Miracle-dz/UniFAR-FTUs huggingface dataset:
Mood Swings: design and evaluation of affective interactive art

The field of affective computing is concerned with developing emphatic products, such as affective consumer products, affective games, and affective art. This paper describes Mood Swings, an affective interactive art system, which interprets and visualizes affect expressed by a person. Mood Swings consists of eight luminous orbs that react to movement. When a person experiences certain emotion, his/her movements are claimed to have certain characteristics. Based on the integration of a framework for affective movements and a color model, Mood Swings recognizes affective movement characteristics, and subsequently displays a color that matches the expressed emotion. Mood Swings was evaluated in a museum for contemporary art by 36 museum visitors. The Trajectory of Interaction (ToI) was applied to assess common phases in interacting with Mood Swings, i.e. response, control, contemplation, belonging, and disengagement. The visitors who interacted with Mood Swings were videotaped. Results showed that The ToI could be identified, although not all phases were experienced by everyone. Few participants reached the contemplation phase and none of them reached the belonging phase. All together, the introduction of the new affective interactive art system was a success.
Predictors of panic attacks in adolescents.

OBJECTIVE To identify risk factors for onset of panic attacks in adolescents, a prospective cohort design was used to evaluate the following risk factors: negative affectivity, female sex, anxiety sensitivity, and childhood separation anxiety disorder. These risk factors were also evaluated for predicting onset of major depression to test their specificity. METHOD The sample consisted of 2,365 high school students assessed over a 4-year period. Assessments included self-report questionnaires and structured clinical interviews. Cox proportional hazards models were used to evaluate risk. RESULTS Consistent with previous studies, prior major depression predicted onset of panic attacks and a history of panic attacks predicted onset of major depression. After adjusting for the effects of prior major depression, negative affectivity and anxiety sensitivity, but not female sex or childhood separation anxiety disorder, predicted onset of 4-symptom panic attacks. However, female sex and negative affectivity but not anxiety sensitivity or childhood separation anxiety disorder predicted onset of major depression after adjustment for the effects of prior panic attacks. CONCLUSION Negative affectivity appears to be a nonspecific risk factor for panic attacks and major depression, whereas anxiety sensitivity appears to be a specific factor that increases the risk for 4-symptom panic attacks in adolescents.
A contrario detection of focal brain perfusion abnormalities based on an arterial spin labeling template

Arterial Spin Labeling (ASL) is a recent MRI perfusion technique which enables quantification of cerebral blood flow (CBF). The presence of regions with atypical CBF can characterize a pathology. In brain tumors for instance, perfusion increase can be directly related to the grading of the malignant tissues. It is therefore of great interest to identify these regions in order to provide the patients with the most appropriate therapy. In this paper, we propose to detect abnormal brain perfusion by using an a contrario framework and an ASL template as a model of normal perfusion. Validation was undertaken by qualitative comparison with CBF extracted from dynamic susceptibility weighted contrast enhanced (DSC) imaging. We experimented this framework on four patients presenting brain tumors. Results show that high perfusion regions found in DSC CBF maps are correctly identified as hyperperfusions with a contrario detection. Automatic detection has clear advantages over manual delineation since it is less time-consuming, does not depend on medical expertise and allows quantification of perfusion abnormalities within the detected regions.
Scalable Semi-supervised Learning with Graph-based Kernel Machine

Acquiring labels are often costly, whereas unlabeled data are usually easy to obtain in modern machine learning applications. Semi-supervised learning provides a principled machine learning framework to address such situations, and has been applied successfully in many real-word applications and industries. Nonetheless, most of existing semi-supervised learning methods encounter two serious limitations when applied to modern and large-scale datasets: computational burden and memory usage demand. To this end, we present in this paper the Graph-based semi-supervised Kernel Machine (GKM), a method that leverages the generalization ability of kernel-based method with the geometrical and distributive information formulated through a spectral graph induced from data for semi-supervised learning purpose. Our proposed GKM can be solved directly in the primal form using the Stochastic Gradient Descent method with the ideal convergence rate $O(\frac{1}{T})$. Besides, our formulation is suitable for a wide spectrum of important loss functions in the literature of machine learning (e.g., Hinge, smooth Hinge, Logistic, L1, and {\epsilon}-insensitive) and smoothness functions (i.e., $l_p(t) = |t|^p$ with $p\ge1$). We further show that the well-known Laplacian Support Vector Machine is a special case of our formulation. We validate our proposed method on several benchmark datasets to demonstrate that GKM is appropriate for the large-scale datasets since it is optimal in memory usage and yields superior classification accuracy whilst simultaneously achieving a significant computation speed-up in comparison with the state-of-the-art baselines.
Elections and the Political Order

