Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of theoretical models in predicting permeability of hydrate bearing sands

Depleted natural gas reservoirs offer significant potential for simultaneous recovery of enhanced coalbed methane and carbon sequestration via clathrate hydrate formation. A major factor affecting the clathrate hydrate formation and that of methane dissociation is the variation of permeability of the porous media in the presence of gas hydrates. In the absence of reliable experimental data, several permeability models have been proposed to establish the relationship between gas hydrate saturation and permeability. In this paper, we introduce a quantitative performance measure to evaluate the effectiveness of a permeability model in fitting the experimental data. Secondly, a novel hybrid model based on the weighted combination of pore-filling and grain coating model is proposed. Experimental permeability and hydraulic conductivity measurements of gas hydrate bearing sands at different carbon dioxide and R-11 synthetic hydrate saturations were used to assess the prediction performance of various permeability models. RÉSUMÉ Appauvri réservoirs de gaz naturel offrent un potentiel considérable pour la récupération simultanée de méthane de houille et à la séquestration de carbone par la formation d'hydrates clathrates. Un facteur important affectant la formation de clathrate hydrate et celle de la dissociation du méthane est la variation de la perméabilité du milieu poreux en présence d'hydrates de gaz. En l'absence de données expérimentales fiables, plusieurs modèles de perméabilité ont été proposées pour établir la relation entre la saturation des hydrates de gaz et de la perméabilité. Dans cet article, nous introduisons une mesure de performance quantitatifs pour évaluer l'efficacité d'un modèle de perméabilité en ajustant les données expérimentales. Deuxièmement, un modèle hybride roman basé sur la combinaison pondérée d'un pore de remplissage et le modèle enrobage des grains est proposé. Perméabilité expérimentale et mesures de conductivité hydraulique de l'hydrate de gaz sables aurifères au dioxyde de carbone différente et R-11 de synthèse saturations hydrate ont été utilisés pour évaluer les performances de prévision de modèles de perméabilité différents.
The Seventeenth CIRP Conference on Electro Physical and Chemical Machining (ISEM) Relationship between occurrence of material removal and bubble expansion in electrical discharge machining

In this study, we observe the tracks of debris particles scattered from the discharge point and bubble expansion and contraction in a single pulse discharge ignited in the parallel flat gap space in order to discuss the mechanism of material removal in electrical discharge machining (EDM). A metal rod and a transparent flat resin plate with metal wire inserts are used as electrodes, and a single pulse discharge was initiated in EDM oil. The tracks of the debris particles scattered from the discharge point and expansion and contraction of the generated bubble are observed using a high-speed video camera. The discharge duration was varied from 60 to 1000 μ s, where the latter condition is intended to maintain the discharge until after the generated bubble expanded and then contracted. By combining the observed results of the scattered debris particles and the generated bubble motion, it is found that material removal occurs while the bubble is expanding, that is, while the pressure at the discharge point is decreasing.
Forensic Voice Comparison in Thai : A Likelihood Ratio-based Approach using Tonal Acoustics

This paper discusses the very first forensic voice comparison (FVC) using the Likelihood Ratio-based approach in the Thai language. FVC concerns the task of comparing two or more speech samples in order to assist the trier of the fact in determining whether two or more speech samples (usually of the suspect(s) and the offender) came from the same speaker or from different speakers. This experiment employs speech acoustics (F0 and duration) from 10 male speakers whose speech samples were elicited in a citation manner. In one test configuration 96% of same-speaker speech data were correctly identified as coming from the same speaker. This suggests that FVC works reasonably well in the Thai language.
A Bivariate Fractional Probit Model Jörg Schwiebert

This paper develops a bivariate fractional probit model for fractional response variables, i.e., variables bounded between zero and one. The model can be applied when there are two seemingly unrelated fractional response variables. Since the model relies on a quite strong bivariate normality assumption, specification tests are discussed and the consequences of misspecification are investigated. It is shown that the model performs well when normal marginal distributions can be established (this can be tested), and does not perform worse when the joint distribution is not characterized by bivariate normality. Simulation evidence shows that the bivariate model generates more efficient estimates than two univariate models applied to each fractional response variable separately. An empirical application illustrates the usefulness of the proposed model in empirical practice.
Efﬁcient 2 3 S positronium production by stimulated decay from the 3 3 P level

