Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-way reversible shape memory effects in a free-standing polymer composite

Shape memory polymers (SMPs) have attracted significant research efforts due to their ease in manufacturing and highly tailorable thermomechanical properties. SMPs can be temporarily programmed and fixed in a nonequilibrium shape and are capable of recovering the original undeformed shape upon exposure to a stimulus, the most common being temperature. Most SMPs exhibit a one-way shape memory (1W-SM) effect since one programming step can only yield one shape memory cycle; an additional shape memory cycle requires an extra programming step. Recently, a novel SMP that demonstrates both 1W-SM and two-way shape memory (2W-SM) effects was demonstrated by one of the authors (Mather). However, to achieve two-way actuation this SMP relies on a constant externally applied load. In this paper, an SMP composite where a pre-stretched 2W-SMP is embedded in an elastomeric matrix is developed. This composite demonstrates 2W-SM effects in response to changes in temperature without the requirement of a constant external load. A transversal actuation of ∼ 10% of actuator length is achieved. Cyclic tests show that the transversal actuation stabilizes after an initial training cycle and shows no significant decreases after four cycles. A simple analytic model considering the programming stress and actuator dimensions is presented and shown to agree well with the transverse displacement of the actuator. The model also predicts that larger actuation can be achieved when larger pre-stretch of 2W-SMP is used. The scheme used for this polymer composite can promote the design of new shape memory composites at micro- and nano-length scales to meet different application requirements.
The Association between Diabetes Mellitus and Nonarteritic Anterior Ischemic Optic Neuropathy: A Systematic Review and Meta-Analysis

Background The association of diabetes mellitus (DM) with nonarteritic anterior ischemic optic neuropathy (NAION) has been inconclusive. Purpose To determine whether DM is associated with an increased risk of NAION. Methods A comprehensive literature search was performed for published studies reporting both DM and NAION based on PubMed and EMBASE. After reviewing characteristics of all the included studies systematically, meta-analytical method was employed to calculate the pooled odds ratio (OR) and associated 95% confidence interval (CI) from random-effects models. Heterogeneity was assessed by Q-statistic test. Funnel Plot, Begg's and Egger's linear regression test were applied to evaluate publication bias. A sensitivity analysis and meta-regression analysis were also performed to assess the robustness of results. Results 2,096 participants from 12 case-control studies were pooled for a meta-analysis. The result of meta-analysis of these studies indicated that DM is associated with increased risk of NAION (pooled OR = 1.64, 95% CI = 1.17–2.30; P = 0.004). Sensitivity analysis indicated our findings are robust, and meta-regression analysis revealed no significant effect in terms of geographical area, gender, age of patients with NAION, the year of the publication, source of the controls, and sample size (all p>0.05). Evidence of publication bias was not observed in our study. Conclusion Meta-analysis suggests that DM might be associated with increased risk of NAION.
Extended phraseological information in a valence dictionary for NLP applications

The aim of this paper is to propose a far-reaching extension of the phraseological component of a valence dictionary for Polish. The dictionary is the basis of two dierent parsers of Polish; its format has been designed so as to maximise the readability of the information it contains and its re-applicability. We believe that the extension proposed here follows this approach and, hence, may be an inspiration in the design of valence dictionaries for other languages.
A Petri Net Model for Evaluating Packet Buffering Strategies in a Network Processor

Previous studies have shown that buffering packets in DRAM is a performance bottleneck. In order to understand the impediments in accessing the DRAM, we developed a detailed Petri net model of IP forwarding application on IXP2400 that models the different levels of the memory hierarchy. The cell based interface used to receive and transmit packets in a network processor, leads to some small size DRAM accesses. Such narrow accesses to the DRAM expose the bank access latency, reducing the bandwidth that can be realized. With real traces up to 30% of the accesses are smaller than the cell size, resulting in 7.7% reduction in DRAM bandwidth. To overcome this problem, we propose buffering these small chunks of data in the on chip scratchpad memory. This scheme also exploits greater degree of parallelism between different levels of the memory hierarchy. Using real traces from the internet, we show that the transmit rate can be improved by an average of 21% over the base scheme without the use of additional hardware. Further, the impact of different traffic patterns on the network processor resources is studied. Under real traffic conditions, we show that the data bus which connects the off-chip packet buffer to the micro- engines, is the obstacle in achieving higher throughput.
Fusion of imprecise, uncertain, and conflicting beliefs with DSm rules of combination

In this paper one studies, within Dezert-Smarandache Theory (DSmT), the case when the sources of information provide imprecise belief functions/masses, and we generalize the DSm rules of combination (classic or hybrid rules) from scalar fusion to sub-unitary interval fusion and, more general, to any set of sub-unitary interval fusion. This work generalizes previous works available in literature which appear limited to IBS (Interval-valued belief structures) in the Transferable Belief Model framework. Numerical didactic examples of these new DSm fusion rules for dealing with imprecise information are also presented.
DinerRouge: Bringing Wealth and Income Inequality to the Table through a Provocative UX

