Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep seismic reflection and refraction profiling along the Aquitaine shelf (Bay of Biscay)

Summary. The 300 km ECORS - Bay of Biscay profile was carried out along the Aquitaine shelf and comprised a complete set of experiments including zero-offset and 7.5 km constant offset vertical seismic reflection and six expanding spread profiles. Large offset recordings were fundamental for the definition of the layered lower crust and the Moho, while ESPs provided decisive complementary information for the geological interpretation. These data show a strong variation in crustal thickness from about 20 km beneath the rifted Parentis basin, a failed arm of the oceanic Bay of Biscay, up to 35 km to the north below the Armorican shelf, in the Hercynian domain, and to the south below the Cantabria shelf, in the vicinity of the Pyrenean deformation front. The results have important implications for the behaviour of the crust during the formation of rifted sedimentary basins and during continental collision.
Exploiting Diversity for Natural Language Processing

Accurate linguistic annotation is a core requirement of natural language processing systems. The demand for accuracy in the face of rapid prototyping constraints and numerous target languages has led to the employment of machine learning methods for developing linguistic annotation systems. The popularity of applying machine learning methods to computational linguistics problems has given rise to a large supply of trainable natural language processing systems. Most problems of interest have an array of off-the-shelf products or downloadable code implementing solutions using various techniques. In situations where these solutions are developed independently, it is observed that their errors tend to be independently distributed. In this thesis we discuss approaches for capitalizing on this situation in a sample problem domain, Penn Treebank-style parsing. The machine learning community provides us with techniques for combining outputs of classifiers, but parser output is more structured and interdependent than classifications. To overcome this, two novel strategies for combining parsers are used: learning to control a switch between parsers and constructing a hybrid parse from multiple parsers' outputs. In this thesis we give supervised and unsupervised techniques for each of these strategies as well as performance and robustness results from evaluation of the techniques. One shortcoming of combining off-the-shelf parsers is that the parsers are not developed with the intention to perform well on complementary data or to compensate for each others' weaknesses. The individual parsers are globally optimized. We present two techniques for producing an ensemble of parsers in such a way that their outputs can be constructively combined. All of the ensemble members will be created using the same underlying parser induction algorithm, and the method for producing complementary parsers is only loosely coupled to that algorithm.
Estimation of proper parameter values for document binarization

Most of the existing document-binarization techniques deal with many parameters that require a priori setting of their values. Due to the unknown of the ground-truth images, the evaluation of document binarization techniques is subjective and employs human observers for the estimation of the appropriate parameter values. The selection of the appropriate values for these parameters is crucial and influences to the final binarization. However, there is no predetermined set of parameters that guarantees optimal binarization for all document images. This paper proposes a new technique that allows the estimation of proper parameters values for each one of the document binarization techniques. The proposed approach is based on a statistical performance analysis of a set of binarization results, which are obtained by applying various binarization techniques with different parameter values. The proposed statistical performance analysis can also depicts the best document binarization result obtained by a set of document binarization techniques.
Graft-Versus-Host Disease With Early Cytomegalovirus Infection in Gastrointestinal Tract Biopsies

Gastrointestinal (GI) graft-versus-host disease (GVHD) and cytomegalovirus (CMV) infection often simulate each other. However, distinction between GVHD and CMV infection is critical in the management of immunosuppression for transplant recipients. This study retrospectively reviewed 16 patients diagnosed with GVHD from 2010 to 2016 and found 4 cases (25%) coinfected with CMV. Two cases were initially diagnosed as GVHD only but found to have CMV infection by serological testing within 3 days after immunosuppression treatment for GVHD. The remarkable histological feature of CMV infection appeared to be significant acute inflammation in addition to apoptotic epithelial injuries, and particularly in an early stage of CMV replication, acute inflammation is possibly the only detectable feature of CMV infection.
Measuring Woody Encroachment along a Forest–Savanna Boundary in Central Africa

Abstract Changes in net area of tropical forest are the sum of several processes: deforestation, regeneration of previously deforested areas, and the changing spatial location of the forest–savanna boundary. The authors conducted a long-term (1986–2006) quantification of vegetation change in a 5400 km2 forest–savanna boundary area in central Cameroon. A cross-calibrated normalized difference vegetation index (NDVI) change detection method was used to compare three high-resolution images from 1986, 2000, and 2006. The canopy dimensions and locations of over 1000 trees in the study area were measured, and a very strong relationship between canopy area index (CAI) and NDVI was found. Across 5400 km2 12.6% of the area showed significant positive change in canopy cover from 1986 to 2000 (0.9% yr−1) and 7.8% from 2000 to 2006 (1.29% yr−1), whereas <0.4% of the image showed a significant decrease in either period. The largest changes were in the lower canopy cover classes: the area with <0.2 m2 m−2 CAI decreased.
Agent-based modeling and simulation

