Dynamic joint sentiment-topic model

Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different ways of accounting for such dependency information: (1) Sliding window where the current sentiment-topic word distributions are dependent on the previous sentiment-topic-specific word distributions in the last S epochs; (2) skip model where history sentiment topic word distributions are considered by skipping some epochs in between; and (3) multiscale model where previous long- and shorttimescale distributions are taken into consideration. We derive efficient online inference procedures to sequentially update the model with newly arrived data and show the effectiveness of our proposed model on the Mozilla add-on reviews crawled between 2007 and 2011. © 2013 ACM 2157-6904/2013/12-ART5 $ 15.00.

An improved memory management scheme for large scale graph computing engine GraphChi

GraphChi is the first reported disk-based graph engine that can handle billion-scale graphs on a single PC efficiently. GraphChi is able to execute several advanced data mining, graph mining and machine learning algorithms on very large graphs. With the novel technique of parallel sliding windows (PSW) to load subgraph from disk to memory for vertices and edges updating, it can achieve data processing performance close to and even better than those of mainstream distributed graph engines. GraphChi mentioned that its memory is not effectively utilized with large dataset, which leads to suboptimal computation performances. In this paper we are motivated by the concepts of 'pin ' from TurboGraph and 'ghost' from GraphLab to propose a new memory utilization mode for GraphChi, which is called Part-in-memory mode, to improve the GraphChi algorithm performance. The main idea is to pin a fixed part of data inside the memory during the whole computing process. Part-in-memory mode is successfully implemented with only about 40 additional lines of code to the original GraphChi engine. Extensive experiments are performed with large real datasets (including Twitter graph with 1.4 billion edges). The preliminary results show that Part-in-memory mode memory management approach effectively reduces the GraphChi running time by up to 60% in PageRank algorithm. Interestingly it is found that a larger portion of data pinned in memory does not always lead to better performance in the case that the whole dataset cannot be fitted in memory. There exists an optimal portion of data which should be kept in the memory to achieve the best computational performance.

Anisotropic characterization of crack growth in the tertiary flow of asphalt mixtures in compression

Asphalt mixtures exhibit primary, secondary, and tertiary stages in sequence during a rutting deterioration. Many field asphalt pavements are still in service even when the asphalt layer is in the tertiary stage, and rehabilitation is not performed until a significant amount of rutting accompanied by numerous macrocracks is observed. The objective of this study was to provide a mechanistic method to model the anisotropic cracking of the asphalt mixtures in compression during the tertiary stage of rutting. Laboratory tests including nondestructive and destructive tests were performed to obtain the viscoelastic and viscofracture properties of the asphalt mixtures. Each of the measured axial and radial total strains in the destructive tests were decomposed into elastic, plastic, viscoelastic, viscoplastic, and viscofracture strains using the pseudostrain method in an extended elastic-viscoelastic correspondence principle. The viscofracture strains are caused by the crack growth, which is primarily signaled by the increase of phase angle in the tertiary flow. The viscofracture properties are characterized using the anisotropic damage densities (i.e., the ratio of the lost area caused by cracks to the original total area in orthogonal directions). Using the decomposed axial and radial viscofracture strains, the axial and radial damage densities were determined by using a dissipated pseudostrain energy balance principle and a geometric analysis of the cracks, respectively. Anisotropic pseudo J-integral Paris' laws in terms of damage densities were used to characterize the evolution of the cracks in compression. The material constants in the Paris' law are determined and found to be highly correlated. These tests, analysis, and modeling were performed on different asphalt mixtures with two binders, two air void contents, and three aging periods. Consistent results were obtained; for instance, a stiffer asphalt mixture is demonstrated to have a higher modulus, a lower phase angle, a greater flow number, and a larger n1 value (exponent of Paris' law). The calculation of the orientation of cracks demonstrates that the asphalt mixture with 4% air voids has a brittle fracture and a splitting crack mode, whereas the asphalt mixture with 7% air voids tends to have a ductile fracture and a diagonal sliding crack mode. Cracks of the asphalt mixtures in compression are inclined to propagate along the direction of the external compressive load. © 2014 American Society of Civil Engineers.

