Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrogeochemical response of acid-producing mine spoil aquifer to induced alkaline recharge

An experiment involving in situ neutralization of acidic ground water was performed on a mine-spoil aquifer in central West Virginia. The 45-acre aquifer was subjected to infiltration of lime slurry through a sludge pond located near the center of the mine. Ground-water and spring-water samples collected before lime infiltration indicate that a localized zone of neutralized ground water (pH 7) existed close to the sludge pond prior to the experiment. Concentrations of elevated sodium, pH and alkalinity correlate with the extent of neutralized ground water. This alkalinity is attributed to infiltration of sodium hydroxide-treated sludge, pumped into the sludge pond from treatment ponds prior to the experiment. Despite infiltration of the lime slurry during the experiment, the spatial extent of aquifer neutralization did not increase within the timeframe of this study. Ground-water chemistry (pH, alkalinity, and calcium) indicates that lime slurry is actively converted to calcite following recharge. A steady-state ground-water flow model using MODFLOW was calibrated based on field measurements of aquifer head and discharge. Advective transport of ground-water flow from recharge to discharge areas was simulated by particle-tracking methods. Results show that alkalinity introduced as recharge through the sludge pond should eventually contribute to the neutralization of three springs approximately 1300 feet from the basin. Simulations also show that two springs closer to the sludge pond (500 feet) are predominantly fed by acidic ground water upgradient of the sludge pond. Binary mixing models developed with the geochemical program PHREEQC simulated reactions for mixing of alkaline sludge with acid water. Results show decreases in aluminum concentration above pH 5.5 caused by Al(OH)3(a) precipitation. Concentrations of dissolved iron decrease above pH 5.4, consistent with precipitation of iron hydroxide. Ground-water samples were characterized by elevated partial pressure of carbon dioxide (pCO2(g) = 10-1.0 atm), suggesting the aquifer may be modeled as a closed system with respect to atmospheric pCO2(g) (10-3.5 atm). A coupled flow and geochemical reaction model was developed to simulate both acid-producing and acid-neutralizing reactions along ground-water flow. Based on results from the steady-state MODFLOW model, mass balances for solutes were calculated through a series of 12 successive cells within a "flow channel" extending from the sludge pond to a spring. Reactions controlling solute concentrations along flow include pyrite oxidation, iron and aluminum hydroxide precipitation, clay mineral buffering, and dolomite dissolution.
SHREC 2011: robust feature detection and description benchmark

Feature-based approaches have recently become very popular in computer vision and image analysis applications, and are becoming a promising direction in shape retrieval. SHREC'11 robust feature detection and description benchmark simulates the feature detection and description stages of feature-based shape retrieval algorithms. The benchmark tests the performance of shape feature detectors and descriptors under a wide variety of transformations. The benchmark allows evaluating how algorithms cope with certain classes of transformations and strength of the transformations that can be dealt with. The present paper is a report of the SHREC'11 robust feature detection and description benchmark results
Cold Sintering - A New Powder Consolidation Process.

Abstract : The plastic deformation of powder particles in a high pressure gradient at ambient temperature results in green densities close to theoretical. Physical contact of freshly formed oxide-free surfaces leads to strong particle-particle bonding; this phenomenon is called cold sintering. High strength levels can be obtained in metals, alloys, composites, ionic and ionic-covalent solids by cold sintering. Subsequent heat treatment of cold sintered material, at temperatures significantly lower than those used in conventional sintering, results in excellent combinations of strength and ductility. Thus, cold sintering offers the potential for retaining metastable constituents, fine-scale microstructures and small precipitates in rapidly solidified powders. Interface reactions or dissolution of phases in metal matrix composites can also be reduced or eliminated. Details of the compacting response, microstructure and mechanical properties of cold sintered and heat treated high speed tool steel and super-alloy powders are presented. Cold sintering characteristics are understood in terms of the interplay of particle shape and particle deformation. Possible cold sintering processing routes of commercial interest are discussed and the limitations of this new technology considered. (Author)
Towards Conditional Independence Test for Relational Data

Conditional independence (CI) tests play a central role in statistical inference, machine learning, and causal discovery. Most existing CI tests assume that the samples are independently and identically distributed (i.i.d.). However, this assumption often does not hold in the case of relational data . We deﬁne Relational Conditional Independence (RCI), a generalization of CI to the relational setting. We show how, under a set of structural assumptions, we can test for RCI by reducing the task of testing for RCI on non-i.i. d. data to the problem of testing for CI on several data sets each of which consists of i.i. d. samples. We develop Kernel Relational CI test (KRCIT), a nonparametric test as a practical approach to testing for RCI by relaxing the structural assumptions used in our analysis of RCI. We describe re-sults of experiments with synthetic relational data that show the beneﬁts of KRCIT relative to traditional CI tests that don’t account for the non-i.i. d. nature of relational data.
Agent-based Simulation of Alliance Formation and its Stability Analysis: Application to Aviation Industry

