Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribuições ao estudo de modelagem de equações estruturais na avaliação da satisfação do cliente de serviços de comunicações móveis

No mercado de telecomunicacoes as transformacoes tecnologicas das ultimas decadas aliaram-se a um cenario formado por empresas de alta tecnologia que caracterizam o setor de comunicacoes moveis pessoais em todo mundo. Neste contexto, as empresas deste setor preocupam-se cada vez mais com a competitividade, oferta de servicos, area de atendimento, demanda reprimida e a lealdade do cliente. Estudos de comportamento do consumidor pesquisam a satisfacao e lealdade de clientes como fatores basicos para relacoes bem sucedidas e duradouras com as empresas. A complexidade das relacoes entre variaveis na avaliacao da satisfacao do cliente em comunicacoes moveis pode ser adequadamente pesquisada com a utilizacao de metodos estatisticos multivariados. Essa tese analisou as relacoes causais envolvendo os antecedentes e consequentes associados a satisfacao do cliente, no segmento de comunicacoes moveis, bem como desenvolveu e validou um modelo comportamental do cliente no uso deste servico, buscando explicar as relacoes entre os construtos envolvidos: satisfacao, qualidade dos servicos, valor percebido, imagem da marca, lealdade e reclamacao. Foi estabelecida uma ampla base teorica para avaliar a importância estrategica do modelo que relaciona a influencia na satisfacao do servico com as percepcoes dos clientes e avaliada a precisao deste modelo, por meio de uma analise comparativa a utilizacao de tres metodos de estimacao dos seus parâmetros, MLE, GLS, e ULS, com o emprego de modelagem de equacoes estruturais. Foram feitas aplicacoes em analises de dados, sendo testada e avaliada empiricamente, a influencia do genero na satisfacao do cliente deste setor, alem de uma segmentacao de mercado utilizando mapas auto-organizaveis e a correspondente validacao deste processo, com modelagem de equacoes estruturais.Os resultados do estudo empirico produziram uma boa qualidade de ajustamento para o modelo teorico proposto, com evidencias do estabelecimento de uma adequada capacidade explicativa e preditiva, destacando-se a relevância da relacao causal entre a satisfacao e lealdade, em consonância com diversos estudos realizados para os mercados de comunicacoes moveis.
Standard Error Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization

In Preference-based Evolutionary Multi-objective Optimization, the decision maker is looking for alternative solutions in a limited area of the objective space. In this area, which is of special interest to the decision maker, the goal is to find a diverse, but locally focused non-dominated front. The preference information allows to focus the optimization efforts on this most relevant part of the Pareto-front, and thereby achieve a better optimization result. Simulation-based optimization is often used to model stochastic systems, and a popular method of handling their objective noise is Dynamic Resampling. The given preference information allows for better Dynamic Resampling strategies to be defined, which further improve the optimization result. In our previous work, we proposed hybrid Dynamic Resampling strategies that base their sampling allocation on multiple resampling criteria. These criteria can be, for example, the elapsed optimization time, the Pareto-rank of a solution, or its distance to the decision maker’s area of interest. In this article, the standard error of the mean objective values of solutions is introduced as a resampling criterion for multi-objective optimization, and several variance-based, hybrid Dynamic Resampling algorithms are proposed and compared with results of non-variance-based Dynamic Resampling algorithms, presented by the authors in [20, 21, 22]. For this purpose, a multi-objective extension of the Standard Error Dynamic Resampling algorithm [11] is proposed. The new variance-based hybrid Dynamic Resampling strategies are evaluated together with the Reference point-guided NSGA-II optimization algorithm (R-NSGAII) on variants of a multi-objective benchmark function with stochastic objectives. The noise strength of these new multi-objective benchmark problems varies throughout the objective space; a function property called Noise Landscape. The algorithm performance is evaluated on noise landscapes with different types of challenges.
ASCA X-ray observations of the disk wind in the dwarf nova Z Camelopardalis

