Miracle-dz/UniFAR-FTUs huggingface dataset:
Molding of Salt Diapirs by Stiff Overburden

Although active diapirs must deform the overburdens they pierce, the shape of passive (downbuilt or syndepositional) diapirs is formed or molded by their overburdens. Molding of salt diapirs is simplified here to profiles of diapirs entirely downbuilt in effectively rigid overburden. The dips of salt-sediment contacts are shaped by the interaction of two processes: local net accumulation of overburden (A = deposition minus compaction) at rate and the net increase in relief of salt structures (R = salt rise minus dissolution) at rate . Steady kinematic molding ratios, /, forward model realistic dips of molded salt contacts, a, at particular depths using / or / = tan a/2. Rising or falling ratios of incremental molding forward model complete diapir profiles. Conversely, molding histories can be read by backstripping profiles of downbuilt diapirs. Salt diapirs are downbuilt in a field of downbuilding (100 > / > 0.01), that is bounded by burial and extrusion. Within this range, aggradation faster than salt can rise (/ 1) molds flaring (widening-upward) salt contacts. Below this range (where / ~100, salt emerges like a fountain and extrudes sheets of allochthonous salt. Extruded salt is recycled back into the ocean by dissolution at the surface or after burial and reactivation in another cycle.
A test, using atmospheric data, of a method for estimating oceanic eddy diffusivity

G. Holloway has proposed a simple method to estimate the effective horizontal eddy diffusivity for oceanic tracers using satellite measurements of sea‐surface height variability. In this method, the diffusivity is assumed to scale as the r.m.s. eddy geostrophic streamfunction. This method should apply analogously in an atmospheric context, in which the energetic eddies are well resolved in data sets and models, and in which both the effective diffusivity and tracer fluxes can be directly calculated. We evaluate Holloway's method using lower‐tropospheric daily atmospheric reanalysis data, and find that at a given height the method succesfully yields estimates of the divergent part of the atmospheric sensible heat flux, to within a fairly uniform scaling factor.
Estimated global nitrogen deposition using NO2 column density

Global nitrogen deposition has increased over the past 100 years. Monitoring and simulation studies of nitrogen deposition have evaluated nitrogen deposition at both the global and regional scale. With the development of remote-sensing instruments, tropospheric NO2 column density retrieved from Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) sensors now provides us with a new opportunity to understand changes in reactive nitrogen in the atmosphere. The concentration of NO2 in the atmosphere has a significant effect on atmospheric nitrogen deposition. According to the general nitrogen deposition calculation method, we use the principal component regression method to evaluate global nitrogen deposition based on global NO2 column density and meteorological data. From the accuracy of the simulation, about 70% of the land area of the Earth passed a significance test of regression. In addition, NO2 column density has a significant influence on regression results over 44% of global land. The simulated results show that global average nitrogen deposition was 0.34 g m−2 yr−1 from 1996 to 2009 and is increasing at about 1% per year. Our simulated results show that China, Europe, and the USA are the three hotspots of nitrogen deposition according to previous research findings. In this study, Southern Asia was found to be another hotspot of nitrogen deposition (about 1.58 g m−2 yr−1 and maintaining a high growth rate). As nitrogen deposition increases, the number of regions threatened by high nitrogen deposits is also increasing. With N emissions continuing to increase in the future, areas whose ecosystem is affected by high level nitrogen deposition will increase.
Multi-instrument comparison of top-of-atmosphere reflected solar radiation

Abstract Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiF.
Multiple System Function Supports with Inverter-Dominated Virtual Power Plant

Recently, renewables equipped with smart inverters are being integrated into distribution networks on a large scale. To address the problem that renewables are too scattered and hard to dispatch uniformly, virtual power plant (VPP) technique has been developed. In this work, we proposed an optimization model to coordinate different system functions and allocate them to various devices in a VPP agent. Peak shaving, congestion management, frequency and voltage regulation are all considered. Then, this scenario-based model is solved with the scenario selection method. Two types of scenarios are carefully selected to form the model, aiming at reducing the computation burden and increasing the strategy’s robustness. The model is tested on a VPP agent modified from the 33-bus system. The simulation demonstrates the effectiveness and efficiency of our work.
U-Pb age of the Baltoro granite, northwest Himalaya, and implications for monazite U-Pb systematics

The Baltoro granite is a major late- to post-tectonic plutonic phase of the Karakoram batholith of the northwest Himalaya in northern Pakistan. U-Pb zircon analyses indicate both emplacement at 21.0 ±0.5 Ma and significant Precambrian zircon inheritance. Dates on monazite are 17-19 Ma and are interpreted to have remained near their closure temperature of about 700 °C for several million years after emplacement, resulting in Pb loss by diffusion. We suggest that the granite was emplaced into rocks which were at high temperature and that they remained so until late Miocene northeast-tilting, rapid uplift and/or tectonic denudation, and cooling.
Calculation of aftershock accumulation from observed postseismic deformation: M6 2004 Parkfield, California, earthquake

