Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Linear In uence Models in Social Networks from Transient

Social networks, forums, and social media have emerged as global platforms for forming and shaping opinions on a broad spectrum of topics like politics, sports and entertainment. Users (also called ‘actors’) oen update their evolving opinions, inuenced through discussions with other users. eoretical models and their analysis on understanding opinion dynamics in social networks abound in the literature. However, these models are oen based on concepts from statistical physics. eir goal is to establish various regulatory phenomena like steady state consensus or bifurcation. Analysis of transient eects is largely avoided. Moreover, many of these studies assume that actors’ opinions are observed globally and synchronously, which is rarely realistic. In this paper, we initiate an investigation into a family of novel data driven inuence models that accurately learn and t realistic observations. We estimate and do not presume edge strengths from observed opinions at nodes. Our inuence models are linear, but not necessarily positive or row stochastic in nature. As a consequence, unlike the previous studies, they do not depend on system stability or convergence during the observation period. Furthermore, our models take into account a wide variety of data collection scenarios. In particular, they are robust to missing observations for several time steps aer an actor has changed its opinion. In addition, we consider scenarios where opinion observations may be available only for aggregated clusters of nodes — a practical restriction oen imposed to ensure privacy. Finally, to provide a conceptually interpretable design of edge inuence, we oer a relatively frugal variant of our inuence model, where the strength of inuence between two connecting nodes depend on the node aributes (demography, personality, expertise etc.). Such an approach reduces the number of model parameters, reduces overing, and oers a tractable and explicable sketch of edge-inuences in the context of opinion dynamics. With six real-life datasets crawled from Twier and Reddit, as well as three more datasets collected from in-house experiments (with 102 volunteers), our proposed system gives signicant accuracy boost over four state-of-the-art baselines. We also observe that a careful design of edge strengths using node properties is crucial, since it oers substantially beer performance than the one with independent edge weights. CCS Concepts: •Social networks →xx; •Opinion dynamics →xx; •Linear models →xx ; •Inuence learning →xx; Additional
An improved VAT photopolymerization cure model demonstrates photobleaching effects

An improved high-fidelity simulation model for a grayscale projection micro-stereolithography process has been developed. The modeling purpose is to accurately predict cured part shapes and dimensions, given a radiation intensity distribution. The model employs COMSOL to solve a series of chemical reaction differential equations that model the evolution of chemical species (photoinitiator, monomer, and polymer) concentrations. Additionally, the model incorporates the effects of oxygen inhibition and species diffusion. This research offers two primary contributions to the cure model: the consideration of volumetric intensity to model variations in photoinitiator absorbance as a function of depth into the resin and a change to the rate model for photoinitiator to free radical conversion. The effects of these changes demonstrate observed photobleaching effects. Simulated cured part profiles are compared to experiments and demonstrate good agreement. Additionally, initial results are presented on the usage of the simulation model in a new process planning method.
Constraints and Language

The concept of "constraint" is widely used in linguistics, computer science, and psychology. However, its implementation varies widely depending on the research domain: namely, language description, knowledge representation, cognitive modelling, and problem solving. These various uses of constraints offer complementary views on intelligent mechanisms. For example, in-depth descriptions implementing constraints are used in linguistics to filter out syntactic or discursive structures by means of dedicated description languages and constraint ranking. In computer science, the constraint programming paradigm views constraints as a whole, which can be used, for example, to build specific structures. Finally, in psycholinguistics, experiments are carried out to investigate the role of constraints within cognitive processes (both in comprehension and production), with various applications such as dialog modelling for people with disabilities. In this context, Constraints and Language builds an extended overview of the use of constraints to model and process language.
Outbreaks of vesicular disease caused by Vaccinia virus in dairy cattle from Goiás State , Brazil ( 2010-2012 ) 1