Phylogenetic analysis of within -host serially-sampled viral data

The primary goal of this dissertation is the study of patterns of viral evolution inferred from serially-sampled sequence data, i.e., sequence data obtained from strains isolated at consecutive time points from a single patient or host. RNA viral populations have an extremely high genetic variability, largely due to their astronomical population sizes within host systems, high replication rate, and short generation time. It is this aspect of their evolution that demands special attention and a different approach when studying the evolutionary relationships of serially-sampled sequence data. New methods that analyze serially-sampled data were developed shortly after a groundbreaking HIV-1 study of several patients from which viruses were isolated at recurring intervals over a period of 10 or more years. These methods assume a tree-like evolutionary model, while many RNA viruses have the capacity to exchange genetic material with one another using a process called recombination. ^ A genealogy involving recombination is best described by a network structure. A more general approach was implemented in a new computational tool, Sliding MinPD, one that is mindful of the sampling times of the input sequences and that reconstructs the viral evolutionary relationships in the form of a network structure with implicit representations of recombination events. The underlying network organization reveals unique patterns of viral evolution and could help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies. In order to comprehensively test the developed methods and to carry out comparison studies with other methods, synthetic data sets are critical. Therefore, appropriate sequence generators were also developed to simulate the evolution of serially-sampled recombinant viruses, new and more through evaluation criteria for recombination detection methods were established, and three major comparison studies were performed. The newly developed tools were also applied to "real" HIV-1 sequence data and it was shown that the results represented within an evolutionary network structure can be interpreted in biologically meaningful ways. ^

Serial evolutionary networks of within-patient HIV-1 sequences reveal patterns of evolution of X4 strains

Background The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships. Results Analysis based on the predicted networks suggests the following:: significantly stronger recombination signals (p = 0.003) for the inferred ancestors of the X4 strains, recombination events between different lineages and recombination events between putative reservoir virus and those from a later population, an early star-like topology observed for four of the patients who died of AIDS. A significantly higher number of recombinants were predicted at sampling points that corresponded to peaks in the viral load levels (p = 0.0042). Conclusion Our results indicate that serial evolutionary networks of HIV sequences enable systematic statistical analysis of the implicit relations embedded in the topology of the structure and can greatly facilitate identification of patterns of evolution that can lead to specific hypotheses and new insights. The conclusions of applying our method to empirical HIV data support the conventional wisdom of the new generation HIV treatments, that in order to keep the virus in check, viral loads need to be suppressed to almost undetectable levels.

Identification of Conserved Splicing Motifs in Mutually Exclusive Exons of 15 Insect Species

Background: During alternative splicing, the inclusion of an exon in the final mRNA molecule is determined by nuclear proteins that bind cis-regulatory sequences in a target pre-mRNA molecule. A recent study suggested that the regulatory codes of individual RNA-binding proteins may be nearly immutable between very diverse species such as mammals and insects. The model system Drosophila melanogaster therefore presents an excellent opportunity for the study of alternative splicing due to the availability of quality EST annotations in FlyBase. Methods: In this paper, we describe an in silico analysis pipeline to extract putative exonic splicing regulatory sequences from a multiple alignment of 15 species of insects. Our method, ESTs-to-ESRs (E2E), uses graph analysis of EST splicing graphs to identify mutually exclusive (ME) exons and combines phylogenetic measures, a sliding window approach along the multiple alignment and the Welch’s t statistic to extract conserved ESR motifs. Results: The most frequent 100% conserved word of length 5 bp in different insect exons was “ATGGA”. We identified 799 statistically significant “spike” hexamers, 218 motifs with either a left or right FDR corrected spike magnitude p-value < 0.05 and 83 with both left and right uncorrected p < 0.01. 11 genes were identified with highly significant motifs in one ME exon but not in the other, suggesting regulation of ME exon splicing through these highly conserved hexamers. The majority of these genes have been shown to have regulated spatiotemporal expression. 10 elements were found to match three mammalian splicing regulator databases. A putative ESR motif, GATGCAG, was identified in the ME-13b but not in the ME-13a of Drosophila N-Cadherin, a gene that has been shown to have a distinct spatiotemporal expression pattern of spliced isoforms in a recent study. Conclusions: Analysis of phylogenetic relationships and variability of sequence conservation as implemented in the E2E spikes method may lead to improved identification of ESRs. We found that approximately half of the putative ESRs in common between insects and mammals have a high statistical support (p < 0.01). Several Drosophila genes with spatiotemporal expression patterns were identified to contain putative ESRs located in one exon of the ME exon pairs but not in the other.