The last section of a well-known earlier production by the same team of University of Michigan psephologists, The American Voter, bore the title, 'The Electoral Decision and the Political System'. It was a short section, which tentatively advanced a few suggestions and frankly recognized the need for further work, focused on the consequences of the electoral process, as against its makings in the personality and the group affiliations of individuals.
Barriers in Concurrent Separation Logic: Now With Tool Support!

We develop and prove sound a concurrent separation logic for Pthreads-style barriers. Although Pthreads barriers are widely used in systems, and separation logic is widely used for verification, there has not been any effort to combine the two. Unlike locks and critical sections, Pthreads barriers enable simultaneous resource redistribution between multiple threads and are inherently stateful, leading to significant complications in the design of the logic and its soundness proof. We show how our logic can be applied to a specific example program in a modular way. Our proofs are machine-checked in Coq. We showcase a program verification toolset that automatically applies the logic rules and discharges the associated proof obligations.
Excellence. Une analyse logométrique

Le nom excellence est choisi comme objet d’etude pour aborder le contenu semantique d’un texte officiel a l’aide d’un graphe de cooccurrence. La methode proposee permet de deceler differentes couches d’organisation du lexique du texte, qui montrent plus ou moins finement comment les mots sont cooccurrents les uns des autres. L’analyse proposee montre que les dimensions semantiques saillantes a la lecture se refletent dans cette organisation en couches.
Students’ preferences for university: a conjoint analysis

Tertiary education has become more competitive in recent years due to reductions in government funding and higher student fees. As the nature of the environment grows more competitive, the role of marketing, previously non‐existent in most universities, has grown significantly. One of the key pieces of information that would assist a university’s marketing effort is an understanding of what determines a student’s university preference. Examines university preference using a form of conjoint analysis, known as adaptive conjoint analysis (ACA), to investigate the importance of a number of attributes to high‐school leavers in Australia. Results indicate that the four most important determinants of university preference were course suitability, academic reputation, job prospects, and teaching quality, which has significance for education managers developing marketing strategies and programs.
Learning Of Autonomous Agent In Virtual Environment

Presented topic is from area of development of artificial creatures and proposes new architecture of autonomous agent. The work builds on a research of the latest approaches to Artificial Life, realized by the Department of Cybernetics, CTU in Prague in the last twenty years. This architecture design combines knowledge from Artificial Intelligence (AI), Ethology, Artificial Life (ALife) and Intelligent Robotics. From the field of classical AI, the fusion of reinforcement learning, planning and artificial neural network into one more complex control system was used here. The main principle of its function is inspired by the field of Ethology, this means that life of given agent tries to be similar to life of an animal in the Nature, where animal learns relatively autonomously from simpler principles towards the more complex ones. The architecture supports on-line learning of all knowledge from the scratch, while the core principle is in hierarchical Reinforcement Learning (RL), this action hierarchy is created autonomously based solely on agents interaction with an environment. The main key idea behind this approach is in original implementation of a domain independent hierarchical planner. Our planner is able to operate with behaviors learned by the RL. It means that an autonomously gained hierarchy of actions can be used not only by action selection mechanisms based on the reinforcement learning, but also by a planning system. This gives the agent ability to utilize high-level deliberative problem solving based solely on his experiences. In order to deal with higher-level control rather than a sensory system, the life of agent was simulated in a virtual environment.
Thromboprophylaxis with graduated compression stockings for elderly inpatients: more evidence is needed

