Miracle-dz/UniFAR-FTUs huggingface dataset:
A Quantitative Description of the Causes of Color in Corundum

GEMS & GEMOLOGY SPRING 2020 Gemstones are valued for their beauty, rarity, and durability, and what typically captures our attention is their magnificent array of colors. Corundum exhibits an extremely wide range of colors in nature (figure 1). From pigeon’s blood red ruby to cornflower blue and lemon yellow sapphire, nearly every color is represented. The only corundum color not represented in nature is a saturated intense emerald green. However, less intense olive green to teal green stones are often found in basalt-hosted corundum deposits. Corundum’s broad range of colors is related to its detailed chemistry. Some minerals possess inherent color because the chromophore is one of the basic chemical components of its makeup. Such stones are termed idiochromatic, meaning self-colored. For example, turquoise, whose chemical formula is CuAl6(PO4)4(OH)8•4H2O, is colored by copper, a primary component of its structure. Other minerals such as corundum are, when very pure, completely colorless. In fact, pure corundum, with the chemical formula Al2O3, is absolutely transparent from the deep ultraviolet region into the infrared. Such minerals are termed allochromatic. Their colors in nature are caused by minor impurities, referred to as trace elements, or other point defects in the crystal lattice that have been incorporated during growth or later equilibration in nature. The causes of color in corundum are many and have been primarily addressed in a non-quantitative way for many years (see, for example, Fritsch and Rossman, 1987, 1988; Häger, 2001; Emmett et al., 2003). Trace elements themselves can be the direct cause of color. Cr3+, for example, creates pink and red coloration in corundum. Trace elements can also interact with each other, creating a new chromophore. The Fe2+-Ti4+ pair is such an example, strongly absorbing in the yellow and red regions of the spectrum and thus creating magnificent blue sapphires. When beryllium-diffused corundum entered the marketplace, we were surprised by the wide range of colors that were produced, seemingly by a single element (Emmett et al., 2003). Measurements of the beryllium levels showed that the concentrations were generally from a few to a few tens of parts per million atomic (ppma), yet the colors produced were often intense. For comparison, red coloration in corundum requires several hundred to a few thousand ppma of Cr3+, a concentration at least two orders of magnitude greater than Be2+, to produce strong color. Our studies of the beryllium-diffused stones (Emmett et al., 2003) demonstrated that the Be2+ ion itself was not the cause of color. However, replacing a trivalent aluminum ion with a divalent beryllium ion required the creation of a trapped hole (h•) for A QUANTITATIVE DESCRIPTION OF THE CAUSES OF COLOR IN CORUNDUM
CONSTRAINED DIFFERENTIAL INCLUSIONS WITH NONLOCAL INITIAL CONDITIONS

We show existence for the perturbed sweeping process with nonlocal initial conditions under very general hypotheses. Periodic, antiperiodic, mean value and multipoints conditions are included in this study. We give abstract results for differential inclusions with nonlocal initial conditions through bounding functions and tangential conditions. Some applications to differential complementarity systems and to vector hysteresis are given.
Citlalmitl: A Laser-based Device for Meteoritical Sample Fabrication with Arbitrary Thermal Histories

We present Citlalmitl (the word for meteorite in the Nahuatl language), a new experimental device designed and built to simulate high-temperature processes relevant for meteoritics, including chondrule formation and the atmospheric entry of micrometeorites (MMs). The main component of Citlalmitl is a 50 W CO2 laser, used to melt samples that simulate the precursors of meteoritical materials. As examples of the operation of our device, we have irradiated silicate samples controlling the laser duty cycle to reproduce heating profiles predicted by shock-wave simulations. Citlalmitl records the sample temperature during and after irradiation, a unique feature that allows us to directly measure the thermal history of the sample, a key parameter for the characteristics observed in MMs and chondrules. We demonstrate that Citlalmitl can reproduce different heating profiles useful to mimic thermal histories in meteoritical processes.
Registration Algorithm Based on Fuzzy Shape Context and Local Vector Similarity Constraint

