Weights Allocation Based on Optimal Uncertainty Evaluation

In the traditional measurement theory, precision is defined as the dispersion of measured value, and is used as the basis of weights calculation in the adjustment of measurement data with different qualities, which leads to the trouble that trueness is completely ignored in the weight allocation. In this paper, following the pure concepts of probability theory, the measured value (observed value) is regarded as a constant, the error as a random variable, and the variance is the dispersion of all possible values of an unknown error. Thus, a rigorous formula for weights calculation and variance propagation is derived, which solves the theoretical trouble of determining the weight values in the adjustment of multi-channel observation data with different qualities. The results show that the optimal weights are not only determined by the covariance array of observation errors, but also related to the model of adjustment.

A fibre-based 2D-slit homogenizer concept for high-precision space-based spectrometer missions

The measurement accuracy of recent and future space-based imaging spectrometers with a high spectral and spatial resolution suffer from the inhomogeneity of the radiances of the observed Earth scene. The Instrument Spectral Response Function (ISRF) is distorted due to the inhomogeneous illumination from scene heterogeneity. This gives rise to a pseudo-random error on the measured spectra. In order to assess the spectral stability of the spectrograph, stringent requirements are typically defined on the ISRF such as shape knowledge and the stability of the centroid position of the spectral sample. The high level of spectral accuracy is particularly crucial for missions quantifying small variations in the total column of well-mixed trace gases like $$\hbox {CO}_{2}$$ CO 2 . In the framework of the $$\hbox {CO}_{2}$$ CO 2 Monitoring Mission (CO2M) industrial feasibility study (Phase A/B1 study), we investigated a new slit design called 2D-Slit Homogenizer (2DSH). This new concept aims to reduce the Earth scene contrast entering the instrument. The 2DSH is based on optical fibre waveguides assembled in a bundle, which scramble the light in across-track (ACT) and along-track (ALT) direction. A single fibre core dimension in ALT defines the spectral extent of the slit and the dimension in ACT represents the spatial sample of the instrument. The full swath is given by the total size of the adjoined fibres in ACT direction. In this work, we provide experimental measurement data on the stability of representative rectangular core shaped fibre as well as a preliminary pre-development of a 2DSH fibre bundle. In our study, the slit concept has demonstrated significant performance gains in the stability of the ISRF for several extreme high-contrast Earth scenes, achieving a shape stability of $$<0.5{\%}$$ < 0.5 % and a centroid stability of $$<0.25 \ \text {pm}$$ < 0.25 pm (NIR). Given this unprecedented ISRF stabilization, we conclude that the 2DSH concept efficiently desensitizes the instrument for radiometric and spectral errors with respect to the heterogeneity of the Earth scene radiance.

A Discrepancy in Thermal Conductivity Measurement Data of Quantum Spin Liquid β′-EtMe3Sb[Pd(dmit)2]2 (dmit = 1,3-Dithiol-2-thione-4,5-dithiolate)

A molecular Mott insulator β′-EtMe3Sb[Pd(dmit)2]2 is a quantum spin liquid candidate. In 2010, it was reported that thermal conductivity of β′-EtMe3Sb[Pd(dmit)2]2 is characterized by its large value and gapless behavior (a finite temperature-linear term). In 2019, however, two other research groups reported opposite data (much smaller value and a vanishingly small temperature-linear term) and the discrepancy in the thermal conductivity measurement data emerges as a serious problem concerning the ground state of the quantum spin liquid. Recently, the cooling rate was proposed to be an origin of the discrepancy. We examined effects of the cooling rate on electrical resistivity, low-temperature crystal structure, and 13C-NMR measurements and could not find any significant cooling rate dependence.

Spatio-Temporal Characteristics and Variation Pattern of the Atmospheric Particulate Matter Concentration: A Case Study of the Beijing–Tianjin–Hebei Region, China

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM2.5 and PM10, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM2.5 and PM10 concentrations and the PM2.5/PM10 ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM2.5/PM10 ratio was highest in winter and lowest in spring; (3) the PM2.5 and PM10 concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R2 values for PM2.5 and PM10 in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate.

