346 research outputs found

    Carbon stock growth in a forest stand: the power of age

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    BACKGROUND: Understanding the relationship between the age of a forest stand and its biomass is essential for managing the forest component of the global carbon cycle. Since biomass increases with stand age, postponing harvesting to the age of biological maturity may result in the formation of a large carbon sink. This article quantifies the carbon sequestration capacity of forests by suggesting a default rule to link carbon stock and stand age. RESULTS: The age dependence of forest biomass is shown to be a power-law monomial where the power of age is theoretically estimated to be 4/5. This theoretical estimate is close to the known empirical estimate; therefore, it provides a scientific basis for a quick and transparent assessment of the benefits of postponing the harvest, suggesting that the annual magnitude of the sink induced by delayed harvest lies in the range of 1–2% of the baseline carbon stock. CONCLUSION: The results of this study imply that forest age could be used as an easily understood and scientifically sound measure of the progress in complying with national targets on the protection and enhancement of forest carbon sinks

    Impact of uniaxial strain and doping on oxygen diffusion in CeO2

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    Doped ceria is an important electrolyte for solid oxide fuel cell applications. Molecular dynamics simulations have been used to investigate the impact of uniaxial strain along the directions and rare-earth doping (Yb, Er, Ho, Dy, Gd, Sm, Nd, and La) on oxygen diffusion. We introduce a new potential model that is able to describe the thermal expansion and elastic properties of ceria to give excellent agreement with experimental data. We calculate the activation energy of oxygen migration in the temperature range 900-1900K for both unstrained and rare-earth doped ceria systems under tensile strain. Uniaxial strain has a considerable effect in lowering the activation energies of oxygen migration. A more pronounced increase in oxygen diffusivities is predicted at the lower end of the temperature range for all the dopants considered

    Age-Dependent Ocular Dominance Plasticity in Adult Mice

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    Background: Short monocular deprivation (4 days) induces a shift in the ocular dominance of binocular neurons in the juvenile mouse visual cortex but is ineffective in adults. Recently, it has been shown that an ocular dominance shift can still be elicited in young adults (around 90 days of age) by longer periods of deprivation (7 days). Whether the same is true also for fully mature animals is not yet known. Methodology/Principal Findings: We therefore studied the effects of different periods of monocular deprivation (4, 7, 14 days) on ocular dominance in C57Bl/6 mice of different ages (25 days, 90–100 days, 109–158 days, 208–230 days) using optical imaging of intrinsic signals. In addition, we used a virtual optomotor system to monitor visual acuity of the open eye in the same animals during deprivation. We observed that ocular dominance plasticity after 7 days of monocular deprivation was pronounced in young adult mice (90–100 days) but significantly weaker already in the next age group (109–158 days). In animals older than 208 days, ocular dominance plasticity was absent even after 14 days of monocular deprivation. Visual acuity of the open eye increased in all age groups, but this interocular plasticity also declined with age, although to a much lesser degree than the optically detected ocular dominance shift. Conclusions/Significance: These data indicate that there is an age-dependence of both ocular dominance plasticity and the enhancement of vision after monocular deprivation in mice: ocular dominance plasticity in binocular visual cortex is mos

    An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals

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    Serotonin has widespread, but computationally obscure, modulatory effects on learning and cognition. Here, we studied the impact of optogenetic stimulation of dorsal raphe serotonin neurons in mice performing a non-stationary, reward-driven decision-making task. Animals showed two distinct choice strategies. Choices after short inter-trial-intervals (ITIs) depended only on the last trial outcome and followed a win-stay-lose-switch pattern. In contrast, choices after long ITIs reflected outcome history over multiple trials, as described by reinforcement learning models. We found that optogenetic stimulation during a trial significantly boosted the rate of learning that occurred due to the outcome of that trial, but these effects were only exhibited on choices after long ITIs. This suggests that serotonin neurons modulate reinforcement learning rates, and that this influence is masked by alternate, unaffected, decision mechanisms. These results provide insight into the role of serotonin in treating psychiatric disorders, particularly its modulation of neural plasticity and learning.info:eu-repo/semantics/publishedVersio

    Enhanced genetic maps from family-based disease studies: population-specific comparisons

