Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic Theory for Rotated Multivariate GARCH Models

In this paper, we derive the statistical properties of a two step approach to estimating multivariate GARCH rotated BEKK (RBEKK) models. By the definition of rotated BEKK, we estimate the unconditional covariance matrix in the first step in order to rotate observed variables to have the identity matrix for its sample covariance matrix. In the second step, we estimate the remaining parameters via maximizing the quasi-likelihood function. For this two step quasi-maximum likelihood (2sQML) estimator, we show consistency and asymptotic normality under weak conditions. While second-order moments are needed for consistency of the estimated unconditional covariance matrix, the existence of finite sixthorder moments are required for convergence of the second-order derivatives of the quasilog-likelihood function. We also show the relationship of the asymptotic distributions of the 2sQML estimator for the RBEKK model and the variance targeting (VT) QML estimator for the VT-BEKK model. Monte Carlo experiments show that the bias of the 2sQML estimator is negligible, and that the appropriateness of the diagonal specification depends on the closeness to either of the Diagonal BEKK and the Diagonal RBEKK models.
Distortion Effects of Export Quota Policy: An Analysis of the China-Raw Materials Dispute

The China-Raw Materials dispute recently arbitrated by the WTO opposed China as defendant to the US, the EU and Mexico as the claimants on the somewhat unusual issue of export restrictions on natural resources. For the claimants, Chinese export restrictions on various raw materials, of which the country is a major producer, create shortages in foreign markets increasing the prices of these goods. China defends export limitations by presenting them as a natural resource conserving policy. This paper offers a theoretical analysis of the dispute with the help of a model of a monopoly extracting a non-renewable resource and selling it on both the domestic and foreign markets. The theoretical results focus on the effects of imposing an export quota on quantities, prices and price distortion. Given the crucial importance of demand elasticities in this theoretical understanding of the conflict, the empirical part of the paper provides estimates of import demand elasticity of the parties for each product concerned in the case. The model and the empirical results challenge the ideas that an export quota always favors conservation of natural resource, that a higher foreign price necessarily follows this policy and that it inherently increases price distortion and therefore discrimination.
Dynamic State Estimation Using Event-Trigger Master-Slave Nonlinear Filter for WAMS Applications

The real-time state estimation becomes greatly important with the wide application of phasor measurement unit (PMU) in distributed generation (DG) for wide-area measurement systems (WAMS). In view of estimation, particle filter (PF) is capable of providing the best performance but at the cost of heavy computation burden. Besides, the growing grid size sustainably boosts the amount of data communication from PMU, causing the congestion. An event-trigger master-slave nonlinear filter (ET-MSNF) is proposed to guarantee the estimation accuracy and get the communication bandwidth relieved. The local slave filter at the generator node carries out the local estimation and event-trigger strategy using unscented transformation, which is identical to the center slave. The master filter at the center is designed using Monte Carlo method to improve the center’s estimation accuracy by the cooperation with the center slave. Such master-slave filtering structure can fully utilize the computation capability both at the center and node. Simulation on the standard IEEE 39-bus system verify the performance of ET-MSNF.
The DTA “Base Format”: A TEI Subset for the Compilation of a Large Reference Corpus of Printed Text from Multiple Sources

In this article we describe the DTA “Base Format” (DTABf), a strict subset of the TEI P5 tag set. The purpose of the DTABf is to provide a balance between expressiveness and precision as well as an interoperable annotation scheme for a large variety of text types of historical corpora of printed text from multiple sources. The DTABf has been developed on the basis of a large amount of historical text data in the core corpus of the project Deutsches Textarchiv (DTA) and text collections from 15 cooperating projects with a current total of 210 million tokens. The DTABf is a “living” TEI format which is continuously adjusted when new text candidates for the DTA containing new structural phenomena are encountered. We also focus on other aspects of the DTABf including consistency, interoperability with other TEI dialects, HTML and other presentations of the TEI texts, and conversion into other formats, as well as linguistic analysis. We include some examples of best practices to illustrate how external corpora can be losslessly converted into the DTABf, thus enabling third parties to use the DTABf in their specific projects. The DTABf is comprehensively documented, and several software tools are available for working with it, making it a widely used format for the encoding of historical printed German text.
DEVELOPMENT AND CHARACTERIZATION OF ELECTROCHEMICAL CANTILEVER SENSOR FOR BIO/CHEMICAL SENSING APPLICATIONS

We report the improvements made to our previously developed electrochemical cantilever (EC) sensor, where nanoporous gold material is employed as working electrodes in microcantilever arrays, while combined counter-reference electrodes are integrated on the chip. For a surface stress change of 1mN/m induced on the microcantilever, the cantilever deflects is 7.3 nm at the free end, indicating high sensitivity to surface stress changes. The results suggest that the performance of the electrochemical cell is stable. A much enhanced sensitivity in surface chemistry-driven actuation can be achieved by using nanoporous gold with a high-surface area to volume ratio.
Software Development Process Supported by Business Process Modeling - An Experience Report