Non-rigid point set registration is an essential research in pattern recognition. Two main contributions are presented based on the current popular non-rigid point set registration algorithm in this paper: 1) Fuzzy shape context feature 2) Local spatial vector similarity constraints based on local vector feature. The correspondence of complementary of features is evaluated, ﬁrstly. At the same time, a fuzzy shape context (FSC) feature is deﬁned and the Gaussian mixture model based on the fuzzy shape context distance and the global feature distance is designed. The spatial transformation of complementary of constraint is updated, secondly. Meanwhile, a local vector feature is deﬁned and the local spatial vector similarity constraint based on local vector feature is built. The proposed algorithm estimates correspondence by using the Gaussian mixture model of complementary of feature. The proposed algorithm updates parameters of transformation by using the expectation maximization algorithm, and completes transformation updating by building energy function that has local spatial vector similarity constraints. Firstly, the retrieval rate of FSC is tested. The performance of point set registration and image registration of the proposed algorithm was tested by using public data sets, secondly. In the comparison experiments of currently popular 10 algorithms, accurate registration results of the proposed algorithm where acquired, and surpassed the popular algorithms in most of the registration precision.
A Novel RLWE-Based Anonymous Mutual Authentication Protocol for Space Information Network

Currently, space information network (SIN) has become an increasingly important role in real life. As a large heterogeneous wireless network, SIN can better provide global mobile services to users anytime and anywhere, even in extreme geographic environments. In addition, there is no need to build the communication base-stations every few kilometers on the ground to ensure high service quality, which greatly reduces the construction costs and can be used as an economical communication method in sparsely populated areas. So there is a trend that more and more end users are more likely to get SIN services than traditional terrestrial cellular networks. However, due to the openness and publicity of the satellite wireless channel and the limited resources of the satellite nodes, the privacy and security cannot be perfectly guaranteed and may even be vulnerable to attacks initiated by the adversary such as replay attacks, impersonation attacks, and eavesdropping attacks. To improve the access security of SIN, researchers have proposed a series of authentication protocols based on different cryptographic assumptions. Nevertheless, existing research shows that these protocols cannot meet the requirements of higher and higher security and short authentication delay. In addition, these protocols are mainly based on public key cryptography mechanisms such as DLP and ECDLP, which can be solved by postquantum computers in polynomial time, so these protocols will no longer be secure. To solve the vulnerability of these protocols, in this paper, we propose a new RLWE-based anonymous mutual authentication and key agreement protocol, which guarantees higher security with low computational overhead even in the postquantum era. Detailed security analysis shows that our protocol meets security requirements and is resistant to a variety of known attacks. Besides, combining security comparison and performance analysis, our proposed protocol is more practical than other protocols in SIN.
PARAOPT: A PARAREAL ALGORITHM FOR OPTIMALITY

The time parallel solution of optimality systems arising in PDE constrained opti-4 mization could be achieved by simply applying any time parallel algorithm, such as Parareal, to solve 5 the forward and backward evolution problems arising in the optimization loop. We propose here a 6 diﬀerent strategy by devising directly a new time parallel algorithm, which we call ParaOpt, for the 7 coupled forward and backward non-linear partial diﬀerential equations. ParaOpt is inspired by the 8 Parareal algorithm for evolution equations, and thus is automatically a two-level method. We pro-9 vide a detailed convergence analysis for the case of linear parabolic PDE constraints. We illustrate 10 the performance of ParaOpt with numerical experiments both for linear and nonlinear optimality 11 systems.
Impacts of Agricultural Technology Adoption in Bolivia