Income and wealth inequality is one of the important social issues of the last decade. Nevertheless, it is rarely discussed through the lense of Human Computer Interaction. In this paper, we aim at investigating how a provocative user experience can contribute to engaging users when it comes to issues about wealth and income inequality. More precisely, we present the design of DinerRouge, a novel mobile application that can spark income inequality discussion by providing a provoking way to split the bill in restaurants based on income. We conducted a preliminary evaluation of DinerRouge with 78 participants which convey the fact that DinerRouge is usable, provocative and informative. Finally, we present open research question to guide future investigations.
Translational and Brownian motion in laser-Doppler flowmetry of large tissue volumes

This study reports the derivation of a precise mathematical relationship existing between the different p-moments of the power spectrum of the photoelectric current, obtained from a laser-Doppler flowmeter (LDF), and the red blood cell speed. The main purpose is that both the Brownian (defining the ‘biological zero’) and the translational movements are taken into account, clarifying in this way what the exact contribution of each parameter is to the LDF derived signals. The derivation of the equations is based on the quasi-elastic scattering theory and holds for multiple scattering (i.e. measurements in large tissue volumes and/or very high red blood cell concentration). The paper also discusses why experimentally there exists a range in which the relationship between the first moment of the power spectrum and the average red blood cells speed may be considered as ‘linear’ and what are the physiological determinants that can result in nonlinearity. A correct way to subtract the biological zero from the LDF data is also proposed. The findings should help in the design of improved LDF instruments and in the interpretation of experimental data.
Un modèle de gouvernance stratégique pour améliorer le rendemen des services d'urgence dans les hôpitaux public de la province d'Ontario au Canada

La demande croissante de soins de sante dans la province de l'Ontario a mene a ce qu’un plus grand nombre de patients se tournent vers les services d'urgence des hopitaux publics pour les soins dont ils ont besoin. La qualite de la gestion des services d'urgence mesuree par les resultats des patients est probablement symptomatique de la qualite de la gestion de l'hopital et, finalement, de celle de la direction de l'hopital. Cette etude est la premiere a notre connaissance reliant la qualite de la gestion a la composition du conseil d'administration des hopitaux. La performance a ete evaluee en determinant les activites qui etaient presentes, en termes de resultats pour les patients. Les donnees ont ete recueillies aupres du ministere de la Sante de l'Ontario : signalements des 109 hopitaux pendant plus de 3 ans et histoire des membres du conseil d’administration. L'effet des activites sur les patients a ete evalue pour des activites ayant un effet positif sur les resultats des patients (classees comme des activites essentielles). La performance des activites a ete etudiee en fonction de la composition et des competences du conseil. Trois liens ont ete trouves entre les conseils et les performances : les conseils avec des membres ayant des competences d'execution operationnelles avaient un rendement superieur, les conseils avec des entrepreneurs et du personnel medical ont eu un effet positif alors que les conseils avec des hommes politiques ont eu un impact negatif sur les performances. C'est pourquoi les conseils d'hopitaux de l'Ontario doivent etre construits de telle sorte que les membres puissent assurer une gouvernance de qualite superieure, conduisant a de meilleurs resultats pour les patients. Cette etude a revele deux activites qui n'avaient pas d’impact ou un impact negatif. La question de qualite de la gestion conseil competence peut etre evaluee en presence de l'activite et de la performance de ces activite
Two kinds of phase transitions in a voting model

In this paper, we discuss a voting model with two candidates, C0 and C1. We consider two types of voters—herders and independents. The voting of independents is based on their fundamental values, while the voting of herders is based on the number of previous votes. We can identify two kinds of phase transitions. One is an information cascade transition similar to a phase transition seen in the Ising model. The other is a transition of super and normal diffusions. These phase transitions coexist. We compared our results to the conclusions of experiments and identified the phase transitions in the upper limit of the time t by using the analysis of human behavior obtained from experiments.
Enhancing the determination of aspect categories and their polarities in Arabic reviews using lexicon-based approaches

Sentiment Analysis (SA) is the process of determining the sentiment of a text written in a natural language to be positive, negative or neutral. It is one of the most interesting subfields of natural language processing (NLP) and Web mining due to its diverse applications and the challenges associated with applying it on the massive amounts of textual data available online (especially, on social networks). Most of the current works on SA focus on the English language and work on the sentence-level or the document-level. This work focuses on the less studied version of SA, which is aspect-based SA (ABSA) for the Arabic language. Specifically, this work considers two ABSA tasks: aspect category determination and aspect category polarity determination, and makes use of the publicly available human annotated Arabic dataset (HAAD) along with its baseline experiments conducted by HAAD providers. In this work, several lexicon-based approaches are presented for the two tasks at hand and show that some of the presented approaches significantly outperforms the best known result on the given dataset.
An Online Hot Topics Detection Approach Using the Improved Ant Colony Text Clustering Algorithm