We present ASCA observations of the dwarf nova Z Camelopardalis during outburst and during a transition from quiescence to another outburst. At the beginning of the transition the X-ray count rate was an order of magnitude higher and the spectrum much harder than during the outburst. As the transition progressed, the spectrum remained hard as the X-ray flux decreased by a factor of 3, with no spectral softening. Spectral modelling reveals an optically-thin, high-temperature component (kT$\approx$10 keV) which dominates the transition observation and is also observed during outburst. This is expected from material accreting onto the white dwarf surface. The outburst spectra require additional emission at lower temperatures, either through an additional discrete temperature component, or a combination of a cooling flow model and an ionised absorber. Fits to both observations show large amounts of absorption ($N_H=8-9\times10^{21}$cm$^{-2}$), two orders of magnitude greater than the measured interstellar value, and consistent with UV measurements of the outburst. This suggests that a disk wind is present even in the earliest stages of outburst, possibly before the outburst heating wave has reached the boundary layer.
Die Effekte von Cannabis und Ecstasy auf die neurokognitive Hirnfunktion beim Menschen

Cannabis und Ecstasy (MDMA) sind die am haufigsten konsumierten illegalen Drogen, wobei sich besonders hohe Pravalenzraten unter jungen Erwachsenen finden. Tierexperimentelle Studien belegen das schadliche und potentiell neurotoxische Potential beider Substanzen. Bisherige Studien mit Konsumenten ergaben Hinweise auf Auffalligkeiten in der kognitiven Leistungsfahigkeit und der zugrundeliegenden kognitiven Hirnfunktion. Eine eindeutige Interpretation der Ergebnisse wird allerdings durch methodische Probleme bisheriger Studien erschwert. Ziel der hier vorgelegten Arbeit war es, mittels funktioneller Kernspintomographie (fMRT) zu untersuchen, ob der Konsum von Ecstasy und Cannabis zu nachhaltigen Veranderungen in der kognitiven Hirnfunktion beim Menschen fuhrt. In der ersten Studie wurde untersucht, ob der Konsum von Cannabis in der Adoleszenz zu Storungen in der normalen Hirnentwicklung fuhren kann. Dabei zeigten erwachsene Cannabis-Konsumenten mit adoleszentem Konsumbeginn relativ zu Konsumenten mit spaterem Konsumbeginn erhohte parietale Aktivierung wahrend der Bearbeitung einer Arbeitsgedachtnisaufgabe. In einer zweiten Studie wurde untersucht, welchen spezifischen Einfluss das Einstiegsalter, die Konsumhaufigkeit und die Konsumdauer auf gedachtnisassoziierte hippokampale Funktion bei Cannabis Konsumenten haben. Hier zeigte sich ein spezifischer Zusammenhang zwischen hoherer Konsumhaufigkeit und erhohter parahippokampaler Aktivierung. In der dritten Studie wurde mittels eines prospektiven Langsschnitt-Designs der Effekt von Ecstasy auf die kognitive Hirnfunktion bei beginnenden Konsumenten untersucht. Hier zeigte sich bei Probanden, welche in den 12 Monaten zwischen den Messungen einen relevanten Konsum entwickelt hatten, eine relativ verminderte gedachtnisassoziierte parahippokampale Aktivierung. Zusammenfassend ergaben sich bzgl. Cannabis: (1) Hinweise auf eine erhohte Vulnerabilitat des adoleszenten Gehirns fur nachhaltige Effekte, (2) Hinweise auf spezifische Einflusse der Konsumhaufigkeit auf hippokampale Auffalligkeiten bei Cannabis-Konsumenten. Bzgl. Ecstasy deuten die Ergebnisse (1) einen direkten Zusammenhang mit veranderter Hirnfunktion, (2) sowie eine erhohte Vulnerabilitat der Hippokampalen Formation an.
A Plug&Play P300 BCI Using Information Geometry

This paper presents a new classification methods for Event Related Potentials (ERP) based on an Information geometry framework. Through a new estimation of covariance matrices, this work extend the use of Riemannian geometry, which was previously limited to SMR-based BCI, to the problem of classification of ERPs. As compared to the state-of-the-art, this new method increases performance, reduces the number of data needed for the calibration and features good generalisation across sessions and subjects. This method is illustrated on data recorded with the P300-based game brain invaders. Finally, an online and adaptive implementation is described, where the BCI is initialized with generic parameters derived from a database and continuously adapt to the individual, allowing the user to play the game without any calibration while keeping a high accuracy.
Content-Aware Texture Synthesis