This paper presents the results of an impact evaluation for the CRIAR program, implemented in rural areas in Bolivia. The objective of this program is to increase the agricultural income and food security of smallholder farmers through productivity gains that result from technological adoption. We use data obtained from a sample of 1,287 households-817 beneficiaries and 470 controlsinterviewed specifically for this evaluation, and rely on a methodology of Propensity Score Matching. Overall, the main impacts of the program are observed in shortand medium-term variables, including crop diversification, input use and expenditures, and variables related to sales and home consumption. For the medium-term variables, the program had a positive impact on sales at the farm gate, market sales, agricultural income from sales, and a decrease in the proportion of production allocated for home consumption. The program also had a significant and positive impact on the food security of beneficiary households. For the long-term indicators, the analysis did not identify significant impacts on productivity variables. The lack of productivity impacts is probably due to the short period after program implementation, which corresponds to only one agricultural cycle. This length of time may have not been sufficient for farmers to gain experience and knowledge with regards to their effective use of the newly acquired technologies or to adjust the production process through input changes.
Tree structures in Poisson series processors

Much of the work concerned with the application of perturbation theories in celestial mechanics, and particularly in the development of analytical theories of the motion of celestial bodies, can be reduced to algebraic operations on Poisson series. The aim of this contribution is to make a review on the use of tree structures for the storage of Poisson series. We analyse a type of structure based on maps, as well as its representation in the form of red–black tree. We also compare the complexity of some fundamental algorithms in their corresponding computer implementation as lists and red–black trees.
"Compressive optical deflectometric tomography: a constrained total-variation approach"

Optical Deflectometric Tomography (ODT) provides an accurate characterization of transparent materials whose complex surfaces present a real challenge for manufacture and control. In ODT, the refractive index map (RIM) of a transparent object is reconstructed by measuring light deflection under multiple orientations. We show that this imaging modality can be made compressive, i.e., a correct RIM reconstruction is achievable with far less observations than required by traditional minimum energy (ME) or Filtered Back Projection (FBP) methods. Assuming a cartoon-shape RIM model, this reconstruction is driven by minimizing the map Total-Variation under a fidelity constraint with the available observations. Moreover, two other realistic assumptions are added to improve the stability of our approach: the map positivity and a frontier condition. Numerically, our method relies on an accurate ODT sensing model and on a primal-dual minimization scheme, including easily the sensing operator and the proposed RIM constraints. We conclude this paper by demonstrating the power of our method on synthetic and experimental data under various compressive scenarios. In particular, the potential compressiveness of the stabilized ODT problem is demonstrated by observing a typical gain of 24dB compared to ME and of 30dB compared to FBP at only 5% of 360 incident light angles for moderately noisy sensing.
Clustering Utilization for Coverage Improvement in Wireless Border Surveillance Networks

: - In many border surveillance applications (such as military, homeland security, etc.), the wireless sensor networks cannot be deployed manually and the barrier coverage breaks can appear along a given surveillance line. This paper introduces a cluster-based algorithm and new metrics to determining the number and the positions of the additional nodes needed to be deployed by drones, robots, or moved in a network; in order to fill the gaps in a randomly deployed network. Simulation results show that the proposed algorithm optimizes the number of additional nodes and outperforms the alternative in 52,15% of cases while it performs similarly in the rest of the cases. The machine learning classification algorithms are used to show that the decision on choosing one or another algorithm is highly classifiable. Precisely, the proposed algorithm is shown to be the approach of choice in implementations where the sensing range is relatively small.
Interactive comment on “Joint Analysis of Convective Structure from the APR-2 Precipitation Radar and the DAWN Doppler Wind Lidar During the 2017 Convective Processes Experiment (CPEX)” by F. Joseph Turk

