102 research outputs found
Patterns of Total Gaseous Mercury Variation Prior to and After Brownfield Remediation in Syracuse, NY
Although mercury toxicity has been recognized for centuries, the atmospheric cycle of this element is still not fully understood. In order to obtain a better perspective of the dynamics of atmospheric mercury in urban areas, total gaseous mercury (TGM) was measured at a brownfield site at the Center of Excellence (CoE) in Syracuse NY from 2011 to 2016. The brownfield was removed on May 2015, and a parking lot was installed. For this study, I had a series of objectives including: (1) to understand vertical and temporal variations in TGM concentration; (2) investigate the influence of meteorological factors on TGM concentrations and variations; (3) evaluate the effect of brownfield removal and site restoration on TGM concentrations and variations; (4) compare TGM variation at this site with other monitoring sites in New York State to confirm hypothesis made in this study. Continuous TGM measurements were made at two different heights (1.8 m and 42.7 m) at the COE. To interpret TGM variations, meteorological data collected by SUNY-ESF were also used in this analysis. In addition, mercury flux measurements from the land surface was conducted at this site on June 2015. Prior to brownfield remediation, the overall average TGM concentrations were 1.6±0.58 ng/m3 and 1.4±0.40 ng/m3 at ground and upper level, respectively. TGM tended to have higher concentrations during night and in the morning, and was positively correlated with air temperature, solar radiation, but negatively correlated with wind speed. After brownfield remediation, TGM concentrations immediately decreased by 32% and 22% at the ground and upper level, respectively and likely to have higher concentrations during nighttime and lower concentrations in the daylight. Relations of TGM concentrations with temperature, solar radiation and wind speed were completely eliminated after brownfield remediation. These results suggest that TGM concentrations at this site were strongly controlled by local mercury evasion prior to brownfield removal, with evasion rate increasing due to higher air temperature and stronger solar radiation. TGM derived from mercury evasion from the site were diluted by horizontal mixing from winds and vertical mixing associated with movement of the PBL
Optimal bike allocations in a competitive bike sharing market
This paper studies the bike allocation problem in a competitive bike sharing market. To overcome computational challenges, a continuum approximation (CA) approach is applied, where the allocation points and user demand are assumed to be continuously distributed in a two-dimensional region. Companies offering bike sharing service bear both allocation cost and bike depreciation cost while earning revenue from fare collection. The user's selection of bike service is affected by both walking distance and preference towards bike quality. The elasticity of the demand is considered in relation to the density of allocation points in the market. A leader-follower Stackelberg competition model is developed to derive the optimal allocation strategy for market leader. Two sets of numerical studies - one hypothetical case and one from a real case - are conducted to specify the impact of the parameters on model performance and illustrate how the proposed model can be applied to support the decision making.<br/
Systematic studies on the kinetic process of 20(S)-protopanaxadiol in rats and dogs: absorption, distribution, metabolism and excretion
Background and ObjectiveGinseng has been regarded as a precious medicinal herb with miraculous effects in Eastern culture. The primary chemical constituents of ginseng are saponins, and the physiological activities of ginsenosides determine their edible and medicinal value. The aim of this study is to comprehensively and systematically investigate the kinetic processes of 20(S)—protopanaxadiol (PPD) in rats and dogs, in order to promote the rational combination of ginseng as a drug and dietary ingredient.MethodsPPD was administered, and drug concentration in different biological samples were detected by liquid chromatography tandem mass spectrometry (LC/MS/MS) and radioactive tracer methods. Pharmacokinetic parameters such as absorption, bioavailability, tissue distribution, plasma protein binding rate, excretion rate, and cumulative excretion were calculated, along with inference of major metabolites.ResultsThis study systematically investigated the absorption, distribution, metabolism, excretion (ADME) of PPD in rats and dogs for the first time. The