Ejecta from impacts at 0.2-2.3 m/s in low gravity

Collisions between planetary ring particles and in some protoplanetary disk environments occur at speeds below 10 m/s. The particles involved in these low-velocity collisions have negligible gravity and may be made of or coated with smaller dust grains and aggregates. We undertook microgravity impact experiments to better understand the dissipation of energy and production of ejecta in these collisions. Here we report the results of impact experiments of solid projectiles into beds of granular material at impact velocities from 0.2 to 2.3 m/s performed under near-weightless conditions on the NASA KC-135 Weightless Wonder V. Impactors of various densities and radii of 1 and 2 cm were launched into targets of quartz sand, JSC-1 lunar regolith simulant, and JSC-Mars-1 martian regolith simulant. Most impacts were at normal or near-normal incidence angles, though some impacts were at oblique angles. Oblique impacts led to much higher ejection velocities and ejecta masses than normal impacts. For normal incidence impacts, characteristic ejecta velocities increase with impactor kinetic energy, KE, as approximately KE^0.5. Ejecta masses could not be measured accurately due to the nature of the experiment, but qualitatively also increased with impactor kinetic energy. Some experiments were near the threshold velocity of 0.2 m/s identified in previous microgravity impact experiments as the minimum velocity needed to produce ejecta [Colwell, J.E., 2003. Icarus 164, 188-196], and the experimental scatter is large at these low speeds in the airplane experiment. A more precise exploration of the transition from low-ejecta-mass impacts to high-ejecta-mass impacts requires a longer and smoother period of reduced gravity. Coefficient of restitution measurements are not possible due to the varying acceleration of the airplane throughout the experiment.     

Experimental study of the sublimation of ice through an unconsolidated clay layer: Implications for the stability of ice on Mars and the possible diurnal variations in atmospheric water

We have studied the sublimation of ice and water vapor transport through various thicknesses of clay (<63 μm grain size). We experimentally demonstrate that both adsorption and diffusion strongly affect the transport of water, and that the processes of diffusion and adsorption can be separately quantified once the system comes to a steady state. At shallow depths of clay, water vapor transport is determined by diffusion through both the atmosphere and the clay layer, whereas at greater depth the rate of sublimation of the ice is governed only by diffusion through the clay. Using two different models, we determine the diffusion coefficient for water vapor through unconsolidated clay layer to be 1.08±0.04×¹⁰⁻⁴ and . We also determined the adsorption isotherms for the clay layer, which follow the Langmuir theory at low water vapor pressure (<100 Pa, where a monolayer of water molecules forms on the surface of the clay) and the BET theory at higher pressure (where multiple water layers form). From our analysis of both types of isotherms we determined the adsorption constants to be and c=30±10, respectively, and specific surface areas of 1.10±0.2×¹⁰⁵ and , respectively. Finally, we report a theoretical kinetic model for the simultaneous diffusion and adsorption from which we determine adsorption kinetic constants according to the Langmuir theory of and . If the martian regolith possesses diffusive properties similar to those of the unconsolidated montmorillonite soil we investigated here, it would not represent a significant barrier to the sublimation of subsurface ice. However, at the low subsurface temperatures of high latitude (180 K on average), ice could survive from the last glaciation period (about 300 to 400,000 years ago). Higher subsurface temperatures in the equatorial regions would prevent long-timescale survival of ice in the shallow subsurface. In agreement with previous work, we show that adsorption of water by a clay regolith could provide a significant reservoir of subsurface water and it might account for the purported diurnal cycle in the water content of the atmosphere.     

The information system of the French Peatland Observation Service: Service National d'Observation Tourbières – A valuable tool to assess the impact of global changes on the hydrology and biogeochemistry of temperate peatlands through long term monitoring

Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ).     

A sequential sparse polynomial chaos expansion using Bayesian regression for geotechnical reliability estimations

Polynomial chaos expansions (PCEs) have been widely employed to estimate failure probabilities in geotechnical engineering. However, PCEs suffer from two deficiencies: (a) PCE coefficients are solved by the least-square minimization method which easily causes overfitting issues; (b) building a high order PCE is often computationally expensive. In order to overcome the aforementioned drawbacks, the Bayesian regression technique is employed to evaluate PCE coefficients, which not only provides a sparse solution but also avoids overfitting. With the aid of the predictive means and variances given by Bayesian analysis, a learning function is proposed to sequentially select the most informative samples that are critical to build a PCE. This sequential learning scheme can highly enhance the computational efficiency of PCEs. Besides, importance sampling (IS) is incorporated into the sequential learning (SL)-PCEs to deal with geotechnical problems with small failure probabilities. The proposed method of SL-PCE-IS is applied to three illustrative examples, which shows that the improved PCE method is more effective and efficient than the common PCEs method, leading to accurate estimations of small failure probabilities using fewer training samples.     

High Resolution Köppen‐Geiger Classifications of Paleoclimate Simulations

The development and application of an algorithm to compute Köppen‐Geiger climate classifications from the Coupled Model Intercomparison Project (CMIP) and Paleo Model Intercomparison Project (PMIP) climate model simulation data is described in this study. The classification algorithm was applied to data from the PMIP III paleoclimate experiments for the Last Glacial Maximum, 21k years before present (yBP), Mid‐Holocene (6k yBP) and the Pre‐Industrial (0k yBP, control run) time slices. To infer detailed classification maps, the simulation datasets were interpolated to a higher resolution. The classification method presented is based on the application of Open Source Software, and the implementation is described with attention to detail. The source code and the exact input data sets as well as the resulting data sets are provided to enable the application of the presented approach.     

Exploring the Spatiotemporal Pattern of Cyberbullying with Yik Yak

Cyberbullying is an emerging social issue along with the prevalence of social media. Previous studies have used extensive surveys or firsthand data primarily from conventional social networks¹1 Social media whose users primarily use their real name and provide identifiable information, although some might use pseudonyms (e.g., Facebook and Twitter).View all notes (e.g., Twitter) to study cyberbullying, which often ignores the factor of anonymity and location. Considering the sensitive nature and contagious effect of cyberbullying, a better understanding of the spatiotemporal pattern in cyberbullying is sorely needed to develop effective policies to combat this toxic social behavior. Grounded in the dramaturgy theory and the emerging literature on technoself, this study aims to compare cyberbullying in the anonymous social media (Yik Yak) with the conventional social media (Twitter) and explore its spatiotemporal patterns. A support vector machine is used to help identify records with bullying content. Average nearest neighbor, kernel density, and Ripley's K-function are used to explore the spatiotemporal patterns of cyberbullying behavior. We have found that cyberbullying is more likely to occur in anonymous than conventional social media. We also detected a clustering pattern corresponding to the student population, which can be explained by the dramaturgy theory and recent studies on technoself. In addition to making suggestions to help reduce cyberbullying in the future, this article also sheds light on the need for future studies.