Adverse experiences in early life are associated with aging-related disease risk and mortality across many species. In humans, confounding factors, as well as the difficulty of directly measuring experiences and outcomes from birth till death, make it challenging to identify how early life adversity impacts aging and health. These challenges can be mitigated, in part, through the study of non-human animals, which are exposed to parallel forms of adversity and can age similarly to humans. Furthermore, studying the links between early life adversity and aging in natural populations of non-human animals provides an excellent opportunity to better understand the social and ecological pressures that shaped the evolution of early life sensitivities. Here, we highlight ongoing and future research directions that we believe will most effectively contribute to our understanding of the evolution of early life sensitivities and their repercussions.
We experimentally demonstrate enhanced sensitivities within non-Hermitian topological lattices realized in a dissipatively-coupled network of time-multiplexed resonators. Our demonstration paves the way for realizing optical sensors with unprecedented sensitivities using notions of non-Hermiticity and topology.
more » « less- Award ID(s):
- 1846273
- PAR ID:
- 10544737
- Publisher / Repository:
- Optica Publishing Group
- Date Published:
- ISBN:
- 978-1-957171-25-8
- Page Range / eLocation ID:
- FM4B.4
- Format(s):
- Medium: X
- Location:
- San Jose, CA
- Sponsoring Org:
- National Science Foundation
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Abstract While the signs of the sensitivities of surface temperature (
T s ) to land use and land cover change‐induced biophysical changes are relatively well understood, their exact magnitude and how their magnitude depends on the scale characterizing the size of the change remain elusive. In this study, we compare the sensitivities of surface temperature to changes in surface albedo and surface water availability from three analytical/semianalytical models, which are designed for small (<1 km), intermediate (from ∼1 to ∼10 km), and large (>10–20 km) scales. Results suggest that the sensitivities of surface temperature to biophysical changes are scale dependent due to atmospheric feedbacks. Our results demonstrate that it is important to consider the scale and the associated atmospheric feedbacks when quantifying the sensitivities of surface temperature to biophysical changes. -
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Summary An analytic differentiation method is presented to calculate the sensitivity of the transverse failure response of carbon fiber composite laminates to the distribution parameters of the fiber/matrix interface properties. The method starts with the evaluation of the sensitivities of the transverse failure response with respect to the interface properties of each fiber, ie, the cohesive failure strength and the critical displacement jump. These individual sensitivities are then used to calculate the sensitivities with respect to the mean and standard deviation of the interface properties. The derived sensitivities are implemented in a nonlinear interface‐enriched generalized finite element method solver specially developed for this application. The interface‐enriched generalized finite element method solver combines a cohesive modeling of the fiber/matrix interface failure with finite element meshes that do not conform to the composite microstructure. The approach is first demonstrated on a model material involving a one‐dimensional domain containing N cohesive interfaces described by randomly selected cohesive failure properties. The method is then applied to the more complex problem of a composite laminate involving a large number of fibers.
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Abstract. Obtaining quantitative information for molecular species present in aerosols from real-time mass spectrometers such as an extractive electrospray time-of-flight mass spectrometer (EESI) and an aerosol mass spectrometer (AMS) can be challenging. Typically, molecular species are calibrated directly through the use of pure standards. However, in some cases (e.g., secondary organic aerosol (SOA) formed from volatile organic compounds (VOCs)), direct calibrations are impossible, as many SOA species can either not be purchased as pure standards or have ambiguous molecular identities. In some cases, bulk OA sensitivities are used to estimate molecular sensitivities. This approach is not sufficient for EESI, which measures molecular components of OA, because different species can have sensitivities that vary by a factor of more than 30. Here, we introduce a method to obtain EESI calibration factors when standards are not available, and we provide a thorough analysis of the feasibility, performance, and limitations of this new technique. In this method, complex aerosol mixtures were separated with high-performance liquid chromatography (HPLC) followed by aerosol formation via atomization. The separated aerosols were then measured by an EESI and an AMS, which allowed us to obtain sensitivities for some species present in standard and SOA mixtures. Pure compounds were used to test the method and characterize its uncertainties, and obtained sensitivities were consistent within ±20 % when comparing direct calibrations vs. HPLC calibrations for a pure standard and within a factor of 2 for a standard mixture. In some cases, species were not completely resolved by chromatography, and positive matrix factorization (PMF) of AMS data enabled further separation. This method should be applicable to other real-time MS techniques. Improvements in chromatography are possible that would allow better separation in complex mixtures.
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We present Pasado, a technique for synthesizing precise static analyzers for Automatic Differentiation. Our technique allows one to automatically construct a static analyzer specialized for the Chain Rule, Product Rule, and Quotient Rule computations for Automatic Differentiation in a way that abstracts all of the nonlinear operations of each respective rule simultaneously. By directly synthesizing an abstract transformer for the composite expressions of these 3 most common rules of AD, we are able to obtain significant precision improvement compared to prior works which compose standard abstract transformers together suboptimally. We prove our synthesized static analyzers sound and additionally demonstrate the generality of our approach by instantiating these AD static analyzers with different nonlinear functions, different abstract domains (both intervals and zonotopes) and both forward-mode and reverse-mode AD.
We evaluate Pasado on multiple case studies, namely soundly computing bounds on a neural network’s local Lipschitz constant, soundly bounding the sensitivities of financial models, certifying monotonicity, and lastly, bounding sensitivities of the solutions of differential equations from climate science and chemistry for verified ranges of initial conditions and parameters. The local Lipschitz constants computed by Pasado on our largest CNN are up to 2750× more precise compared to the existing state-of-the-art zonotope analysis. The bounds obtained on the sensitivities of the climate, chemical, and financial differential equation solutions are between 1.31 − 2.81× more precise (on average) compared to a state-of-the-art zonotope analysis.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1364/CLEO_FS.2023.FM4B.4
