Carbon to oxygen ratios in extrasolar planetesimals

Observations of small extrasolar planets with a wide range of densities imply a variety of planetary compositions and structures. Currently, the only technique to measure the bulk composition of extrasolar planetary systems is the analysis of planetary debris accreting onto white dwarfs, analogous to abundance studies of meteorites. We present measurements of the carbon and oxygen abundances in the debris of planetesimals at ten white dwarfs observed with the Hubble Space Telescope, along with C/O ratios of debris in six systems with previously reported abundances. We find no evidence for carbon-rich planetesimals, with C/O ) = −0.92, and oxygen-rich objects with C/O less than or equal to that of the bulk Earth. The latter group may have a higher mass fraction of water than the Earth, increasing their relative oxygen abundance

The Dust Content of Galaxy Clusters

We report on the detection of reddening toward z ~ 0.2 galaxy clusters. This is measured by correlating the Sloan Digital Sky Survey cluster and quasar catalogs and by comparing the photometric and spectroscopic properties of quasars behind the clusters to those in the field. We find mean E(B-V) values of a few times 10^-3 mag for sight lines passing ~Mpc from the clusters' center. The reddening curve is typical of dust but cannot be used to distinguish between different dust types. The radial dependence of the extinction is shallow near the cluster center suggesting that most of the detected dust lies at the outskirts of the clusters. Gravitational magnification of background z ~ 1.7 sources seen on Mpc (projected) scales around the clusters is found to be of order a few per cent, in qualitative agreement with theoretical predictions. Contamination by different spectral properties of the lensed quasar population is unlikely but cannot be excluded.Comment: 4 pages, 3 figure

Perceived privacy risk in the Internet of Things: determinants, consequences, and contingencies in the case of connected cars

The Internet of Things (IoT) is permeating all areas of life. However, connected devices are associated with substantial risks to users’ privacy, as they rely on the collection and exploitation of personal data. The case of connected cars demonstrates that these risks may be more profound in the IoT than in extant contexts, as both a user's informational and physical space are intruded. We leverage this unique setting to collect rich context-immersive interview (n = 33) and large-scale survey data (n = 791). Our work extends prior theory by providing a better understanding of the formation of users’ privacy risk perceptions, the effect such perceptions have on users’ willingness to share data, and how these relationships in turn are affected by inter-individual differences in individuals’ regulatory focus, thinking style, and institutional trust

Privacy Risk Perceptions in the Connected Car Context

Connected car services are rapidly diffusing as they promise to significantly enhance the overall driving experience. Because they rely on the collection and exploitation of car data, however, such services are associated with significant privacy risks. Following guidelines on contextualized theorizing, this paper examines how individuals perceive these risks and how their privacy risk perceptions in turn influence their decision-making, i.e., their willingness to share car data with the car manufacturer or other service providers. We conducted a multi-method study, including interviews and a survey in Germany. We found that individuals’ level of perceived privacy risk is determined by their evaluation of the general likelihood of IS-specific threats and the belief of personal exposure to such threats. Two cognitive factors, need for cognition and institutional trust, are found to moderate the effect that perceived privacy risk has on individuals’ willingness to share car data in exchange for connected car services

Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment.Comment: 33 pages, 14 Figures; A typo in Eq.A11 is fixed. The C++/Python codes for ECGMM can be downloaded from: https://sites.google.com/site/jiangangecgmm

Large‐Scale Daylight Photoluminescence: Automated Photovoltaic Module Operating Point Detection and Performance Loss Assessment by Quantitative Signal Analysis

Daylight photoluminescence (DPL) is a relatively novel imaging technique utilized in photovoltaic (PV) system inspection, using the sun as excitation source. Filtering the luminescence signal from the strong sun irradiation is its main challenge. Images acquired at two different operating points (OPs) of the module, allow subtraction of the background radiation while maintaining the luminescence signal. A DPL-ready inverter, which is able to toggle between manually selectable OPs of connected PV modules, is presented in this work. Synchronization of image acquisition and OP switching becomes particularly challenging if the camera is applied to unmanned aerial vehicles. To overcome this challenge, an algorithm is developed to identify OP switches in a set of images taken in the field by investigating image intensities. Further, by working out the detailed dependencies of the signal recorded during DPL, the temperature coefficient of photoluminescence intensity is derived theoretically, and its impact on quantitative inspections. The potential field application of DPL images to identify performance loss in PV modules is investigated by two approaches: recording the signal intensity of images over time and comparing the signal intensity of different PV modules in one image. For both approaches, their hypothetical applicability is shown experimentally.Daylight photoluminescence (DPL) is a novel inspection method for large-scale photovoltaic (PV) module inspections. A new inverter development allows direct operating point switching of connected PV modules. An investigation of quantifying the luminescence signal intensity in DPL images shows the possibilities of using this technique for performance loss degradation analysis.image (c) 2023 WILEY-VCH Gmb

Symmetry and Measuring: Ways to Teach the Foundations of Mathematics Inspired by Yupiaq Elders

Evident in human prehistory and across immense cultural variation in human activities, symmetry has been perceived and utilized as an integrative and guiding principle. In our long-term collaborative work with Indigenous Knowledge holders, particularly Yupiaq Eskimos of Alaska and Carolinian Islanders in Micronesia, we were struck by the centrality of symmetry and measuring as a comparison-of-quantities, and the practical and conceptual role of qukaq [center] and ayagneq [a place to begin]. They applied fundamental mathematical principles associated with symmetry and measuring in their everyday activities and in making artifacts. Inspired by their example, this paper explores the question: Could symmetry and measuring provide a systematic and integrative way to teach the foundations of mathematical thinking? We illustrate how the fundamental structures of symmetry, measuring, and comparison-of-quantities, starting with the embodied orthogonal axes, form a basis for properties of equality, aspects of numbers and operations (including place value), geometry and number line representations, functions, algebraic reasoning, and measurement. We conclude by embedding the earlier geometric constructions of triangles and squares within the unit circle and making explicit connections to trigonometric functions