1 Kuipers S, Schreijer AJ, Cannegieter SC, Middeldorp S, Buller HR, Rosendaal FR. The absolute risk of venous thrombosis after air travel (WRIGHT study). J Thromb Haemost 2005; 3: P1657. 2 Schreijer AJ, Cannegieter SC, Meijers JC, Middeldorp S, Buller HR, Rosendaal FR. Activation of coagulation system during air travel: a crossover study. Lancet 2006; 367: 832–8. 3 Martinelli I, Taioli E, Battaglioli T, Podda GM, Passamonti SM, Pedotti P, Manucci PM. Risk of venous thromboembolism after air travel: interaction with thrombophilia and oral contraceptives. Arch Intern Med 2003; 163: 2771–4. 4 GeertsWH, PineoGF, Heit JA, Bergqvist D, LassenMR, Colwell CW, Ray JG. Prevention of venous thromboembolism: the Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy.Chest 2004; 126: 338S–400S. 5 Chen AH, Frangos SG, Kilaru S, Sumpio BE. Intermittent pneumatic compression devices — physiological mechanisms of action. Eur J Vasc Endovasc Surg 2001; 21: 383–92. 6 Giddings JC, Morris RJ, Ralis HM, Jennings GM, Davies DA, Woodcock JP. Systemic haemostasis after intermittent pneumatic compression. Clues for the investigation of DVT prophylaxis and travellers thrombosis. Clin Lab Haematol 2004; 26: 269–73.
Effect of haemodilution with diaspirin cross‐linked haemoglobin on the oxygen reserve in a rodent model of surgical blood loss

Summary. The efficacy of pre‐operative haemodilution is limited by the reduction in haemoglobin concentration. Acellular haemoglobin‐based oxygen carriers provide an alternative to colloid as a haemodiluent, potentially extending the safe limits of this procedure. The aim of this investigation was to determine whether haemodilution with a cross‐linked haemoglobin solution, diaspirin cross‐linked haemoglobin solution (DCLHb), would enhance the oxygen reserve compared to pentastarch.
Questioning the validity of criminal profiling: an evidence-based approach

Criminal profiling is used in complex investigations, and, in a number of jurisdictions, as expert evidence in criminal trials. This article seeks to move beyond the many anecdotal accounts of success by profilers and examine the evidence available as to the discipline's validity. As it stands, profiling is based on theories that are uncertain at best, and little research has been undertaken to assess the actual accuracy of generated profiles. This absence of validation is in part due to genuine difficulties associated with designing appropriate testing models. It is exacerbated by the reluctance of profilers to engage in such a process, relying instead on the well-rehearsed, yet somewhat circular argument that the continuing demand for profiling advice is in itself reassuring evidence of the method's validity. It is the lack of objective evidence of validity in this area that will be critically considered in this article.
MRI image segmentation based on fast global minimization of snake model

Snakes, or active contours, have been widely used to locate boundaries of image segmentation and computer vision. Problem associated with the existence of the local minima in the active contour energy function makes snakes have poor convergence in segmentation process; therefore, the poor convergence has limited applications. In this work, a fast minimization of snake model is used for an MRI knee image segmentation. This method provides a satisfied result. As a result, it is a good candidate for MRI image segmentation approach.
Robustness of Prediction Based Delay Compensation for Nonlinear Systems

Abstract Control of systems where the information between the controller, actuator, and sensor can be lost or delayed can be challenging with respect to stability and performance. One way to overcome the resulting problems is the use of prediction based compensation schemes. Instead of a single input, a sequence of (predicted) future controls is submitted and implemented at the actuator. If suitable, so-called prediction consistent compensation and control schemes, such as certain predictive control approaches, are used, stability of the closed loop in the presence of delays and packet losses can be guaranteed. In this paper, we show that control schemes employing prediction based delay compensation approaches do posses inherent robustness properties. Specifically, if the nominal closed loop system without delay compensation is ISS with respect to perturbation and measurement errors, then the closed loop system employing prediction based delay compensation techniques is robustly stable. We analyze the influence of the prediction horizon on the robustness gains and illustrate the results in simulation.
Deletion of the CUL4B gene in a boy with mental retardation, minor facial anomalies, short stature, hypogonadism, and ataxia