Sant’Ana F.J.F. , Leal A.A. , Rabelo R.E. , Vulcani V.A. S. , Ferreira Junior J.A. , Cargnelutti J.F. & Flores E.F. 2013. Outbreaks of vesicular disease caused by Vaccinia virus in dairy cattle from Goiás State, Brazil (2010-2012). Pesquisa Veterinária Brasileira 33(7):860-866. Laboratório de Patologia Veterinária, Universidade de Brasília, Brasília, DF 70910-900, Brazil. E-mail: santanafjf@yahoo.com Cases of vesicular and exanthematic disease by Vaccinia virus (VACV) have been reported in dairy herds of several Brazilian regions, occasionally also affecting humans. The present article describes eight outbreaks of vesicular disease caused by VACV in dairy herds of six counties of Goiás state, Midwestern Brazil (2010-2012), involving a total of 122 cows, 12 calves and 11 people. Dairy cows (3 to 9 years old) were affected in all cases and calves (2 to 9 months old) were affected in five outbreaks, presenting oral lesions. The morbidity ranged between 8 and 100% in cows, and 1.5 to 31% in calves. In the cows, the clinical signs started with vesicles (2-7mm), painful and coalescent papules (3-8 mm), which resulted in ulcers (525mm) and scabs in teats, and, occasionally, in the muzzle. The clinical course lasted from 16 to 26 days. The histopathology of bovine skin samples revealed superficial perivascular inflammatory infiltrate of lymphocytes, plasma cells, neutrophils, macrophages and multifocal areas of acanthosis, spongiosis, hipergranulosis and parakeratotic or orthokeratotic hyperkeratosis with adjacent focally extensive ulcers. Eosinophilic inclusion bodies were noted in the cytoplasm of the keratinocytes. PCR to vgf gene of Orthopoxvirus was positive in samples collected from all outbreaks, and in some cases, genomic VACV sequences were identified by nucleotide sequencing of the PCR amplicons. Infectious virus was isolated in cell culture from scabs from one outbreak. Antibodies to Orthopoxvirus were detected in at least 3 or 4 animals in most outbreaks, by ELISA (outbreaks 1, 2, 3, 4, 5 and 7) or virus-neutralization (outbreak 6). Neutralizing titers ranging from 8 to 64 in outbreak 6. In all outbreaks, VACV infection was suspected based on the clinical and pathological findings and it was confirmed by laboratory tests. Upon the etiological confirmation, other agents associated with vesicular disease were discarded. In all outbreaks, at least one milker who handled the affected cows developed malaise, headache, fever, painful vesico-pustular lesions mainly in the hands, but also in the neck and nose. These results confirm the circulation of VACV in the region and call attention for a correct diagnosis and the adoption of prophylactic and control measures.
Recurrent and Dynamic Networks that Predict Streaming Video Quality of Experience

Streaming video services represent a very large fraction of global bandwidth consumption. Due to the exploding demands of mobile video streaming services coupled with limited bandwidth availability, video streams are often transmitted through unreliable, low-bandwidth networks. This unavoidably leads to two types of major streaming-related impairments: compression artifacts and/or rebuffering events. In streaming video applications, the human observer is the end-user; hence being able to predict the subjective Quality of Experience (QoE) associated with streamed videos could lead to the creation of perceptually optimized resource allocation strategies driving higher quality video streaming services. We propose a variety of recurrent dynamic networks that conduct continuous-time subjective QoE prediction. By formulating the problem as one of time series forecasting, we train a variety of recurrent neural networks and non-linear autoregressive models to predict QoE using several recently developed subjective QoE databases. These models combine multiple, diverse network inputs such as predicted video quality scores, rebuffering measurements, and data related to memory and its effects on human behavioral responses, using them to learn to predict QoE on video streams impaired by both compression artifacts and rebuffering events. Instead of finding a single time series prediction model, we propose and evaluate ways of aggregating different models into a forecasting ensemble that delivers improved results with reduced forecasting variance. We also deploy appropriate new evaluation metrics for comparing time series predictions in streaming applications. Our experimental results demonstrate improved prediction performance that approaches human performance.
SUMMARY Properties of Polyphenoloxidase and Peroxidase from Granada