bioavailabilities of PPD were relatively low, with oral absorption nearly complete, and the majority underwent first-pass metabolism. PPD had a high plasma protein binding rate and was relatively evenly distributed in the body. Following oral administration, PPD underwent extensive metabolism, potentially involving one structural transformation and three hydroxylation reactions. The metabolites were primarily excreted through feces and urine, indicating the presence of enterohepatic circulation. The pharmacokinetic processes of PPD following intravenous administration aligned well with a three-compartment model. In contrast, after gastric administration, it fitted better with a two-compartment model, conforming to linear pharmacokinetics and proportional elimination. There were evident interspecies differences between rats and dogs regarding PPD, but individual variations of this drug were minimal within the same species.ConclusionThis study systematically studied the kinetic process of PPD in rats and also investigated the kinetic characteristics of PPD in dogs for the first time. These findings lay the foundation for further research on the dietary nutrition and pharmacological effects of PPD
VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition
Enhancing automatic speech recognition (ASR) performance by leveraging
additional multimodal information has shown promising results in previous
studies. However, most of these works have primarily focused on utilizing
visual cues derived from human lip motions. In fact, context-dependent visual
and linguistic cues can also benefit in many scenarios. In this paper, we first
propose ViLaS (Vision and Language into Automatic Speech Recognition), a novel
multimodal ASR model based on the continuous integrate-and-fire (CIF)
mechanism, which can integrate visual and textual context simultaneously or
separately, to facilitate speech recognition. Next, we introduce an effective
training strategy that improves performance in modal-incomplete test scenarios.
Then, to explore the effects of integrating vision and language, we create
VSDial, a multimodal ASR dataset with multimodal context cues in both Chinese
and English versions. Finally, empirical results are reported on the public
Flickr8K and self-constructed VSDial datasets. We explore various cross-modal
fusion schemes, analyze fine-grained crossmodal alignment on VSDial, and
provide insights into the effects of integrating multimodal information on
speech recognition.Comment: Accepted to ICASSP 202
Mechanically robust, flame-retardant poly(lactic acid) biocomposites via combining cellulose nanofibers and ammonium polyphosphate
Expanding the application range of flame-retardant polymer biocomposites remains a huge challenge for a sustainable society. Despite largely enhanced flame retardancy, until now the resultant poly(lactic acid) (PLA) composites still suffer reduced tensile strength and impact toughness due to improper material design strategies. We, herein, demonstrate the design of a green flame retardant additive (ammonium polyphosphate (APP)@cellulose nanofiber (CNF)) via using the cellulose nanofibers (CNFs) as the green multifunctional additives hybridized with ammonium polyphosphate (APP). The results show that PLA composite with 5 wt % loading of APP@CNF can pass the UL-94 V-0 rating, besides a high limited oxygen index of 27.5%, indicative of a significantly enhanced flame retardancy. Moreover, the 5 wt % of APP@CNF enables the impact strength (σi) of the PVA matrix to significantly improve from 7.63 to 11.8 kJ/m2 (increase by 54%), in addition to a high tensile strength of 50.3 MPa for the resultant flame-retardant PLA composite. The enhanced flame retardancy and mechanical strength performances are attributed to the improved dispersion of APP@CNF and its smaller phase size within the PLA matrix along with their synergistic effect between APP and CNF. This work opens up a facile innovative methodology for the design of high-performance ecofriendly flame retardants and their advanced polymeric composites
Simulation study of BESIII with stitched CMOS pixel detector using ACTS
Reconstruction of tracks of charged particles with high precision is very
crucial for HEP experiments to achieve their physics goals. As the tracking
detector of BESIII experiment, the BESIII drift chamber has suffered from aging
effects resulting in degraded tracking performance after operation for about 15
years. To preserve and enhance the tracking performance of BESIII, one of the
proposals is to add one layer of thin CMOS pixel sensor in cylindrical shape
based on the state-of-the-art stitching technology, between the beam pipe and