The purpose of this paper is two -fold: The first is to develop an agent -based simulation model for simulating alliance formation processes of the business world, and to analyze stability of alliance structures generated by it. The second purpose is to apply the simulation model to the civil aviation industry for validating it as well as for obtaining insightful and unique findings about the industry. As the results, we find the alliances in the industry are basically formed for network connectivity rather than management complementarities. Wealso suggest possibility that American Airlines and British Airways may may get separated.
Soil Response During the 1988 Armenia Earthquake

Synopsis: Building damage statistics from the 1988 Armenia earthquake are presented and discussed. These statistics are correlated to the local soil profiles in the two major cities of Leninakan and Kirovakan. The soil amplification effects on building damage during this earthquake are investigated. One-dimensional site response analysis results and valley effects are presented to explain the extent and pattern of damage in the two cities.
Home Blood Pressure Monitoring in Heart Transplant Recipients: Comparison with Ambulatory Blood Pressure Monitoring

Background How reliable is home blood pressure monitoring (HBPM) in heart transplant recipients is not known. Possibly, it may underestimate hypertensive burden, because blood pressure (BP) nondipper profile is frequent among these patients. This prospective study has been designed to determine whether HBPM adequately identifies hypertension in heart transplant recipients. Method We compared HBPM with ambulatory blood pressure monitoring (ABPM) for the diagnosis of uncontrolled hypertension in 74 patients 13.5±6.7 years after heart transplantation. HBPM was measured with a validated semiautomatic device twice every morning and twice every evening on 7 consecutive days, within 15 days of ABPM. We also measured the relationship between HBPM, ABPM, and organ damage as measured by albuminuria and left ventricular mass. Results A nondipper profile was found in 53 (72%) patients. HBPM and ABPM were close according to Pearson bivariate correlations. There was no significant correlation between left ventricular mass and BP either at HBPM or ABPM. Proteinuria significantly correlated with systolic BP either at HBPM (R=0.42; P=0.0002) or ABPM (R=0.25; P=0.03). HBPM adequately classified 61 of 74 (82%) patients as hypertensives or as nonhypertensives or controlled hypertensives. Conclusion Despite a high prevalence of nondipper profile, HBPM gives a reliable estimate of BP burden in most heart transplant recipients. Thus, our results strongly suggest that HBPM is useful for the long-term follow-up of heart transplant recipients.
A voxel-based morphometric study of age- and sex-related changes in white matter volume in the normal aging brain

Objective To carry out a cross-sectional study of 187 cognitively normal Chinese adults using the voxel-based morphometry (VBM) approach to delineate age-related changes in the white matter volume of regions of interest in the brain and further analyze their correlation with age. Materials and methods A total of 187 cognitively normal adults were divided into the young, middle, and old age-groups. Conventional magnetic resonance imaging was performed with the Achieva 3.0 T system. Structural images were processed using VBM8 and statistical parametric mapping 8. Regions of interest were obtained by WFU PickAtlas, and all realigned images were spatially normalized. Results Females showed significantly greater total white matter volume than males (t=2.36, P=0.0096, false-discovery rate [FDR] corrected). VBM demonstrated statistically significant age-related differences in white matter volume between the young age-group and the middle age-group (P<0.05, FDR corrected) and between the middle age-group and the old age-group (P<0.05, FDR corrected). No interaction was found between age and sex on white matter volume (P<0.05, FDR corrected). Logistic regression analysis revealed nonlinear correlation between total white matter volume and age (R2=0.124, P<0.001). White matter volume gradually increased before 40 years of age, peaked around 50 years of age, and rapidly declined after 60 years of age. Conclusion Significant age-related differences are present in white matter volume across multiple brain regions during aging. The VBM approach may help differentiate underlying normal neurobiological aging changes of specific brain regions from neurodegenerative impairments.
Hamiltonian Monte Carlo Sampling for Bayesian Hierarchical Regression in Prognostics