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    Abstract Background Accurate genetic maps are required for successful and efficient linkage mapping of disease genes. However, most available genome-wide genetic maps were built using only small collections of pedigrees, and therefore have large sampling errors. A large set of genetic studies genotyped by the NHLBI Mammalian Genotyping Service (MGS) provide appropriate data for generating more accurate maps. Results We collected a large sample of uncleaned genotype data for 461 markers generated by the MGS using the Weber screening sets 9 and 10. This collection includes genotypes for over 4,400 pedigrees containing over 17,000 genotyped individuals from different populations. We identified and cleaned numerous relationship and genotyping errors, as well as verified the marker orders. We used this dataset to test for population-specific genetic maps, and to re-estimate the genetic map distances with greater precision; standard errors for all intervals are provided. The map-interval sizes from the European (or European descent), Chinese, and Hispanic samples are in quite good agreement with each other. We found one map interval on chromosome 8p with a statistically significant size difference between the European and Chinese samples, and several map intervals with significant size differences between the African American and Chinese samples. When comparing Palauan with European samples, a statistically significant difference was detected at the telomeric region of chromosome 11p. Several significant differences were also identified between populations in chromosomal and genome lengths. Conclusions Our new population-specific screening set maps can be used to improve the accuracy of disease-mapping studies. As a result of the large sample size, the average length of the 95% confidence interval (CI) for a 10 cM map interval is only 2.4 cM, which is considerably smaller than on previously published maps.http://deepblue.lib.umich.edu/bitstream/2027.42/112826/1/12881_2010_Article_748.pd

    HECTD2, a candidate susceptibility gene for Alzheimer's disease on 10q

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    Background: Late onset Alzheimer's disease (LOAD) is a neurodegenerative disorder characterised by the deposition of amyloid plaques and neurofibrillary tangles in the brain and is the major cause of dementia. Multiple genetic loci, including 10q, have been implicated in LOAD but to date, with the exception of APOE, the underlying genes have not been identified. HECTD2 maps to 10q and has been implicated in susceptibility to human prion diseases which are also neurodegenerative conditions associated with accumulation of misfolded host proteins. In this study we test whether the HECTD2 susceptibility allele seen in prion disease is also implicated in LOAD.Methods: DNA from 320 individuals with Alzheimer's disease and 601 controls were genotyped for a HECTD2 intronic tagging SNP, rs12249854 (A/T). Groups were further analysed following stratification by APOE genotype.Results: The rs12249854 minor allele (A) frequency was higher (5.8%) in the Alzheimer's disease group as compared to the controls (3.9%), however, this was not statistically significant (P = 0.0668). No significant difference was seen in minor allele frequency in the presence or absence of the APOE epsilon 4 allele.Conclusion: The common haplotypes of HECTD2, tagged by rs12249854, are not associated with susceptibility to LOAD

    Structure Learning in Human Sequential Decision-Making

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    Studies of sequential decision-making in humans frequently find suboptimal performance relative to an ideal actor that has perfect knowledge of the model of how rewards and events are generated in the environment. Rather than being suboptimal, we argue that the learning problem humans face is more complex, in that it also involves learning the structure of reward generation in the environment. We formulate the problem of structure learning in sequential decision tasks using Bayesian reinforcement learning, and show that learning the generative model for rewards qualitatively changes the behavior of an optimal learning agent. To test whether people exhibit structure learning, we performed experiments involving a mixture of one-armed and two-armed bandit reward models, where structure learning produces many of the qualitative behaviors deemed suboptimal in previous studies. Our results demonstrate humans can perform structure learning in a near-optimal manner

    Integrating human and ecosystem health through ecosystem services frameworks

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    The pace and scale of environmental change is undermining the conditions for human health. Yet the environment and human health remain poorly integrated within research, policy and practice. The ecosystem services (ES) approach provides a way of promoting integration via the frameworks used to represent relationships between environment and society in simple visual forms. To assess this potential, we undertook a scoping review of ES frameworks and assessed how each represented seven key dimensions, including ecosystem and human health. Of the 84 ES frameworks identified, the majority did not include human health (62%) or include feedback mechanisms between ecosystems and human health (75%). While ecosystem drivers of human health are included in some ES frameworks, more comprehensive frameworks are required to drive forward research and policy on environmental change and human health
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