the drift chamber. The improvement of tracking performance of BESIII with such
an additional pixel detector compared to that with only the existing drift
chamber is studied using the modern common tracking software ACTS, which
provides a set of detector-agnostic and highly performant tracking algorithms
that have demonstrated promising performance for a few high energy physics and
nuclear physics experiments
The Effect of Hexavalent Chromium on the Incidence and Mortality of Human Cancers: A Meta-Analysis Based on Published Epidemiological Cohort Studies
Background: Hexavalent chromium [Cr(VI)] is an occupational carcinogen that can cause lung and nasal cancers, but its association with mortality and incidence in many other cancers is unclear.Objectives: In this meta-analysis, we aimed to evaluate the relationship between exposure to Cr(VI) and the mortality and incidence of human cancers.Methods: We performed a search of the literature and extracted the standardized mortality ratios (SMRs), standardized incidence ratios (SIRs), and their corresponding 95% confidence intervals (CIs), to estimate risk values. Subgroup analyses were conducted by sex, occupation, and types of cancer to identify groups that were at high-risk or predisposed to certain cancers.Results: A total of 47 cohort studies covering the period 1985–2016 were included (37 studies reporting SMRs and 16 studies reporting SIRs). The summary SMR for all studies combined was 1.07 (95% CI: 1.01–1.15). Summary SMRs were higher among chromate production workers, chrome platers, and masons, and especially male workers. In the subgroup analysis, Cr(VI) exposure was related to a higher risk of death owing to lung, larynx, bladder, kidney, testicular, bone, and thyroid cancer. The meta-SIR of all studies combined was 1.06 (95% CI: 1.04–1.09). Summary SIRs were elevated among cement industry workers and tanners. Cr(VI) exposure was related to an elevated risk of respiratory system, buccal cavity, pharynx, prostate, and stomach cancers.Conclusions: Cr(VI) might cause cancers of the respiratory system, buccal cavity and pharynx, prostate, and stomach in humans, and it is related to increased risk of overall mortality owing to lung, larynx, bladder, kidney, testicular, bone, and thyroid cancer. In addition, there was a strong association between incidence and mortality risk of cancers and concentration of Cr(VI) in the air and the exposure time
Past and future predictions of climate change and urbanization effects on the carbon, nitrogen, and water dynamics in Northeastern Forest ecosystems
Human activities have significantly influenced the structure and function of forest ecosystems in the northeastern US. Urbanization directly reduces forest area and alters forest functions. Forest growth, health, and function can also be affected by climate change, atmospheric carbon dioxide (CO2) concentrations, and air pollution including ground-level ozone (O3) and atmospheric nitrogen (N) deposition. Critical questions for research and environmental management are: How will urbanization, climate change, and air pollution interact to influence the function of forest ecosystems, and how will changes in these environmental drivers alter the function of forests in the future? In this dissertation, I simulate the historical and possible future interactive effects of urbanization, climate change, air pollution, and CO2 fertilization on the carbon, nitrogen, and water dynamics in northeastern forest ecosystems. The dissertation is divided into four phases. In Phase 1, I calibrated and tested the forest biogeochemical model PnET-CN-daily using data from an intensive study site at Harvard Forest in Petersham MA. Following model testing I simulated historical patterns of carbon, nitrogen, and water cycling in the forest ecosystem and evaluated the contribution of individual and collective disturbance factors (past land disturbance, climate, CO2 and ozone concentrations, atmospheric N deposition) to these dynamics. In Phase 2, the calibrated PnET-CN-daily model is employed to forecast changes in carbon, nitrogen, and water processing at Harvard Forest under different future scenarios. The development of these scenarios encompasses both climate and air chemistry drivers. Specifically, the climate and CO2 scenarios utilized in this study include simulations from a suite of global circulation models (GCMs (CCSM4, GFDL-ESM2G, and GFDL-ESM2M)) for future climate conditions. Projections of air chemistry data, including N deposition and O3 concentration, were obtained from the output of the Community Multiscale Air Quality (CMAQ) model, considering