The mechanisms linking convection and cloud dynamical processes is a major factor in much of the uncertainty in both weather and climate prediction. Further constraining the uncertainty in convective cloud processes linking 3-D air motion and cloud structure through models and observations is vital for improvements in weather forecasting, and understanding limits on atmospheric predictability. To date, there have been relatively few airborne observations specifically targeted for linking the 3-D air motion surrounding developing clouds to the subsequent development (or non15 development) of convective precipitation. During the May-June 2017 Convective Processes Experiment (CPEX), NASA DC-8-based airborne observations were collected from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2-um Doppler Aerosol Wind (DAWN) lidar during approximately 100 flight hours. For CPEX, the APR-2 provided vertical air motion and structure of the cloud systems in nearby precipitating regions where DAWN is unable to sense. Conversely, DAWN sampled vertical wind profiles in aerosol-rich regions surrounding the convection, but is unable to sense the wind 20 field structure within most clouds. In this manuscript, the complementary nature of these data are presented from the June 10-11 flight dates, including the APR-2 precipitation structure and Doppler wind fields, and adjacent wind profiles from the DAWN data.
Determination of Amount of Theoretical Zones and Feed Location in Multicomponent Distillation

Determination of tray location in multicomponent distillation is important for the designing of a distillation columns because it determines the vapour liquid flow rate, components purity, reflux ratio among other important parameters. This information is often calculated using theoretical methods taking into consideration initial conditions at the feed and final product concentration rather than experimental. In the present article, we analyze the case of multicomponent distillation in which a feed of 100 mol/h are added to a fractionating tower at the boiling point and 405.3 kPa pressure. The system consists of a mixture of CC4HH10, CC5HH12, CC6HH12 and CC7HH14. We aim to determine the characterization of light and heavy phase, component distribution, tower temperature, particularly at top and bottom. Accordingly, we approach the use of approximate methods to determine the minimum reflux ratio, amount of theoretical zones and feed location. Key-Words: multicomponent distillation, process design, minimum reflux ratio, approximate method, algorithm design, Underwood method, equilibrium stages
Combined inner and outer loop feedback in an intelligent tutoring system for statistics in higher education

Intelligent tutoring systems (ITSs) can provide inner loop feedback about steps within tasks, and outer loop feedback about performance on multiple tasks. While research typically addresses these feedback types separately, many ITSs offer them simultaneously. This study evaluates the effects of providing combined inner and outer loop feedback on social sciences students' learning process and performance in a first-year university statistics course. In a 2 x 2 factorial design (elaborate inner loop vs. minimal inner loop and outer loop vs. no outer loop feedback) with 521 participants, the effects of both feedback types and their combination were assessed through multiple linear regression models. Results showed mixed effects, depending on students' prior knowledge and experience, and no overall effects on course performance. Students tended to use outer loop feed-back less when also receiving elaborate inner loop feedback. We therefore recommend introducing feedback types one by one and offering them for substantial periods of time.
The Lightning Jump, the 2018 ”Picking up Hailstones” Campaign and a Climatological Analysis for Catalonia for the 2006-2018 Period

Previous analysis in Catalonia (NE Iberian Peninsula) demonstrated the high correlation between Lightning Jump (LJ) algorithm warnings and the occurrence of severe weather. The algorithm was put into operations in the Servei Meteorològic de Catalunya (SMC) (Meteorological Service of Catalonia) in 2016, exclusively considering lightning data. We found that more than 80% of the alerts were associated with at least one severe weather register in the area of study. This percentage could be even higher because of the lack of observations in some events that occurred in low-density population areas or at night. To collect surface registers that improve the information associated with the phenomena that occurred in severe thunderstorms in 2017, we started a citizen campaign (called ”Plega la pedra”, translated as ”Picking up Hailstones” using social networks (mainly, twitter -#meteocatpedraand a WhatsApp channel). Thanks to the high contribution of the citizen campaign, the number of registers were higher than the average in comparable situations for previous years. The first part of this paper shows how it is functioning in the SMC, and the campaign results reported during 2018. The second part of the analysis consisted of a complete climatological study of its behavior in Catalonia, based on 13 years of data related to LJ alerts available. The study considered some characteristics such as the lead time, or the spatial, the monthly and yearly distributions. These features were compared and matched to severe weather observations recorded during this period in the same area. This analysis can help us to better understand the thunderstorms which triggered the warnings and the relationship between the alert and the severe weather observations on the surface.
Forecasting inflation for India with the Phillips Curve: Evidence from internet search data

