Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experiment in mixing evolving and preprogrammed robots

Artificial evolution of robot behavior is commonly conducted in environments containing a single robot or multiple robots that are all controlled by evolving behavioral logic. In this paper, we take a novel approach and study how the presence of preprogrammed robots affects the evolutionary process and the solutions evolved. We evolve behavioral control that enables robots to forage. The robots are situated in an environment that contains a nest and a number of prey. The robots must either push or carry the prey to the nest. We analyze the behaviors evolved in mixed setups in which one or more preprogrammed robots are present. We compare these behaviors to behaviors evolved in non-mixed setup in which no preprogrammed robots are present. The results show that although the evolved robots do not use their capacity to communicate, they do collaborate with the preprogrammed robots. We find that the performance of some of the solutions evolved in the mixed setup is higher than the performance of homogeneous groups of robots.
Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms

This paper presents CROWN, an automatically constructed extension of WordNet that augments its taxonomy with novel lemmas from Wiktionary. CROWN fills the important gap in WordNet’s lexicon for slang, technical, and rare lemmas, and more than doubles its current size. In two evaluations, we demonstrate that the construction procedure is accurate and has a significant impact on a WordNet-based algorithm encountering novel lemmas.
The in vivo distribution of brain tissue loss in Richardson’s syndrome and PSP‐parkinsonism: a VBM‐DARTEL study

In this study, we wished to test, using magnetic resonance imaging and voxel‐based morphometry (VBM), whether specific cortical and subcortical patterns of brain grey (GM) and white matter (WM) tissue loss can be detected in patients with Richardson’s syndrome (PSP‐RS) and progressive supranuclear palsy‐parkinsonism (PSP‐P), and possibly account for their clinical heterogeneity. Twenty patients with PSP, classified as PSP‐RS (10 patients) or PSP‐P (10 patients), and 24 healthy controls were studied. The Statistical Parametric Mapping (SPM5) and the Diffeomorphic Anatomical Registration using Exponentiated Lie algebra method were used to perform a VBM analysis. Compared with controls, both patient groups showed GM loss in the central midbrain, cerebellar lobes, caudate nuclei, frontotemporal cortices and right hippocampus. WM loss was detected in both conditions in the midbrain, left superior cerebellar peduncle, internal capsulae, and left premotor and bilateral prefrontal regions. Compared with PSP‐P, patients with PSP‐RS showed additional regions of GM loss in the midbrain, left cerebellar lobe and dentate nuclei. PSP‐RS was also associated with a more severe WM loss in the midbrain, internal capsulae, and orbitofrontal, prefrontal and precentral/premotor regions, bilaterally. Patients with PSP‐P showed a more pronounced GM loss only in the frontal cortex, bilaterally. This study shows that, albeit the overall pattern of brain atrophy associated with PSP appears remarkably consistent across the spectrum of clinical features recorded in life, major anatomical differences between these two conditions do exist. Such a different topographical distribution of tissue damage may account for the clinical differences between PSP‐RS and PSP‐P.
Exogenous shocks and the dynamics of city growth: evidence from New York

This article was presented at a conference organized by the Federal Reserve Bank of New York in April 2005, "Urban Dynamics in New York City. " The goal of the conference was threefold: to examine the historical transformations of the engine-of-growth industries in New York and distill the main determinants of the city's historical dominance as well as the challenges to its continued success; to study the nature and evolution of immigration flows into New York; and to analyze recent trends in a range of socioeconomic outcomes, both for the general population and recent immigrants more specifically.
Class-specific feature sets in classification

The classical Bayesian approach to classification requires knowledge of the probability density function (PDF) of the data or sufficient statistic under all class hypotheses. Since it is difficult or impossible to obtain a single low-dimensional sufficient statistic, it is often necessary to utilize a sub-optimal yet still relatively high-dimensional feature set. The performance of such an approach is severely limited by the ability to estimate the PDF on a high-dimensional space from training data. A new theorem shows that by introducing a special "noise-only" signal class, it is possible to re-formulate the classical approach based upon M sufficient statistics, one corresponding to each signal class. Also, the optimal classifier requires knowledge of only the PDF's sufficient statistics under the corresponding signal class and under noise-only condition. We present simulation results of a 9-class synthetic problem showing dramatic improvements over the traditional high-dimensional approach.
Learning to summarise XML documents using content and structure

Documents formatted in eXtensible Markup Language (XML) are becoming increasingly available in collections of various document types. In this paper, we present an approach for the summarisation of XML documents. The novelty of this approach lies in that it is based on features not only from the content of documents, but also from their logical structure. We follow a machine learning like, sentence extraction-based summarisation technique. To find which features are more effective for producing summaries this approach views sentence extraction as an ordering task. We evaluated our summarisation model using the INEX dataset. The results demonstrate that the inclusion of features from the logical structure of documents increases the effectiveness of the summariser, and that the learnable system is also effective and well-suited to the task of summarisation in the context of XML documents.
Monsieur Rémy Chrétien

