Miracle-dz/UniFAR-FTUs huggingface dataset:
RELATÓRIO DE SUSTENTABILIDADE OU RELATO INTEGRADO DAS EMPRESAS LISTADAS NA BM&FBOVESPA: FATORES DETERMINANTES DE DIVULGAÇÃO

Essa pesquisa objetivou identificar quais variaveis sao capazes de influenciar na probabilidade de publicacao do relatorio de sustentabilidade ou relato integrado pelas empresas listadas na BM&FBOVESPA nos anos de 2011 a 2014. O estudo analisou 386 companhias. Utilizou-se os modelos logit com dados empilhados e erros padrao robustos clusterizados e logit em painel com efeitos aleatorios para testar as hipoteses de que tamanho, rentabilidade, nivel de governanca corporativa, participacao no Indice de Sustentabilidade Empresarial (ISE) e setor de atuacao das empresas com atividades de alto grau de impacto ambiental influenciam positivamente na probabilidade de divulgacao de um dos relatorios citados. Como resultados, observou-se que o tamanho e a participacao da empresa na carteira do ISE impactam de forma positiva sua probabilidade de publicacao de um dos relatorios. Por outro lado, as variaveis “rentabilidade”, “nivel de governanca corporativa” e “setor” nao tiveram resultados significativos para a amostra selecionada.
Tweet Contextualization using Continuous Space Vectors: Automatic Summarization of Cultural Documents

In this paper we describe our participation in the INEX 2016 Tweet Contextualization track. The tweet contextualization process aims at generating a short summary from Wikipedia documents related to the tweet. In our approach, we analyzed tweets and created a query to retrieve the most relevant Wikipedia article. We combine Information Retrieval and Automatic Text Summarization methods to generate the tweet context.
A resolution comparison of several time-frequency representations

Two signal components are considered resolved in a time-frequency representation when two distinct peaks can be observed. The time-frequency resolution limit of two Gaussian components, alike except for their time and frequency centers, are determined for the Wigner distribution and smoothed variants of the Wigner distribution (the pseudo-Wigner distribution, the smoothed Wigner distribution, and the squared magnitude of the short-time Fourier transform). The matched-window short-time Fourier transform has the highest resolution in time-frequency; it is about 24% greater than that of the Wigner distribution. An explanation of this rather surprising result is presented. The pseudo-Wigner distribution provides more resolution in one direction than the other representations, if substantial resolution in the other direction can be sacrificed. <<ETX>>
Efficient and Accurate Statistical Analog Yield Optimization and Variation-Aware Circuit Sizing Based on Computational Intelligence Techniques

In nanometer complementary metal-oxide-semiconductor technologies, worst-case design methods and response-surface-based yield optimization methods face challenges in accuracy. Monte-Carlo (MC) simulation is general and accurate for yield estimation, but its efficiency is not high enough to make MC-based analog yield optimization, which requires many yield estimations, practical. In this paper, techniques inspired by computational intelligence are used to speed up yield optimization without sacrificing accuracy. A new sampling-based yield optimization approach, which determines the device sizes to optimize yield, is presented, called the ordinal optimization (OO)-based random-scale differential evolution (ORDE) algorithm. By proposing a two-stage estimation flow and introducing the OO technique in the first stage, sufficient samples are allocated to promising solutions, and repeated MC simulations of non-critical solutions are avoided. By the proposed evolutionary algorithm that uses differential evolution for global search and a random-scale mutation operator for fine tunings, the convergence speed of the yield optimization can be enhanced significantly. With the same accuracy, the resulting ORDE algorithm can achieve approximately a tenfold improvement in computational effort compared to an improved MC-based yield optimization algorithm integrating the infeasible sampling and Latin-hypercube sampling techniques. Furthermore, ORDE is extended from plain yield optimization to process-variation-aware single-objective circuit sizing.
Wavelet-based seamless image stitching under l1 and l2 norm