This paper forecasts inflation based on the New Keynesian Phillips curve for India using internet search-based inflation expectations. We find that compared to inflation forecasts based on traditional time-series estimation method like AR(1) or household-survey based inflation expectations, our model that employs inflation expectations of agents based on real time inflation-related internet search, has better inflation forecasting performance. From a policy standpoint, this underscores the importance of analysing big data for the purpose of forecasting inflation.
PEER INFLUENCE ON ETHNIC-RACIAL IDENTITY

The peer context features prominently in theory, and incr easingly in empirical research, regarding ethnic-racial identity (ERI) development, but no studies have assessed pee r network influence on ERI. We examined peer influence on ERI centrality, private and public regard using longitudinal social network analysis. Data were drawn from two sites: a predominantly Latina/o Southwestern (SW) school ( N = 1034; Mage = 12.10) and a diverse Midwestern (MW) school (N = 513; Mage = 11.99). Findings showed that peers influenced youths’ public regard over time at both sites. However, peer influence on centrality was evident in the SW site, whereas peer influence on private regard was evident in he MW site. Importantly, peer influence was ev id nt after controlling for selection effects.
The Response of a Transformer Differential Relay to Internal Faults While Influenced by Geomagnetically Induced Currents

When influenced by quasi-dc ground currents, the magnetization characteristics of wye-connected transformers produce second harmonics that may approach or surpass secondharmonic levels commonly experienced during transformer inrush events. Transformer protection typically incorporates harmonic blocking and/or harmonic restraint to prevent the relay from operating during these inrush events. Newer relays also use waveshape recognition. In this paper, we discuss a saturable transformer model simulation composed to create a matrix of tests that varied the magnitude of transformer internal fault current and the magnitude of quasi-dc ground current. We applied test currents on two transformer differential relay designs. One set of test currents was to validate that the relays remain secure for geomagnetically induced current (GIC) saturation, and the other to compare how the relays perform for internal faults with varying amounts of fault resistance and increasing levels of GIC. We explore cross-harmonic blocking and harmonic restraint as variables and evaluate the relationship of the pickup levels for the operate/restraint curve. We include recommendations for possible mitigation techniques.
Bessel Smoothing and Multi-Distribution Property Estimation

We consider a basic problem in statistical learning: estimating properties of multiple discrete distributions. Denoting by ∆k the standard simplex over [k] := {0, 1, . , k}, a property of d distributions is a mapping from ∆k to R. These properties include well-known distribution characteristics such as Shannon entropy and support size (d = 1), and many important divergence measures between distributions (d = 2). The primary problem being considered is to learn the property value of an unknown d-tuple of distributions from its sample. The study of such problems dates back to the works of Good (1953); Carlton (1969); Efron and Thisted (1976); Thisted and Efron (1987), and has been pushed forward steadily during the past decades. Surprisingly, before our work, the general landscape of this fundamental learning problem was insufficiently understood, and nearly all the existing results are for the special case d ≤ 2. Our first main result provides a near-linear-time computable algorithm that, given independent samples from any collection of distributions and for a broad class of multi-distribution properties, learns the property as well as the empirical plug-in estimator that uses samples with logarithmicfactor larger sizes. As a corollary of this, for any ε > 0 and fixed d ∈ Z, a d-distribution property over [k] that is Lipschitz and additively separable can be learned to an accuracy of ε using a sample of sizeO(k/(ε √ log k)), with high probability. Our second result addresses a closely related problem – tolerant independence testing: One receives samples from the unknown joint and marginal distributions, and attempts to infer the `1 distance between the joint distribution and the product distribution of the marginals. We show that this testing problem also admits a sample complexity sub-linear in the alphabet sizes, demonstrating the broad applicability of our approach.