We investigate experimentally the possibility of enhancing the production of 2 3 S positronium atoms by driving the 1 3 S –3 3 P and 3 3 P –2 3 S transitions, overcoming the natural branching ratio limitation of spontaneous decay from 3 3 P to 2 3 S . The decay of 3 3 P positronium atoms toward the 2 3 S level has been efﬁciently stimulated by a 1312.2 nm broadband IR laser pulse. The dependence of the stimulating transition efﬁciency on the intensity of the IR pulse has been measured to ﬁnd the optimal enhancement conditions. A maximum relative increase of × (3 . 1 ± 1 . 0) in the 2 3 S production efﬁciency, with respect to the case in which only spontaneous decay is present, was obtained.
Challenges and Opportunities using Software-defined Visualization in MegaMol

In this paper we describe how we integrated the OSPRay ray tracing engine into the traditionally GPU-centric MegaMol visualization framework. Since OSPRay is purely CPUbased, this adds software-defined visualization to MegaMol. This enables us to use MegaMol for in-situ rendering on HPC systems that lack GPUs. Furthermore, we designed the integration so that the new OSPRay rendering can be used alongside the classical OpenGL-based rendering. We describe how the ray tracing paradigm, where the whole scene has to be available during rendering, changes the module graph of MegaMol. The performance of the OSPRay ray tracing is shown to be at least competitive with classical GPU-accelerated rendering methods for particle rendering available in MegaMol.
Evidences of somatic retrotransposition in the octopus brain

(1) Biology and Evolution of Marine Organisms, Stazione Zoologica Anton Dohrn, Napoli, Italy (2) Bioinformatics Core Facility, Institute of Molecular Biology gGmbH (IMB), Mainz, Germany (3) Department of Molecular Evolution and Development, University of Vienna, Vienna, Austria (4) Department of Neuroscience and Brain Technologies, Italian Institute of Technologies (IIT), Genova, Italy (5) Area of Neuroscience, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
The Role of Utterance Boundaries and Word Frequencies for Part-of-speech Learning in Brazilian Portuguese Through Distributional Analysis

In this study, we address the problem of part-of-speech (or syntactic category) learning during language acquisition through distributional analysis of utterances. A model based on Redington et al.’s (1998) distributional learner is used to investigate the informativeness of distributional information in Brazilian Portuguese (BP). The data provided to the learner comes from two publicly available corpora of child directed speech. We present preliminary results from two experiments. The first one investigates the effects of different assumptions about utterance boundaries when presenting the input data to the learner. The second experiment compares the learner’s performance when counting contextual words’ frequencies versus just acknowledging their co-occurrence with a given target word. In general, our results indicate that explicit boundaries are more informative, frequencies are important, and that distributional information is useful to the child as a source of categorial information. These results are in accordance with Redington et al.’s findings for English.
Efficient and Accurate Numerical Integration for High Order Immersed Boundary Methods

Several approaches have been suggested to improve the performance and accuracy of the numerical quadrature. For XFEM applications, it was shown that nearly optimal convergence rates can be achieved in combination with NURBS-enhanced finite elements [1]. The treatment of cut elements in the context of Isogeometric Analysis combined with trimmed CAD surfaces was studied in [2]. For the Finite Cell Method, the triangulation of the cut cells and its influence on the convergence behavior was discussed in [3].
Political Social Networks Reveal Strong Party Loyalty in Brazil and Weak Regionalism

Politics fascinate people—we all live in places with political structures governing many aspects of our daily lives. In several countries, people identify themselves not only with their country but they tend to demonstrate some “regionalism” in their attitude. We have seen examples of regionalism in di↵erent parts of the world (e.g. Kurdistan in Iraq, Catalonia in Spain, Crimea in Ukraine, to name but a few). Politicians at the lower house are elected to represent one particular region in the national congress and the population in those regions expect the politicians to work for the benefit of the region. In this paper we collected data from 6 di↵erent legislatures in Brazil and investigated its structure. One very surprising finding in this study is that politicians appear to put party interest over the interest of the region they represent—we found almost no evidence of regionalism but strong party loyalty. We also found two main legislators characteristics in the Brazilian Chamber of Deputies: (i) the party borders are not as clear as in bipartisan systems, a feature that leads to collaborations across party lines, and (ii) the opposition in the last legislatures appears to be diminishing its size and weakening its structure.
Late auditory evoked potentials in Cochlear Implant Listeners during the first days of hearing rehabilitation ( Auditorische Hirnrindenpotentiale bei Cochlear