Analyse automatique de propriétés d'équivalence pour les protocoles cryptographiques Résumé À mesure que le nombre d'objets capables de communiquer croît, le besoin de sécuriser leurs interactions également. La conception des protocoles cryptographiques nécessaires pour cela est une tâche notoirement complexe et fréquem-ment sujette aux erreurs humaines. La vérification formelle de protocoles entend offrir des méthodes automatiques et exactes pour s'assurer de leur sécurité. Nous nous intéressons en particulier aux méthodes de vérification automatique des propriétés d'équivalence pour de tels protocoles dans le modèle symbolique et pour un nombre non borné de sessions. Les propriétés d'équivalence sont naturellement employées pour s'assurer, par exemple, de l'anonymat du vote électronique ou de la non-traçabilité des passeports électroniques. Parce que la vérification de propriétés d'équivalence est un problème complexe, nous proposons dans un premier temps deux méthodes pour en simplifier la vérification : tout d'abord une méthode pour supprimer l'utilisation des nonces dans un protocole tout en préservant la correction de la vérification automatique; puis nous démontrons un résultat de typage qui permet de restreindre l'espace de recherche d'attaques sans pour autant affecter le pouvoir de l'attaquant. Dans un second temps nous exposons trois classes de protocoles pour lesquelles la vérification de l'équivalence dans le modèle symbolique est décidable. Ces classes bénéficient des méthodes de simplification présentées plus tôt et permettent d'étudier automatiquement des protocoles taggués, avec ou sans nonces, ou encore des protocoles ping-pong. 2 Acknowledgements I would first like to thank my advisors, Véronique Cortier and Stéphanie Delaune, for offering me such a wonderful opportunity. These years have been excellent and working with you was a real pleasure. I am very grateful to David Basin and Bruno Blanchet who kindly accepted to review this manuscript. I also thank Thomas Jensen, David Pointcheval and Dominique Unruh and who accepted to be part of the jury. I would also like to thank Géraud Sénizergues for his collaboration and presence for my defense. I also thank all the members of LSV for making this thesis such an enjoyable experience. Thank you for the stimulating discussions and the help throughout these years. Thank you in particular to the PhD students for making the laboratory far more than just a work place. I want to give special thanks to all my family, who has always supported me and believed in me. Thank you for blessing me with such a nurturing home and helping me become a better …
Modeling Strength of Multidirectional Laminates under Thermo-Mechanical Loads

This paper investigates the progressive failure process in a multidirectional composite laminate subjected to an arbitrary thermo-mechanical load condition. A micromechanics modeling approach is employed to predict each-ply failure strength of the laminate and to identify the corresponding failure mode. The analysis has incorporated both material non-linearity and stiffness reduction. The load shared by each lamina in the laminate is determined based on the classical laminate theory, whereas the internal stresses in the constituent fibers and matrix of the lamina are explicitly related to this load by making use of combining the bridging model and the Benveniste and Dvorak’s formula. The lamina failure is assumed whenever any constituent material attains its ultimate stress state. A generalized maximum normal stress criterion is employed to detect the constituent failure. In this approach, all the simulation equations are given explicitly, no iteration is involved, and a minimum number of input data are required. Comparison of the predicted thermo-mechanical strengths of several laminates with available experimental data is favorable.
xDSL systems prototyping using a flexible emulation environment

In this paper we describe the methodology and architecture of a flexible modular environment for prototyping data transmission systems and its application on xDSL systems. The development environment is based on custom and commercially available software tools and a custom hardware emulation platform for mapping the basic data-pump modules of xDSL systems into hardware/software functional modules. The road-map from a high-level xDSL system model to the actual prototype is based on the progressive substitution of high-level submodules of the initial model with their respective hardware/software counterparts, and their integration into a complete functional system. A library of custom blocks is used for data exchange and synchronization between the high-level model and the emulation platform, and for real-time visualization of the critical parameters of the emulated system as well. The application of the proposed development environment in the implementation and testing of an emulator of a bundle of DSL lines and of a centralized bit-loading algorithm for multicarrier ADSL systems is also described.
A 2.4 GHz-868 MHz dual-band wake-up radio for wireless sensor network and IoT

Wake-up radio is an emerging technology with the ambitious goal of reducing the communication power consumption in smart sensor networks and Internet of Things. This reduction in power consumption will enable a new generation of applications which could achieve a longer lifetime than is achievable today. Wake up radios are required to work with a low power budget and should exhibit low latency coupled with high sensitivity and addressing capabilities. Typically they are combined with existing radio transceiver and power management techniques to reduce the overall communication power while maintaining the same communication performance. This paper presents a dual band (2.4GHz and 868MHz) wake up radio with the above mentioned characteristics. The dual band solution is exploited to increase the flexibility of the wake up radio, allowing interoperability with the two most common frequencies used in Wireless Sensors Networks and Internet of Things. Simulation results present a system able to exploit the two bands with sensitivity as low as -53dBm at 868MHz and -45dBm at 2450MHz. Experimental results on power consumption demonstrate the low power consumption of the proposed solution with only 1. 276μW of power consumption in listening mode. The addressing is performed by an ultra low power on board PIC microcontroller with 40nW of power consumption when the wake up radio is in listening mode and only 70 μW when the data are received and parsed.
Distinct Signaling Cascades Elicited by Different Formyl Peptide Receptor 2 (FPR2) Agonists