The postseismic stress accumulation τ(t) over the interval 0.004 to 880 days following the 2004 Parkfield earthquake (M6) can be inferred from GPS measurements of postseismic deformation. The stress relaxation τ(t) − τ′lt, where τ′l is the interseismic loading rate and t is the time after the earthquake, plotted as a function of the number of M > 1.5 aftershocks Na(t) that have occurred by time t is bilinear with the slope of the fit to the first half of the aftershock sequence less than the slope of the fit to the second half. Thus, the aftershock seismicity rate is not proportional to the stress relaxation rate τ′(t) − τ′l over the entire sequence, but rather exhibits two distinct proportionalities. The observed postearthquake accumulation of M > 1.5 earthquakes in the aftershock zone as a function of time can be explained with the rate‐and‐state friction relation proposed by Dieterich (1994) between the cumulative number of earthquakes and τ(t).
Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Dysfunction and Psychopathology in Preadolescents

The search for biomarkers of psychiatric disorders has remained elusive, in part, due to high comorbidity, low specificity, and poor concordance between neurobiological abnormalities and existing diagnostic categories. Developmental factors that have impacts on symptom expression and brain function further complicate biomarker identification. Growing evidence suggests that incorporating cognition into studies of psychopathology may be a path forward, as cognitive dysfunction is a common feature across psychiatric disorders. Recent neuroimaging advances have allowed for characterization of functional connectomes, the collective set of functional connectivity across the whole-brain, using resting-state fMRI. Functional connectomes may be useful psychiatric biomarkers as they have been shown to underlie individual differences in cognition and explain variance in psychopathology across individuals. In the present study, we sought to identify brain-based dimensions that are associated with general cognitive capacity and psychopathology using canonical correlation analysis in a sample of 7,383 preadolescents from the Adolescent Brain Cognitive Development study. Our analysis revealed patterns of functional connectivity correlated with cognitive control capacity and psychopathology. In particular, we identified a principal connectome-based latent brain variate that was positively correlated with cognitive measures across domains and negatively correlated with parent-reported psychopathology across diagnoses and domains. Functional connectivity loadings of the brain variate were across distributed cortical and subcortical brain networks and showed a dose-dependent relationship with the cumulative number of current psychiatric disorders in present. These findings provide preliminary evidence for a connectome-based biomarker that underlies individual differences in cognitive function and predicts transdiagnostic psychopathology in a dose-dependent fashion. pointing to a dose-response relationship. Our findings provide preliminary support that this connectome-based brain measure could represent a resiliency biomarker for protection against transdiagnostic psychopathology during preadolescence. vulnerability in preadolescents. That the brain variate exhibits a dose-response relationship with cumulative number of current suggests potential clinical applicability as a diagnostic-severity staging biomarker, exploration. our findings require cautious interpretation until out of sample validation and prospective testing is performed, they provide early support for the latent connectome-based brain variate being a candidate biomarker indexing individual differences in risk for transdiagnostic psychopathology and cognition in preadolescents.
Placing the 2012–2015 California‐Nevada drought into a paleoclimatic context: Insights from Walker Lake, California‐Nevada, USA

Assessing regional hydrologic responses to past climate changes can offer a guide for how water resources might respond to ongoing and future climate change. Here we employed a coupled water balance and lake evaporation model to examine Walker Lake behaviors during the Medieval Climate Anomaly (MCA), a time of documented hydroclimatic extremes. Together, a 14C‐based shoreline elevation chronology, submerged subfossil tree stumps in the West Walker River, and regional paleoproxy evidence indicate a ~50 year pluvial episode that bridged two 140+ year droughts. We developed estimates of MCA climates to examine the transient lake behavior and evaluate watershed responses to climate change. Our findings suggest the importance of decadal climate persistence to elicit large lake‐level fluctuations. We also simulated the current 2012–2015 California‐Nevada drought and found that the current drought exceeds MCA droughts in mean severity but not duration.
Constraining climate forecasts: The role of prior assumptions