Image stitching is used to combine several individual images having some overlap into a composite image. In this paper, a novel wavelet based seamless image stitching algorithm is introduced, where the dissimilarity is defined in the gradient and curvature domain. In order to reduce the artifacts in image stitching due to the misalignment of image registration, we design a new energy function combining different norm function for different frequency subbands of wavelet transform according to the priors of multiresolution image representation. The good stitched image will optimize the energy function by efficient convex optimization algorithm. The experimental results show that our method can produce visually pleasant results when trivial misalignment exists.
An Architecture for the Analysis and Management of Security in Industrial Control Systems

The security of Industrial Control Systems (ICS) has become an important topic. Attacks such as the Stuxnet worm have shown that inadequately protecting control systems could have disastrous consequences for society. Our research focuses on the creation of a tool that aims to enhance the security of Industrial Control Systems. It will be possible for system owners and operators to model their control systems in our tool. Using formal methodologies, the tool can extract a list of vulnerabilities in the system. Users can reason about the effects on system security of component changes or newly discovered vulnerabilities.
Selective Bayesian Classifier: Feature Selection For The Naive Bayesian Classifier Using Decision Trees

It is known that Naive Bayesian classifier (NB) works very well on some domains, and poorly on some. The performance of NB suffers in domains that involve correlated features. C4.5 decision trees, on the other hand, typically perform better than the Naive Bayesian a lgorithm on such domains. This paper describes a Selective Bayesian classifier (SBC) that simply uses only those features that C4.5 would use in its decision tree when learning a small example of a training set, a combination of the two different natures o f classifiers. Experiments conducted on eleven datasets indicate that SBC performs reliably better than NB on all domains, and SBC outperforms C4.5 on many datasets of which C4.5 outperform NB. SBC also can eliminate, on most cases, more than half of the original attributes, which can greatly reduce the size of the training and test data, as well as the running time. Further, the SBC algorithm typically learns faster than both C4.5 and NB, needing fewer training examples to reach high accuracy of classification.
A mixed-methods approach to assessing actual risk readership on branded drug websites

Despite FDA requirements that drug benefits and risks be presented in a ‘fair balance’ manner, little is known about the extent to which individuals actually seek and process risk information. Self-report measures of drug risk reading show mixed results. This exploratory study investigates this topic within the context of a branded prescription drug website for a fictional seasonal allergy drug. We use a mixed-methods approach involving eye-tracking, survey and qualitative data. While approximately 80% of participants (N = 29) claimed to have read half or more of the risk information, eye-tracking measures revealed limited to no risk reading when given the opportunity to freely view the site without explicit directions to read risk information. Survey results showed minimal unaided recall and modest aided recall of risks. To gain insight into why participants failed to seek drug risk information, we analyzed retro-active think aloud post-task interviews for potential explanations and looked for expressions of social desirability, information avoidance, optimism bias and familiarity. Perceived familiarity with the health condition, its risks and companion drug options surfaced as the primary explanation for failure to seek, and subsequently process, the risk information. This perceived familiarity prompted participants to ignore the risk information and discount the commercial information source. We offer practical recommendations to encourage risk reading in light of our findings.
Relationship of secondhand smoke exposure with sociodemographic factors and smoke-free legislation in the European Union.