The CUL4B gene encodes a member of Cullin–RING ubiquitin ligase complex. Point mutations in CUL4B were identified recently in patients with syndromic X‐linked mental retardation (XLMR). Here, using oligoarray‐based comparative genomic hybridization (array CGH), we identified a de novo deletion of the CUL4B gene in a boy with syndromic mental retardation, minor facial anomalies, short stature, delayed puberty, hypogonadism, relative macrocephaly, gait ataxia, and pes cavus, all manifestations described previously in patients with CUL4B point mutations. Interestingly, our patient also presented with aortic valvular “dysplasia” and vertebral anomalies similar to those seen in Scheuermann disease, both of which may also be part of this syndrome. This report further suggests that point mutations and deletions of the CUL4B gene lead to a recognizable phenotype. The association of facial anomalies, short stature, hypogonadism, and gait ataxia in a mentally retarded boy should prompt molecular analyses of the CUL4B gene. © 2009 Wiley‐Liss, Inc.
A 10 mV-Input Boost Converter With Inductor Peak Current Control and Zero Detection for Thermoelectric and Solar Energy Harvesting With 220 mV Cold-Start and $-$14.5 dBm, 915 MHz RF Kick-Start

A boost converter for thermoelectric energy harvesting in 130 nm CMOS achieves energy harvesting from a 10 mV input, which allows wearable body sensors to continue operation with low thermal gradients. The design uses a peak inductor current control scheme and duty cycled, offset compensated comparators to maintain high efficiency across a broad range of input and output voltages. The measured efficiency ranges from 53% at VI=20 mV to a peak efficiency of 83% at VI=300 mV. A cold-start circuit starts the operation of the boost converter from 220 mV, and an RF kick-start circuits starts it from -14.5 dBm at 915 MHz RF power.
Kiss and Tell: Surveying Sex in the Twentieth Century

Learning the details of others' sex lives is possibly the most enticing of guilty pleasures. We measure our own practices against the "normalcy" sex surveys seek to capture. Special interest groups often use or attack survey findings (such as the claim that 10% of Americans are gay) for their own ends. This text chronicles the history of sex surveys in the USA over a century of changing social and sexual mores. It reveals that the survey questions asked, more than the answers elicited, expose and shape the popular image of appropriate sexuality. As much, therefore, can be learned about the history and practice of sexuality by looking at surveyors' changing concerns as can be learned by reading the results of their surveys. The authors show how surveys have reflected societal anxieties about adolescent development, teen sex and promiscuity, and AIDS, and have been employed in efforts to preserve marriage and to control women's sexuality.
Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech

We present the joint task of incremental disfluency detection and utterance segmentation and a simple deep learning system which performs it on transcripts and ASR results. We show how the constraints of the two tasks interact. Our joint-task system outperforms the equivalent individual task systems, provides competitive results and is suitable for future use in conversation agents in the psychiatric domain.
Multi-Objective Aerodynamic Optimization of Elements' Setting for High-lift Airfoil Using Kriging Model

In this paper, a multi-objective design optimization for a three-element airfoil consisted of a slat, a main wing, and a flap was carried out. The objective functions were defined as the maximization of lift coefficient at landing (Cl8) and near stall (Cl20)conditions simultaneously. Genetic Algorithm (GA) was used as an optimizer. Although it has advantage of global exploration, its computational cost is expensive. To reduce the computational cost, the kriging model which was constructed based on several sample designs was introduced. The solution space was explored based on the maximization of Expected Improvement (EI) value corresponding to objective functions on the kriging model to consider the predicted value by kriging model and its uncertainty. The improvement of the model and the exploration of the optimum can be advanced at the same time by maximizing EI value. In this study, 90 sample points are evaluated using the Reynolds averaged Navier-Stokes simulation (RANS) for the construction of the kriging model. Through the present exploration process, several designs were obtained with better performance than the baseline setting in each objective function. Functional Analysis of Variance (ANOVA) which is one of the data mining techniques showing the effect of each design variable on the objectives is applied. Main-effects of the design variables are calculated to recognize which design variable has the effect on the objective functions. This result suggests that the gap and the deflection of the flap have a remarkable effect on each objective function and the gap of the slat has an effect on Cl20.
Soil microbial biomass under mulch types in an integrated apple orchard from Southern Brazil