Any attempt to estimate climate sensitivity using observations requires a set of models or model‐versions that simultaneously predict both climate sensitivity and some observable quantity(‐ies) given a range of values of unknown climate system properties, represented by choices of parameters, subsystems or even entire models. The choices researchers make with respect to these unknown properties play a crucial role in conditioning their climate forecasts. We show that any probabilistic estimate of climate sensitivity, and hence of the risk that a given greenhouse gas stabilisation level might result in a “dangerous” equilibrium warming, is critically dependent on subjective prior assumptions of the investigators, not simply on constraints provided by actual climate observations. This apparent arbitrariness can be resolved by focussing on the intended purpose of the forecast: while uncertainty in long‐term equilibrium warming remains high, an objectively determined 10–90% (5–95%) range of uncertainty in climate sensitivity that is relevant to forecasts of 21st century transient warming under nearly all current emission scenarios is 1.4–4.1°C with a median of 2.4°C, in good agreement with the “traditional” range.
Fast and accurate three‐dimensional controlled source electromagnetic modelling †

We present a fast approximate method for three‐dimensional low frequency controlled source electro‐magnetic modeling. We apply the method to a synthetic model in a typical marine controlled source electromagnetic scenario, where conductivity and permittivity are different from the known background medium. For 3D configurations, fast computational methods are relevant for both forward and inverse modelling studies. Since this problem involves a large number of unknowns, it has to be solved efficiently to obtain results in a timely manner, without compromising accuracy. For this reason, the Born approximation, extended Born approximation and iterative extended Born approximation are implemented and compared with the full solution of the conjugate gradient fast Fourier transformation method. These methods are based on an electric field domain integral equation formulation. It is shown here how well the iterative extended Born approximation method performs in terms of both accuracy and speed with different configurations and different source positions. The improved accuracy comes at virtually no additional computational cost. With the help of this method, it is now possible to perform sensitivity analysis using 3D modelling in a timely manner, which is vital for controlled source electromagnetic applications. For forward modeling the solution at the sea‐bottom is of interest, because that is where the receivers are usually located. For inverse modeling, the accuracy of the solution in the target zone is important to obtain reasonably accurate conductivity values from the inversion using this approximate solution method. Our modelling studies show that the iterative extended Born approximation method is fast and accurate for both forward and inverse modelling. Sensitivity analysis as a function of the source position and different reservoir sizes validate the accuracy of the iterative extended Born approximation.
Enhancing Cyber-Physical Resiliency of Power Grids under IoT-Enabled Dynamic Botnet Attacks

The wide adoption of Internet of Things (IoT)enabled energy devices improves the quality of life, but simultaneously, it enlarges the attack surface of the power grid system. The adversary can gain illegitimate control of a large number of these devices and use them as a mean to compromise the physical grid operation, a mechanism known as the IoT botnet attack. This paper aims to improve the resiliency of cyberphysical power grids to such attacks. Specifically, we use an epidemic model to understand the dynamic botnet formation which facilitates the assessment of cyber layer vulnerability of the grid. The attacker aims to exploit this vulnerability to enable a successful physical compromise, while the system operator’s goal is to ensure a normal operation of the grid by mitigating cyber risks. We develop an optimization framework for effective defense design that enhances cyber-physical grid resiliency by considering strategic attack behaviors. Case studies are used to corroborate the devised approach
Micro air vehicle trajectory generation in pitch plane

For autonomous operations, unmanned micro air vehicles depend on novel trajectory generation schemes. Trajectories parallel to the ground are fairly well understood in surveillance and reconnaissance contexts. In addition, trajectories with altitude as one of the navigational parameters are also envisioned for aerial robots, urban terrain coverage, etc. In these missions, trajectory generation in pitch plane becomes an important problem. In this article, a linear algebraic procedure is applied to generate the pitch plane trajectories. That is, when a terrain (latitude, longitude and altitude) is sensed from a global positioning system, a trajectory to navigate the aircraft along the terrain is presented. By linear algebra, the state vector is spanned using a set of known vectors and some of their scalars (coefficients of spanning vectors) are solved in an optimization framework so that the state variables mapping the desired terrain are determined. After the trajectories are generated, normally smoothening is recommended so that the trajectories are continuous for autonomous control development. Thus, an extended Kalman filter is applied to smooth the trajectories. A nonlinear micro air vehicle model is considered to illustrate the trajectory generation and smoothening scheme.
Forecasting river flow rate during low‐flow periods using neural networks

The pollution in the river Arno downstream of the city of Florence is a severe environmental problem during low‐flow periods when the river flow rate is insufficient to support the natural waste assimilation mechanisms which include degradation, transport, and mixing. Forecasting the river flow rate during these low‐flow periods is crucial for water quality management. In this paper a neural network model is presented for forecasting river flow for up to 6 days. The model uses basin‐averaged rainfall measurements, water level, and hydropower production data. It is necessary to use hydropower production data since during low‐flow periods the water discharged into the river from reservoirs can be a major fraction of total flow rate. Model predictions were found to be accurate with root‐mean‐square error on the predicted river flow rate less then 8% over the entire time horizon of prediction. This model will be useful for managing the water quality in the river when employed with river quality models.
Assessing Soil Microbial Community Composition Across Landscapes: Do Surface Soils Reveal Patterns?