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations. Such progress suggests the potential of ABMS to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use agent-based models as electronic laboratories. Some contend that ABMS “is a third way of doing science” and could augment traditional deductive and inductive reasoning as discovery methods. This brief tutorial introduces agent-based modeling by describing the foundations of ABMS, discussing some illustrative applications, and addressing toolkits and methods for developing agent-based models.
Kriging metamodeling in constrained simulation optimization: an explorative study

This paper describes two experiments exploring the potential of the Kriging methodology for constrained simulation optimization. Both experiments study an (s, S) inventory system with the objective of finding the optimal values of s and S. The goal function and constraints in these two experiments differ, as does the approach to determine the optimum combination predicted by the Kriging model. The results of these experiments indicate that Kriging offers opportunities for solving constrained optimization problems in stochastic simulation; future research will focus on further refining the methodology.
Conjunctive Keyword Search With Designated Tester and Timing Enabled Proxy Re-Encryption Function for E-Health Clouds

An electronic health (e-health) record system is a novel application that will bring great convenience in healthcare. The privacy and security of the sensitive personal information are the major concerns of the users, which could hinder further development and widely adoption of the systems. The searchable encryption (SE) scheme is a technology to incorporate security protection and favorable operability functions together, which can play an important role in the e-health record system. In this paper, we introduce a novel cryptographic primitive named as conjunctive keyword search with designated tester and timing enabled proxy reencryption function (Re-dtPECK), which is a kind of a time-dependent SE scheme. It could enable patients to delegate partial access rights to others to operate search functions over their records in a limited time period. The length of the time period for the delegatee to search and decrypt the delegator's encrypted documents can be controlled. Moreover, the delegatee could be automatically deprived of the access and search authority after a specified period of effective time. It can also support the conjunctive keywords search and resist the keyword guessing attacks. By the solution, only the designated tester is able to test the existence of certain keywords. We formulate a system model and a security model for the proposed Re-dtPECK scheme to show that it is an efficient scheme proved secure in the standard model. The comparison and extensive simulations demonstrate that it has a low computation and storage overhead.
Automatic image registration and target recognition with multiresolution hybrid evolutionary algorithm

A novel method for multi-resolution automatic target recognition is described that employs the hybrid evolutionary algorithm and image transform in a form of image local response. The recognition task is re-formulated as a nonlinear global optimization problem, i.e. the search for a proper transformation A(V) that provides the best match between the images of the target and the scene. Given the images of the scene and the targeted object located in the scene, the proposed method repeatedly applies response analysis on different resolution levels (zooming in), in order to find the region of interest (ROI) containing the target in the large-scale image of the scene. On every resolution level, the response matrices are computed for the images of ROI and the target. Cross correlation of the response matrices built for ROI and the target outlines the potential locations of the latter. Once the locations are successfully identified, the algorithm zooms in on the found locations. The hybrid evolutionary algorithm is applied to the response matrices MR; it attempts to minimize the least squared difference of the pixel values of the response matrices corresponding to the images, thus searching for the correct parameter vector V for the targeted object with the reference to ROI.
Tertiary structural relationships between Alps and Apennines: the critical Torino Hill and Monferrato area. Northwestern Italy

The relationship between the Alpine and Apenninic orogenic systems is concealed at the surface by Tertiary sediments of two main tectono-stratigraphic units: the ‘Alpine-related’ Torino Hill domain and the ‘Apennines-related’ Monferrato domain. Mapping and structural analyses carried out in the area behind the Mio-Pliocene Apenninic-Padane thrust front allow comparison of the kinematic history of the Torino Hill and Monferrato domains. These are separate by the transpressive Tlio Freddo Deformation Zone' (RFDZ), interpreted here as the superficial expression of a crustal discontinuity along which the Alpine metamorphic basement overrode the Apenninic Ligurian nappes during the Palaeogene. The Western Monferrato structural setting is the result of: (i) Late Oligocene-Burdigalian transpressive tectonics due to lateral displacement between the Alps-related and the Apennines-related domains; and (ii) compressive post-Messinian tectonics related to northward transport along the main Padane thrust front. Post-Messinian tectonic events affected also the NW-vergent asymmetrical Torino Hill anticline.
System Identification of Thermal Process using Elman Neural Networks with No Prior Knowledge of System Dynamics

