Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Statement for Lucas Kovar 1

My research interests have revolved around creating realistic animated humans. Animated humans are important to a variety of applications, including: entertainment, where they appear as characters in games and as special effects in movies; training simulations, which are used by the military to prepare soldiers and by industry to instruct workers in using equipment; and visualization aids, such as for medical analysis (studying an injured person’s gait) and equipment design (determining if controls can be comfortably accessed). My thesis work focused specifically on animating realistic human motion; that is, having characters move correctly, regardless of how (for example) their skin and clothing looks. This is a challenging problem for two reasons. First, human motion is intrinsically complicated. The human body is an intricate structure containing hundreds of individual bones and muscles, and it is capable of both subtle movements (such as shrugging shoulders) and highly dynamic motions (such as a back flip). Second, people are natural experts on human motion. Having seen other people move our entire lives, we are highly attuned to the subtleties of human movement, and casual viewers can readily identify even minor inaccuracies in animated motion. A popular way of animating realistic motion is to use a technology called motion capture, which obtains accurate 3D recordings of the movement of a live performer. However, by itself motion capture offers no control over what a character does; much like a video, it can only be used to play back the original performance. My thesis shows how to use motion capture data to build generative models that provide high-level control over a character’s actions, while preserving the realism of the original data. For example, an artist might ask a character to walk down a path and open a door, and the model would handle the details of constructing appropriate walking and door-opening motions. The single most important contribution of my existing research is the development of automated methods that make it feasible to work with large data sets. This is crucial because data-driven models can only reliably produce motion “near” the original examples, and hence expressive models require large amounts of data. My thesis work provides a comprehensive set of techniques that span multiple levels of focus, from enforcing low-level kinematic properties during motion synthesis, to building models that can synthesize entire motions at once, to providing intuitive high-level interfaces for creating motions with specific properties.
histone demethylase KDM 2 B upregulates histone methyltransferase eZh 2 expression and contributes to the progression of ovarian cancer in vitro and in vivo

and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). OncoTargets and Therapy 2017:10 3131–3144 OncoTargets and Therapy Dovepress
Tramadol Pharmacology Relevant to Drug Abuse Assessment

There is no direct answer to this question. The classification of a substance as an ‘opioid’ depends on (1) the substance’s affinity for opioid receptors in vitro and (2) the substance’s display of morphine-like effects in vivo. The antinociceptive effect of tramadol in animals and the analgesic effect of tramadol in humans has been demonstrated in multiple studies to be produced by the combined contribution of both opioid, and non-opioid, analgesic mechanisms (e.g., Hennies et al., 1988; Raffa et al., 1992; Kayser et al., 1992; Desmeules et al., 1996; Oliva et al., 2002; Barann et al., 2006; Berrocosco et al., 2006; Ide et al., 2006). Tramadol itself has very little affinity for opioid receptors. For example, the binding affinity of tramadol for cloned human μ opioid receptors is 2.4 μM (Gillen et al., 2000) and it is even less for δ or κ opioid receptors (Raffa et al., 1992). For comparison, the binding affinity of morphine in the same study was 0.62 nM, more than 2 orders of magnitude greater (400-fold) than tramadol. Tramadol’s affinity is too low to be considered an opioid by many pharmacologists and, in fact, is too low to be detected in most modern high-throughput screens for opioids. Further, tramadol does not produce several characteristic opioid effects (e.g., Preston et al., 1991). However, tramadol is metabolized (via CYP450-2D6) to O-demethyl tramadol (Lintz et al., 1981; Paar et al., 1992; Subrahmanyam et al., 2001; Wu et al., 2002), designated the M1 metabolite, which has significant affinity for opioid receptors. For example, the affinity of M1 for cloned human opioid receptors is 5.4 nM and this activity is primarily due to the (R)-(+) enantiomer of M1 (3.4 nM) (Gillen et al., 2000). This is about 1/10 the affinity of morphine for μ opioid receptors:
Better indicators for better regulation: the OECD iREG experience

Los Indicadores de Política y Gobernanza Regulatoria(iREG) de la OCDE figuran entre los principales indicadores mundiales de mejora de la regulación. Miden el progreso de los países de la OCDE en la implementación de prácticas de política regulatoria como se aconseja en la Recomendación de 2012 sobre Política y Gobernanza Regulatoria y cubren en detalle los requisitos y prácticas en las áreas de involucración de partes interesadas, evaluación de impacto regulatorio (RIA) y evaluación ex post. Este artículo describe cómo la OCDE desarrolló estos indicadores en cooperación con sus países miembros, presenta los hallazgos clave de la edición 2018 de iREG y reflexiona sobre los factores críticos de éxito que los convirtieron en una herramienta de valor incalculable para impulsar la reforma regulatoria.
’ s repository of research publications and other research outputs Email shape analysis Conference or Workshop Item