Estabilização de órbitas periódicas instáveis utilizando controle por modos deslizantes com compensação adaptativa

The chaotic behavior has been widely observed in nature, from physical and chemical phenomena to biological systems, present in many engineering applications and found in both simple mechanical oscillators and advanced communication systems. With regard to mechanical systems, the effects of nonlinearities on the dynamic behavior of the system are often of undesirable character, which has motivated the development of compensation strategies. However, it has been recently found that there are situations in which the richness of nonlinear dynamics becomes attractive. Due to their parametric sensitivity, chaotic systems can suffer considerable changes by small variations on the value of their parameters, which is extremely favorable when we want to give greater flexibility to the controlled system. Hence, we analyze in this work the parametric sensitivity of Duffing oscillator, in particular its unstable periodic orbits and Poincar´e section due to changes in nominal value of the parameter that multiplies the cubic term. Since the amount of energy needed to stabilize Unstable Periodic Orbits is minimum, we analyze the control action needed to control and stabilize such orbits which belong to different versions of the Duffing oscillator. For that we will use a smoothed sliding mode controller with an adaptive compensation term based on Fourier series.

O Centro de Referência da Assistência Social e a Psicanálise: efeitos de uma escuta singularizada

This paper emerged from an experience of 18 months in the CRAS – Reference Center for Social Assistance – which aroused a question about the listening of the singularity in the professional practice of Psi in the context of social assistance. The literature review revealed, on the one hand, a series of studies that aim to a discussion about of the process of professional integration of psychologists in the field of social welfare, proposing and / or analyzing practices directed towards the psychosocial assistance directed to the group and for the assurance of rights, forming citizen subjects. On the other hand, supported by a psychoanalytic perspective, we found studies that point to the importance of the singularity listening considering the subjectivity and symbolic resources of those who seek help in Basic Assistance Service. In this perspective, we aim to analyze, in a posteriori, the effects of offering a singularized listening in the context of CRAS and discuss its implications for the Psi professional practice in social institution. This is a theoretical and clinical research, based on Freudian and Lacanian psychoanalysis, in which two cases, placed as investigation boosters, are analyzed in the light of the concept of the subject. We conclude that a singularized listening allowed a significant sliding and the consequent repositioning of the subject, in each case, front to their suffering. The effects collected allowed us to affirm the importance of a singular listening in the treatment of the demands that appear within the institutional framework

Organização nuclear do sistema serotonérgico no encéfalo de morcegos Artibeus planirostris

Serotonin or 5-hydroxytryptamine (5-HT) is a substance found in many tissues of the body, including the nervous system acting as a neurotransmitter. Within the neuro-axis, the location of the majority of the 5-HT neurons is superimposed with raphe nuclei of the brain stem, in the median line or its vicinity, so that neuronal 5-HT can be considered a marker of the raphe nuclei. Serotonergic neurons are projected to almost all areas of the brain. Studies show the participation of serotonin in regulating the temperature, feeding behavior, sexual behavior, biological rhythms, sleep, locomotor function, learning, among others. The anatomy of these groups has been revised in many species, including mouse, rabbit, cat and primates, but never before in a bat species from South America. This study aimed to characterize the serotonergic clusters in the brain of the bat Artibeus planirostris through immunohistochemistry for serotonin. Seven adult bat males of Artibeus planirostris species (Microchiroptera, Mammalia) were used in this study. The animals were anesthetized, transcardially perfused and their brains were removed. Coronal sections of the frozen brain of bats were obtained in sliding microtome and subjected to immunohistochemistry for 5-HT. Delimit the caudal linear (CLi), dorsal (DR), median (MnR), paramedian (PMnR), pontine (PNR), magnus (MgR), pallidus (RPA) and obscurus (ROb) raphe nucleus, in addition to the groups B9 and rostral and caudal ventrolateral (RVL/CVL). The serotonergic groups of this kind of cheiroptera present morphology and cytoarchitecture relatively similar to that described in rodents and primates, confirming the phylogenetic stability of these cell clusters.

