Magnetic properties of the LL5 ordinary chondrite Chelyabinsk (fall of February 15, 2013)

Here we characterize the magnetic properties of the Chelyabinsk chondrite (LL5, S4, W0) and constrain the composition, concentration, grain size distribution, and mineral fabric of the meteorite's magnetic mineral assemblage. Data were collected from 10 to 1073 K and include measurements of low‐field magnetic susceptibility (χ₀), the anisotropy of χ₀, hysteresis loops, first‐order reversal curves, Mössbauer spectroscopy, and X‐ray microtomography. The REM and REM′ paleointensity protocols suggest that the only magnetizations recorded by the chondrite are components of the Earth's magnetic field acquired during entry into our planet's atmosphere. The Chelyabinsk chondrite consists of light and dark lithologies. Fragments of the light lithology show logχ₀ = 4.57 ± 0.09 (s.d.) (n = 135), while the dark lithology shows 4.65 ± 0.09 (n = 39) (where χ₀ is in 10^?9 m³ kg^?1). Thus, Chelyabinsk is three times more magnetic than the average LL5 fall, but is similar to a subgroup of metal‐rich LL5 chondrites (Paragould, Aldsworth, Bawku, Richmond) and L/LL5 chondrites (Glanerbrug, Knyahinya). The meteorite's room‐temperature magnetization is dominated by multidomain FeNi alloys taenite and kamacite (no tetrataenite is present). However, below approximately 75 K remanence is dominated by chromite. The metal contents of the light and dark lithologies are 3.7 and 4.1 wt%, respectively, and are based on values of saturation magnetization.     

Linear waves in a radiating and scattering grey medium

The equation of radiative acoustics is derived by taking into account the effect of a transverse magnetic field, which is quite similar to the acoustic equation derived in Paper I. The only difference is that theadiabatic, isothermal, andisentropic speeds of sound and theradiation-acoustic speed are replaced by theadiabatic, isothermal, andisentropic magnetoacoustic speeds and theradiation-magnetoacoustic speed, respectively. The main results shown in Paper I are valid even in the presence of a transverse magnetic field.     

The Ushnus in the astronomy of the Inca culture

Inferences are made about the relationship that existed between the Ushnus, pyramid-shaped, terraced structures used by the Incas in the most important ceremonies of the Tawantinsuyo, and Inka Astronomy. We draw attention to Ayni, Kawsaypacha, Duality, and Tinkuy principles, multidimensional codes of conduct and wisdom that are at the root of the Andean cosmovision and on their perception of the world and the Cosmos. These principles, examined as postulates, allow to elaborate axiomatic propositions to identify the Ushnus with ancient Astronomy practices. In a complementary statement, starting from a bi-conditional proposition, we may infer through reciprocal corollaries that the Inka earliest roots to a holistic learning and educational ambient in the Tawantinsuyo was not elitist, instead it was based on a epistemological construct that differs from the corresponding Western educational ambients. An epistemological and cognitive approach allows to identify an ancient elaborate process of knowledge construction, based on the four fundamental principles, corresponding to different levels of assimilation and comprehension. As a complementary aspect, we identify some of the most preserved Ushnus of the Inka “Empire.” Then we complement this contribution with a broader interpretation for the Ushnus.     

Edge-to-Stem Variability in Wet-Canopy Evaporation From an Urban Tree Row

Evaporation from wet-canopy (\(E_\mathrm{C}\)) and stem (\(E_\mathrm{S}\)) surfaces during rainfall represents a significant portion of municipal-to-global scale hydrologic cycles. For urban ecosystems, \(E_\mathrm{C}\) and \(E_\mathrm{S}\) dynamics play valuable roles in stormwater management. Despite this, canopy-interception loss studies typically ignore crown-scale variability in \(E_\mathrm{C}\) and assume (with few indirect data) that \(E_\mathrm{S}\) is generally \({<}2\%\) of total wet-canopy evaporation. We test these common assumptions for the first time with a spatially-distributed network of in-canopy meteorological monitoring and 45 surface temperature sensors in an urban Pinus elliottii tree row to estimate \(E_\mathrm{C}\) and \(E_\mathrm{S}\) under the assumption that crown surfaces behave as “wet bulbs”. From December 2015 through July 2016, 33 saturated crown periods (195 h of 5-min observations) were isolated from storms for determination of 5-min evaporation rates ranging from negligible to 0.67 \(\hbox {mm h}^{-1}\). Mean \(E_\mathrm{S}\) (0.10 \(\hbox {mm h}^{-1}\)) was significantly lower (\(p < 0.01\)) than mean \(E_\mathrm{C}\) (0.16 \(\hbox {mm h}^{-1}\)). But, \(E_\mathrm{S}\) values often equalled \(E_\mathrm{C}\) and, when scaled to trunk area using terrestrial lidar, accounted for 8–13% (inter-quartile range) of total wet-crown evaporation (\(E_\mathrm{S}+E_\mathrm{C}\) scaled to surface area). \(E_\mathrm{S}\) contributions to total wet-crown evaporation maximized at 33%, showing a general underestimate (by 2–17 times) of this quantity in the literature. Moreover, results suggest wet-crown evaporation from urban tree rows can be adequately estimated by simply assuming saturated tree surfaces behave as wet bulbs, avoiding problematic assumptions associated with other physically-based methods.     