1 Departamento de Ciência e Tecnologia de Alimentos, Universidade Federal de Pelotas, CP 354, CEP 96010-900, Pelotas, RS, Brazil, e-mail: torashow@cefetrs.tche. br EMBRAPA Clima Temperado, KM 78, BR 392, CP 403; CEP 960001-970, Pelotas, RS, Brazil; e-mail: vendrusc@cpact.embrapa. br Centro de Biotecnologia, Universidade Federal de Pelotas, Pelotas, RS e-mail: claire@ufpel.tche. br Departamento Bioquímica, Universidade Federal de Pelotas, Pelotas, RS Departamento de Ciência e Tecnologia de Alimentos, Universidade Federal de Pelotas, Pelotas, RS 1 Ricardo Peraça TORALLES 2* João Luiz VENDRUSCOLO 3 Claire Tondo VENDRUSCOLO 4 Francisco Augusto Burkert DEL PINO 5 Pedro Luiz ANTUNES Estudou-se o escurecimento enzimático objetivando definir a enzima mais termoestável responsável pelo escurecimento na cv. Granada, que é amplamente cultivada no Sul do Rio Grande do Sul, Brasil. A polifenoloxidase (PPO) e peroxidase (POD) foram extraídas da cultivar de pêssego Granada usando o método do pó-de-acetona, purificação parcial pela precipitação com (NH ) SO seguido de diálise. As ótimas condições de reação foram 4 2 4 estudadas usando catecol como substrato para PPO e guaiacol: H O para POD. O pH ótimo foi 2 2 6,2 em catecol e 5,0 guaiacol:H O respectivamente. A temperatura ótima para máxima 2 2 0 atividade foi 30 C e ambas enzimas foram afetadas pela desnaturação térmica, sendo a PPO mais termoestável. A PPO e POD de pêssego Granada mostraram atividade com todos substratos o-difenólicos: catecol, pirogalol, 4-metil-catecol e L-dopa. Além disso, POD oxidou o guaiacol na presença de peróxido de hidrogênio, mas a PPO não foi capaz disso. O K foi 9,7 M mM de catecol para PPO e 5,2 mM de guaiacol para POD. Na eletroforese, duas isoenzimas foram detectadas com os substratos catecol e guaiacol:H O . 2 2
Spatial and Motion Saliency Prediction Method Using Eye Tracker Data for Video Summarization

Video summarization is the process to extract the most significant contents of a video and to represent it in a concise form. The existing methods for video summarization could not achieve a satisfactory result for a video with camera movement and significant illumination changes. To solve these problems, in this paper, a new framework for video summarization is proposed based on eye tracker data, as human eyes can track moving object accurately in these cases. The smooth pursuit is the state of eye movement when a user follows a moving object in a video. This motivates us to implement a new method to distinguish smooth pursuit from other type of gaze points, such as fixation and saccade. The smooth pursuit provides only the location of moving objects in a video frame; however, it does not indicate whether the located moving objects are very attractive (i.e., salient regions) to viewers or not, as well as the amount of motion of the moving objects. The amount of salient regions and object motions are the two important features to measure the viewer’s attention level for determining the key frames for video summarization. To find the most attractive objects, a new spatial saliency prediction method is also proposed by constructing a saliency map around each smooth pursuit gaze point based on human visual field, such as fovea, parafoveal, and perifovea regions. To identify the amount of object motions, the total distances between the current and the previous gaze points of viewers during smooth pursuit are measured as a motion saliency score. The motivation is that the movement of eye gaze is related to the motion of the objects during smooth pursuit. Finally, both spatial and motion saliency maps are combined to obtain an aggregated saliency score for each frame and a set of key frames are selected based on user selected or system default skimming ratio. The proposed method is implemented on Office video data set that contains videos with camera movements and illumination changes. Experimental results confirm the superior performance of the proposed spatial and motion saliency prediction method compared with the state-of-the-art methods.
The Role of Kidney Oxygen Homeostasis for the Development of Kidney Disease

