enable history
modeling in all system components. Moreover, we show that the reranker
component contributes to the model performance by providing a regularization
effect. Finally, further in-depth analyses are performed to provide new
insights into ORConvQA.Comment: Accepted to SIGIR'2
Laboratory Characterization of PM Emissions from Combustion of Wildland Biomass Fuels
[1] Particle emissions from open burning of southwestern (SW) and southeastern (SE) U.S. fuel types during 77 controlled laboratory burns are presented. The fuels include SW vegetation types: ceanothus, chamise/scrub oak, coastal sage scrub, California sagebrush, manzanita, maritime chaparral, masticated mesquite, oak savanna, and oak woodland, as well as SE vegetation types: 1 year, 2 year rough, pocosin, chipped understory, understory hardwood, and pine litter. The SW fuels burned at higher modified combustion efficiency (MCE) than the SE fuels resulting in lower particulate matter mass emission factor. Particle mass distributions for six fuels and particle number emission for all fuels are reported. Excellent mass closure (slope = 1.00, r2 = 0.94) between ions, metals, and carbon with total weight was obtained. Organic carbon emission factors inversely correlated (R2 = 0.72) with average MCE, while elemental carbon (EC) had little correlation with average MCE (R2 = 0.10). The EC/total carbon ratio sharply increased with MCE for MCEs exceeding 0.94. The average levoglucosan and total polycyclic aromatic hydrocarbon (PAH) emissions factors ranged from 25 to 1272 mg/kg fuel and 1.8 to 11.3 mg/kg fuel, respectively. No correlation between average MCE and emissions of PAHs/levoglucosan was found. Additionally, PAH diagnostic ratios were observed to be poor indicators of biomass burning. Large fuel type and regional dependency were observed in the emission rates of ammonium, nitrate, chloride, sodium, and potassium
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