Advances in computational speed have enabled the development of many Bayesian probabilistic models due to Markov-Chain-Monte-Carlo (MCMC) posterior sampling methods. These models includes Bayesian hierarchical regression methods, which use group level information to inform individual asset predictions. Hierarchical models are increasingly used for prognostics as they recognise that the parameter estimates for an individual asset may be rationally influenced by data from other similar assets. Larger and high dimensional datasets require more efficient sampling methods for calculations, than traditional MCMC techniques. Hamiltonian Monte Carlo (HMC) has been used across many fields to address high dimensional, sparse, or non-conjugate data. Due to the need to find the posterior derivative and the flexibility in the tuning parameters, HMC is often difficult to hand code. We investigate a probabilistic programming language, Stan, which allows the implementation of HMC sampling, with particular focus on Bayesian hierarchical models in prognostics. The benefits and limitations for HMC using Stan are explored and compared to the widely used Gibbs Sampler and Metropolis-Hastings (MH) algorithm. Results are demonstrated using three case studies on lithiumion batteries. Stan reduced coding complexity and sampled from posterior distributions more efficiently than parameters sampled with the Metropolis-Hastings algorithm. HMC sampling became less efficient with increasing data-size and hierarchical complexity, due to high curvature in the posterior distribution. Stan was shown to be a robust language which allows for easier inference to be made in the Bayesian paradigm.
Multiclass Molecular Classification

Molecular classification involves the classification of samples into groups of biological phenotypes. Studies on molecular classification generally focus on cancer for the following reason: Molecular classification of tumor samples from patients into different molecular types or subtypes is vital for diagnosis, prognosis, and effective treatment of cancer (Slonim, Tamayo, Mesirov, Golub, and Lander, 2000). Traditionally, such classification relies on observations regarding the location (Slonim et al., 2000) and microscopic appearance of the cancerous cells (Garber et al., 2001). These methods have proven to be slow and ineffective; there is no way of predicting with reliable accuracy the progress of the disease, since tumors of similar appearance have been known to take different paths in the course of time. With the advent of the microarray technology, data regarding the gene expression levels in each tumor sample may now prove to be a useful tool in molecular classification. This is because gene expression data provide snapshots of the activities within the cells and thus, the profile of the state of the cells in the tissue. The use of microarrays for gene expression profiling was first published in 1995 (Schena, Shalon, Davis, and Brown, 1995). In a typical microarray experiment, the expression levels of up to 10,000 or more genes are measured in each sample. The high-dimensionality of the data means that feature selection (FS) plays a crucial role in aiding the classification process by reducing the dimensionality of the input to the classification process. In the context of FS, the terms gene and feature will be used interchangeably in the context of gene expression data.
A case study on learning a steering controller from scratch with reinforcement learning

In this case study we show how reinforcement learning can be applied successfully for low level control tasks in autonomous driving like steering control as an alternative to controllers from classical control theory. We describe the learning procedure and compare the resulting control policies with a classical controller. The experiments are made both in simulation and on a real car and we discuss the case of driving forwards as well as of driving backwards.
Microplanning with Communicative Intentions: The SPUD System

The process of microplanning in natural language generation (NLG) encompasses a range of problems in which a generator must bridge underlying domain‐specific representations and general linguistic representations. These problems include constructing linguistic referring expressions to identify domain objects, selecting lexical items to express domain concepts, and using complex linguistic constructions to concisely convey related domain facts.
Rapid Application Development on Multi-processor Reconfigurable Systems

Considering the ability to perform multi-processor architecture systems on FPGA, partial reconfiguration is an opportunity to improve weak soft-core performances by specializing coprocessors according to context-dependent application needs. But at the application level, there is a need for straightforward programming models that allow applications to be easily mapped on an ad hoc architecture without tedious rewriting, while at the same time ensuring efficient production code. In this paper we describe two programming libraries XTask and XFunc, which are written in C and rely on a reconfigurable MPSoC architecture model (XPSoC) and on HW/SW libraries of standard functions that can be easily used by means of HW independent API. Finally, we demonstrate the XPSoC methodology, with the design of a self-adaptive image encoding system including runtime configuration decisions.
Partial-Information-Based Distributed Filtering in Two-Targets Tracking Sensor Networks

In this paper, the partial-information-based (PIB) distributed filtering problem is addressed for two-targets tracking sensor networks. Different from existing distributed filters, the information communication between the sensors are assumed to have an imperfect physical condition-only partial information can be transmitted. Furthermore, for different pairs of adjacent nodes, the partly transmitted information can be completely distinct. The constraint on “partial information transmission” makes the filtering problem in sensor networks more challenging and practical. Some criteria concerning the connection gains are derived and used to design efficient PIB distributed filter to achieve the following objectives: i) the sensor network can efficiently tract two desired targets in the absence of disturbance and noise; ii) the filter satisfies certain given performance constraint. By using the regrouping method, which is an effective way to derive the main results, some simple yet effective criteria are derived for PIB distributed filtering. A numerical example is utilized to illustrate the effectiveness of the theoretical results.
Twin signatures: an alternative to the hash-and-sign paradigm