Existing example-based texture synthesis techniques are inherently unadapted to textures consisting of a set of randomly disposed, individually discernible shapes. Local methods striving at pixel-based discontinuity reduction hardly preserve input's long-range structures. Alternatively, research built upon the supposed respect by the input's features of given placement rules are too restrictive to be straightly extended to stochastic arrangements. In this paper we present a new method for analyzing and resynthesizing such arrangements. Our objective is to acquire their constitutive shapes to enable structure-aware resynthesis. What characterizes such shapes is their repetition throughout the input. We exploit this trait by recording recurrences of visually similar neighborhoods which are later extended to regions. We bring those together to compute the input's coverage map and extract final repetitive shapes. By directly manipulating shapes, resynthesis can be enriched with high-level information unavailable in pixel-based approaches. We gather statistics on their placement and appearance variations and use those to produce new images. To achieve this, we draw inspiration and improve techniques for capturing element arrangements, techniques once limited to vectorized NPR primitives.
Environmental oversight and the citizen activist: Lessons from an oral history of activism surrounding Elmira, Ontario’s 1989 water crisis

Abstract In this article, the author presents an oral history of community-based water activism in Elmira, Ontario, Canada, and draws insights from it for theory and praxis in community organization. In 1989, a group of citizens calling themselves “APT Environment” came together over a concern about chemical pollution in their community that eventually triggered the closure of municipal drinking water wells. Organizing themselves and building capacity within the group, these grassroots citizens pushed for action against considerable backlash, and emerged as a significant player in the ongoing struggle to mitigate further contamination, to have the contamination remediated, and to see environmental justice served. The story of APT Environment is one of shifting activist identities that evolve with a shifting political context. Drawing on this oral history, the author offers implications for social movement theory and for community organizing in other contexts.
An adaptive algorithm for position and linear velocity estimation of mobile robots using inertial sensors and omnidirectional vision

This paper presents a novel and effective method for estimating the position and linear velocity of a mobile robot in real-time in unknown environments by fusing visual information from an omnidirectional vision system with the measurements of an inertial sensor system. Based on a new projection model of the omnidirectional vision system, we propose a novel adaptive algorithm, similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the position and linear velocity of the robot on-line using continuously tracked natural feature points in image sequence, the robot's acceleration, angular velocity and orientation measured by inertial sensor system. It is proven that our algorithm leads to global exponential convergence of the estimation errors of the robot's position and linear velocity to zero. Experiments demonstrate the performance of the proposed algorithm.
Crystallographic refinement of ricin to 2.5 Å

The plant cytotoxin ricin consists of two disulfide‐linked chains, each of about 30,000 daltons. An initial model based on a 2.8 Å MIR electron density map has been refined against 2.5 Å data using rounds of hand rebuilding coupled with either a restrained least squares algorithm or molecular dynamics (XPLOR). The last model (9) has an R factor of 21.6% and RMS deviations from standard bond lengths and angles of 0.021 Å and 4.67°, respectively. Refinement required several peptide segments in the original model to be adjusted translationally along the electron density. A wide range of lesser changes were also made. The RMS deviation of backbone atoms between the original and model 9 was 1.89 Å. Molecular dynamics proved to be a very powerful refinement tool. However, tests showed that it could not replace human intervention in making adjustments such as local translations of the peptide chain. The R factor is not a completely satisfactory indicator of refinement progress; difference Fouriers, when observed carefully, may be a better monitor.
Fluctuation effects and multiscaling of the reaction-diffusion front for A+B to OE