Recently, with an increasing number of major events spreading all over the Internet, the research for online hot topics detection system has been paid more and more attention. In this paper, we proposed an unsupervised and efficient hot topics detection approach, which is based on an improved ant colony text clustering (IACTC) algorithm. In view of the deficiencies of the basic ant colony text clustering (BACTC) method, the inverse tangent function is introduced into the proposed algorithm as a novel probability function, which could be flexibly adjusted. Meanwhile, in order to reduce ants’ blinding movement, we add the memory organ to each ant, and we develop the concept of adaptive moving range. Additionally, we design a practical system framework with technical details to solve the problems involving in the real-time hot topics detection system (e.g., information collecting, web preprocessing and text processing). This system is also used to evaluate our proposed method . The experimental results show that our approach has numerous advantages and achieves satisfying results.
Political support to public debt repudiation in a Monetary Union - the role of the geographical allocation of debt

The main arguments for the Stability and Growth Pact turn on the need to protect the European Central Bank against inflationary pressures from the fiscally prodigal countries (repudiation through inflation). Taking a political economy approach, in this paper we inquire into the conditions under which national governments may reach the decision for a partial or total repudiation of their debt. The main result produced by our model is that a debt management policy of lowering effective yields might be the dominant option for a self-interested government whose creditors consist in part of non-residents. On the basis of such result we argue that the impact of the fiscal position of the various member countries on the stability of EMU does not depend on the stock of debt but on the proportion of it that is held abroad.
Improving the Computational Thinking Pedagogical Capabilities of School Teachers

The idea of computational thinking as skills and universal competence which every child should possess emerged last decade and has been gaining traction ever since. This raises a number of questions, including how to integrate computational thinking into the curriculum, whether teachers have computational thinking pedagogical capabilities to teach children, and the important professional development and training areas for teachers. The aim of this paper is to address the strategic issues by illustrating a series of computational thinking workshops for Foundation to Year 8 teachers held at an Australian university. Data indicated that teachers' computational thinking understanding, pedagogical capabilities, technological know-how and confidence can be improved in a relatively short period of time through targeted professional learning.
An investigation of incremental 4D‐Var using non‐tangent linear models

We investigate the convergence of incremental four‐dimensional variational data assimilation (4D‐Var) when an approximation to the tangent linear model is used within the inner loop. Using a semi‐implicit semi‐Lagrangian model of the one‐dimensional shallow water equations, we perform data assimilation experiments using an exact tangent linear model and using an inexact linear model (a perturbation forecast model). We find that the two assimilations converge at a similar rate and the analyses are also similar, with the difference between them dependent on the amount of noise in the observations. To understand the numerical results, we present the incremental 4D‐Var algorithm as a Gauss–Newton iteration for solving a least‐squares problem and consider its fixed points. Copyright © 2005 Royal Meteorological Society.
Si mulation Techniques and Control Schemes in Electromyography for A Lower Limb and Power Assist Exoskeleton

Th is paper represents the first part of our work in which a successful exoskeleton system has been designed. With this design, the concentration is on effects of compliant human – exoskeleton robot on kinematics and muscle activity during human walking with or without carrying loads. In order to achieve these aims, two control methods are used: kinematic and surface electromyography (sEMG) – based control. In this article, three simulation techniques of sEMG signal are investigated. The obtained results of this work are very useful in designing and testing our actual exoskeleton system.
Discrimination of Virtual Environments Under Visual and Haptic Rendering Delays

Many virtual reality systems have a distributed structure for certain purposes such as more computational power, tele-presence, collaboration, and portability. However, network delays are inevitable in the distributed structure and often make sensory information delivered behind time to the user. In the literature, the effect of network delays on the quality of virtual environments has been considered mostly with respect to task performances. In this paper, we pay attention to whether perceptual artifacts caused by network delays are perceptible by the user, which is a more stringent criterion than the degradation of task performance. We examined minimum perceptible visual and/or haptic rendering delays by measuring their discrimination thresholds between normal and delayed virtual environments with and without a task, and report the results in this paper. We also provide a simple guideline for determining whether some active delay compensation algorithms are required in a distributed virtual reality system by comparing representative network delays to the measured discrimination thresholds.
On continuous null space projections for torque-based, hierarchical, multi-objective manipulation

