Functional disability with systematic trends and uncertainty: a comparison between China and the US

China and the US are two contrasting countries in terms of functional disability and long-term care. China is experiencing declining family support for long-term care and developing private long-term care insurance. The US has a more developed public aged care system and private long-term care insurance market than China. Changes in the demand for long-term care are driven by the levels, trends and uncertainty in mortality and functional disability. To understand the future potential demand for long-term care, we compare mortality and functional disability experiences in China and the US, using a multi-state latent factor intensity model with time trends and systematic uncertainty in transition rates. We estimate the model with the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and the US Health and Retirement Study (HRS) data. The estimation results show that if trends continue, both countries will experience longevity improvement with morbidity compression and a declining proportion of the older population with functional disability. Although the elderly Chinese have a shorter estimated life expectancy, they are expected to spend a smaller proportion of their future lifetime functionally disabled than the elderly Americans. Systematic uncertainty is shown to be significant in future trends in disability rates and our model estimates higher uncertainty in trends for the Chinese elderly, especially for urban residents.

Numerical Uncertainty in Density Estimation for Background Oriented Schlieren

Background Oriented Schlieren (BOS) is an image-based density measurement technique. BOS estimates the density gradient from the apparent distortion of a target pattern viewed through a medium with varying density using cross-correlation, tracking, or optical flow algorithms. The density gradient can then be numerically integrated to yield a spatially resolved estimate of the density [1]. A method was recently proposed to estimate the a-posteriori instantaneous and spatially resolved density uncertainty for BOS [2] and showed good agreement between the propagated uncertainties and the random error. However, the density uncertainty quantification method could not account for the systematic uncertainty in the density field due to the discretization errors introduced during the numerical integration, which could be much larger than the displacement random errors [2]. In this work, we propose a method to estimate the numerical uncertainty introduced by the density integration in BOS measurements, using a Richardson extrapolation framework. A procedure is also introduced to combine this systematic uncertainty with the random uncertainty from the previous work to provide an instantaneous, spatially-resolved total uncertainty on the density estimates. The method will be tested with synthetic fields and synthetic BOS images.

Validation of Sentinel-3 SLSTR Land Surface Temperature Retrieved by the Operational Product and Comparison with Explicitly Emissivity-Dependent Algorithms

Land surface temperature (LST) is an essential climate variable (ECV) for monitoring the Earth climate system. To ensure accurate retrieval from satellite data, it is important to validate satellite derived LSTs and ensure that they are within the required accuracy and precision thresholds. An emissivity-dependent split-window algorithm with viewing angle dependence and two dual-angle algorithms are proposed for the Sentinel-3 SLSTR sensor. Furthermore, these algorithms are validated together with the Sentinel-3 SLSTR operational LST product as well as several emissivity-dependent split-window algorithms with in-situ data from a rice paddy site. The LST retrieval algorithms were validated over three different land covers: flooded soil, bare soil, and full vegetation cover. Ground measurements were performed with a wide band thermal infrared radiometer at a permanent station. The coefficients of the proposed split-window algorithm were estimated using the Cloudless Land Atmosphere Radiosounding (CLAR) database: for the three surface types an overall systematic uncertainty (median) of –0.4 K and a precision (robust standard deviation) 1.1 K were obtained. For the Sentinel-3A SLSTR operational LST product, a systematic uncertainty of 1.3 K and a precision of 1.3 K were obtained. A first evaluation of the Sentinel-3B SLSTR operational LST product was also performed: systematic uncertainty was 1.5 K and precision 1.2 K. The results obtained over the three land covers found at the rice paddy site show that the emissivity-dependent split-window algorithms, i.e., the ones proposed here as well as previously proposed algorithms without angular dependence, provide more accurate and precise LSTs than the current version of the operational SLSTR product.

