Miracle-dz/UniFAR-FTUs huggingface dataset:
Marionnet: a virtual network laboratory and simulation

We present Marionnet 1 , a high-level simulation tool allowing to accurately reproduce the behavior of physical computer networks made by computers, hubs, switches and routers; virtual machines run unmodiﬁed GNU/Linux binaries for the x86 architecture at nearly native speed. Individual virtual devices can be dynamically created, de-stroyed or modiﬁed while the rest of the virtual network is running, providing many opportunities for experimentation without any need for clumsy hardware setup. Marionnet has a very intuitive graphical user interface also suitable to inexperienced users, and is being used with success for teaching computer networks at Universit´e Paris 13. We believe its adoption can be extended to other specialits in the ﬁeld of network, in order to ease the design and debug of computer networks, applications and protocols. This work presents Marionnet from a user point of view, complementing its description with a practical use scenario showing an example of how the application could be prof-itably employed in the industry.
Mining the Hierarchy of Resting-State Brain Networks: Selection of Representative Clusters in a Multiscale Structure

The hierarchical organization of brain networks can be captured by clustering time series using multiple numbers of clusters, or scales, in resting-state functional magnetic resonance imaging. However, the systematic examination of all scales is a tedious task. Here, I propose a method to select a limited number of scales that are representative of the full hierarchy. A bootstrap analysis is first performed to estimate stability matrices, which quantify the reliability of the clustering for every pair of brain regions, over a grid of possible scales. A subset of scales is then selected to approximate linearly all stability matrices with a specified level of accuracy. On real data, the method was found to select a relatively small (~7) number of scales to explain 95% of the energy of 73 scales ranging from 2 to 1100 clusters. The number of selected scales was very consistent across 43 subjects, and the actual scales also showed some good level of agreement. This approach thus provides a principled approach to mine hierarchical brain networks, in the form of a few scales amenable to detailed examination.
The Relationship between Sex Guilt and Sexual Desire in a Community Sample of Chinese and Euro-Canadian Women

Many studies have documented significant differences in sexual desire between individuals of European and Chinese descent, but few have examined the mechanisms that underlie these differences. A recent study of university students found that sex guilt is one mechanism by which culture influences sexual desire among Chinese and Euro-Canadian women. The goal of this study was to examine whether sex guilt also mediates the relationship between ethnicity and sexual desire in a sample that is more representative of women in the general population. Euro-Canadian (n = 78; mean age = 42.1 years) and Chinese (n = 87; mean age = 42.8 years) women were recruited from the community. Euro-Canadian women reported greater sexual desire and less sex guilt. In the entire sample, sex guilt mediated the relationship between ethnicity and sexual desire such that the Chinese women reported greater sex guilt, which, in turn, was associated with lower sexual desire. Among the Chinese women, sex guilt mediated the relationship between mainstream acculturation (degree of Westernization) and sexual desire such that more Westernized Chinese women reported less sex guilt, which, in turn, was associated with greater sexual desire. These results support recent findings and further suggest that sex guilt may be one mechanism by which ethnicity affects sexual desire.
Polarization-based transparent surface modeling from two views

In this paper, we propose a novel method to recover the surface shape of transparent objects. The degree of polarization of the light reflected from the object surface depends on the reflection angle which, in turn, depends on the object's surface normal; thus, by measuring the degree of polarization, we are able to calculate the surface normal of the object. However, degree of polarization and surface normal does not correspond one-to-one, making us to analyze two polarization images taken from two different view in order to solve the ambiguity. A parabolic curve will be a strong clue to correspond a point in one image to a point in the other image, where both points represent the same point on object surface. By comparing the degree of polarization at such corresponding points, the true surface normal can be determined.
Brazilian Journal of Chemical Engineering EXTRACTION OF BIXIN FROM ANNATTO SEEDS USING SUPERCRITICAL CARBON DIOXIDE

The solubility of 93% pure bixin in supercritical carbon dioxide (SC-CO2) and of the bixin present in annatto seeds (Bixa orellana L.) was measured. For the seeds, the measurements were made in a temperature range from 30 to 50C and pressure between 10 and 35 MPa and for the pure bixin, at 40C from 10 to 35 MPa. The main pigments of annatto seeds are bixin and norbixin, but the extracts only showed the presence of cis and trans-bixin, indicating that norbixin is not soluble in SC-CO2. The annatto seeds used in the experiments contained about 2.7% bixin and 3.1% oil. In the seeds, the crossover point of solubility was at about 28 MPa and values for solubility were about ten times higher than those of the pure bixin, giving evidence that the oil acted as a co-solvent with the CO2.
An Intermediate Language for Semantic Exceptions in Context-Aware Systems