Objectives: The late auditory evoked potentials (LAEPs) are an objective method for measurement of the central hearing system activity. It is possible to elicit LAEPs both by acoustic stimulation in normal hearing subjects, subjects with hearing aids and cochlear implant (CI) and also by electrical stimulation of cochlear implant electrodes in CI listeners. LAEPs are able to reflect neuronal reorganisation due to hearing loss, due to restoration of acoustic input after deafness or due to hearing training. It was found that LAEPs parameters correlate significantly with speech understanding. The information about the cortical signal processing through CI in the earlier period of CI usage could be useful for adequate setting of the speech processor and hearing training of CI patients. As there still aren’t any electroencephalographic (EEG) studies, which concentrate on the inexperienced CI users, the objectives of this study were to determinate: 1) whether LAEPs as P1-N1-P2 complex and acoustic change complex (ACC) can be observed during the first few days after CI processor switch-on; 2) whether parameters of LAEPs change during the first few days of hearing rehabilitation.
ON THE SEMANTICS OF FICTIONAL NAMES

This paper proposes an account of the semantics of names in fiction (fictional names). In doing so, it addresses the semantics of proper names first, which are seen as unstructured linguistic expressions, with no descriptive content or inherent meaning, whose sole function is to denote an individual directly. Their semantic value lies in their denotation, and they are like constants in the logical form. In contrast, fictional names are seen to function like variables bound by the existential quantifier, the individuals they denote in the worlds of fiction being identified at the actual world by description.
Comparison of various approaches for modelling interaction of dispersive media and electromagnetic waves

In this paper various approaches for calculation transient response of systems containing frequency depended materials excited by an electromagnetic wave are compared. As an example, implementation of Debye media. The frequency dependence of Debye media can be expressed as a sum of single pole systems on s plane. Efficiency and accuracy of different methodologies is compared: inverse Fourier transform of a multiple frequency domain simulations and direct modification of time domain marching schemes. The latter is presented in a formalism of digital filters.
True Overconfidence , Revealed through Actions : An Experiment februAry 2017

IZA DP No. 10545 februAry 2017 True Overconfidence, Revealed through Actions: An Experiment* We report an experiment that infers true overconfidence in relative ability through actions, as opposed to reported beliefs. Subjects choose how to invest earnings from a skill task when the returns depend solely upon risk, or both risk and relative placement, enabling joint estimation of individual risk preferences and implied subjective beliefs of placing in the top half. We find evidence of aggregate overconfidence only in a treatment that receives minimal feedback on performance in a trial task. In treatments that receive more detailed feedback, aggregate overconfidence is not observed although identifiable segments of overand underconfident individuals persist. JEL Classification: C91, D03, D81, D83
Lifecycle scenario design for product end-of-life strategy

This paper proposes and investigates the use of embedding sensors in products when designing and manufacturing them to improve the efficiency during their end-of-life (EOL) processing. First, separate design of experiments studies based on orthogonal arrays are carried out for conventional products (CPs) and sensor embedded products (SEPs). In order to calculate the response values for each experiment, detailed discrete event simulation models of both cases are developed considering the precedence relationships among the components together with the routing of different appliance types through the disassembly line. Then, pair-wise t-tests are conducted to compare the two cases based on different performance measures. The results showed that sensor embedded products improve revenue and profit while achieving significant reductions in backorder, disassembly, disposal, holding, testing and transportation costs. While the paper addresses the EOL processing of dish washers and dryers, the approach provided could be extended to any other industrial product.
CLASSIFICATION OF CANCER GENE SUBTYPES FROM CLUSTERING OF GENE EXPRESSION DATA

Typically, microarray gene expression data obscure imperative information which is necessary for the understanding of molecular biology processes that occurs in a specific organism with respect to its environment. Uncovering gene expression data’s invisible patterns will lead to a remarkable desire to enhance the interpretation of functional genomics. Biological networks intricacy and the presence of huge amount of genes raise the difficulties of understanding of the high dimension data, which resides lots of measurements. Thus, clustering techniques which are crucial in the data mining process are used as the first step to address this challenge to discover logical structures and predict significant patterns in the hidden data. These patterns may offer shreds of evidence about the biological process related to different physiological conditions. On deep, this paper focuses on the co-clustering algorithm to cluster genes and conditions simultaneously to obtain co-clusters further utilised for classification. The method called an improved network assisted co-clustering for the identification of cancer subtypes (iNCIS). Fundamentally, it integrates gene network information with gene expression to achieve biologically significant clusters. The classes obtained from clusters were used in the classification of genes to improve accuracy. This method applied to breast cancer and glioblastoma multiforme datasets. The discovered structures disclosed strong biological significance associations between functional annotations of genes with related conditions.
A Survey on Compressed Sensing Based Banknote Classification