This manuscript has been created by the Univ. of Chicago as operator of Argonne National Lab. under Contract no. W-31-109-ENG-38 with the U.S. Dep. of Energy. The U.S. government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the government.Soil Sci. Soc. Am. J. 71:730–734doi:10.2136/sssaj2006.0301NReceived 27 Aug. 2006. *Corresponding author (allisonv@landcareresearch.co.nz). © Soil Science Society of America677 S. Segoe Rd. Madison WI 53711 USAAll rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.Abbreviations: gs, growing season; PCA, principle components analysis; PLFA, phospholipid fatty acid.
First mesopause temperature profiles from a fixed southern hemisphere site

The INPE sodium lidar was recently modified so as to enable measurements to be made of the Doppler temperature of the Na atoms in the atmospheric sodium layer. Measurements have been made on a total of 15 nights from July to October, 1998, providing temperature profiles between heights of about 83 and 105 km. Almost all measurements showed a mesopause temperature structure strongly perturbed by oscillations which appear to be caused by gravity waves and/or tides, with peaks in sodium density occurring at almost the same height as the temperature maxima on the bottom side of the sodium layer. The lowest temperatures, between 170 and 200 K, typically occur above 100 km, and the average profile for all our measurements is similar to the winter profile seen at mid‐latitudes, with a mesopause temperature of 190 K at 103 km.
Revised magnetostratigraphy and characteristics of the fluviolacustrine sedimentation of the Kashmir basin, India, during Pliocene‐Pleistocene

[1] The Pliocene-Pleistocene Karewa Group sediments of the Kashmir basin, India, provide an important continental archive for past climatic reconstruction. The present study reevaluates the magnetic polarity stratigraphy and the nature of the depositional environment at a 440-m-thick section along Romushi river near Pakharpur (33°48′50″N, 74°45′54″E). Magnetic remanences are predominantly carried by Ti-rich titanomagnetite and magnetite. We identified eight normal and eight reversed-polarity magnetozones in this succession, ranging between 4.40 and 0.77 Ma. The polarity sequence includes the new identification of the Cochiti and the Mammoth and their preceding and succeeding reversed/normal as well as the Jaramillo subchrons. Anisotropy of magnetic susceptibility data suggest the existence of northeast- and northwest-flowing fluvial system before 4.18 Ma, indicating the Pir Panjal range at the southwest as the sediment source area. Following this, the valley was under the influence of fluviolacustrine environment between 4.18 and 0.77 Ma. Our results suggest relatively strong flow velocity toward the northeast during the upper Gilbert, Gauss, and lower and middle Matuyama chrons (4.18–1.07 Ma). In the upper Matuyama chron (<1.07 Ma), the prevailing paleocurrent direction in the basin changed toward the northwest with a reduced flow velocity, indicating the emergence of the ancestral Jhelum river. On the basis of the magnetic polarity chronology, the sediment accumulation rate indicates a very low value of ∼4.6 cm kyr−1 before 1.95 Ma to ∼33 cm kyr−1 between 1.95 and 1.77 Ma and 23 cm kyr−1 after 1.77 Ma. We attribute temporal changes in sedimentation rate to the interplay between climate (predominantly westerlies) and tectonics (pulsating Pir Panjal uplift).
Finding Robust Solutions for Many-Objective Optimization Using NSGA-III

The primary task of evolutionary multi-objective optimization (EMO) is to find the globally best Pareto-optimal front. However, often decision makers (DMs) are not interested in obtaining the global frontier. Instead, they prefer a set of solutions for which there is no significant change in objective values within a small neighborhood of each decision variable vector, resulting in a set of robust solutions. The corresponding objective vectors are said to lie on the robust front. In practical applications, such as in engineering designs, designers are interested in robust designs which are less sensitive to the perturbation in the design variables and parameters, caused by the manufacturing process tolerances, material non-uniformity, uncertainties in supply-chain process, and by many other practical matters. An earlier robust EMO study proposed two different robustness measures and used the elitist non-dominated sorting genetic algorithms (NSGA-II) to find respective robust fronts. However, the limitation of NSGA-II in generating well-distributed and diverse set solutions for many-objective optimization, the robust optimization concept must be extended with evolutionary many-objective optimization (EMaO) algorithms to investigate the efficacy in more than three-objective problems. This study proposes an extension of test problems for robust many-objective optimization tasks and demonstrates the performance of updated NSGA-III procedure to two to eight-objective test and real-world problems.