Semantic exceptions mean undesirable contexts with respect to application semantics in context aware systems. Description of such semantic exceptions is based on regular expressions, which entails high complexity to detect exceptions. In this paper we devise an intermediate language for semantic exceptions of context aware applications. By bridging the gap between high level programming languages and event stream processing engines, this language is expected to mitigate the complexity and to provide opportunities to optimize exception detection process.
Readability of the gaze and expressions of a robot museum visitor: Impact of the low level sensory-motor control

In this paper we propose a neural network allowing a mobile robot to learn artwork appreciation. The learning is based on the social referencing approach. The robot acquires its knowledge (artificial taste) from the interaction with humans. We present and analyze specifically the visual system, its impact on the robot behavior, and at the end, we analyze the readability of our robot behavior according to visitors comments. We show that the low level spatial competition between the values associated to areas of interest in the image are important for the coherence of the robot's object evaluation and the readability of its behavior.
Tracking control of the orbitally flat kinematic car with a new time-scaling input

The paper defines a time-scaling scheme such that the scaling function depends on the state variables of the system and on an external variable referred to as the time-scaling input. The system evolving according to the scaled time has thus one more input variable compared to the original system. This time- scaling scheme is applied to the kinematic car with one input, namely the steering angle. The longitudinal velocity of the car is a measurable external signal and cannot be influenced by the controller. Using an on-line time-scaling, which is driven by the longitudinal velocity of the car, by a time-scaling output of the tracking controller, and by their time derivatives up to the second order, one can achieve exponential tracking of any sufficiently smooth reference trajectory with non-vanishing velocity, similar to the two-input differentially flat model of the kinematic car. The time derivatives of the longitudinal velocity and the time-scaling output are no longer necessary if one designs the tracking controller for the linearized error dynamics around the reference path.
Chapter 4 PARSEME multilingual corpus of verbal multiword expressions

Agata Savary1, Marie Candito2, Verginica BarbuMititelu3, Eduard Bejček4, Fabienne Cap5, Slavomír Čéplö6, Silvio Ricardo Cordeiro7, Gülşen Eryiğit8, Voula Giouli9, Maarten van Gompel10, Yaakov HaCohen-Kerner11, Jolanta Kovalevskaitė12, SimonKrek13, Chaya Liebeskind11, JohannaMonti14, Carla Parra Escartín15, Lonneke van der Plas6, Behrang QasemiZadeh16, Carlos Ramisch7, Federico Sangati17, Ivelina Stoyanova18 & Veronika Vincze19 1Université de Tours (France), 2Université Paris Diderot (France), 3Romanian Academy Research Institute for Artificial Intelligence (Romania), 4Charles University (Czech Republic), 5Uppsala University (Sweden), 6University of Malta (Malta), 7Aix Marseille University (France), 8Istanbul Technical University (Turkey), 9Athena Research Center in Athens (Greece), 10Radboud University in Nijmegen (Netherlands), 11Jerusalem College of Technology (Israel), 12Vytautas Magnus University in Kaunas (Lithuania), 13Jožef Stefan Institute in Ljubljana (Slovenia), 14“L’Orientale” University of Naples (Italy), 15ADAPT Centre, Dublin City University (Ireland), 16University of Düsseldorf (Germany), 17independent researcher (Italy), 18Bulgarian Academy of Sciences in Sofia (Bulgaria), 19Univer-
Elevated exhalation of hydrogen peroxide in patients with non-small cell lung cancer is not affected by chemotherapy

ABSTRACT Objectives: Reactive oxygen species, which are implicated in the process of carcinogenesis, are also responsible for cell death during chemotherapy (CHT). Therefore, the aim of the study was to evaluate exhaled H2O2 levels in non-small cell lung cancer (NSCLC) patients before and after CHT. Methods: Thirty patients (age 61.3 ± 9.3 years) with advanced NSCLC (stage IIIB–IV) and 15 age-matched healthy cigarette smokers were enrolled into the study. Patients received four cycles of cisplatin or carboplatin with vinorelbine every three weeks. Before and after the first, second, and fourth cycle, the concentration of H2O2 in exhaled breath condensate was measured with respect to treatment response. Results: At the baseline, NSCLC patients exhaled 3.8 times more H2O2 than the control group (0.49 ± 0.14 vs. 0.13 ± 0.03 µmol/L, P < 0.05); this difference persisted throughout the study. CHT had no noticeable effect on exhaled H2O2 levels independent of the treatment response (partial remission vs. progressive disease). Pre- and post-CHT cycles of H2O2 levels generally correlated positively. Discussion: The study demonstrated the occurrence of oxidative stress in the airways of advanced NSCLC patients. Exhaled H2O2 level was not affected by CHT and independent of treatment results and changes in the number of circulating neutrophils.
Flexible Wavelet Transforms Using Lifting