: Understanding businesses and how they work can help software engineers build systems that really meet the corresponding business goals. For instance, methods such as the Rational Uniﬁed Process (RUP) include activities to model a business before eliciting requirements. However, during our software development practice in academic and ”real-life” projects, we found problems using these artefacts with stakeholders. Here we present our experience on integrating BPMN (Business Process Modeling and Notation) diagrams with RUP, aiming to improve the elicitation of software requirements. These diagrams appeared to be easier to understand by stakeholders. The current paper discusses the challenges we faced in using RUP and the way in which we integrate conceptual maps and BPMN into the process. In addition, we illustrate the changes using models that reﬂect real project implementations realized by using this approach.
TRACING THE ANCESTRY OF THE GREAT WHITE SHARK, CARCHARODON CARCHARIAS, USING MORPHOMETRIC ANALYSES OF FOSSIL TEETH

Abstract The evolutionary origin of the great white shark (Carcharodon carcharias) is unclear, with debate centering around two principal hypotheses. The first, based on similarity in tooth shape, claims that C. carcharias originated from a group of extinct mako sharks that includes Isurus hastalis. The second hypothesis, based mostly on cladistic evidence, claims that C. carcharias originated from the same lineage as the giant megatoothed sharks, sharing a close evolutionary ancestor with the extinct Carcharodon megalodon. To distinguish between the two hypotheses we performed several morphometric analyses. In the first analysis, we used Procrustes method and principal components analysis to quantify variation between C. carcharias, I. hastalis, and C. megalodon in four different positions within the dentition. The results indicate no significant difference in tooth shape between C. carcharias and I. hastalis. In the second analysis, correlating tooth size with age, we analyzed teeth from upper anterior and lower anterior positions. For both tooth positions, we show that the growth rate of C. carcharias is more congruent with the growth rate of I. hastalis than that of C. megalodon. Finally, we used scanning electron microscopy to show that the tooth serrations of C. carcharias are distinct from those of the megatooths and more similar in size to those of slightly serrated mako teeth. Taken together, these results indicate that C. carcharias originated from an extinct group of mako sharks and not from the megatoothed sharks.
Codimension growth of special simple Jordan algebras

Let R be a special simple Jordan algebra over a field of characteristic zero. We exhibit a noncommutative Jordan polynomial f multialternating on disjoint sets of variables which is not a polynomial identity of R. We then study the growth of the polynomial identities of the Jordan algebra R through an analysis of its sequence of Jordan codimensions. By exploiting the basic properties of the polynomial f , we are able to compute the exponential rate of growth of the sequence of Jordan codimensions of R and prove that it equals the dimension of the Jordan algebra over its center. We also show that for any finite dimensional special Jordan algebra, such an exponential rate of growth cannot be strictly between 1 and 2.
Dungeons and DQNs: Toward Reinforcement Learning Agents that Play Tabletop Roleplaying Games

Game playing has been an important testbed for artiﬁcial intelligence. Board games, ﬁrst-person shooters, and real-time strategy games have well-deﬁned win conditions and rely on strong feedback from a simulated environment. Text adventures require natural language understanding to progress through the game but still have an underlying simulated environment. In this paper, we propose tabletop roleplaying games as a challenge due to an inﬁnite action space, multiple (collaborative) players and models of the world, and no explicit reward signal. We present an approach for reinforcement learning agents that can play tabletop roleplaying games.
NEURAL NETWORKS FOR THE CLASSIFICATION OF BUILDING USE FROM STREET-VIEW IMAGERY

Abstract. Within this paper we propose an end-to-end approach for classifying terrestrial images of building facades into five different utility classes (commercial, hybrid, residential, specialUse, underConstruction) by using Convolutional Neural Networks (CNNs). For our examples we use images provided by Google Street View. These images are automatically linked to a coarse city model, including the outlines of the buildings as well as their respective use classes. By these means an extensive dataset is available for training and evaluation of our Deep Learning pipeline. The paper describes the implemented end-to-end approach for classifying street-level images of building facades and discusses our experiments with various CNNs. In addition to the classification results, so-called Class Activation Maps (CAMs) are evaluated. These maps give further insights into decisive facade parts that are learned as features during the training process. Furthermore, they can be used for the generation of abstract presentations which facilitate the comprehension of semantic image content. The abstract representations are a result of the stippling method, an importance-based image rendering.
Atmospheric Pressure Plasmas at the Liquid Interface

