939 resultados para Heat-Treated Wood, Heat and Mass Transfer, Modelling, Validation
Resumo:
The total sea level variation (SLV) is the combination of steric and mass␣induced SLV, whose exact shares are key to understanding the oceanic response to climate system changes. Total SLV can be observed by radar altimetry satellites such as TOPEX/POSEIDON and Jason 1/2. The steric SLV can be computed through temperature and salinity profiles from in situ measurements or from ocean general circulation models (OGCM), which can assimilate the said observations. The mass-induced SLV can be estimated from its time-variable gravity (TVG) signals. We revisit this problem in the Mediterranean Sea estimating the observed, steric, and mass-induced SLV, for the latter we analyze the latest TVG data set from the GRACE (Gravity Recovery and Climate Experiment) satellite mission launched in 2002, which is 3.5 times longer than in previous studies, with the application of a two-stage anisotropic filter to reduce the noise in high-degree and -order spherical harmonic coefficients. We confirm that the intra-annual total SLV are only produced by water mass changes, a fact explained in the literature as a result of the wind field around the Gibraltar Strait. The steric SLV estimated from the residual of “altimetry minus GRACE” agrees in phase with that estimated from OGCMs and in situ measurements, although showing a higher amplitude. The net water fluxes through both the straits of Gibraltar and Sicily have also been estimated accordingly.
Resumo:
The sea level variation (SLVtotal) is the sum of two major contributions: steric and mass-induced. The steric SLVsteric is that resulting from the thermal and salinity changes in a given water column. It only involves volume change, hence has no gravitational effect. The mass-induced SLVmass, on the other hand, arises from adding or subtracting water mass to or from the water column and has direct gravitational signature. We examine the closure of the seasonal SLV budget and estimate the relative importance of the two contributions in the Mediterranean Sea as a function of time. We use ocean altimetry data (from TOPEX/Poseidon, Jason 1, ERS, and ENVISAT missions) to estimate SLVtotal, temperature, and salinity data (from the Estimating the Circulation and Climate of the Ocean ocean model) to estimate SLVsteric, and time variable gravity data (from Gravity Recovery and Climate Experiment (GRACE) Project, April 2002 to July 2004) to estimate SLVmass. We find that the annual cycle of SLVtotal in the Mediterranean is mainly driven by SLVsteric but moderately offset by SLVmass. The agreement between the seasonal SLVmass estimations from SLVtotal – SLVsteric and from GRACE is quite remarkable; the annual cycle reaches the maximum value in mid-February, almost half a cycle later than SLVtotal or SLVsteric, which peak by mid-October and mid-September, respectively. Thus, when sea level is rising (falling), the Mediterranean Sea is actually losing (gaining) mass. Furthermore, as SLVmass is balanced by vertical (precipitation minus evaporation, P–E) and horizontal (exchange of water with the Atlantic, Black Sea, and river runoff) mass fluxes, we compared it with the P–E determined from meteorological data to estimate the annual cycle of the horizontal flux.
Resumo:
Reply to comment by L. Fenoglio-Marc et al. on “On the steric and mass-induced contributions to the annual sea level variations in the Mediterranean Sea”.
Resumo:
We quantify the rate and efficiency of picosecond electron transfer (ET) from PbS nanocrystals, grown by successive ionic layer adsorption and reaction (SILAR), into a mesoporous SnO2 support. Successive SILAR deposition steps allow for stoichiometry- and size-variation of the QDs, characterized using transmission electron microscopy. Whereas for sulfur-rich (p-type) QD surfaces substantial electron trapping at the QD surface occurs, for lead-rich (n-type) QD surfaces, the QD trapping channel is suppressed and the ET efficiency is boosted. The ET efficiency increase achieved by lead-rich QD surfaces is found to be QD-size dependent, increasing linearly with QD surface area. On the other hand, ET rates are found to be independent of both QD size and surface stoichiometry, suggesting that the donor–acceptor energetics (constituting the driving force for ET) are fixed due to Fermi level pinning at the QD/oxide interface. Implications of our results for QD-sensitized solar cell design are discussed.