two energy usage policies: a business as usual (BAU) energy policy and an aggressive policy to decarbonize the power sector. In Phase 3, I use regional data sets of air temperature, atmospheric concentrations of CO2 and O3, and N deposition to establish empirical relationships between urbanization as quantified by impervious surface area (ISA) with these environmental drivers. Then I conducted a suite of hypothetical simulations using the parameterized PnET-CN-daily model for Harvard Forest applying the empirical relations with arbitrary values of ISA to evaluate the effects of increasing urbanization on the processing of carbon, nitrogen, and water in a forest ecosystem in New England and the relative contribution of different drivers of urbanization in these processes. I also tested these simulations against experimental observations from plots established along an urbanization gradient in Massachusetts. Finally, in Phase 4 I conducted regional scale simulations of future scenarios of land cover, climate, and air quality on the landscape processing of carbon, nitrogen, and water for New England using PnET-CN-daily over the period from 2020 to 2050. This analysis builds on future land cover scenarios that were developed by the New England Landscape Future (NELF) project by scientists at Harvard Forest. I considered three of these land cover scenarios, including Yankee Cosmopolitan, Growing Global, and Recent Trends scenarios. I also considered two climate scenarios (BAU and RCP 8.5), two air quality scenarios including a BAU, and an aggressive decarbonization scenario for these land cover conditions. I tested the results of these spatial simulations against regional measurements including aboveground biomass data from the USDA Forest Service Inventory and Analysis (FIA) program and soil organic carbon data from Gridded National Soil Survey Geographic (gNATSGO). Cross-site analysis of weather records, CO2 concentrations, O3 concentrations, and N deposition data reveals significant variations in the microclimate of urban areas, characterized by elevated air temperature, CO2 concentrations, N deposition, and lower O3 concentrations along an increasing urbanization gradient. Total and plant C storage are projected to continue to increase from the beginning of the 20th century to the end of the 21st century at the regional scale. Meanwhile, ecosystem N storage is projected to increase throughout the 20th century but is expected to decline in the 21st century due to the combined impacts of urbanization and climate change. Despite an overall increase in evapotranspiration (ET) due to increasing photosynthesis and temperatures since 2000, soil water stress will not be an important limitation because of the increase in precipitation and improved water use efficiency (WUE) due to elevated CO2 concentrations. The simulation suggests that urbanization is the dominant factor for C and N storage in New England, which directly reduces C and N storage in the urbanized area, especially in Connecticut, Massachusetts, and Rhode Island. Fortunately, C storage in New England is concentrated in Maine, which has a relatively low level of urbanization. As a result, total ecosystem C storage is projected to continue to increase across all land cover scenarios, mitigating the adverse effects of urbanization. Unlike carbon, the majority of N storage is associated with soil, and atmospheric deposition represents an important external source of N to ecosystems in New England. Therefore, while urbanization directly decreases ecosystem N storage, N deposition is insufficient to compensate for this loss throughout model simulations. CO2 fertilization is the dominant environmental factor for forest growth by enhancing photosynthesis and improving WUE. However, the CO2 fertilization effect generally diminishes over time due to nutrient limitations. Continuous N uptake by plants leads to N oligotrophication in the soil, which ultimately limits forest growth. Furthermore, enhanced forest growth increases the soil C: N ratio, decreasing N mobilization and availability. Elevated air temperatures are likely to increase soil decomposition, which can offset the N immobilization resulting from the increasing soil C: N ratio. However, this phenomenon is only observed under extreme climate change scenarios (RCP8.5) not under moderate climate change (RCP4.5) in the late 21st century. Atmospheric N deposition serves as an external N resource that mitigates N oligotrophication, however, predictions indicate that N deposition will decrease due to emissions regulations
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