7,348 research outputs found
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model
Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape
Pedestrian Trajectory Prediction with Structured Memory Hierarchies
This paper presents a novel framework for human trajectory prediction based
on multimodal data (video and radar). Motivated by recent neuroscience
discoveries, we propose incorporating a structured memory component in the
human trajectory prediction pipeline to capture historical information to
improve performance. We introduce structured LSTM cells for modelling the
memory content hierarchically, preserving the spatiotemporal structure of the
information and enabling us to capture both short-term and long-term context.
We demonstrate how this architecture can be extended to integrate salient
information from multiple modalities to automatically store and retrieve
important information for decision making without any supervision. We evaluate
the effectiveness of the proposed models on a novel multimodal dataset that we
introduce, consisting of 40,000 pedestrian trajectories, acquired jointly from
a radar system and a CCTV camera system installed in a public place. The
performance is also evaluated on the publicly available New York Grand Central
pedestrian database. In both settings, the proposed models demonstrate their
capability to better anticipate future pedestrian motion compared to existing
state of the art.Comment: To appear in ECML-PKDD 201
Higgs boson enhancement effects on squark-pair production at the LHC
We study the Higgs boson effects on third-generation squark-pair production
in proton-proton collision at the CERN Large Hadron Collider (LHC), including
\Stop \Stop^*, \Stop\Sbot^*, and \Sbot \Sbot^*. We found that substantial
enhancement can be obtained through s-channel exchanges of Higgs bosons at
large , at which the enhancement mainly comes from , , and initial states. We compute the complete set of electroweak
(EW) contributions to all production channels. This completes previous
computations in the literature. We found that the EW contributions can be
significant and can reach up to 25% in more general scenarios and at the
resonance of the heavy Higgs boson. The size of Higgs enhancement is comparable
or even higher than the PDF uncertainties and so must be included in any
reliable analysis. A full analytical computation of all the EW contributions is
presented.Comment: 23 pages, 7 figures, 1 tabl
The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption
BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services
On the selection and design of proteins and peptide derivatives for the production of photoluminescent, red-emitting gold quantum clusters
Novel pathways of the synthesis of photoluminescent gold quantum clusters (AuQCs) using biomolecules as reactants provide biocompatible products for biological imaging techniques. In order to rationalize the rules for the preparation of red-emitting AuQCs in aqueous phase using proteins or peptides, the role of different organic structural units was investigated. Three systems were studied: proteins, peptides, and amino acid mixtures, respectively. We have found that cysteine and tyrosine are indispensable residues. The SH/S-S ratio in a single molecule is not a critical factor in the synthesis, but on the other hand, the stoichiometry of cysteine residues and the gold precursor is crucial. These observations indicate the importance of proper chemical behavior of all species in a wide size range extending from the atomic distances (in the AuI-S semi ring) to nanometer distances covering the larger sizes of proteins assuring the hierarchical structure of the whole self-assembled system
Strain- and Adsorption-Dependent Electronic States and Transport or Localization in Graphene
The chapter generalizes results on influence of uniaxial strain and
adsorption on the electron states and charge transport or localization in
graphene with different configurations of imperfections (point defects):
resonant (neutral) adsorbed atoms either oxygen- or hydrogen-containing
molecules or functional groups, vacancies or substitutional atoms, charged
impurity atoms or molecules, and distortions. To observe electronic properties
of graphene-admolecules system, we applied electron paramagnetic resonance
technique in a broad temperature range for graphene oxides as a good basis for
understanding the electrotransport properties of other active carbons. Applied
technique allowed observation of possible metal-insulator transition and
sorption pumping effect as well as discussion of results in relation to the
granular metal model. The electronic and transport properties are calculated
within the framework of the tight-binding model along with the Kubo-Greenwood
quantum-mechanical formalism. Depending on electron density and type of the
sites, the conductivity for correlated and ordered adsorbates is found to be
enhanced in dozens of times as compared to the cases of their random
distribution. In case of the uniaxially strained graphene, the presence of
point defects counteracts against or contributes to the band-gap opening
according to their configurations. The band-gap behaviour is found to be
nonmonotonic with strain in case of a simultaneous action of defect ordering
and zigzag deformation. The amount of localized charge carriers (spins) is
found to be correlated with the content of adsorbed centres responsible for the
formation of potential barriers and, in turn, for the localization effects.
Physical and chemical states of graphene edges, especially at a uniaxial strain
along one of them, play a crucial role in electrical transport phenomena in
graphene-based materials.Comment: 16 pages, 10 figure
NLO QCD Corrections to -to-Charmonium Form Factors
The meson to S-wave Charmonia transition form factors are
calculated in next-to-leading order(NLO) accuracy of Quantum
Chromodynamics(QCD). Our results indicate that the higher order corrections to
these form factors are remarkable, and hence are important to the
phenomenological study of the corresponding processes. For the convenience of
comparison and use, the relevant expressions in asymptotic form at the limit of
for the radiative corrections are presented
Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats
This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets
Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs
Non-conding RNAs play a key role in the post-transcriptional regulation of
mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact
with their target RNAs through protein-mediated, sequence-specific binding,
giving rise to extended and highly heterogeneous miRNA-RNA interaction
networks. Within such networks, competition to bind miRNAs can generate an
effective positive coupling between their targets. Competing endogenous RNAs
(ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk.
Albeit potentially weak, ceRNA interactions can occur both dynamically,
affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA
networks as a whole can be implicated in the composition of the cell's
proteome. Many features of ceRNA interactions, including the conditions under
which they become significant, can be unraveled by mathematical and in silico
models. We review the understanding of the ceRNA effect obtained within such
frameworks, focusing on the methods employed to quantify it, its role in the
processing of gene expression noise, and how network topology can determine its
reach.Comment: review article, 29 pages, 7 figure
Atomic-scale combination of germanium-zinc nanofibers for structural and electrochemical evolution
Alloys are recently receiving considerable attention in the community of rechargeable batteries as possible alternatives to carbonaceous negative electrodes; however, challenges remain for the practical utilization of these materials. Herein, we report the synthesis of germanium-zinc alloy nanofibers through electrospinning and a subsequent calcination step. Evidenced by in situ transmission electron microscopy and electrochemical impedance spectroscopy characterizations, this one-dimensional design possesses unique structures. Both germanium and zinc atoms are homogenously distributed allowing for outstanding electronic conductivity and high available capacity for lithium storage. The as-prepared materials present high rate capability (capacity of similar to 50% at 20 C compared to that at 0.2 C-rate) and cycle retention (73% at 3.0 C-rate) with a retaining capacity of 546 mAh g(-1) even after 1000 cycles. When assembled in a full cell, high energy density can be maintained during 400 cycles, which indicates that the current material has the potential to be used in a large-scale energy storage system
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