Comparative Study of Different Measurement Methods for Characterizing Rheological Properties of Lubrication Layer

The lubrication layer plays a governing role in predicting the pumpability of fresh concrete. To determine the effect of measurement methods on the characterization of the rheological properties of the lubrication layer, different measurement systems, including Sliper, tribometer, and the utilization of a mortar rheometer, were employed. The rheological properties and workability of bulk concrete were measured in parallel to investigate the correlation between them and the rheological properties of the lubrication layer. The results show that the measured values of the rheological parameters of the lubrication layer differ due to the systematic deviation between different measurement methods. The results obtained by both tribometer and mortar rheometer were well-correlated, having a linear relationship with the rheological parameters of bulk concrete. The correlation coefficient between results gained with Sliper and rheological parameters of concrete or lubrication layer determined with other methods was not high enough. Addition friction led to the large accidental error and overestimated yield stress obtained with Sliper. The workability of concrete is only suitable for characterizing the rheological properties of bulk concrete.

A comparison of optic disc area measured by confocal scanning laser tomography versus Bruch’s membrane opening area measured using optical coherence tomography

Background Precise optic disc size measurements based on anatomically exact disc margins are fundamental for a correct assessment of glaucoma suspects. Computerized imaging techniques, such as confocal-scanning-laser-tomography (CSLT), which applies operator defined boundaries and optical-coherence-tomography (OCT), which incorporates an alternative detectable landmark (Bruch’s-membrane-opening (BMO)), have simplified the planimetry of the optic disc and BMO-area, respectively. This study’s objectives are to compare both modalities for area and to define a threshold for macro-BMO using BMO-OCT. Methods Retrospectively, patients that simultaneously received CSLT and BMO-OCT scans were included. Their images were correlated and agreement was determined using Bland-Altman-analysis. The diagnostic power of a macro-BMO threshold using OCT was derived after creating a receiver-operating-characteristics-curve using the well-established analogous CSLT threshold (2.43 mm2). Results Our study included 373 eyes with a median optic disc area by CSLT/ BMO-area by OCT of 2.56 mm2 and 2.19 mm2 respectively. The Bland-Altman-analysis revealed a systematic deviation with a diverging tendency with increasing area, which enabled the creation of the following mathematical relation: disc-area (CSLT)*0.73 + 0.3 = BMO-area (OCT). BMO-area of 2.19 mm2 showed the best diagnostic power for identifying macro-BMOs using OCT (sensitivity: 75%, specificity: 86%). Conclusions Area measurements (CSLT optic disc area vs. BMO-area by OCT) showed a systematic deviation with a divergent tendency with increasing size. Our mathematical equation offers an estimated comparison of these anatomically diverse entities. Considering BMO-OCT´ anatomical accuracy, the 2.19 mm2 threshold may improve discernment between glaucoma suspects and norm variants.

Conductors’ tempo choices shed light over Beethoven’s metronome

During most part of Western classical music history, tempo, the speed of music, was not specified, for it was considered obvious from musical context. Only in 1815, Maelzel patented the metronome. Beethoven immediately embraced it, so much as to add tempo marks to his already published eight symphonies. However, these marks are still under dispute, as many musicians consider them too quick to be played and even unmusical, whereas others claim them as Bethoven’s supposedly written will. In this work, we develop a methodology to extract and analyze the performed tempi from 36 complete symphonic recordings by different conductors. Our results show that conductor tempo choices reveal a systematic deviation from Beethoven’s marks, which highlights the salience of “correct tempo” as a perceptive phenomenon shaped by cultural context. The hasty nature of these marks could be explained by the metronome’s ambiguous scale reading point, which Beethoven probably misinterpreted.

The distinct stellar-to-halo mass relations of satellite and central galaxies: insights from the IllustrisTNG simulations

ABSTRACT We study the stellar-to-halo mass relation (SHMR) for central and satellite galaxies with total dynamical masses above $10^{10.5}\, \rm {M}_\odot$ using the suite of cosmological magnetohydrodynamical simulations IllustrisTNG. In particular, we quantify environmental effects on satellite populations from TNG50, TNG100, and TNG300 located within the virial radius of group- and cluster-like hosts with total masses of $10^{12\!-\!15.2}\, \rm {M}_\odot$. At fixed stellar mass, the satellite SHMR exhibits a distinct shift towards lower dynamical mass compared to the SHMR of centrals. Conversely, at fixed dynamical mass, satellite galaxies appear to have larger stellar-to-total mass fractions than centrals by up to a factor of a few. The systematic deviation from the central SHMR is larger for satellites in more massive hosts, at smaller cluster-centric distances, with earlier infall times, and that inhabits higher local density environments; moreover, it is in place already at early times (z ≲ 2). Systematic environmental effects might contribute to the perceived galaxy-to-galaxy variation in the measured SHMR when galaxies cannot be separated into satellites and centrals. The SHMR of satellites exhibits a larger scatter than centrals (by up to ∼0.8 dex), over the whole range of dynamical mass. The shift of the satellite SHMR results mostly from tidal stripping of their dark matter, which affects satellites in an outside-in fashion: The departure of the satellite SHMR from the centrals’ relation diminishes for measurements of dynamical mass in progressively smaller apertures. Finally, we provide a family of fitting functions for the SHMR predicted by IllustrisTNG.