Roger L. Claypoole, Jr. and Richard G. Baraniuk, Rice University Summary We introduce and discuss biorthogonal wavelet transforms using the lifting construction. The lifting construction exploits a spatial{domain, prediction{error interpretation of the wavelet transform and provides a powerful framework for designing customized transforms. We discuss the application of lifting to adaptive and non{linear transforms, transforms of non{uniformly sampled data, and related issues. Introduction Many applications (compression, analysis, denoising, etc.) bene t from signal representation with as few coe cients as possible. We also wish to characterize a signal as a series of course approximations, with sets of ner and ner details. The Discrete Wavelet Transform (DWT) provides such a representation. The DWT represents a real-valued discrete-time signal in terms of shifts and dilations of a lowpass scaling function and a bandpass wavelet function [2]. The DWT decomposition is multiscale: it consists of a set of scaling coe cients c0[n], which represent coarse signal information at scale j = 0, and a set of wavelet coe cients dj [n], which represent detail information at scales j = 1; 2; : : : ; J . The forward DWT has an e cient implementation in terms of a recursive multirate lterbank based around a lowpass lter h and highpass lter g [12, pp. 302{332]. The inverse DWT employs an inverse lterbank with lowpass lter eh and highpass lter eg, as shown in Figure 1 For special choices of h, g, eh, and eg, the underlying wavelet and scaling functions form a biorthogonal wavelet basis [2].
The offline and online channels for requesting tourist services

This study aimed to investigate the perceived quality in attributes of attendance of travel agencies that are located in São Paulo city and the willingness of migration of their customers to the Internet in their behavior of requesting a tourist service. Based on the models SERVQUAL by Parasuraman et al (1988), SERVPERF by Cronin and Taylor (1992 and 1944), TAM2 by Venkatesh and Davis (2000), two researches were carried out, one of qualitative nature and the other one of quantitative nature, along with tourist service users. For the analysis of the results, the cluster analysis technique was applied. Through it, some homogeneous groups of users were obtained regarding the levels of evaluation of quality attributes of tourism agencies and the variables of TAM2 model. The study revealed that there is not an inverse relation between the quality of services of tourism agencies (offline channel) and intention level of requesting tourism services through Internet (online channel). Thus, the tourism companies may consider the Internet as a partner in the process of conquest and retention of clients.
Simulation and Visualization of Fluid Flows Around Real Objects in Augmented Reality

The long-term vision of augmented reality is to seamlessly integrate digital content into the real world, which provides new means to make physical processes visible that are usually invisible to the naked eye. One such example is the motion of air around us. With the help of a head-mounted augmented reality device, an interactive air ﬂow simulation and the tracking of real-world objects, we develop a ﬂow visualization tool box in which users interactively explore approximations of the real-world air ﬂow around real objects. Since the ﬂows respond dynamically to real-world objects, the inﬂuence of obstacle size and air ﬂow speed on the creation and movement of vortices can be explored interactively using geometry-based ﬂow visualization techniques, including pathlines and streaklines. We see our setup mainly used in an educational context or for science communication. This is the authors preprint. The deﬁnitive version is available at https://onlinelibrary.wiley. com/ and at https://diglib.eg. org/.
Deep learning with maximal figure-of-merit cost to advance multi-label speech attribute detection

In this work, we are interested in boosting speech attribute detection by formulating it as a multi-label classification task, and deep neural networks (DNNs) are used to design speech attribute detectors. A straightforward way to tackle the speech attribute detection task is to estimate DNN parameters using the mean squared error (MSE) loss function and employ a sigmoid function in the DNN output nodes. A more principled way is nonetheless to incorporate the micro-F1 measure, which is a widely used metric in the multi-label classification, into the DNN loss function to directly improve the metric of interest at training time. Micro-F1 is not differentiable, yet we overcome such a problem by casting our task under the maximal figure-of-merit (MFoM) learning framework. The results demonstrate that our MFoM approach consistently outperforms the baseline systems.
Practical prescribing with aripiprazole in schizophrenia: consensus recommendations of a UK multidisciplinary panel