Testing electric field models using ring current ion energy spectra from the Equator-S ion composition (ESIC) instrument

During the main and early recovery phase of a geomagnetic storm on February 18, 1998, the Equator-S ion composition instrument (ESIC) observed spectral features which typically represent the differences in loss along the drift path in the energy range (5–15 keV/e) where the drift changes from being E × B dominated to being gradient and curvature drift dominated. We compare the expected energy spectra modeled using a Volland-Stern electric field and a Weimer electric field, assuming charge exchange along the drift path, with the observed energy spectra for H⁺ and O⁺. We find that using the Weimer electric field gives much better agreement with the spectral features, and with the observed losses. Neither model, however, accurately predicts the energies of the observed minima.     

Deep soil water dynamics in an undisturbed primary forest in central Amazonia: Differences between normal years and the 2005 drought

Understanding how Amazonian rainforests deal with extended droughts is critical in the face of changing climate. This research analyze the physical properties and the soil water dynamics of a deep soil profile in an area of primary forest in central Amazonia to elucidate these processes under drought and nondrought conditions. Physical soil properties derived from soil cores exhibited a distinctive layer between 480 and 880 cm deep, characterized by higher microporosity and low plant water availability. In situ soil moisture measurements collected during the period from January 2003 through February 2006 and for depths ranging from 10 to 1,430 cm suggest that, in the study site, the top 480 cm of the soil profile satisfied most of the transpirational demands in normal climatological years. However, during exceptionally dry periods, such as the 2005 drought, root uptake occurs below 480 cm. As concluded by previous studies, most of the uptake is concentrated in the first meter of the soil profile: More than 40% of the total demand for transpiration is supplied by the top meter of soil. Because deep root uptake occurred at greater depths than normal during the 2005 drought, our results suggest that this is a fundamental mechanism to cope with prolonged droughts.     

Dense collection areas and terrestrial alteration of meteorites in the Atacama Desert

In the last 15 years, more than 2700 meteorites have been recovered and officially classified from the Atacama Desert. Although the number of meteorites collected in the Atacama has risen, the physical and climatic properties of the dense collection areas (DCAs) have not been fully characterized. In this article, we compiled the published data of all classified meteorites found in the Atacama Desert to (i) describe the distribution by meteorite groups, (ii) compare the weathering degree of chondrites among different Atacama DCAs and other hot and cold deserts, and (iii) determine the preservation conditions of chondrites in the main Atacama DCAs in relation with the local climatic conditions. The 35 DCAs so far identified in the Atacama Desert are located in three main morphotectonic units: The Coastal Range (CR), Central Depression (CD), and Pre-Andean Range/Basement. A comparison with reported weathering data from other cold and hot deserts indicates that the mean terrestrial weathering of Atacama chondrites (W1–2), displays less alteration than other hot deserts (W2–3) and resembles the weathering distribution of the Antarctic meteorites (W1–2). The highest abundance of Atacama chondrites with low weathering (≤W2) is localized in the CD (78.8%, N = 1435), which is protected from the coastal fog influence and seasonal rainfalls and displays the oldest surfaces in the Atacama Desert. The morphogenetic classification based on present-day temperatures and precipitations of the main Atacama DCAs reveals similar regional/subregional climatic conditions in the most productive areas and a truly productive surface for meteorite recovery between 5% and 58% of the quadrangles formally defined for each Atacama DCA. Our morphogenetic classification lacks consideration of some meteorological parameters such as the coastal fog, so it cannot fully explain the differences in weathering patterns among CR chondrites. Future studies of chondrite preservation in the Atacama DCAs should consider other meteorological variables such as relative humidity, specific humidity, or dew point, in combination with exposure ages of meteorites and its surfaces.     

Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.