This paper introduces a simple alternative to the hash-and-sign paradigm, from the security point of view but for signing short messages, called twinning. A twin signature is obtained by signing twice a short message by a signature scheme. Analysis of the concept in different settings yields the following results: We prove that no generic algorithm can efficiently forge a twin DSA signature. Although generic algorithms offer a less stringent form of security than computational reductions in the standard model, such successful proofs still produce positive evidence in favor of the correctness of the new paradigm.We prove in standard model an equivalence between the hardness of producing existential forgeries (even under adaptively chosen message attacks) of a twin version of a signature scheme proposed by Gennaro, Halevi and Rabin and the Flexible RSA Problem.We consequently regard twinning as an interesting alternative to hash functions for eradicating existential forgery in signature schemes.
Tables and trees don't mix (very well)

There are principal differences between the relational model and XML's tree model. This causes problems in all cases where information from these two worlds has to be brought together. Using a few rules for mapping the incompatible aspects of the two models, it becomes easier to process data in systems which need to work with relational and tree data. The most important requirement for a good mapping is that the conceptual model is available and can thus be used for making mapping decisions.
Determination of shear wave velocity and shear modulus estimation of peat soil using seismic geophysical method

This research is about dynamic characterization of peat using field seismic geophysical method. There are demands on dynamic characteristics in construction due to their importance towards the society. The dynamic behaviours of peat are shear velocity (Vs) and shear modulus (G). The scope of this research is meant for peat and soft clay by using multi-channel analysis of surface wave (MASW) method and seismic refraction method. The estimation of shear modulus is based on shear wave velocity and soil bulk density using the sampler with 0.5 m depth each. Peat sampler was used to verify the soil profiles at every location except for soft clay. The shear wave velocity for peat is ranging from 26.02 – 95.89 m/s. Meanwhile, for soft clay, it has velocity from 61.25 – 86.37 m/s. As for shear modulus of peats, the range is between 0.82 – 7.26 MPa while for soft clay, the range is between 7.29 MPa – 13.92 MPa. The variations of shear wave velocity and shear modulus of peat are due to the differences in peat soils properties in term of organic content, fibre content, void ratio and moisture content for every research location. Furthermore, seismic attenuation in peat is also affected the seismic wave velocity. The dynamic behaviour of peat and soft clay have slight changes in shear wave velocity. However it has significant difference in shear modulus due to the existence of organic content that contributes to their differences. Shear wave velocity was obtained by applying seismic refraction method. The data shows the increment of velocity with depth. The determination of dynamic behaviour of peats was achieved by using seismic geophysical method have shown good findings.
Sensitivity of tropical tropospheric composition to lightning NOx production as determined by replay simulations with GEOS‐5

The sensitivity of tropical tropospheric composition to the source strength of nitrogen oxides (NOx) produced by lightning (LNOx) is analyzed for September through November 2007 using the NASA GEOS‐5 model constrained by MERRA fields, with full GMI stratospheric‐tropospheric chemistry and an LNOx algorithm that is appropriate for use in a climate modeling setting; satellite retrievals from OMI, TES, and OMI/MLS; and in situ measurements from SHADOZ ozonesondes. Global mean LNOx production rates of 0 to 492 mol NO flash−1 and the subsequent responses of NOx, ozone (O3), hydroxyl radical (OH), nitric acid (HNO3), peroxyacetyl nitrate (PAN), and NOy (NOx + HNO3 + PAN) are investigated. The radiative implications associated with LNOx‐induced changes in tropospheric O3 are assessed. Increasing the LNOx production rate by a factor of 4 (from 123 to 492 mol flash−1) leads to tropical upper tropospheric enhancements of greater than 100% in NOx, OH, HNO3, and PAN. This increase in LNOx production also leads to O3 enhancements of up to 60%, which subsequently yields a factor‐of‐three increase in the mean net radiative flux at the tropopause. An LNOx source of 246 mol flash−1 agrees reasonably well with measurements, with an approximate factor‐of‐two uncertainty due to the short length of the study, inconsistencies in the observational data sets, and systematic biases in modeled LNOx production. Further research into the regional dependencies of lightning flash rates and LNOx production per flash, along with improvements in satellite retrievals, should help resolve the discrepancies that currently exist between the model and observations.
Successful myomectomy of a bleeding myoma in a twin pregnancy

Uterine fibroids are often seen in pregnancy, with a reported prevalence between 0.1% and 15%. 1 The incidence is increasing because more women delay pregnancy. The effect of uterine fibroids on fertility and pregnancy depends on number, size and location.1,2 In 2% of all pregnancies with uterine fibroids, conservative therapy fails and myomectomy by laparotomy or laparoscopy had to be performed, mainly for unbearable pain or haemoperitoneum.2 In these cases myomectomy appears to improve pregnancy outcome,3,4 although uterine rupture may occur at a time later in pregnancy.5