Resumo:
Dynorphins are important neuropeptides with a central role in nociception and pain alleviation. Many mechanisms regulate endogenous dynorphin concentrations, including proteolysis. Proprotein convertases (PCs) are widely expressed in the central nervous system and specifically cleave at C-terminal of either a pair of basic amino acids, or a single basic residue. The proteolysis control of endogenous Big Dynorphin (BDyn) and Dynorphin A (Dyn A) levels has a profound impact on pain perception and the role of PCs remain unclear. The objective of this study was to decipher the role of PC1 and PC2 in the proteolysis control of BDyn and Dyn A levels using cellular fractions of spinal cords from wild type (WT), PC1-/+ and PC2-/+ animals and mass spectrometry. Our results clearly demonstrate that both PC1 and PC2 are involved in the proteolysis regulation of BDyn and Dyn A with a more important role for PC1. C-terminal processing of BDyn generates specific peptide fragments Dynorphin 1-19, Dynorphin 1-13, Dynorphin 1-11 and Dynorphin 1-7 and C-terminal processing of Dyn A generates Dynorphin 1-13, Dynorphin 1-11 and Dynorphin 1-7, all these peptide fragments are associated with PC1 or PC2 processing. Moreover, proteolysis of BDyn leads to the formation of Dyn A and Leu-Enk, two important opioid peptides. The rate of formation of both is significantly reduced in cellular fractions of spinal cord mutant mice. As a consequence, even partial inhibition of PC1 or PC2 may impair the endogenous opioid system.
Resumo:
Dynorphins are important neuropeptides with a central role in nociception and pain alleviation. Many mechanisms regulate endogenous dynorphin concentrations, including proteolysis. Proprotein convertases (PCs) are widely expressed in the central nervous system and specifically cleave at C-terminal of either a pair of basic amino acids, or a single basic residue. The proteolysis control of endogenous Big Dynorphin (BDyn) and Dynorphin A (Dyn A) levels has a profound impact on pain perception and the role of PCs remain unclear. The objective of this study was to decipher the role of PC1 and PC2 in the proteolysis control of BDyn and Dyn A levels using cellular fractions of spinal cords from wild type (WT), PC1-/+ and PC2-/+ animals and mass spectrometry. Our results clearly demonstrate that both PC1 and PC2 are involved in the proteolysis regulation of BDyn and Dyn A with a more important role for PC1. C-terminal processing of BDyn generates specific peptide fragments Dynorphin 1-19, Dynorphin 1-13, Dynorphin 1-11 and Dynorphin 1-7 and C-terminal processing of Dyn A generates Dynorphin 1-13, Dynorphin 1-11 and Dynorphin 1-7, all these peptide fragments are associated with PC1 or PC2 processing. Moreover, proteolysis of BDyn leads to the formation of Dyn A and Leu-Enk, two important opioid peptides. The rate of formation of both is significantly reduced in cellular fractions of spinal cord mutant mice. As a consequence, even partial inhibition of PC1 or PC2 may impair the endogenous opioid system.
Resumo:
The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.
Resumo:
Low concentrations of organic carbon in slowly accumulating sediments from Sites 597, 600, and 601 reflect a history of low marine productivity in the subtropical South Pacific since late Oligocene times. The distributions of n-alkanes, n-alkanoic acids, and n-alkanols provide evidence of the microbial alteration of sediment organic matter. Landderived hydrocarbons, possibly from eolian transport, dominate n-alkane distributions in these samples.
Resumo:
Primary productivity (14C) and mass flux measurements using a free-drifting sediment trap deployed at 900 m were made at four stations in the Pacific Ocean between 12°N and 6°S at 153°W. The latitudinal variations in productivity were consistent with historical patterns showing the equator as a zone of high production and the oligotrophic waters north of the equatorial region as an area of low productivity. The correlation coefficient between the two sets of independent measurements was 0.999, indicating that in this oceanic area the activity of the primary producers was closely related to the total mass flux. A re-examination of historical data suggests that the downward flux of particulate organic carbon varies in direct proportion to the quotient of surface primary production raised to the 1.4 power and depth raised to the 0.63 power.