BACKGROUND To explore whether exposure to secondhand smoke (SHS) among non-smokers in the European Union (EU) showed any association with sociodemographic factors and/or the extent of national tobacco control policies. METHODS A secondary analysis was performed on data from 26 751 individuals ≥15 years old from 27 EU member states (EU MS), collected during the 2012 Special Eurobarometer survey (wave 77.1). Respondents were asked whether they had been exposed to SHS in eating or drinking establishments during the past 6 months, and/or in their workplace. Data on smoke-free policies were extracted from the European Tobacco Control Status Report and the European Tobacco Control Scale (TCS) in 2013. RESULTS In total, 29.0% of non-smoking participants reported being exposed to SHS in indoor areas. Males (vs. females) as well as individuals with difficulties to pay bills (vs. those with no difficulties), had significantly greater odds of being exposed to SHS in bars, restaurants and workplaces. For every unit increase of a country's score on the Smoke-free Component of the TCS (indicating greater adherence to smoke-free legislations) the odds ratio of reporting exposure to SHS was 0.82 in bars, 0.85 in restaurants and 0.94 in workplaces. CONCLUSIONS Differences in exposure to SHS clearly exist between and within EU MS, despite the fact that they all have signed the Framework Convention on Tobacco Control, with the burden found to disproportionally affect younger people and individuals with financial difficulties. Moreover, enforcement of smoke-free legislation was inversely associated with SHS exposure, highlighting the importance of enforcing comprehensive smoking bans.
A Comparison of Methods to Move Visual Objects Between Personal Mobile Devices in Different Contexts of Use

As people increasingly own multiple mobile and portable devices (such as smartphones, tablets, and laptops), situations where several devices are used together have become more common. A frequent problem in such situations is how to move virtual visual objects (such as content items or application windows) between device displays. We present a comparative evaluation of three methods for moving objects between personal mobile devices: Tray, Transfer Mode, and Device Touch. The participants' preferences of the methods in different real-life scenarios were found to strongly depend on the task and the context of use, making the design of a single optimal cross-display object movement method a challenging task. We identify several clusters of contextual factors that influenced the users' preferences. We also report more detailed differences in efficiency, novelty, learnability, physical device handling, and task completion strategies between the three methods included in the evaluation.
A robust general constrained random pattern generator for constraints with variable ordering

Constrained random verification (CRV) methodology has been identified as an efficient solution to functional verification challenges. In practical cases, it is required to implement constraints with variable ordering to put essential efforts on cared patterns. However, handling constraints with variable ordering may encounter performance degradation of pattern generation speed and distribution. To resolve these challenges, we provide a preprocessing technique to analyze solution space by adaptively splitting ranges of variables and prove the feasibility of each subspace. This analysis allows us to perform effective range-reduction to enhance pattern generation speed and ensure the desired distribution. From the experimental results, our framework outperforms a state-of-art tool with 10X speedup in average and retains better stability of performance with the increase of number of variable orders.
Caenorhabditis elegans MPP+ Model of Parkinson’s Disease for High-Throughput Drug Screenings

The neurotoxin MPTP and its active metabolite MPP+ cause Parkinson’s disease (PD)-like symptoms in vertebrates by selectively destroying dopaminergic neurons in the substantia nigra. MPTP/MPP+ models have been established in rodents to screen for pharmacologically active compounds. In addition to being costly and time consuming, these animal models are not suitable for large scale testings using compound libraries. We present a novel MPP+-based model for high-throughput screenings using the nematode Caenorhabditis elegans. Incubation of C. elegans with MPTP or its active metabolite MPP+ resulted in strong symptomatic defects including reduced mobility and increased lethality, and is correlated with a specific degeneration of the dopaminergic neurons. The phenotypic consequences of MPTP/MPP+ treatments were recorded using automated hardware and software for quantification. Incubation of C. elegans with a variety of pharmacologically active components used in PD treatment reduced the MPP+-induced defects. Our data suggest that the C. elegans MPTP/MPP+ model can be used for the quantitative evaluation of anti-PD drugs.
Rate allocation for HARQ in relay-based cooperative transmission