We consider the properties of the diffusion-controlled reaction A+B to OE in the steady state, where fixed currents of A and B particles are maintained at opposite edges of the system. Using renormalization-group methods, we explicitly calculate the asymptotic forms of the reaction front and particle densities as expansions in (JD-1 mod x mod d+1)-1, where J are the (equal) applied currents, and D the (equal) diffusion constants. For the asymptotic densities of the minority species, we find, in addition to the expected exponential decay, fluctuation-induced power-law tails, which, for d 2, we find similar power laws with mu =d+3, but with non-universal coefficients. Logarithmic corrections occur in d=2. These results imply that, in the time-dependent case, with segregated initial conditions, the moments integral mod x mod qR(x,t) dx fail to satisfy simple scaling for q> mu +1. Finally, it is shown that the fluctuation-induced wandering of the position of the reaction front centre may be neglected for large enough systems.
Linguistic Programmes in Castilla-La Mancha: a study of teachers´, parents´ and students´ attitudes towards bilingualism in secondary education institutions

The present paper aims at examining students´, teachers´ and parents´attitudes toward bilingualism and foreign language learning in the region of Castilla-La Mancha, Spain. To do so, three types of questionnaires were designed for students, teachers and parents involved in a specific linguistic programme in two secondary education schools located in the south of Castilla-La Mancha. In particular, the study seeks to determine the relationship between bilingual education and students´ self-concept as well as their motivation towards language learning. Besides, teachers´ and parents´ attitudes towards linguistic programmes and their effect on students´ motivation are analyzed.
1 Documenting Motion Sequences : Development of a Personalized Annotation System

Kanav Kahol, Priyamvada Tripathi, Sethuraman Panchanathan Center for Cognitive Ubiquitous Computing (CUbiC) Arizona State University 699 S Mill Avenue Tempe, Arizona-85281, USA {kanav,pia,panch}@asu.edu Abstract We present a novel technique for motion annotation that adapts to a user’s style and vocabulary of basic movements, herein called gestures. Initial testing suggests that software based on this technique could be an effective aid in teaching, documentation, and dissemination of stylized motions, such as dance and sports.
Design and analysis of a two-stage CMOS op-amp using Silterra's 0.13 μm technology

This paper presents the design and analysis of a high-gain, low-power, two-stage CMOS operational amplifier (op-amp) for a sigma-delta ADC. Op-amp topologies, such as folded cascade, telescopic and two-stage, are discussed in this paper. The theoretical and topological analyses of each design are highlighted in detail, including the tradeoff among various parameters such as gain, noise, output swings and power consumption. The designs have been simulated using 0.13 μm CMOS technology from Silterra (Malaysia) with Cadence EDA tools. From the simulation results, the two-stage amplifier gives better performance compared to other topologies, especially in terms of gain, output swing, slew rate and CMRR. The circuit is able to achieve 85.93 dB gain, a 1.1 V output swing, a 44.29 V/μs slew rate and a CMRR of 61 dB with a power supply voltage of 1.2 V.
Silencing quorum sensing and ICE mobility through antiactivation and ribosomal frameshifting

Mobile genetic elements run an evolutionary gauntlet to maintain their mobility in the face of selection against their selfish dissemination but, paradoxically, they can accelerate the adaptability of bacteria through the gene-transfer events that they facilitate. These temporally conflicting evolutionary forces have shaped exquisite regulation systems that silence mobility and maximize the competitive fitness of the host bacterium, but maintain the ability of the element to deliver itself to a new host should the opportunity arise. Here we review the excision regulation system of the Mesorhizobium loti symbiosis island ICEMlSymR7A, a 502-kb integrative and conjugative element (ICE) capable of converting non-symbiotic mesorhizobia into plant symbionts. ICEMlSymR7A excision is activated by quorum sensing, however, both quorum sensing and excision are strongly repressed in the vast majority of cells by dual-target antiactivation and programmed ribosomal-frameshifting mechanisms. We examine these recently discovered regulatory features under the light of natural selection and discuss common themes that can be drawn from recent developments in ICE biology.
A Non-Line-of-Sight error mitigation method in wireless location system

A key obstacle to high accuracy location is the None Line of Sight (NLOS) transmission of signal in wireless localization. It adds positive error to distance measurements. An effective location algorithm based on nonlinear constraint optimization is proposed to mitigate NLOS errors. The proposed method forms distance error optimization constraint using the geometric relationship between the base stations and mobile station. It improves the location accuracy by calibrating the distance measurements and modifying the objective function. Simulation results show that this new method can efficiently reduce the effect of the NLOS error, and is robust to different NLOS error.
Modified MFCCs for robust speaker recognition