Dynamic Neural networks have been verified as identifiers due to its capability for manipulating processes in parallel and enduring noisy sorts of the input signals. They make them outstanding contenders for system identification applications. This paper presents a method for a black box system identification based on Elman neural network (ENN) for thermal process system to generate a prototype for the dynamical system of the thermal process without any past information about the system dynamics. This identification approach is compared to its counterpart conventional feedforward neural network (CFFNN) based system identification. The comparative simulations show that the ERNN gives an excellent results and outperforms the CFFNN in terms of accuracy with little degradation in the speed of convergence which make this neural network a motivating candidate for adaptive and gain scheduling controllers.
Network Selection Algorithm for Heterogeneous Wireless Environment

Service delivery in a heterogeneous wireless environment requires the selection of an optimal radio access network. In order that users could be always connected through the optimal network, it is necessary to develop an adequate model for its selection. This paper presents the proposal of optimal network selection algorithm in wireless heterogeneous environment that is based on TOPSIS method when solving the multicriteria analysis. The wireless networks in this model represent the alternatives, while the network parameters (available bandwidth, quality of service level, security level, data transfer cost) are considered as the criteria for determining the optimal network.
Toward a Literature-Driven Definition of Big Data in Healthcare

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.
Low Resistin Level is Associated with Poor Hospitalization-Free Survival in Hemodialysis Patients

Malnutrition and inflammation are related to high rates of morbidity and mortality in hemodialysis patients. Resistin is associated with nutrition and inflammation. We attempted to determine whether resistin levels may predict clinical outcomes in hemodialysis patients. We conducted a prospective evaluation of 100 outpatients on hemodialysis in a single dialysis center (male, 46%; mean age, 53.7 ± 16.4 yr). We stratified the patients into 4 groups according to quartiles of serum resistin levels. During the 18-month observational period, patients with the lowest quartile of serum resistin levels had poor hospitalization-free survival (log rank test, P = 0.016). After adjustment of all co-variables, patients with the lowest quartile of serum resistin levels had poor hospitalization-free survival, compared with reference resistin levels. Higher levels of interleukin-6 were an independent predictor of poor hospitalization-free survival. In contrast, serum resistin levels were not correlated with interleukin-6 levels. The current data showed that low resistin levels may independently predict poor hospitalization free survival in hemodialysis patients.
A rationale for old water discharge through macropores in a steep, humid catchment.

Simultaneous observations of rapid preferential flow through macropores and isotopically “Old” water displacement remain unresolved in the Maimai (M8) catchment. Continuous, three-dimensional soil moisture energy conditions were monitored in two discrete catchment positions for a series of storm events in 1987. Tensiometric response was related to the soil water characteristic curve, hillslope throughflow, and total catchment runoff. For events yielding ≪2 mm hr−1 peak runoff, near-stream valley bottom groundwater systems discharged water volumes sufficient to account for storm period streamflow. This process was assisted by regular low ( 2 mm hr−1 peak storm flow, hillslope hollow drainage into steeply sloping first-order channels dominated old water production and most of the catchment storm flow. Highly transient macropore-driven processes of crack infiltration (bypass flow), slope water table development, and lateral pipe flow enabled large volumes of stored water to be delivered to the first-order channel bank at the appropriate time to satisfy catchment storm flow volumes and water isotopic and chemical composition.
Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity

In this paper we present a scalable approach for robustly computing a 3D surface mesh from multi-scale multi-view stereo point clouds that can handle extreme jumps of point density (in our experiments three orders of magnitude). The backbone of our approach is a combination of octree data partitioning, local Delaunay tetrahedralization and graph cut optimization. Graph cut optimization is used twice, once to extract surface hypotheses from local Delaunay tetrahedralizations and once to merge overlapping surface hypotheses even when the local tetrahedralizations do not share the same topology. This formulation allows us to obtain a constant memory consumption per sub-problem while at the same time retaining the density independent interpolation properties of the Delaunay-based optimization. On multiple public datasets, we demonstrate that our approach is highly competitive with the state-of-the-art in terms of accuracy, completeness and outlier resilience. Further, we demonstrate the multi-scale potential of our approach by processing a newly recorded dataset with 2 billion points and a point density variation of more than four orders of magnitude - requiring less than 9GB of RAM per process.
Structure plan of clastic dikes