We analyze HARQ transmission over a fading channel with the help of a relay node. In the absence of the channel state information (CSI) at the transmitters, we establish the problem of maximizing the overall throughput of HARQ transmission by optimizing the variable transmission rate. We present a closed form of the throughput with respect to the transmission rates and use the well-known Dynamic Programming technique along with the necessary simplifications on the problem to find the optimal set of transmission rates for both the Source node and the Relay node in source-relay-destination scenario. We show that such an approach yields a significant increase in throughput compared to fixed-rate HARQ.
EFICIÊNCIA DA SELEÇÃO DENTRO DE FAMÍLIAS S4 DE MILHO-PIPOCA, VISANDO À OBTENÇÃO DE LINHAGENS/ EFFICIENCY OF SELECTION WITHIN POPCORN S4 FAMILIES, AIMING INBRED LINE DEVELOPMENT

Embora no processo de desenvolvimento de linhagens seja importante considerar a selecao de plantas em familias, sua eficiencia diminui com o aumento da endogamia. O objetivo deste trabalho foi investigar a eficiencia da selecao dentro de progenies S4, visando a obtencao de linhagens. O experimento, conduzido na Universidade Federal de Vicosa, na safra 2001/2002, foi delineado em blocos incompletos, sendo cada um formado por um grupo distinto de familias S4 da populacao de milho-pipoca Beija-Flor e duas testemunhas. As analises de variância evidenciaram variabilidade genotipica entre progenies quanto a capacidade de expansao (CE) e producao. A variância genotipica entre familias foi inferior a variância dentro de progenies, quando consideradas a CE e a producao das plantas autofecundadas. As magnitudes dos ganhos preditos e realizados evidenciaram, em geral, eficiencia da selecao dentro. A selecao de uma planta em cada progenie superior maximizou o ganho dentro realizado em CE, com ganho real positivo ou negativo em producao.
A hybrid representation for modeling, interactive editing, and real-time visualization of terrains with volumetric features

Terrain rendering is a crucial part of many real-time applications. The easiest way to process and visualize terrain data in real time is to constrain the terrain model in several ways. This decreases the amount of data to be processed and the amount of processing power needed, but at the cost of expressivity and the ability to create complex terrains. The most popular terrain representation is a regular 2D grid, where the vertices are displaced in a third dimension by a displacement map, called a heightmap. This is the simplest way to represent terrain, and although it allows fast processing, it cannot model terrains with volumetric features. Volumetric approaches sample the 3D space by subdividing it into a 3D grid and represent the terrain as occupied voxels. They can represent volumetric features but they require computationally intensive algorithms for rendering, and their memory requirements are high. We propose a novel representation that combines the voxel and heightmap approaches, and is expressive enough to allow creating terrains with caves, overhangs, cliffs, and arches, and efficient enough to allow terrain editing, deformations, and rendering in real time.
Risk Assessment of User-Defined Security Configurations for Android Devices

The wide spreading of mobile devices, such as smartphones and tablets, and their advancing capabilities, ranging from taking photos to accessing banking accounts, make them an attractive target for attackers. This, together with the fact that users frequently store critical information in such devices and that many organizations allow employees to use their personal devices to access the enterprise information infrastructure and applications, makes security assessment a key need. This paper proposes an approach for assessing the security risk posed by user-defined configurations in Android devices. The approach is based on the analysis of the risk (impact and likelihood) of user misconfiguration to harm the device or the user. The impact and likelihood values are defined based on a Multiple-Criteria Decision Analysis (MCDA) performed on the inputs provided by a set of security experts. A case study considering the user-defined configurations of 561 Android devices is presented, showing that the majority of the users neglect important and basic security configurations and that the proposed approach can be used in practice to characterize the security risk level of such devices.
Immunochemical characterization of three components of the hemidesmosome and their expression in cultured epithelial cells