Evaluation of the Effect of Hamao Detention Pond on Excess Runoff from the Abukuma River in 2019 and Simple Remodeling of the Pond to Increase Its Flood Control Function

Due to the recent increase in the intensity of rainstorms, the Japanese government has announced a new policy of flexible flood mitigation measures that presupposes the release of water volumes exceeding the river channel capacity onto floodplains. However, due to the limited amount of quantitative measurement data on excess runoff, it will take time to formulate planning standards for remodeling and newly constructing flood control facilities reasonable enough under current budgetary constraints. In this study, the capacity shortage of a flood detention pond was evaluated against the excess runoff from a severe 2019 flood event by combining the fragmentary measurement data with a numerical flow simulation. Although the numerical model was a rather simple one commonly used for rough estimation of inundation areas in Japan, the results were overall consistent with the observations. Next, in accordance with the new policy, an inexpensive remodeling of the detention basin, which was designed according to conventional standards, was simulated; the upstream side of the surrounding embankment was removed so that excess water flowed up onto the floodplain gradually. Numerical experiments using the simple model indicated that the proposed remodeling increased the effectiveness of flood control remarkably, even for floods greater than the 2019 flood, without much inundation damage to upstream villages.

Uncertainty Analysis and Experimental Validation of Identifying the Governing Equation of an Oscillator Using Sparse Regression

In recent years, the rapid growth of computing technology has enabled identifying mathematical models for vibration systems using measurement data instead of domain knowledge. Within this category, the method Sparse Identification of Nonlinear Dynamical Systems (SINDy) shows potential for interpretable identification. Therefore, in this work, a procedure of system identification based on the SINDy framework is developed and validated on a single-mass oscillator. To estimate the parameters in the SINDy model, two sparse regression methods are discussed. Compared with the Least Squares method with Sequential Threshold (LSST), which is the original estimation method from SINDy, the Least Squares method Post-LASSO (LSPL) shows better performance in numerical Monte Carlo Simulations (MCSs) of a single-mass oscillator in terms of sparseness, convergence, identified eigenfrequency, and coefficient of determination. Furthermore, the developed method SINDy-LSPL was successfully implemented with real measurement data of a single-mass oscillator with known theoretical parameters. The identified parameters using a sweep signal as excitation are more consistent and accurate than those identified using impulse excitation. In both cases, there exists a dependency of the identified parameter on the excitation amplitude that should be investigated in further research.

Considering decoupled phenotypic diversification between ontogenetic phases in macroevolution: An example using Triggerfishes (Balistidae)

Across the Tree of Life, most studies of phenotypic disparity and diversification have been restricted to adult organisms. However, many lineages have distinct ontogenetic phases that do not reflect the same traits as their adult forms. Non-adult disparity patterns are particularly important to consider for coastal ray-finned fishes, which often have juvenile phases with distinct phenotypes. These juvenile forms are often associated with sheltered nursery environments, with phenotypic shifts between adults and juvenile stages that are readily apparent in locomotor morphology. However, whether this ontogenetic variation in locomotor morphology reflects a decoupling of diversification dynamics between life stages remains unknown. Here we investigate the evolutionary dynamics of locomotor morphology between adult and juvenile triggerfishes. Integrating a time-calibrated phylogenetic framework with geometric morphometric approaches and measurement data of fin aspect ratio and incidence, we reveal a mismatch between morphospace occupancy, the evolution of morphological disparity, and the tempo of trait evolution between life stages. Collectively, our results illuminate how the heterogeneity of morpho-functional adaptations can decouple the mode and tempo of morphological diversification between ontogenetic stages.

A Coupled Experimental and Statistical Approach for an Assessment of the Airborne Infection Risk in Event Locations

Operators of event locations are particularly affected by a pandemic. Resulting restrictions may cause uneconomical business. With previous models, only an incomplete quantitative risk assessments is possible, whereby no suitable restrictions can be derived. Hence, a mathematical and statistical model has been developed in order to link measurement data of substance dispersion in rooms with epidemiological data like incidences, reproduction numbers, vaccination rates and test qualities. This allows a first time overall assessment of airborne infection risks in large event locations. In these venues displacement ventilation concepts are often implemented. In this case simplified theoretical assumptions fail for the prediction of relevant airflows for infection processes. Thus, with locally resolving trace gas measurements and specific data of infection processes, individual risks can be computed more detailed. Via inclusion of many measurement positions, an assessment of entire event locations is possible. Embedding the overall model in a flexible application, daily updated epidemiological data allow latest calculations of expected new infections and individual risks of single visitors for a certain event. With this model, an instrument has been created that can help policymakers and operators to take appropriate measures and to check restrictions for their effect.