The use of non-equilibrium atmospheric pressure plasmas for medicinal and biological applications has shown great promise. Possibilities exist for potential cancer therapies as well as sterilisation and wound healing. A fundamental understanding of the plasma chemistry is important to the further development of these applications. Of particular importance are the chemical kinetics and energy transport mechanisms at the liquid interface. The aim of this work is to obtain measurements of the important reactive neutral species in this region in order to better understand and control the plasma chemical environment. Direct observation of free radicals is complex due to their very short lifetimes. Spin trapping is used to selectively convert unstable radicals to persistent ones, which are then detected by electron paramagnetic resonance (EPR) spectroscopy. The interaction between a kHz dielectric barrier discharge (DBD) plasma jet (operated using a helium feed gas and molecular gas admixtures) with liquids, gels and single layers of organic compounds are investigated and presented in this piece of work.
Optical properties of AlN x O y thin films deposited by DC magnetron sputtering

The aluminium oxynitride system offers the possibility to obtain a wide range of optical responses, by combining metallic aluminium, aluminium oxide and aluminium nitride properties, and thus opening a significant number of possible applications. The main purpose of the present work is to study the variation of the optical properties of AlNxOy thin films as a function of their composition (by varying both x and y coefficients), and the correspondent changes in their morphology and structure. The films were deposited by DC reactive magnetron sputtering, with the discharge parameters monitored during the deposition in order to control the chemical composition. The measurements reveal a smooth change of films Reflectance/Transmittance as a function of the concentration ratio of non metallic elements (O+N) to metallic Al, thus revealing the possibility to tailor the films optical properties according to the application envisaged.
Neural correlates of the Extreme Male Brain theory in adolescents with and without autism spectrum disorders

NEURAL CORRELATES OF THE EXTREME MALE BRAIN THEORY IN ADOLESCENTS WITH AND WITHOUT AUTISM SPECTRUM DISORDERS Audrey Meyer Carson, M.S. Marquette University, 2013 The Extreme Male Brain (EMB) theory (Baron-Cohen, 2003) is a behavioral theory of autism spectrum disorders (ASD), suggesting that the triad of behavioral impairments in ASD can be conceptualized psychologically as impairment in empathizing, coupled with a superior capacity for systemizing. Despite studies of the behavioral manifestations of this theory, it lacks neurological findings, specifically evidence of less coordinated activity between the left and right hemisphere in ASD (i.e. more lateralized activity). This study attempted to investigate neural correlates of the EMB theory utilizing EEG coherence, an index of neural connectivity, to determine if a more lateralized profile exists in the brain of adolescents with ASD compared to typically developing teens. In addition, relationships among coherence values and behavioral data were explored, and group membership was predicted using a “traditional model” of ASD characteristics (social skills and ratings of autism symptomatology) and an “EMB theory model” (EEG coherence and behavioral ratings of empathizing and sympathizing). Results revealed that teenagers with ASD displayed decreased coherence between the left and right frontal lobes in the alpha and theta frequency bands, while coherence between the frontal and temporal-parietal lobes within each hemisphere did not differ from typically developing teens at any frequency band. This pattern of results suggests that teens with ASD displayed a more lateralized profile, consistent with the EMB theory. Also, increased frontal-frontal coherence at the alpha and theta frequencies was associated with increased social skills in the total sample. In addition, the EMB model and the traditional characteristics model did not differ in their ability to correctly classify the groups, as a significant difference between the percent classified by each group did not emerge. Taken together, it seems that male adolescents with ASD display a more lateralized neural profile with less connectivity between the hemispheres than their typically developing peers. This pattern provides neural support for the EMB theory of autism, while also highlighting a potentially important neural marker for ASD.
Application of the Unscented Transformation to Obtain Target Range, Bearing, Elevation, Range Rate, Speed and Course Estimates and Errors From Tracks Given in Cartesian Coordinates

Abstract : The unscented transformation is applied to tracks given in Cartesian coordinates to obtain target range, bearing, elevation, range rate, speed and course estimates, and their associated errors. This approach is attractive because it does not require tedious closed-form mathematical derivations, is not computationally expensive, and does not require a pseudo-random number generator. Example code and results are given to demonstrate the applicability of the approach.
Automatic Playlist Generation and Music Library Visualisation with Timbral Similarity Measures