The use of mulching is an alternative to control weeds but there are few studies on its effect on soil quality. In this sense, this study aimed to evaluate the effect of types of mulching on the attributes of microbial carbon, nitrogen and phosphorus in a Typic Hapludox with production of integrated apples in southern Brazil. The experiment was conducted in randomized blocks in the Vacaria, state of Rio Grande do Sul, southern Brazil. The soil mulch types studied were: pine needle, sawdust, black plastic and a control. The soil samples were collected in February (summer) and August (winter) of 2006, and the attributes related to total organic and microbial carbon, nitrogen and phosphorus were determined. Organic mulchings (pine needle and sawdust) promoted lower soil temperature, and greater moisture, microbial carbon (Cmic), microbial nitrogen (Nmic), and the ratios Cmic:Corg, Nmic:Norg and microbial C:N than black plastic. Microbial phosphorus was greater in winter. Sawdust mulching promoted the best conditions to microbial biomass in winter. The mulch types increased the microbial compartment in winter as compared to the nonweeded control .
Insulin Kinetics in Type I Diabetic Patients Treated by Continuous Intraperitoneal Insulin Infusion: Influence of Anti‐insulin Antibodies

Continuous intraperitoneal insulin infusion (CIPII) is a promising therapy of patients with Type 1 (insulin‐dependent) diabetes mellitus (IDDM), since it improves metabolic control and decreases frequency of severe hypoglycaemia. This could be due to more appropriate insulin kinetics. Our aim, therefore, was to compare plasma free insulin levels achieved in patients with Type 1 diabetes chronically treated with CSII or CIPII. Furthermore, as anti‐insulin antibodies increase with this treatment, we wanted to assess their influence upon insulin kinetics. Plasma free insulin profiles were obtained during the night and then after the bolus for breakfast and the bolus for lunch in 11 patients with Type 1 diabetes treated successively by CSII and CIPII. In another group of 16 patients with long‐term Type 1 diabetes, treated by CIPII, we examined the influence of anti‐insulin antibody level on insulin kinetics after a bolus. During the night, plasma free insulin levels were lower with CIPII than with CSII (12:00 am: 10.1 ± 1.7 vs 18.5 ± 2.6 mU l−1; 4:00 am: 9.1 ± 2 vs 15 ± 3 mU l−1), p < 0.01. After the bolus, CIPII lead to an earlier (1h vs 3h) and higher (25.8 ± 3.3 vs 18 ± 2.7, p < 0.05) plasma free insulin peak than CSII. With CIPII, the return to baseline level was observed within 3 h. Conversely, during CSII, insulin levels did not return to baseline until the next meal. After the bolus, high insulin‐antibody levels were associated with a reduced maximal value of plasma free insulin peak. Taken together, these findings suggest that CIPII provides plasma free insulin profiles which are much closer to physiology than CSII. This could explain the lower rate of severe hypoglycaemia observed with this type of treatment. But in long‐term CIPII treated patients with high anti‐insulin antibody level, insulin profile could be moderately modified. This emphasizes the need for a less immunogenic insulin preparation.
Increasing the efficiency of the General Equal Treatment Act: an economic analysis

This paper examines the verdict in the case of Mrs Sule Eisele Gaffaroglu vR+V Lebensversicherungs AG, Wiesbaden Labour Court. The economic analysis of law focuses on the three main paragraphs of the General Equal Treatment Act 1 (Allgemeines Gleichbehandlungsgesetz, abbreviated to AGG): §22 – Burden of proof for the plaintiff and reversing the onus of proof to the defendant; §15 Para. 1 – Compensation of material losses; and §15 Para. 2 – Monetary compensation for non-economic loss. The analysis of the verdict concludes that the AGG, in the version currently in force, is not efficient. However, this paper also suggests possible ways of increasing the efficiency of the AGG.