Frame-semantic parsing

Frame semantics is a linguistic theory that has been instantiated for English in the FrameNet lexicon. We solve the problem of frame-semantic parsing using a two-stage statistical model that takes lexical targets (i.e., content words and phrases) in their sentential contexts and predicts frame-semantic structures. Given a target in context, the first stage disambiguates it to a semantic frame. This model uses latent variables and semi-supervised learning to improve frame disambiguation for targets unseen at training time. The second stage finds the target's locally expressed semantic arguments. At inference time, a fast exact dual decomposition algorithm collectively predicts all the arguments of a frame at once in order to respect declaratively stated linguistic constraints, resulting in qualitatively better structures than naïve local predictors. Both components are feature-based and discriminatively trained on a small set of annotated frame-semantic parses. On the SemEval 2007 benchmark data set, the approach, along with a heuristic identifier of frame-evoking targets, outperforms the prior state of the art by significant margins. Additionally, we present experiments on the much larger FrameNet 1.5 data set. We have released our frame-semantic parser as open-source software.United States. Defense Advanced Research Projects Agency (DARPA grant NBCH-1080004)National Science Foundation (U.S.) (NSF grant IIS-0836431)National Science Foundation (U.S.) (NSF grant IIS-0915187)Qatar National Research Fund (NPRP 08-485-1-083

Development of a source oriented version of the WRF/Chem model and its application to the California regional PM₁₀ / PM_2.5 air quality study

A source-oriented version of the Weather Research and Forecasting model with chemistry (SOWC, hereinafter) was developed. SOWC separately tracks primary particles with different hygroscopic properties rather than instantaneously combining them into an internal mixture. This approach avoids artificially mixing light absorbing black + brown carbon particles with materials such as sulfate that would encourage the formation of additional coatings. Source-oriented particles undergo coagulation and gas-particle conversion, but these processes are considered in a dynamic framework that realistically "ages" primary particles over hours and days in the atmosphere. SOWC more realistically predicts radiative feedbacks from anthropogenic aerosols compared to models that make internal mixing or other artificial mixing assumptions. <br><br> A three-week stagnation episode (15 December 2000 to 6 January 2001) in the San Joaquin Valley (SJV) during the California Regional PM₁₀ / PM_2.5 Air Quality Study (CRPAQS) was chosen for the initial application of the new modeling system. Primary particles emitted from diesel engines, wood smoke, high-sulfur fuel combustion, food cooking, and other anthropogenic sources were tracked separately throughout the simulation as they aged in the atmosphere. <br><br> Differences were identified between predictions from the source oriented vs. the internally mixed representation of particles with meteorological feedbacks in WRF/Chem for a number of meteorological parameters: aerosol extinction coefficients, downward shortwave flux, planetary boundary layer depth, and primary and secondary particulate matter concentrations. Comparisons with observations show that SOWC predicts particle scattering coefficients more accurately than the internally mixed model. Downward shortwave radiation predicted by SOWC is enhanced by ~1% at ground level chiefly because diesel engine particles in the source-oriented mixture are not artificially coated with material that increases their absorption efficiency. The extinction coefficient predicted by SOWC is reduced by an average of 0.012 km⁻¹ (4.8%) in the SJV with a maximum reduction of ~0.2 km⁻¹. Planetary boundary layer (PBL) height is increased by an average of 5.2 m (1.5%) with a~maximum of ~100 m in the SJV. Particulate matter concentrations predicted by SOWC are 2.23 μg m⁻³ (3.8%) lower than the average by the internally mixed version of the same model in the SJV because increased solar radiation at the ground increases atmospheric mixing. <br><br> The changes in predicted meteorological parameters and particle concentrations identified in the current study stem from the mixing state of black carbon. The source-oriented model representation with realistic aging processes predicts that hydrophobic diesel engine particles remain largely uncoated over the +7 day simulation period, while the internal mixture model representation predicts significant accumulation of secondary nitrate and water on diesel engine particles. Similar results will likely be found in any air pollution stagnation episode that is characterized by significant particulate nitrate production. Future work should consider episodes where coatings are predominantly sulfate and/or secondary organic aerosol

Recyclation of Textil Waste

Bakalářská práce se zaměřuje na recyklaci textilního odpadu. Popisuje situaci v České Republice a v zahraničí, především v Severských státech. Popisuje metody sběru, třídění a recyklace v některých podnicích a organizacích v Dánsku, Finsku, Švédsku, Německu a České Republice a možnostech dalšího využití.My Bachelor thesis focuses on recyclation of textile waste. It describes the situation in Czech Republic a in foreign countries, especially in Nordic countries. It describes methods of collection, sorting and recyclation of some companies and organizations in Denmark, Finland, Sweden, Germany and Czech Republic and options for further use.546 - Institut environmentálního inženýrstvídobř

Implementation of warm-cloud processes in a source-oriented WRF/Chem model to study the effect of aerosol mixing state on fog formation in the Central Valley of California

The source-oriented Weather Research and Forecasting chemistry model (SOWC) was modified to include warm cloud processes and was applied to investigate how aerosol mixing states influence fog formation and optical properties in the atmosphere. SOWC tracks a 6-D chemical variable (<i>X</i>, <i>Z</i>, <i>Y</i>, size bins, source types, species) through an explicit simulation of atmospheric chemistry and physics. A source-oriented cloud condensation nuclei module was implemented into the SOWC model to simulate warm clouds using the modified two-moment Purdue Lin microphysics scheme. The Goddard shortwave and long-wave radiation schemes were modified to interact with source-oriented aerosols and cloud droplets so that aerosol direct and indirect effects could be studied. <br><br> The enhanced SOWC model was applied to study a fog event that occurred on 17 January 2011, in the Central Valley of California. Tule fog occurred because an atmospheric river effectively advected high moisture into the Central Valley and nighttime drainage flow brought cold air from mountains into the valley. The SOWC model produced reasonable liquid water path, spatial distribution and duration of fog events. The inclusion of aerosol–radiation interaction only slightly modified simulation results since cloud optical thickness dominated the radiation budget in fog events. The source-oriented mixture representation of particles reduced cloud droplet number relative to the internal mixture approach that artificially coats hydrophobic particles with hygroscopic components. The fraction of aerosols activating into cloud condensation nuclei (CCN) at a supersaturation of 0.5&thinsp;% in the Central Valley decreased from 94&thinsp;% in the internal mixture model to 80&thinsp;% in the source-oriented model. This increased surface energy flux by 3&ndash;5 W m^&minus;2 and surface temperature by as much as 0.25&thinsp;K in the daytime

Correlates of Adherence Among Rural Indian Women Living With HIV/AIDS

In this prospective, randomized clinical trial, correlates of adherence to antiretroviral therapy (ART) were assessed using a baseline questionnaire among 68 rural women living with AIDS (WLA) in India. Unadjusted analyses revealed positive relationships of ART adherence with Hindu religion, and support from spouses and parents, whereas negative associations were found with depression, poor quality of life, and having ten or more HIV symptoms. Multiple linear regression analysis also revealed that WLA who were Hindu, not depressed, had ART support from spouses and parents, and perceived some benefit from ART were more adherent to ART than their respective counterparts. This study reveals the unique challenges which rural WLA experience and the need to mitigate these challenges early in ART treatment. Further, the findings enable the refinement of an intervention program which will focus on strengthening ART adherence among rural WLA