ABSTRACT Background: The atypical antipsychotic, aripiprazole, differs from other antipsychotics in its pharmacology and clinical outcomes. Aripiprazole's clinical outcomes include beneficial effects on mood, quality of life and cognition; favourable tolerability with low potential for sedation; and a favourable physical health profile, with low potential for weight change, sexual dysfunction or adverse metabolic effects. Such outcomes, particularly cognitive improvements, may allow for greater psychosocial intervention and improved social inclusion. In accordance with the UK NICE guidance on the use of antipsychotic treatment for schizophrenia (2002), aripiprazole may be an appropriate therapeutic option for patients with schizophrenia who are newly diagnosed, in acute relapse or experiencing tolerability problems, adverse metabolic effects or dissatisfaction with their current medication. Scope: A multidisciplinary panel was convened in the UK in October 2006 to discuss and provide practical guidance regarding the potential benefits and risks of prescribing aripiprazole. This report describes the consensus recommendations agreed during the meeting and includes practical guidance on the optimal approach to prescribing aripiprazole, which patients might benefit from aripiprazole and how best to approach initiation of and switching to treatment with aripiprazole. A PubMed/MEDLINE literature search was conducted to support these recommendations. Findings: To support antipsychotic therapy, a therapeutic partnership should be established between the patient and a well-informed, multidisciplinary care team. Aripiprazole should be initiated at the minimal efficacious dose (10 mg/day) and titrated as required (usually to 15 mg/day) after a minimum of 2 weeks. The primary goal during aripiprazole initiation is to ensure the patient completes the first few days of treatment, with support from concomitant medications if required. Nausea, insomnia and agitation may occur in 10–20% of patients, but are manageable and typically resolve during the first 3–7 days of therapy. The dose of any prior antipsychotic should remain stable until the response to aripiprazole is satisfactory and then the previous antipsychotic should be tapered off slowly over several weeks or more. Conclusion: Patients are more likely to adhere to treatment with aripiprazole – and indeed any other antipsychotic – and derive long-term therapeutic benefits if they and a well-informed care team are involved in the treatment decision, establish a therapeutic partnership, are aware of the transient nature of any adverse events and understand what the potential long-term benefits are.
VISUAL REASONING IN THE DESIGN PROCESS The differences between expert and novice

In design studies, information-processing and reflection-in-action paradigms were mainstreams in describing designing. This study however took the viewpoint of the visual design reasoning theory where abstract, conceptual knowledge and perceptually-based knowledge were interlinked. The major purpose was examining the design process using visual design reasoning to discover the essential features of design activities. The minor purpose was to demonstrate the differences between a novice and an expert result from the dissimilar abilities of visual reasoning. Retrospective protocol analysis and DCOCS were utilized to explore the interactions between physical drawing and goal-setting. Two main findings were: visual reasoning occupied significant portion of the design process, and to continuously apply visual reasoning is the essential ability of an experienced designer. The idea of visual reasoning was discussed.
The Right Tool for the Right Job: Assessing Model Transformation Quality

Model-Driven Engineering (MDE) is a software engineering discipline in which models play a central role. One of the key concepts of MDE is model transformations. Because of the crucial role of model transformations in MDE, they have to be treated in a similar way as traditional software artifacts. They have to be used by multiple developers, they have to be maintained according to changing requirements and they should preferably be reused. It is therefore necessary to define and assess their quality. In this paper, we give two definitions for two different views on the quality of model transformations. We will also give some examples of quality assessment techniques for model transformations. The paper concludes with an argument about which type of quality assessment technique is most suitable for either of the views on model transformation quality.
Perceiving mixed valence emotions reduces intergroup dehumanisation

ABSTRACT To deny others’ humanity is one of the most heinous forms of intergroup prejudice. Given evidence that perceiving various forms of complexity in outgroup members reduces intergroup prejudice, we investigated across three experiments whether the novel dimension of emotional complexity, or outgroup members’ joint experience of mixed-valence emotions, would also reduce their dehumanisation. Experiment 1 found that perceiving fictitious aliens’ experience of the same primary emotions (e.g. sadness) presented in mixed vs. non-mixed valence pairs led to reduced prejudice via attenuated dehumanisation, i.e. attribution of uniquely human emotions. Experiment 2 confirmed these results, using an unfamiliar real-world group as an outgroup target. Experiment 3 used a familiar outgroup and found generally similar effects, reducing social distance through reduced dehumanisation. These processes suggest that an alternate route to reduced dehumanising of outgroups might involve presenting mixed valence emotions.
Regression Test Suite Selection and Minimization Based on Feature Modeling

Regression testing of enterprise software is expensive as the whole system needs to be retested after code changes. Most of regression testing can be automated, but it still requires a lot of resources and time. Previous work at Ultimate Software designed and implemented a taxonomy manager to allow domain experts to categorize and organize tests by modeling the application domain as a set of hierarchical features, and any cross-dependencies among them. One of the long term goals of this type of modeling is to provide cost effective testing during regression as modifications to the software are validated over time. To enable this type of testing, this work presents the design and implementation of an approach for reestablishing traceability links between features and source code. With that, code metrics can be collected on the feature level and used for assessing risks and the current state of the application on the system level. It is shown that categorizing tests can greatly reduce the amount of time needed to select and run regression tests using an industrial case study. By applying knowledge gained from the traceability links between features and source code to risk-based testing it is also possible to minimize test suites by simplifying or removing tests of low risk features.