Carvalho, C. 2019. The Role of Kidney Oxygen Homeostasis for the Development of Kidney Disease. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1581. 56 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0691-9. The relation between oxygen supply and demand determines tissue oxygen tension (PO2). When intrarenal tissue PO2 decreases, any compensatory increase in oxygen supply via increased renal blood flow is likely to increase glomerular filtration rate. The resulting increased tubular load of electrolytes destined for active transport increases oxygen consumption, thus affecting intrarenal tissue PO2. Consequently, the kidney is particularly sensitive to alterations in oxygen homeostasis and kidney hypoxia is acknowledged as a common pathway to end stage renal disease. Different factors that can affect intrarenal oxygen homeostasis, including alterations in blood pressure and sodium intake dietary or pathologies such as diabetes mellitus, anemia or atherosclerosis. This thesis focuses on understanding how these factors influence kidney oxygen homeostasis. Pronounced reduction in sodium intake caused tissue hypoxia in kidney cortex via activation of the renin-angiotensin-aldosterone leading to increased tubular sodium reabsorption. Angiotensin II and aldosterone affect kidney oxygen handling differently. Whereas angiotensin II mainly affects kidney oxygen delivery, aldosterone mainly affects oxygen consumption. The hypoxia-inducible factor (HIF) system is a cellular defense mechanism against prolonged hypoxia. Although diabetes causes intrarenal hypoxia, hyperglycemia per se also prevents HIF-activation. Therefore, the effects of type 1 diabetes were evaluated in genetically modified mice with chronic HIF-activation. Diabetic mice with globally increased HIF activity, due to heterozygote prolyl hydroxylase-2 deficiency, displayed reduced mitochondria leak respiration and preserved cortical PO2. Diabetic mice with kidney-specific HIF activation, due to homozygous deficiency of von Hippel-Lindau, developed reduced mitochondria leak respiration and reduced urinary albumin excretion. The normal age-related decline in kidney function has been proposed to be due to, at least in part, increased oxidative stress, which can induce mitochondrial leak respiration via activation of uncoupling proteins. Indeed, two-year old mice deficient of uncoupling protein-2 presented with improved mitochondria efficiency and reduced urinary protein excretion. Summarizing, the data presented in this thesis provide clear support for potent influence of the renin-angiotensin-aldosterone system, HIF activation and mitochondria function on intrarenal oxygen availability. Maintaining kidney oxygen homeostasis may be a unifying strategy to protect kidney function.
People Tracking and Posture Recognition for Human-Robot Interaction

The paper deals with a system for simultaneous people tracking and posture recognition in cluttered environments in the context of human-robot interaction. We adopt no particular assumptions on the movement of a person nor on its appearance, making the system suitable to several real-world applications. The system can be roughly subdivided into two highly correlated phases: tracking and recognition. The tracking is concerned with establishing coherent relations of the same subject between frames. We adopted a version of particle filters known as Condensation algorithm due to its robustness in highly cluttered environments. The recognition phase adopts a modified eigenspace technique in order to classify between several different postures. The system has demonstrated to be robust in different working conditions and permits to exploit a rich interaction between a human user and a robotic system by means of a set of natural gestures.
Journal of Quantitative Analysis in Sports 2008 NORTHERN

The nature of the relationship Bill James found between the win/loss percentage of a Major League Baseball team and the number of runs the team scores and allows over the course of a season is investigated for the National Hockey League (NHL). We find the optimal form of James' model for the NHL using the absolute error criterion and demonstrate that far more complex forms of James' model yield little in additional predictive power. We also provide empirical evidence that the relationship between win/loss percentage and goals scored and allowed varies relatively little across recent seasons.
Molecular characterization of ascaris from Tibetan pigs by three mitochondrial markers of nad 1 , cox 1 and cox 2

Ascaris is a helminthic parasite, which infects a wide range of host species causing ascariasis, a predominant disease worldwide. This parasite causes significant economic losses to the pig industry. The current study was designed to determine the Ascaris nematode by the genetic characterization of three mitochondrial (mt) genes namely NADH dehydrogenase subunit 1 (nad1), cytochrome oxidase subunit 1 (cox1) and cytochrome oxidase subunit 2 (cox2). A high infection rate of Ascaris nematode has been found in Tibetan pigs at the slaughter houses in Tibet Autonomous Region of China. The nad1, cox1 and cox2 genes sequences collected from adult Ascaris individuals were amplified by polymerase chain reaction. The cloned-amplicons and the positive products were sequenced and phylogenetic analysis was performed. The results indicated that the Ascaris infecting the Tibetan pigs were Ascaris suum (A. suum). This is the first report on the isolation, identification and genetic characterization of three mitochondrial genomes (nad1, cox1, and cox2) of A. suum originated from Tibetan pigs at high altitudes in Tibet.
THE MEASUREMENT OF DEFORMATION OF A SILICON ELASTOMER TUBE USING DIGITAL IMAGE PROCESSING