The size of personal digital music collections has grown significantly over the past decade, but common consumer media players offer limited options for library browsing and navigation. Various experimental prototypes implement visualisations derived from both content-based and contextual song features, but their lack of integration into existing media software prevents evaluation of such systems across a widespread user base. This project introduces the first content-based music library visualisation implemented as an extension to an existing consumer software media player. The SoundBite add-on for Songbird media player exploits timbral audio similarity measures to facilitate two-dimensional map and network-based navigation and browsing of personal music collections. The similarity measures also support automatic playlist generation within Songbird. Incorporating previous work in timbre modelling, this project evaluates statistical dimensionality reduction techniques in the audio similarity domain with a focus on minimising computational requirements. The realised system achieves a high quality twodimensional representation of a higher dimensional similarity space without exceeding the computational or memory constraints imposed by the media player environment. SoundBite for Songbird provides an entry point for real world consumer adoption of experimental music browsing and navigation methods that have previously been limited to prototype systems and small-scale user evaluations. Feedback from the Songbird user community will provide insight into the merits of content-based visualisation in the digital music marketplace, and SoundBite will provide users with a new interactive context for exploration of their music collections.
Design of a Dual-Polarized Wideband Conformal Loop Antenna for Capsule Endoscopy Systems

This paper presents a dual-polarized conformal loop antenna for capsule endoscopy systems. The antenna is designed on the capsule shell, with two orthogonal counterparts to generate dual-polarized radiation. This design exhibits broad impedance bandwidths of 271 and 247 MHz for each port, covering the entire Medical Device Radiocommunications Service band as well as the 433.05–434.79 MHz Industrial Scientific Medical band. Due to the highly orthogonal current distributions of the proposed structure, an isolation of higher than 33 dB is achieved among the operating frequency bands in measurement. The dual-polarized antenna also shows an omnidirectional radiation property and a low cross-polarization level of around −40 dB, which helps to enhance communication quality, regardless of position and orientation. Whether other electronics and biocompatible coatings are included or an electromagnetic interference shielding is considered, the antenna still presents a robust performance. The cubic tissue phantom model is utilized for the initial design and optimization of the antenna structure. Moreover, the CST voxel human model is applied to study the conformal antenna in a realistic environment. Measurements are implemented using a solid tissue-mimicking phantom, and performances consistent with theoretical predictions are achieved. Finally, the wireless biotelemetry property is evaluated via the calculation of the communication link budget with an external antenna.
Treatment of Alopecia Areata in Mice by Stimulating the Hair Follicles Using Parathyroid Hormone Agonists Linked to a Collagen Binding Domain

Abstract Alopecia Areata is a patchy hair loss from autoimmune-mediated destruction of hair follicles, for which there is no adequate therapy. PTH-CBD is a fusion protein of parathyroid hormone and a bacterial collagen-binding domain, providing targeted delivery of a hair cycle stimulator to skin and promoting hair growth. Objectives: We tested the effects of PTH-CBD on hair growth in an established animal model for alopecia areata, the C3H/HeJ engrafted mouse. Methods: C3H/HeJ engrafted mice (Jackson Laboratories, Bar Harbor, ME) were treated subcutaneously for 8 weeks with either vehicle or different doses of PTH-CBD (320 mcg/kg x1, 1000 mcg/kg x1 or 1000 mcg/kg/wk). Results: Vehicle animals showed progressive hair loss, as expected. In PTH-CBD treated animals, grey scale quantification showed a greater proportion of PTH-CBD treated animals without significant hair loss at the end of the 2 month period (18/22 PTH-CBD vs. 4/11 vehicle), with no observed differences between the different PTH-CBD treatment regimens. Histological examination revealed no change in CD8+ cells, but there was a marked increases in the number of anagen VI hair follicles in PTH-CBD treated animals. There were also increased levels of betacatenin, a known initiator of the hair cycle, observed around the bulge region of hair follicles. Conclusions: C3H/HeJ engrafted animals treated with PTH-CBD showed rapid and persistent improvements in hair growth in the majority of tested animals. There were marked increases in anagen hair follicles despite an ongoing immune reaction. Increased beta catenin levels suggest that PTH-CBD stimulates hair growth by activating the Wnt pathway.
A Scalable Heterogeneous Parallel SOM Based on MPI / CUDA

Self-Organizing Map (SOM) is a kind of artificial neural network used in unsupervised machine learning, which is widely applied to clustering, dimension reduction and visualization for high-dimensional data, etc. There are two major versions of the training algorithm: original algorithm and batch algorithm. Compared with the original, the batch algorithm has some advantages including faster convergence and less computation, and is suitable for parallelization. However, it is still confronted with the challenge of efficiency in the case of massive data, high-dimensional data or a large-scale map. In this paper, a scalable heterogeneous parallel SOM based on the batch algorithm is proposed which combines process-level and thread-level parallelism by MPI and CUDA. To boost the parallel efficiency on GPUs and make full use of the high floating-point computing capability, we design matrix operations for the the most time-consuming steps, the computation of best match units and weights update, making the steps available for the implementation by cuBLAS. In addition, the memory optimization methods are adopted. The experiments show that the proposed heterogeneous parallel SOM is effective, efficient and scalable.