Treatment of bovine tongue mucosa with 1 M KCl induced a split in the lamina densa of the basement membrane zone (BMZ). The epithelium was then separated from the underlying connective tissue. Electron microscopic analysis of the stripped epithelium revealed that hemidesmosomes and their associated intermediate filaments (IF) remain along the basal surface of the epithelium. This surface was solubilized in an SDS/urea-containing buffer. Characterization of components of this protein mixture was undertaken using human autoantibodies from bullous pemphigoid (BP) patients that have been shown to recognize hemidesmosomal plaque elements (Mutasim, D. F., Y. Takahashi, R. S. Labib, G. J. Anhalt, H. P. Patel, and L. A. Diaz. 1985. J. Invest. Dermatol. 84:47-53) and by production of mAbs. Affinity-purified autoantibodies directed against 180- and 240-kD polypeptides present in the protein preparation generated strong immunofluorescence staining patterns along the BMZ of bovine tongue mucosa. Furthermore, immunogold localization revealed that these two polypeptides are associated with the hemidesmosomal plaque. A mAb preparation directed against a 125-kD polypeptide present in this same protein mixture lamina lucida side of the hemidesmosome. Autoantibodies in BP serum samples, affinity- purified 180-kD autoantibodies and the mAb preparation generated a punctate stain along the substratum attached surface of epithelial cells maintained on glass substrata for approximately 1 wk. The spots appeared to be associated with bundles of IF in cultured mouse keratinocytes. These monospecific antibody probes should prove invaluable for the study of hemidesmosome structure, assembly, and function.
Functional Consequences of Differential O-glycosylation of MUC1, MUC4, and MUC16 (Downstream Effects on Signaling)

Glycosylation is one of the most abundant post-translational modifications that occur within the cell. Under normal physiological conditions, O-linked glycosylation of extracellular proteins is critical for both structure and function. During the progression of cancer, however, the expression of aberrant and truncated glycans is commonly observed. Mucins are high molecular weight glycoproteins that contain numerous sites of O-glycosylation within their extracellular domains. Transmembrane mucins also play a functional role in monitoring the surrounding microenvironment and transducing these signals into the cell. In cancer, these mucins often take on an oncogenic role and promote a number of pro-tumorigenic effects, including pro-survival, migratory, and invasive behaviors. Within this review, we highlight both the processes involved in the expression of aberrant glycan structures on mucins, as well as the potential downstream impacts on cellular signaling.
Broadcasting with Selective Reduction : A Poweful Model of Parallel Computation

Broadcasting with selective s€duclion (BSR) is a model ofparallel computation in which N processors hare M memory locatjons. Duritrg the cxecution of an algorithnr, several processors rnay read fiom or write to the same nremory location simultaneousi)', such that cach processor gains access to at most oile iocation. An additional type ofmenrory access is also permitted in BSR by means ofwhich all processors may gain access to ail memory locadons at th€ same time for the purpose ofwriting. At each menrotl location, a subset of the incoming broadcast data is selectcd (according to one or more appropriate selection criteria) and rcduced to one value (using an appropriate reduction opemtor). This value is finally stored in the memory location. It has been shown that BSR, while more powerful than the strongesr variant of the PRAM, nanely the COMBININC CRCW PRAM. demands no urore resources to be implemcnted than its weakest variant, namely the EREW PRAM. This chapter reviews several existing implementations of BSR. lt also presents tsSR soiutions to a variety of computational problems. These solutiohs allow us to illustrate effectively the power and elegailce ofBSR as shown by the conciseness and simplic' ity ofthe algorithms it affords. For all the problems addressed, the BSR algorithms run in constant time and use a number ofprocessors lineat in the size ofthe input. To our knowledge. BSR is the only existing model ofparallel conputation capable ofachieving these results.
A New Type of Group Blind Signature Scheme Based on Bilinear Pairings

Abstract: This paper constructs a new group blind signature scheme on the basis of CZK group signature scheme. The security of the new scheme is under the computational Diffie-Hellman problem in the random oracle model. In our scheme, to blind the group signature of CZK only adds the computation of modular addition; while the scheme in LR98 adds the computation of double discreet logarithm, root of the discreet logarithm and random permutation in order to blind the group signature of CS97. As far as the computation complexity is concerned, our scheme is more efficient than LR98.