According to the latest research the nonlinear elastic model with hysteresis is the most realistic to model the blood vessel. Relationship between the transmural pressure and external diameter of the blood vessel, modelled by a silicon elastomer tube is studied under stress. This paper focuses on the measurement method using digital image processing. Edge detection algorithms are developed using Matlab software environment to determine the diameter of the tube under specific inner pressure. Results reproduce the static and dynamic behaviour of the silicon elastomer material.
Optimization for Aiding Grasp Synthesis Algorithms using Reinforcement Learning

Worcester Polytechnic Institute, Computer Science Department, Robotics Engineering Program, 85 Prescott St, Worcester, MA-01605, USA; Pontifical Catholic University of Rio de Janeiro, Department of Electrical Engineering, R. Marquês de São Vicente, 225 Gávea, RJ, 22451-900, Rio de Janeiro; Delft University of Technology, BioMechanical Engineering Department, Mekelweg 2, 2628 CD, Delft The Netherlands.
Is inhibition implemented during bilingual production and comprehension? n-2 language repetition costs unchained

ABSTRACT Many models assume that inhibition plays an integral role during bilingual language control, a process that restricts bilingual language processing to the target language. However, there is limited evidence for such a claim. In the current study, we set out to investigate one known marker of bilingual inhibition (n-2 language repetition costs) that has, so far, mainly been investigated with digits in a production task. Hence, we ran a n-2 language repetition study with other types of stimuli (i.e. pictures and written words) in a production and a comprehension task. The results showed that n-2 language repetition costs were found with both stimulus types in a production task. In the comprehension tasks, n-2 language repetition costs were only observed with one of the two stimulus types and in only one language. These results indicate that inhibition is implemented during bilingual production, and is possible, but not necessary, during bilingual comprehension.
Low-cost time-lapse seismic with distributed Compressive Sensing — impact on repeatability

Irregular or off-the-grid spatial sampling of sources and receivers is inevitable in field seismic acquisitions. Consequently, time-lapse surveys become particularly expensive since current practices aim to replicate densely sampled surveys for monitoring changes occurring in the reservoir due to hydrocarbon production. We demonstrate that under certain circumstances, high-quality prestack data can be obtained from cheap randomized subsampled measurements that are observed from nonreplicated surveys. We extend our time-jittered marine acquisition to time-lapse surveys by designing acquisition on irregular spatial grids that render simultaneous, subsampled and irregular measurements. Using the fact that different time-lapse data share information and that nonreplicated surveys add information when prestack data are recovered jointly, we recover periodic densely sampled and colocated prestack data by adapting the recovery method to incorporate a regularization operator that maps traces from an irregular spatial grid to a regular periodic grid. The recovery method is, therefore, a combined operation of regularization, interpolation (estimating missing fine-grid traces from subsampled coarse-grid data), and source separation (unraveling overlapping shot records). By relaxing the insistence on replicability between surveys, we find that recovery of the time-lapse difference shows little variability for realistic field scenarios of slightly nonreplicated surveys that suffer from unavoidable natural deviations in spatial sampling of shots (or receivers) and pragmatic compressed-sensing based nonreplicated surveys when compared to the “ideal” scenario of exact replicability between surveys. Moreover, the recovered densely sampled prestack baseline and monitor data improve significantly when the acquisitions are not replicated, and hence can serve as input to extract poststack attributes used to compute time-lapse differences. Our observations are based on experiments conducted for an ocean-bottom cable survey acquired with time-jittered continuous recording assuming source equalization (or same source signature) for the time-lapse surveys and no changes in wave heights, water column velocities or temperature and salinity profiles, etc.