Contactless Localization of Premature Laminar–Turbulent Flow Transitions on Wind Turbine Rotor Blades in Operation

Thermographic flow visualization enables a noninvasive detection of the laminar–turbulent flow transition and allows a measurement of the impact of surface erosion and contamination due to insects, rain, dust, or hail by quantifying the amount of laminar flow reduction. The state-of-the-art image processing is designed to localize the natural flow transition as occurring on an undisturbed blade surface by use of a one-dimensional gradient evaluation. However, the occurrence of premature flow transitions leads to a high measurement uncertainty of the localized transition line or to a completely missed flow transition detection. For this reason, regions with turbulent flow are incorrectly assigned to the laminar flow region, which leads to a systematic deviation in the subsequent quantification of the spatial distribution of the boundary layer flow regimes. Therefore, a novel image processing method for the localization of the laminar–turbulent flow transition is introduced, which provides a reduced measurement uncertainty for sections with premature flow transitions. By the use of a two-dimensional image evaluation, local maximal temperature gradients are identified in order to locate the flow transition with a reduced uncertainty compared to the state-of-the-art method. The transition position can be used to quantify the reduction of the laminar flow regime surface area due to occurrences of premature flow transitions in order to measure the influence of surface contamination on the boundary layer flow. The image processing is applied to the thermographic measurement on a wind turbine of the type GE 1.5 sl in operation. In 11 blade segments with occurring premature flow transitions and a high enough contrast of the developed turbulence wedge, the introduced evaluation was able to locate the flow transition line correctly. The laminar flow reduction based on the evaluated flow transition position located with a significantly reduced systematic deviation amounts to 22% for the given measurement and can be used to estimate the reduction of the aerodynamic lift. Therefore, the image processing method introduced allows a more accurate estimation of the effects of real environmental conditions on the efficiency of wind turbines in operation.

A Neural Network-Based Rain Effect Correction Method for HY-2A Scatterometer Backscatter Measurements

The backscattering coefficients measured by Ku-band scatterometers are strongly affected by rainfall, resulting in a systematic error in sea surface wind field retrieval. In rainy conditions, the radar signals are subject to absorption by the raindrops in their round-trip propagation through the atmosphere, while the backscatter of raindrops raises the echo energy. In addition, raindrops give rise to roughness by impinging the ocean surface, resulting in an increase in the echo energy measured by a scatterometer. Under moderate wind conditions, the comprehensive impact of rainfall causes the wind speeds retrieved by the scatterometer to be higher than their actual values. The HY-2A scatterometer is a Ku-band, pencil-beam, conically scanning scatterometer. To correct the systematic error of the HY-2A scatterometer measurement in rainy conditions, a neural network model is proposed according to the characteristics of the backscatter coefficients measured by the HY-2A scatterometer in the presence of rain. With the neural network, the wind fields of the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data were used as the reference to correct the deviation in backscatter coefficients measured by the HY-2A scatterometer in rainy conditions, and the accuracy in wind speeds retrieved using the corrected backscatter coefficients was significantly improved. Compared with the cases of wind retrieval without rain effect correction, the wind speeds retrieved from the corrected backscatter coefficients by the neural network show a much lower systematic deviation, which indicates that the neural network can effectively remove the systematic deviation in the backscatter coefficients and the retrieved wind speeds caused by rain.

High-efficiency ultra-precision comparator for d-spacing mapping measurement of silicon

This article describes a high-efficiency experimental configuration for a self-referenced lattice comparator with a `brush beam' of synchrotron radiation from a bending magnet and two linear position-sensitive photon-counting-type X-ray detectors. The efficiency is more than ten times greater compared with the `pencil-beam' configuration and a pair of zero-dimensional detectors. A solution for correcting the systematic deviation of d-spacing measurements caused by the horizontal non-uniformity of the brush beam is provided. Also, the use of photon-counting-type one-dimensional detectors not only improves the spatial resolution of the measurements remarkably but can also adjust the sample's attitude angles easily.

Making biased but better predictions: The trade-offs strategists face when they learn and use heuristics

The heuristics strategists use to make predictions about key decision variables are often learned from only a small sample of observations, which leads to a risk of inappropriate generalization when strategists misjudge regularities. Building on the statistical learning literature, we show how strategists can mitigate this risk. Strategies to learn heuristics that accept a bias, that is, a systematic deviation of predictions from actual outcomes, can outperform unbiased strategies because they can reduce the variance component of prediction error: the degree to which random fluctuations in observational data are inappropriately generalized. We demonstrate how strategists who are aware of the trade-off between bias and variance can learn heuristics more effectively if they are also aware of the relevant characteristics of their learning environment. We discuss the implications of our results for our understanding of heuristics, (dynamic) capabilities, and managerial cognitive capabilities, and we outline opportunities for empirical work.