Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate

Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. We use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate

Environmental coupling of selection and heritability limits evolution

There has recently been great interest in applying theoretical quantitative genetic models to empirical studies of evolution in wild populations. However, while classical models assume environmental constancy, most natural populations exist in variable environments. Here, we applied a novel analytical technique to a long-term study of birthweight in wild sheep and examined, for the first time, how variation in environmental quality simultaneously influences the strength of natural selection and the genetic basis of trait variability. In addition to demonstrating that selection and genetic variance vary dramatically across environments, our results show that environmental heterogeneity induces a negative correlation between these two parameters. Harsh environmental conditions were associated with strong selection for increased birthweight but low genetic variance, and vice versa. Consequently, the potential for microevolution in this population is constrained by either a lack of heritable variation ( in poor environments) or by a reduced strength of selection ( in good environments). More generally, environmental dependence of this nature may act to limit rates of evolution, maintain genetic variance, and favour phenotypic stasis in many natural systems. Assumptions of environmental constancy are likely to be violated in natural systems, and failure to acknowledge this may generate highly misleading expectations for phenotypic microevolution

Changes in Magnetization and in Dislocation Arrangements in Cyclically Deformed Iron and Nickel

There are a lot of experimental results concerning the effect of stress, elastic and plastic deformation and dislocation structure on the magnetic properties of ferromagnetic material. Atherton et al. measured stress induced changes in the magnetization of steel pipesl. Schroeder et al. studied domain arrangement in plastically deformed iron single crystals2. Hayashi et al. found that the application of an oscillating magnetic field during tensile testing reduced the flow stress of nickel3. Jiles and Atherton4,5D reported changes in magnetization during one stress cycle as a function of an external magnetic field. They have also reported a theory that describes ferromagnetic hysteresis and the effect of stress on magnetization. This theory is based on the Langevins theory of paramagnetism. Jiles and Atherton4 have experimentally shown that the modified Langevins equation gives the change in magnetization as a function of the applied magnetic field

Aerothermodynamic Analysis of a Reentry Brazilian Satellite

This work deals with a computational investigation on the small ballistic reentry Brazilian vehicle SARA (acronyms for SAt\'elite de Reentrada Atmosf\'erica). Hypersonic flows over the vehicle SARA at zero-degree angle of attack in a chemical equilibrium and thermal non-equilibrium are modeled by the Direct Simulation Monte Carlo (DSMC) method, which has become the main technique for studying complex multidimensional rarefied flows, and that properly accounts for the non-equilibrium aspects of the flows. The emphasis of this paper is to examine the behavior of the primary properties during the high altitude portion of SARA reentry. In this way, velocity, density, pressure and temperature field are investigated for altitudes of 100, 95, 90, 85 and 80 km. In addition, comparisons based on geometry are made between axisymmetric and planar two-dimensional configurations. Some significant differences between these configurations were noted on the flowfield structure in the reentry trajectory. The analysis showed that the flow disturbances have different influence on velocity, density, pressure and temperature along the stagnation streamline ahead of the capsule nose. It was found that the stagnation region is a thermally stressed zone. It was also found that the stagnation region is a zone of strong compression, high wall pressure. Wall pressure distributions are compared with those of available experimental data and good agreement is found along the spherical nose for the altitude range investigated.Comment: The paper will be published in Vol. 42 of the Brazilian Journal of Physic

Immunological characterization of chromogranins A and B and secretogranin II in the bovine pancreatic islet

Antisera against chromogranin A and B and secretogranin II were used for analysing the bovine pancreas by immunoblotting and immunohistochemistry. All three antigens were found in extracts of fetal pancreas by one dimensional immunoblotting. A comparison with the soluble proteins of chromaffin granules revealed that in adrenal medulla and in pancreas antigens which migrated identically in electrophoresis were present. In immunohistochemistry, chromogranin A was found in all pancreatic endocrine cell types with the exception of most pancreatic polypeptide-(PP-) producing cells. For chromogranin B, only a faint immunostaining was obtained. For secretorgranin II, A-and B-cells were faintly positive, whereas the majority of PP-cells exhibited a strong immunostaining for this antigen. These results establish that chromogranins A and B and secretogranin II are present in the endocrine pancreas, but that they exhibit a distinct cellular localization

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Impact on short-lived climate forcers (SLCFs) from a realistic land-use change scenario via changes in biogenic emissions

More than one quarter of natural forests have been cleared by humans to make way for other land-uses, with changes to forest cover projected to continue. The climate impact of land-use change (LUC) is dependent upon the relative strength of several biogeophysical and biogeochemical effects. In addition to affecting the surface albedo and exchanging carbon dioxide (CO2) and moisture with the atmosphere, vegetation emits biogenic volatile organic compounds (BVOCs), altering the formation of short-lived climate forcers (SLCFs) including aerosol, ozone (O3) and methane (CH4). Once emitted, BVOCs are rapidly oxidised by O3, and the hydroxyl (OH) and nitrate (NO3) radicals. These oxidation reactions yield secondary organic products which are implicated in the formation and growth of aerosol particles and are estimated to have a negative radiative effect on the climate (i.e. a cooling). These reactions also deplete OH, increasing the atmospheric lifetime of CH4, and directly affect concentrations of O3; the latter two being greenhouse gases which impose a positive radiative effect (i.e. a warming) on the climate. Our previous work assessing idealised deforestation scenarios found a positive radiative effect due to changes in SLCFs; however, since the radiative effects associated with changes to SLCFs result from a combination of non-linear processes it may not be appropriate to scale radiative effects from complete deforestation scenarios according to the deforestation extent. Here we combine a land-surface model, a chemical transport model, a global aerosol model, and a radiative transfer model to assess the net radiative effect of changes in SLCFs due to historical LUC between the years 1850 and 2000

Structure and mechanism of human DNA polymerase η

The variant form of the human syndrome xeroderma pigmentosum (XPV) is caused by a deficiency in DNA polymerase eta (Pol eta), a DNA polymerase that enables replication through ultraviolet-induced pyrimidine dimers. Here we report high-resolution crystal structures of human Pol eta at four consecutive steps during DNA synthesis through cis-syn cyclobutane thymine dimers. Pol eta acts like a 'molecular splint' to stabilize damaged DNA in a normal B-form conformation. An enlarged active site accommodates the thymine dimer with excellent stereochemistry for two-metal ion catalysis. Two residues conserved among Pol eta orthologues form specific hydrogen bonds with the lesion and the incoming nucleotide to assist translesion synthesis. On the basis of the structures, eight Pol eta missense mutations causing XPV can be rationalized as undermining the molecular splint or perturbing the active-site alignment. The structures also provide an insight into the role of Pol eta in replicating through D loop and DNA fragile sites

HCV IRES manipulates the ribosome to promote the switch from translation initiation to elongation.

The internal ribosome entry site (IRES) of the hepatitis C virus (HCV) drives noncanonical initiation of protein synthesis necessary for viral replication. Functional studies of the HCV IRES have focused on 80S ribosome formation but have not explored its role after the 80S ribosome is poised at the start codon. Here, we report that mutations of an IRES domain that docks in the 40S subunit's decoding groove cause only a local perturbation in IRES structure and result in conformational changes in the IRES-rabbit 40S subunit complex. Functionally, the mutations decrease IRES activity by inhibiting the first ribosomal translocation event, and modeling results suggest that this effect occurs through an interaction with a single ribosomal protein. The ability of the HCV IRES to manipulate the ribosome provides insight into how the ribosome's structure and function can be altered by bound RNAs, including those derived from cellular invaders