Conclusions drawn from field observations are that vertical sandstone dikes of the White River Badlands, South Dakota, originated as open fractures that were filled with debris supplied by erosion of overlying formations. One existing explanation is that the dikes formed in deep desiccation cracks which developed at the surface as the silts and clays of the Oligocene White River group became consolidated. Evidence from a recent study of a small area of clastic dikes is incompatible with the desiccation-crack theory of origin. The pattern of intersecting dikes, when mapped, resembles a fracture system rather than having a hexagonal arrangement normally associated with desiccation cracks. Shear fractures appear on the map intersecting at angles of 54° to 71°, the acute bisectrix varying in strike from N 45°W to N 54°W. One dike occupies a major tension fracture, strikes N 50°W, and extends vertically through two beds of strikingly different lithology, a condition unlikely to occur with desiccation cracks. South of the area, normal faults of small vertical displacement, trending northwest, suggest minor regional tension, which may well have caused the development of a fracture pattern as displayed by the dikes. If these fractures were open at the surface, subsequent filling from above would follow, resulting in numerous intersecting clastic dikes.
Influence of Scattering on Seismic Waves: Physical Mechanisms Contributing to Attenuation in the Crust

Abstract : The mechanisms contributing to the attenuation of earthquake ground motion in the distance range of 10 to 200 km are studied with the aid of laboratory data, coda waves and strong motion attenuation measurements in the northeastern United States and Canada and theoretical models. The relative contributions to attenuation of anelasticity of crustal rocks (constant Q), fluid flow and scattering are evaluated. Scattering is found to be strong with albedo of Bo - 0.9 and scattering extinction length of about 17 km. The intrinsic attenuation in the crust can be explained by a high constant Q (500 or = sub 0 2000) and a frequency dependent mechanism most likely due to fluid effects in rocks and cracks. A fluid-flow attenuation model gives a frequency dependence (Q approx Q sub 0 f to the 5th power) similar to those determined from the analysis of coda waves of regional seismograms.
Survey of the use and effect of assistive devices in patients with early rheumatoid arthritis: a two-year followup of women and men.

OBJECTIVE To identify activity limitation in early rheumatoid arthritis (RA) to detect patients needing assistive devices. To evaluate the effects of assistive devices. METHODS A multicenter cohort of 284 early RA patients was examined using the Evaluation of Daily Activity Questionnaire 12 and 24 months after diagnosis. RESULTS The extent of activity limitation was stable over time for both women and men. Most limitations concerned eating and drinking. Women reported more difficulties than did men. The use of assistive devices was related to subgroups with severe disease and more disability. Use of assistive devices reduced difficulties significantly. For both women and men, assistive devices were mostly used in activities related to eating and drinking. CONCLUSION Already 1 year after diagnosis, RA patients reported activity limitation that remained stable over time. Use of assistive devices was related to more severe disease and more pronounced disability. Use of devices reduced difficulties significantly.
Melt migration in a silicate liquid-olivine system: An experimental test of compaction theory

To investigate the kinetics of porous flow in partially molten peridotite, a melt migration couple – formed from a disc of fine-grained olivine plus ∼15% of a synthetic K-Al silicate glass and a disc of poly crystalline olivine – was heated at 1255°C under a confining pressure of 300 MPa for 2 hr. Driven by capillary forces, silicate liquid in the source disc infiltrates along three-grain junctions into the sink disc. To analyze the resulting melt migration profile in terms of compaction theory, the equations developed by McKenzie [1984] to describe porous flow of a liquid in a deformable matrix were modified by replacing the buoyancy force term with a capillary force term. The governing equations were then solved numerically with the initial and boundary conditions specified by the experimental design. Comparison of the melt migration profile obtained from the experiment with those generated by numerical simulation demonstrates that compaction theory provides a good description of the experimental results provided that the permeability of these solid-liquid materials increases linearly with increasing liquid fraction.
On How Agents Make Friends: Mechanisms for Trust Acquisition

We need models of trust to facilitate cooperation in multi-agent systems, where agents, human and artificial, do not know each other beforehand. This paper lists and proposes simple mechanisms for trust acquisition based on a very basic and general definition of trust, making no assumptions on the internal cognitive models of the involved agents. We also show how trust acquired one-on-one can be propagated in a social network of agents.