Email has become an integral part of everyday life. Without a second thought we receive bills, bank statements, and sales promotions all to our inbox. Each email has hidden features that can be extracted. In this paper, we present a new mechanism to characterize an email without using content or context called Email Shape Analysis. We explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering, and social-context based finger printing. Our in-depth analysis of botnet detection leads to very high accuracy of tracing templates and spam campaigns. However, when it comes to spam filtering we do not propose new method but rather a complementing method to the already high accuracy Bayesian spam filter. We also look at its ability to classify individual senders in personal email inbox’s.
Rotation, spectral variability, magnetic geometry and magnetosphere of the Of?p star CPD -28° 2561

We report magnetic and spectroscopic observations and modeling of the Of? p star CPD−28 ◦ 2561. Using more than 75 new spectra, we have measured the equivalent width variations and examined the dynamic spectra of photospheric and wind-sensitive spectral lines. A period search results in an unambiguous 73.41 d variability period. High resolution spectropolarimetric data analyzed using Least-Squares Deconvolution yield a Zeeman signature detected in the mean Stokes V profile corresponding to phase 0.5 of the spectral ephemeris. Interpreting the 73.41 d period as the stellar ro tational period, we have phased the equivalent widths and inferred longitudinal field measurem ents. The phased magnetic data exhibit a weak sinusoidal variation, with maximum of about 565 G at phase 0.5, and a minimum of about -335 G at phase 0.0, with extrema approximately in phase with the (double-wave) Hα equivalent width variation. Modeling of the Hα equivalent width variation assuming a quasi-3D magnetospheric model produces a unique solution for the ambiguous couplet of inclination and magnetic obliquity angles: (i,β) or (β, i) = (35 ◦ , 90 ◦ ). Adopting either geometry, the longitudinal field variation yields a dipole polar inten sity Bd = 2.6± 0.9 kG, consistent with that obtained from direct modelling of the Stokes V profiles. We derive a wind magnetic (%) (%)
AN IMPLANT FOR A VISUAL CORTICAL STIMULATOR

We present the design of an implantable micro-stimulator intended for a cortical visual prosthesis. The device is composed of several integrated modules to be assembled on a thin and flexible substrate providing placement flexibility on the cortex. The stimulator provides the user with significant usage flexibility, supplying biphasic current pulses using either monopolar or bipolar configurations, with single or distributed return electrode, and having a fixed or dynamic reference voltage. Monitoring of electrode-tissue interface condition is possible by measuring both simulation currents and voltages at any electrode for enhanced safety, and for enabling troubleshooting after implantation. In order to avoid erroneous stimulation to be executed, potentially caused by the implant's wireless transcutaneous power transfer, constant parameters stored in volatile memory are constantly monitored, and in case of data corruption, stimulation is automatically disabled. A power efficient recovery and regulation circuit is proposed for providing dual supply voltages. Also, a bidirectional wireless link with data rates up to 1.5 Mbps and 500 kbps, downlink and uplink respectively, has been designed for use with a 13.56 MHz carrier. Performances attained with a prototype, combined with the stimulator module's configurable communication protocol, are suitable for a cortical implant having more than 1000 stimulation sites, which is expected to be sufficient for providing blind subjects with a useful vision.
Nonparametric Density Estimation with a Parametric Start

The traditional kernel density estimator of an unknown density is by construction completely nonparametric in the sense that it has no preferences and will work reasonably well for all shapes. The present paper develops a class of semiparametric methods that are designed to work better than the kernel estimator in a broad nonparametric neighbourhood of a given parametric class of densities, for example, the normal, while not losing much in precision when the true density is far from the parametric class. The idea is to multiply an initial parametric density estimate with a kernel-type estimate of the necessary correction factor. This works well in cases where the correction factor function is less rough than the original density itself. Extensive comparisons with the kernel estimator are carried out, including exact analysis for the class of all normal mixtures. The new method, with a normal start, wins quite often, even in many cases where the true density is far from normal. Procedures for choosing the smoothing parameter of the estimator are also discussed. The new estimator should be particularly useful in higher dimensions, where the usual nonparametric methods have problems. The idea is also spelled out for nonparametric regression.
Associations of student characteristics to measures of introductory Pascal computer programming achievement for suburban community college students (abstract only)