The technological progress in the field of robotics results in more and more complex manipulators. However, having an increasing number of degrees of freedom raises the question of how to use them effectively. In turn, establishing manipulators in human environments, e.g., as service robots, calls for the fulfillment of various constraints and tasks at the same time. In the context of torque controlled robotic systems, we provide an approach to simultaneously deal with a multitude of tasks and constraints which are arranged in a hierarchy, utilizing the large number of actuated joints of the manipulator. To this end, we propose a continuous null space projection technique to consider unilateral constraints, singular Jacobian matrices and dynamic variations of the priority order within the hierarchical structure. We show that activating and deactivating tasks as well as crossing singularities does not lead to a discontinuous control law. Simulations and experiments on the humanoid Justin of the German Aerospace Center (DLR) validate our approach. The presented concept is supposed to contribute to whole-body control frameworks.
Exploring Genom ic Context Patterns for Rhodobacter sphaeroides in the HERBE Knowledge Discovery Environm ent

Sophisticated information strategies are increasingly essential for biologists. W e have built a powerful knowledge discovery resource using novel genomic context methods, interactive visualization strategies, and computational environment technologies. The Heuristic Entity Relationship Building Environment (HERBE) is a research platform for advanced database technologies that fuses data management solutions with knowledge management components to support the dynamic capture of concepts and observations as biologists explore large-scale data. The Similarity Box visualization software supports the ability of biologists to interact with large-scale computational results and evaluate relationships based on natural reasoning processes. W e have applied these knowledge methods in the exploration of complex microbial genome relationships. W e extracted a complete set of gene neighbor patterns for Rhodobacter sphaeroides using HERBE to map data structures for chromosomal contiguity against sequence similarity. W e then organized these gene neighbor patterns by their phylogenetic profiles using Similarity Box to enable biologists to explore the results.
Backpropagation Training for Fisher Vectors within Neural Networks

Fisher-Vectors (FV) encode higher-order statistics of a set of multiple local descriptors like SIFT features. They already show good performance in combination with shallow learning architectures on visual recognitions tasks. Current methods using FV as a feature descriptor in deep architectures assume that all original input features are static. We propose a framework to jointly learn the representation of original features, FV parameters and parameters of the classifier in the style of traditional neural networks. Our proof of concept implementation improves the performance of FV on the Pascal Voc 2007 challenge in a multi-GPU setting in comparison to a default SVM setting. We demonstrate that FV can be embedded into neural networks at arbitrary positions, allowing end-to-end training with back-propagation.
An unsupervised transfer learning approach to discover topics for online reputation management

Microblogs play an important role for Online Reputation Management. Companies and organizations in general have an increasing interest in obtaining the last minute information about which are the emerging topics that concern their reputation. In this paper, we present a new technique to cluster a collection of tweets emitted within a short time span about a specific entity. Our approach relies on transfer learning by contextualizing a target collection of tweets with a large set of unlabeled "background" tweets that help improving the clustering of the target collection. We include background tweets together with target tweets in a TwitterLDA process, and we set the total number of clusters. In practice, this means that the system can adapt to find the right number of clusters for the target data, overcoming one of the limitations of using LDA-based approaches (the need of establishing a priori the number of clusters). Our experiments using RepLab 2012 data show that using the background collection gives a 20% improvement over a direct application of TwitterLDA using only the target collection. Our data also confirms that the approach can effectively predict the right number of target clusters in a way that is robust with respect to the total number of clusters established a priori.
In-flight performances of the BeppoSAX gamma-ray burst monitor

The Italian-Dutch satellite for x-ray astronomy BeppoSAX is successfully operating on a 600 km equatorial orbit since May 1996. We present here the in-flight performances of the gamma ray burst monitor experiment during its first year of operation. The GRBM is the secondary function of the four CsI(Na) slabs primarily operating as an active anticoincidence of the PDS hard x-ray experiment. It has a geometric area of about 400 cm2 but, due to its location in the core of the satellite its effective area is dependent on the energy and direction of the impinging photons. A dedicated electronics allows to trigger on cosmic gamma-ray bursts. When the trigger condition is satisfied the light curve of the event is recorded from 8 s before to 98 s after the trigger time, with a maximum time resolution of 0.48 ms, in an energy band of 40 - 700 keV. As an instrument housekeeping the 1 s event ratemeter of the same detectors in the same energy band is stored regardless the trigger condition, allowing for an off- line detection of non-triggered events. Finally, the onboard software collects the event count rate that is used as anticoincidence, i.e. the events above a given energy threshold, typically kept at 100 keV. The flight-data screening is in progress, in order to extract real gamma ray bursts from the many sources of background. Already many results have been obtained, as those GRBs detected simultaneously with the wide field cameras oinboard BeppoSAX itself.