A liquid nitrogen-cooled Ca+ optical clock with systematic uncertainty of 3×10-18

Here we present a liquid nitrogen-cooled Ca+ optical clock with an overall systematic uncertainty of 3×10-18. In contrast with the room-temperature Ca+ optical clock that we have reported previously, the temperature of the blackbody radiation (BBR) shield in vacuum has been reduced to 82(5) K using liquid nitrogen. An ion trap with a lower heating rate and improved cooling lasers were also introduced. This allows cooling the ion temperature to the Doppler cooling limit during the clock operation, and the systematic uncertainty due to the ion’s secular (thermal) motion is reduced to < 1×10-18. The uncertainty due to the probe laser light shift and the servo error are also reduced to < 1×10-19 and 4×10-19 with the hyper-Ramsey method and the higher-order servo algorithm, respectively. By comparing the output frequency of the cryogenic clock to that of a room-temperature clock, the differential BBR shift between the two was measured with a fractional statistical uncertainty of 7×10-18. The differential BBR shift was used to calculate the static differential polarizability, and it was found in excellent agreement with our previous measurement with a different method. This work suggests that the BBR shift of optical clocks can be well suppressed in a liquid nitrogen environment. This is advantageous because conventional liquid-helium cryogenic systems for optical clocks are more expensive and complicated. Moreover, the proposed system can be used to suppress the BBR shift significantly in other types of optical clocks such as Yb+, Sr+, Yb, Sr, etc.

How to constrain warm dark matter with the Lyman-α forest

ABSTRACT The flux power spectrum (FPS) of the high-resolution Lyman-α forest data exhibits suppression at small scales. The origin of this suppression can be due to long-sought warm dark matter (WDM) or to thermal effects, related to the largely unknown reionization history of the Universe. Previous works explored a specific class of reionization histories that exhibit sufficiently strong thermal suppression and leave little room for WDM interpretation. In this work, we choose a different class of reionization histories, fully compatible with available data on evolution of reionization, but much colder than the reionization histories used by previous authors in determining the nature of dark matter, thus leaving the broadest room for the WDM interpretation of the suppression in the FPS. We find that WDM thermal relics with masses below 1.9 keV (95 per cent CL) would produce a suppression at scales that are larger than observed maximum of the FPS, independently of assumptions about thermal effects. This WDM mass is significantly lower than previously claimed bounds, demonstrating the level of systematic uncertainty of the Lyman-α forest method, due to the previous modelling. We also discuss how this uncertainty may affect also data at large scales measured by eBOSS(Baryon Oscillation Spectroscopic Survey).

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

Replication. Part I

There has been considerable debate and analysis about the nature and extent of what many believe to be a replication crisis in psychology and other social sci­ences. And perhaps to a lesser degree in the medical sciences. Our approach to the nature and value of replication has been based on the idea that the overriding purpose of replication is to ferret out and identify confounding causes. In other words, to reduce systematic uncertainty. This has led us to understand replication in a broader sense than ordinarily understood. We have developed this approach in considerable detail in three recent books which include both abstract analysis and many case studies drawn primarily, but not exclusively, from physics. We have, for example, considered the difficulty of deciding whether a replication has been successful or has failed, the roles of null experiments, and episodes in which a single experiment has been sufficient to decide, or to further investigate, an issue. In this two-part essay we will review and summarize our approach and results.

Replication Part II

There has been considerable debate and analysis about the nature and extent of what many believe to be a replication crisis in psychology and other social sci­ences. And perhaps to a lesser degree in the medical sciences. Our approach to the nature and value of replication has been based on the idea that the overriding purpose of replication is to ferret out and identify confounding causes. In other words, to reduce systematic uncertainty. This has led us to understand replication in a broader sense than ordinarily understood. We have developed this approach in considerable detail in three recent books which include both abstract analysis and many case studies drawn primarily, but not exclusively, from physics. We have, for example, considered the difficulty of deciding whether a replication has been successful or has failed, the roles of null experiments, and episodes in which a single experiment has been sufficient to decide, or to further investigate, an issue. In this two-part essay we will review and summarize our approach and results.