The purpose of the study was the construction and testing of student characteristic models for predicting the performance of 162 students on several dependent measures of computer programming achievement under generic setting and treatment conditions. The dependent measures were tests for program reading and writing, lab problems, composite performance and relative course success categories. Student characteristics were measured within the categories of demography, academic background, ability and personality; ability measures included iconic pattern detection, vocabulary, analogies and algorithmic and quantitative problem solving; personality measures included self-assessments of abilities, motivations and computer attitudes, and Gittenger's cognitive style. The predictor models accounted for 59%, 56%, 27% and 64% of the variance for the reading, writing, lab and composite measures of programming achievement, respectively. The composite achievement model also placed students into course success categories with 87% accuracy. The analysis results led to the following conclusions:Different sets of student characteristics were associated with the dependent measures; the strongest linkages were quantitative ability and high school grades to reading, verbal ability, negative computer attitudes inverse and achievement motivation to writing, age, introvert/regulated cognitive style and female gender to lab, and a blend of ability and personality measures to composite performance. Ability and personality were more effective than previous academic performance in predicting course achievement. Both iconic pattern detection ability and self-assessed math ability enhanced performance. Students with basic introvert/regulated cognitive style performed significantly better than students with extrovert/flexible style. High school computer coursework, positive computer attitudes and self-assessed programming ability were all unrelated to performance. Both students who dropped and those who finished with low achievement had similar characteristics; low ability levels and negative computer attitudes were the primary predictors of poor performance.
Adaptive information retrieval system based on fuzzy profiling

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.
OFQ reverses the κ‐opioid receptor‐mediated depression of calcium current in rat dorsal root ganglion neurons

SINCE the characterization of orphanin FQ (OFQ), the endogenous ligand of ORL1 receptor, much work has focused on its physiological functions. OFQ was reported to antagonize the effect of opioid-induced antinociception, although its mechanism remains obscure. In the present study, whole-cell patch clamp recording technique was used to observe if OFQ can reverse the inhibition of calcium current produced by the κ-opioid agonist U50,488H (U50) in acutely dissociated rat DRG neurons. The concentrations of OFQ and U50 were 50 nM and 10 μM, respectively. Among 49 cells recorded, the calcium channel currents of 37 (75.5%) cells were inhibited by U50, of which 30 (81.1%) cells could be reversed by OFQ. It was interesting to note the similarity between OFQ and the well characterized anti-opioid peptide CCK-8 in that it reversed κ-opioid receptor agonist induced suppression on calcium channel current, while by itself showed a calcium channel suppressive effect. Thus OFQ may be regarded as another anti-opioid peptide.
A geometric alternative to Nesterov accelerated gradient descent

In this lecture we will look at one of the approaches for optimizing smooth and strongly convex functions. The gradient descent has the convergence rate of 1 − 1 κ . The famous and widely-used Nesterov’s accelerated gradient descent (AGD) has quadratically faster convergence rate compared to classic gradient descent: 1 − 1 √ κ . This is an optimal rate of convergence among the class of first-order methods, [5, 6]. However, Nesterov’s AGD has no physical interpretation and is hard to understand. There have been multiple attempts to provide an intuition behind Nesterov’s AGD [1, 4, 7, 3] Today we will look at the method proposed by Bubeck et al. [2], which provides a simple geometric interpretation and achieves the optimal convergence rate.
Applying Graph Algorithms to Text Segmentation

Text segmentation is an important aid in Natural Language Processing (NLP). Applications can be found in text summarization, information retrieval, and anaphora resolution. Previous works on text segmentation mainly focused on lexical cohesion to divide texts into segments. This thesis suggests two algorithms which analyze semantic graphs for that purpose. The goal of this idea is to enhance text segmentation with more semantic information than it has been done in other works. Three main goals are pursued in this thesis: First, related work on the topic of text segmentation is presented, analyzed, and classified into categories which indicate the methods that are used to determine segment boundaries. Second, two new segmentation algorithms are presented which are based on semantic graphs. Cluster Blocks tries to find segments in the text according to topical clusters of the semantic graph. Compact Segments identifies an optimum segmentation with respect to the two criteria Compactness and Boundary Strength which are analyzed for every possible segment of a text: Compactness pertains to the strength of semantic relatedness values within the segment candidate, and Boundary Strength indicates the weakness of semantic relatedness values between terms within and outside the candidate. Finally, an evaluation reveals the quality of the new approaches compared to existing ones by use of the evaluation metrics Pk and WindowDiff. Compact Segments proves to be able to keep up with state-of-the-art algorithms for smaller documents. Four different evaluation corpora have been used one of which, a Wikipedia-based corpus, has been designed and generated for this thesis.
Tendencies and Characteristics of Financial Distress: An Introductory Comparative Study among Three Industries in Albania