In this paper, we propose a Compressed Sensing based Banknote Classification Method (CSBCM), the aim of which is to study the image classification of banknote in the complex lighting environment. After briefly analyzing the traditional methods of banknote classification and introducing the relevant concept of the compressed sensing theory, we explore the robustness of CS theory in the application of pattern recognition. The proposed method involves the creation of banknote image database, the construction of banknote dictionary bases and so on. All our experiments are made on the self-built banknote database and we compare the traditional ways of banknote classification with the CSBCM to lead to the conclusion of this text: the feature extraction is not critical in CSBCM and the calculating efficiency and the classification accuracy of the CSBCM is superior to that of the traditional method.
Modeling Intra-household Activity Time Allocation from Group Decision Making Process

The objective of this study is to analyze group decision-making process leading to the intrahousehold activity time allocation models. Each household is characterized as a group of individuals making joint decisions about their activity participation, time allocation and consumption of goods. Household members make several decisions jointly, not by an individual member, including independent and joint activity time allocations as well as private and shared consumption of goods. Since the individualbased activity time allocation models are not realistic for multi-person households, it is beneficial to consider group decision-making process in modeling time allocation behavior of household members. We summarize various intra-household activity time allocation models, ranging from unitary models to collective models, based on different group decision-making processes. The models are presented under microeconomic principle of utility maximization to represent the economic behavior of the households.
Understanding Implicit Bias: Putting the Criticism into Perspective

What is the status of research on implicit bias? In light ofmeta-analyses revealing ostensibly low average correlations between implicit measures and behavior, as well as various other psychometric concerns, criticism has become ubiquitous. We argue that while there are significant challenges and ample room for improvement, research on the causes, psychological properties, and behavioral effects of implicit bias continues to deserve a role in the sciences of the mind as well as in efforts to understand, and ultimately combat, discrimination and inequality.
Analysis of the entrepreneurial ability of college students in a network environment

With increasing employment pressure in China, independent entrepreneurship has become a trend for college students. As Internet technology is developing continuously, how to develop the ability of college students in a network environment is an important topic. In this article is presented a thorough analysis of the concept and constituent factors of the entrepreneurial ability of college students, so as to provide a theoretical basis. Through research and analysis of the entrepreneurial ability and motivation of college students in the network environment, the positive and adverse factors influencing entrepreneurial ability in the network environment were determined. Finally, a strategy was proposed to enhance the entrepreneurial ability of college students, which has great significance for expansion of such ability.
3D mass digitization: a milestone for archeological documentation

In the heritage field, the demand for fast and efficient 3D digitization technologies for historic remains is increasing. Besides, 3D digitization has proved to be a promising approach to enable precise reconstructions of objects. Yet, unlike the digital acquisition of cultural goods in 2D widely used today, 3D digitization often still requires a significant investment of time and money. To make it more widely available to heritage institutions, the Competence Center for Cultural Heritage Digitization at the Fraunhofer Institute for Computer Graphics Research IGD has developed CultLab3D , the world’s first 3D mass digitization facility for collections of three-dimensional objects. CultLab3D is specifically designed to automate the entire 3D digitization process thus allowing to scan and archive objects on a large-scale. Moreover, scanning and lighting technologies are combined to capture the exact geometry, texture, and optical material properties of artefacts to produce highly accurate photo-realistic representations. The unique setup allows to shorten the time needed for digitization to several minutes per artefact instead of hours, as required by conventional 3D scanning methods.
Including traffic lightrecognition in generalobject detection withYOLOv 2

With an in vehicle camera many different things can be done that are essential for ADAS or autonomous driving mode in a vehicle. First, it can be used for detection of general objects, for example cars, cyclists or pedestrians. Secondly, the camera can be used for traffic light recognition, which is localization of traffic light position and traffic light state recognition. No method exists at the moment able to perform general object detection and traffic light recognition at the same time, therefore this work proposes methods to combine general object detection and traffic light recognition. The novel method presented is including traffic light recognition in a general object detection framework. The single shot object detector YOLOv2 is used as base detector. As general object class dataset COCO is used and the traffic light dataset is LISA. Two different methods for combined detection are proposed: adaptive combined training and YOLOv2++. For combined training YOLOv2 is trained on both datasets with the YOLOv2 network unchanged and the loss function adapted to optimize training on both datasets. For YOLOv2++ the feature extractor of YOLOv2 pre-trained on COCO is used as feature extractor. On the features LISA traffic light states are trained with a small sub-network. It is concluded the best performing method is adaptive combined training which reaches for IOU 0.5 a AUC of 24.02% for binary and 21.23% for multi-class classification. For IOU of 0.1 this increases to 56.74% for binary and 41.87% for multi-class classification. The performance of the adaptive combined detector is 20% lower than the baseline performance of an detector only detecting LISA traffic light states and 5% lower than the baseline of a detector only detecting COCO classes, however detection of classes from both dataset is almost twice as fast as separate detection with different networks for both datasets.