Mel-scale frequency cepstrum coefficients (MFCCs) are commonly used featues in speaker recognition systems, but MFCC values are not very robust in the presence of noise. thus, the modified MFCCs (named as SMN-CMN-MFCC) based on the general noisy speech model is proposed in this paper, which uses spectrum mean normalization (SMN) to suppress the additive noise, and uses cepstral mean normalization (CMN) to remove the effect of convolutional noise. Theoretical analyses show that the combination of SMN and CMN can inhibit additive and convolutional noise at the same time. To verify the performance of the SMN-CMN-MFCC, we have conducted some speaker recognition tests. With the same convolutional noise component, the additive white noise experiments and the additive factory noise experiments show that SMN-CMN-MFCC provides 10.5% and 9.6% relative improvement than the conventional MFCC and ΔMFCC features, respectively.
Content based image retrieval system with fuzzified texture similarity measurement

Content based image retrieval (CBIR) system is a database management system for retrieval of images based on the similarity of image content with the query image. In the proposed CBIR system, Tamura texture features are extracted as image content. To measure similarity of query image with images in database, a fuzzified distance measure, fuzzy hamming distance (FHD), is used. The database is sorted in the increasing order of similarity measure, and made available to user. The proposed technique is implemented in Matlab and its effectiveness is verified using the standard Bordatz texture database.
“Impossible Is Nothing”: Expressing Difficult Knowledge Through Digital Storytelling

The study focuses on a digital storytelling project conducted in a school district's transition program, in which adolescent refugee and immigrant English learners were invited to share aspects of their identities and social worlds through a range of modes. In this article, the authors look closely at one student's digital story through a multimodal analysis of three slides. The findings show how engaging with nonlinguistic modes provided enhanced opportunities for the student to explore and make visible complex and abstract facets of his life and identity, particularly as they relate to difficult past experiences.
Erythropoietin improves neurobehavior by reducing dopaminergic neuron loss in a 6-hydroxydopamine-induced rat model

The purpose of this study was to determine the effectiveness of the systemic administration of high dose erythropoietin (EPO) in a 6-hydroxydopamine (6-OHDA)- induced rat model. Rats were divided into 7 groups. Groups 1–4 were administered daily EPO doses of 0; 2,500; 5,000 and 10,000 U/kg via intraperitoneal injection (i.p.) for 5 days. The EPO concentration in cerebrospinal fluid (CSF) was determined by enzyme-linked immunosorbent assay (ELISA) and western blot analysis. The dose of 10,000 U/kg was then selected for subsequent experiments. In group 5, rats received saline via medial forebrain bundle (MFB). In group 6, rats received 6-OHDA via MFB. In group 7, an EPO concentration of 10,000 U/kg was constantly administered i.p. for 5 days to rats prior to 6-OHDA injection via MFB. Behavioral analysis was performed for groups 5–7 by rat rotation tests. The number of tyrosine hydroxylase (TH)-immunopositive cells in the substantia nigra (SN) was measured by immunocytochemistry. The activation of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), p38 mitogen-activated protein kinases (MAPKs) and caspase-3 signaling in rats were analyzed using western blotting. The results showed that there was a significant increase in EPO levels in the CSF in 10,000 U/kg group compared with the 2,500 and 5,000 U/kg groups (P<0.01). Significantly fewer rotational counts were obtained in rats that were pretreated with EPO compared with saline-pretreated 6-OHDA-lesioned rats (P<0.001). The dopaminergic neurons in the 6-OHDA-lesioned SN were also increased in the EPO-pretreated rats when compared with control rats (P<0.01). Western blot analysis revealed that EPO inhibited the 6-OHDA-induced activation of JNK, ERK, p38 MAPK and caspase-3 signaling in the rat model. In conclusion, systemic administration of a high dose of EPO exerted neuroprotective effects in reversing behavioral deficits associated with Parkinson’s disease and prevented loss of the dopaminergic neurons through the MAPK pathway.