Due to the presence fiscal evasion and the lack of publicly available financial statements, one of the least studied characteristics of the Albanian entrepreneurship activities during the last 25 years has been the bankruptcy potential. Considered as the leading business sector of the local economy, this research studies the financial distress characteristics of the energy, telecommunication, and construction sector in the Albanian economy. Due to the lack of financial market data, and bureaucratic loopholes in the Albanian legal framework, the methodology employed is in line with Altman (2000) for predicting financial distress. The probability of default of the Albanian corporations, considered in this paper, is assessed based on the Zâ€² and Zâ€³ methodology, according to which the driving factors to financial distress are liquidity, profitability, productivity, leverage, and the sales generating the ability of the assets of companies considered in this research. The insolvency tendencies and characteristics of the three industries are analyzed in this research. The source of data is the National Registration Center (NRC) of Albanian businesses, for Albanian "VIP" companies, as classified from the Albanian Tax Authority. None of the sectors in the study can be classified as default, based on the samples analyzed and the models employed. Telecommunication shows the lowest exposure to default in the most recent year. The liquidity and leverage of the sector decreases the probability of default. All ratios show a gradual decrease of the financial health for energy, while the construction sector ratios seem more volatile from year to year. The difficulty in identifying bankruptcy cases is one of the limitations of this study. A natural extension of this study might be the quantitative bankruptcy modeling of Albanian companies. Factor loadings of the explanatory variables may change from the original models of Altman Zâ€² and Zâ€³.
Low Voltage Power Supply in Modular Multilevel Converter based Split Battery Systems for Electrical Vehicles

Usually the low voltage power supply in electric vehicles is generated out of the high voltage DC-BUS by a dedicated DC/DC converter. When substituting the conventional drive train/motor converter by a modular multilevel converter with split batteries, this DC-BUS is obliterated. In this paper we introduce an approach to generate this low voltage supply efficiently based on the modular concept. By adding just, a single capacitor based module to each converter arm, a solution for an efficient bidirectional energy exchange between the low voltage power supply and the traction battery can be realized. The comparison to state-of-the art solutions shows that the new approach enables an efficient integration not only of the low voltage power supply, but of any energy consumer and producer into split Battery Storage Systems. It will be shown by simulations and measurements on a first prototype, that an implementation based on that technology enables a power exchange in any operation point of the electrical vehicle.
Programiranje i primjena inovatinog ekspernog susatava ekološkog uzgoja bilja za potrebe obiteljskih poljoprivrednih gospodarstava Hrvatske

Inovativni ekspertni sustav – računalna aplikacija “AgBase – Priručnik za ekološki uzgoj bilja – opća načela i agrotehnika (tehnologija) ekološkog uzgoja bilja” sadrži cjelovitu i sažetu tehnologiju (agrotehniku) povrćarskih i ratarskih kultura na ekološki način te opća načela proizvodnje bilja, temeljna načela biodinamičke poljoprivrede (BD) i opća načela uzgoja bilja. Ova računalna aplikacija je izrađena kreirana u CSS-u po standardu CSS3, te Javascript tehnologiji i u sustavu prikladnom za WEB sučelje. U svijetu je sličan način prikazivanja vrlo zastupljen, jer je riječ o ekspertnim sustavima u ekološkom načinu uzgoja bilja (poljoprivredi), pogodnim za postavljanje na internetska sučelja. Na taj se jednostavan za uporabu i inovativan način omogućuje potencijalnim korisnicima brz pristup saznanjima o novim sortama, agrotehničkim zahvatima te nizu drugih korisnih informacija o profitabilnom uzgoju bilja. Izrađena je digitalna baza ekološkog načina uzgoja i temeljnih načela ekološke proizvodnje bilja, iz kojih su realizirani digitalni priručnici za potrebe obiteljskog gospodarstva. Otvaranjem aplikacija pojavi se grafičko sučelje (frame) s nizom izbornika vezanih za pojedine teme i padajuće menije. U svega nekoliko sekundi moguć je pristup svim temama od interesa za korisnike. Cilj kreiranja ovakvog ekspertnog sustava bio je omogućiti velikom broju poljoprivrednih proizvođača korištenje znanja koje inače posjeduje jedna osoba – stručnjak/znanstvenik. Ekspertni sustavi značajni su zbog sadržaja i ažuriranja značajne količine informacija. Ujedno ovakvi sustavi u praksi značajno smanjuju i troškove obuke zaposlenika. Iz navedenog su realizirana tri digitalna priručnika za potrebe obiteljskih gospodarstava (AgBase I. – Digitalni priručnik za ekološki uzgoj bilja – Opća načela ekološkog uzgoja bilja - ratarske kulture, AgBase II. – Digitalni priručnik za ekološki uzgoj bilja – Opća načela ekološkog uzgoja bilja - povrćarske kulture, te AgBase III. – Digitalni priručnik za ekološki uzgoj bilja – Tehnologija (agrotehnika) ekološkog uzgoja).
Measuring Vulnerability to Poverty

Many argue that poverty is intimately linked with 'vulnerability'. Still, there is no consensus about how to define and measure 'vulnerability'. We review theory and describe strengths and limits of recently proposed measures. We then propose a definition of vulnerability and develop a general empirical framework that combines Monte Carlo and bootstrap statistical techniques. The approach estimates the expected distribution of future expenditures for each household and then calculates vulnerability measures as a function of those distributions.