207 research outputs found
A Quantitative Methodology for Identifying Evolvable Space Systems
1st AIAA Space Exploration Conference
January 2005, Orlando, FL.With the growing emphasis on spiral development, a system’s ability to evolve is
becoming increasingly critical. This is especially true in systems designed for the exploration
of space. While returning to the Moon is widely regarded as the next step in space
exploration, our journey does not end there. Therefore, the technologies, vehicles, and
systems created for near-term lunar missions should be selected and designed with the
future in mind. Intelligently selecting evolvable systems requires a method for quantitatively
measuring evolvability and a procedure for comparing these measurements. This paper
provides a brief discussion of a quantitative methodology for evaluating space system
evolvability and an in-depth application of this methodology to an example case study
Connecting Earth Observation to High-Throughput Biodiversity Data
There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services
Connecting Earth observation to high-throughput biodiversity data
Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services
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Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings
Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural activity. Although these two classes of models operate at different scales, it is relatively straightforward to create neural mass models of ensemble activity that are equipped with priors obtained after fitting data generated by detailed microscopic models. This provides generative (forward) models of measured neuronal responses that retain construct validity in relation to compartmental models. We illustrate our approach using cross spectral responses obtained from V1 during a visual perception paradigm that involved optogenetic manipulation of the basal forebrain. We find that the resulting neural mass model can distinguish between activity in distinct cortical layers – both with and without optogenetic activation – and that cholinergic input appears to enhance (disinhibit) superficial layer activity relative to deep layers. This is particularly interesting from the perspective of predictive coding, where neuromodulators are thought to boost prediction errors that ascend the cortical hierarchy
Improved Measurement of the Asymmetry in the Nucleon Sea
Measurements of the ratio of Drell-Yan yields from an 800 \rm{GeV/c} proton
beam incident on liquid hydrogen and deuterium targets are reported.
Approximately 360,000 Drell-Yan muon pairs remained after all cuts on the data.
From these data, the ratio of anti-down () to anti-up ()
quark distributions in the proton sea is determined over a wide range in
Bjorken-. These results confirm previous measurements by E866 and extend
them to lower . From these data, and
are evaluated for . These results are
compared with parameterizations of various parton distribution functions,
models and experimental results from NA51, NMC, and HERMES.Comment: 17 pages, 15 figure
Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes
Cardiometabolic Pregnancy Complications in Association With Autism-Related Traits as Measured by the Social Responsiveness Scale in ECHO
Prior work has examined associations between cardiometabolic pregnancy complications and autism spectrum disorder (ASD) but not how these complications may relate to social communication traits more broadly. We addressed this question within the Environmental Inf luences on Child Health Outcomes program, with 6,778 participants from 40 cohorts conducted from 1998–2021 with information on ASD-related traits via the Social Responsiveness Scale. Four metabolic pregnancy complications were examined individually, and combined, in association with Social Responsiveness Scale scores, using crude and adjusted linear regression as well as quantile regression analyses. We also examined associations stratified by ASD diagnosis, and potential mediation by preterm birth and low birth weight, and modification by child sex and enriched risk of ASD. Increases in ASD-related traits were associated with obesity (β = 4.64, 95% confidence interval: 3.27, 6.01) and gestational diabetes (β = 5.21, 95% confidence interval: 2.41, 8.02), specifically, but not with hypertension or preeclampsia. Results among children without ASD were similar to main analyses, but weaker among ASD cases. There was not strong evidence for mediation or modification. Results suggest that common cardiometabolic pregnancy complications may inf luence child ASD-related traits, not only above a diagnostic threshold relevant to ASD but also across the population
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