Contribuições para estratégia de controle aplicada à geração fotovoltaica interconectada à rede elétrica

Generation systems, using renewable sources, are becoming increasingly popular due to the need for increased use of electricity. Currently, renewables sources have a role to cooperate with conventional generation, due to the system limitation in delivering the required power, the need for reduction of unwanted effects from sources that use fossil fuels (pollution) and the difficulty of building new transmission and/or distribution lines. This cooperation takes place through distributed generation. Therefore, this work proposes a control strategy for the interconnection of a PV (Photovoltaic) system generation distributed with a three-phase power grid through a connection filter the type LCL. The compensation of power quality at point of common coupling (PCC) is performed ensuring that the mains supply or consume only active power and that his currents have low distorcion. Unlike traditional techniques which require schemes for harmonic detection, the technique performs the harmonic compensation without the use of this schemes, controlling the output currents of the system in an indirect way. So that there is effective control of the DC (Direct Current) bus voltage is used the robust controller mode dual DSMPI (Dual-Sliding Mode-Proportional Integral), that behaves as a sliding mode controller SM-PI (Sliding Mode-Proportional Integral) during the transition and like a conventional PI (Proportional Integral) in the steady-state. For control of current is used to repetitive control strategy, which are used double sequence controllers (DSC) tuned to the fundamental component, the fifth and seventh harmonic. The output phase current are aligned with the phase angle of the utility voltage vector obtained from the use of a SRF-PLL (Synchronous Reference Frame Phase-Locked-Loop). In order to obtain the maximum power from the PV array is used a MPPT (Maximum Power Point Tracking) algorithm without the need for adding sensors. Experimental results are presented to demonstrate the effectiveness of the proposed control system.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Network approaches for the analysis of resting state fMRI data

Negli ultimi anni la teoria dei network è stata applicata agli ambiti più diversi, mostrando proprietà caratterizzanti tutti i network reali. In questo lavoro abbiamo applicato gli strumenti della teoria dei network a dati cerebrali ottenuti tramite MRI funzionale “resting”, provenienti da due esperimenti. I dati di fMRI sono particolarmente adatti ad essere studiati tramite reti complesse, poiché in un esperimento si ottengono tipicamente più di centomila serie temporali per ogni individuo, da più di 100 valori ciascuna. I dati cerebrali negli umani sono molto variabili e ogni operazione di acquisizione dati, così come ogni passo della costruzione del network, richiede particolare attenzione. Per ottenere un network dai dati grezzi, ogni passo nel preprocessamento è stato effettuato tramite software appositi, e anche con nuovi metodi da noi implementati. Il primo set di dati analizzati è stato usato come riferimento per la caratterizzazione delle proprietà del network, in particolare delle misure di centralità, dal momento che pochi studi a riguardo sono stati condotti finora. Alcune delle misure usate indicano valori di centralità significativi, quando confrontati con un modello nullo. Questo comportamento `e stato investigato anche a istanti di tempo diversi, usando un approccio sliding window, applicando un test statistico basato su un modello nullo pi`u complesso. Il secondo set di dati analizzato riguarda individui in quattro diversi stati di riposo, da un livello di completa coscienza a uno di profonda incoscienza. E' stato quindi investigato il potere che queste misure di centralità hanno nel discriminare tra diversi stati, risultando essere dei potenziali bio-marcatori di stati di coscienza. E’ stato riscontrato inoltre che non tutte le misure hanno lo stesso potere discriminante. Secondo i lavori a noi noti, questo `e il primo studio che caratterizza differenze tra stati di coscienza nel cervello di individui sani per mezzo della teoria dei network.