The formyl peptide receptor 2 (FPR2) is a remarkably versatile transmembrane protein belonging to the G-protein coupled receptor (GPCR) family. FPR2 is activated by an array of ligands, which include structurally unrelated lipids and peptide/proteins agonists, resulting in different intracellular responses in a ligand-specific fashion. In addition to the anti-inflammatory lipid, lipoxin A4, several other endogenous agonists also bind FPR2, including serum amyloid A, glucocorticoid-induced annexin 1, urokinase and its receptor, suggesting that the activation of FPR2 may result in potent pro- or anti-inflammatory responses. Other endogenous ligands, also present in biological samples, include resolvins, amyloidogenic proteins, such as beta amyloid (Aβ)-42 and prion protein (Prp)106–126, the neuroprotective peptide, humanin, antibacterial peptides, annexin 1-derived peptides, chemokine variants, the neuropeptides, vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase activating polypeptide (PACAP)-27, and mitochondrial peptides. Upon activation, intracellular domains of FPR2 mediate signaling to G-proteins, which trigger several agonist-dependent signal transduction pathways, including activation of phospholipase C (PLC), protein kinase C (PKC) isoforms, the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) pathway, the mitogen-activated protein kinase (MAPK) pathway, p38MAPK, as well as the phosphorylation of cytosolic tyrosine kinases, tyrosine kinase receptor transactivation, phosphorylation and nuclear translocation of regulatory transcriptional factors, release of calcium and production of oxidants. FPR2 is an attractive therapeutic target, because of its involvement in a range of normal physiological processes and pathological diseases. Here, we review and discuss the most significant findings on the intracellular pathways and on the cross-communication between FPR2 and tyrosine kinase receptors triggered by different FPR2 agonists.
Exploring the Link between Bolstered Classification Error and Dataset Complexity for Gene Expression Based Cancer Classification

Gene expression profiles were shown to be useful in genomic si gnal processing when discriminating between cancer and normal (healthy) ex amples and/or between different types of cancer. K-nearest neighbors (k-NN) is on e f the classification algorithms that demonstrated good performance for gene expre ssion based cancer classification. Given that distance metric is fixed, the conventi onal k-NN has a single parameter (k the number of nearest neighbors for each examp le) to set, which makes k-NN a very attractive choice in addition to the fact that it d oes not need training. Classification performance of any classifier, including a kNN, is typically characterized by classification error achieved on independent e xamples, which are often unavailable for the considered task. Thus, unbiased and low -variance error estimation is of ultimate importance in this case. We found that bolster ed error satisfies these requirements and it was therefore chosen for our study. Bolste red rror estimation is built on random sampling in the neighborhood of each example (with example-dependent neighborhood radius) and computing the number of errors mad e on such artificially created data. Because of random sampling, all examples can b e employed in assessing the error, unlike cross-validation or bootstrap procedure s. In this work, we investigate the link between k-NN bolstered error and dataset complexity characterizing how difficult to classify a certa in dataset. Our measure for the dataset complexity is the normalized Wilcoxon rank sum s tatistic. Through extensive simulation coupled with the copula method for analysis of association in bivariate data, we show that dataset complexity and bolstered error ar e related in terms of several dependence types such as positive quadrant dependence , tail monotonicity, and stochastic monotonicity. 2 Oleg Okun, Giorgio Valentini, and Helen Priisalu As a result, we propose a new scheme for generating ensembles of k-NN classifiers, which is based on the selection of low complexity featu re subsets for k-NNs in the ensemble, which constitutes to choosing accurate k-NNs according to the found dependence relation. The candidate subsets are randomly sa pled from the whole set of the original features in order to make predictions of indi vidual k-NNs diverse. Experiments carried out on eight gene expression datasets c on aining different types of cancer demonstrate that our ensemble generating sc heme is superior (in terms of bolstered resubstitution error) to a single best classifi er in the ensemble and to the traditional ensemble construction scheme that is ignorant of dataset complexity. It also outperforms the redundancy-based filter, especially d esigned to remove irrelevant genes.
Mathematical Model of Embodied Symbols: Cognition and Perceptual Symbol System

A mathematical model of perceptual symbol system is developed. This development requires new mathematical methods of dynamic logic (DL), which have overcome limitations of classical artificial intelligence and connectionist approaches. The paper discusses these past limitations, relates them to combinatorial complexity (exponential explosion) of algorithms in the past, and relates it further to the static nature of classical logic. DL is a process-logic; its salient property is evolution of vague representations into crisp. We first consider one aspect of PSS: situation learning from object perceptions. Next DL is related to PSS mechanisms of concepts, simulators, grounding, embodiment, productiveity, binding, recursion, and to the mechanisms relating embodied-grounded and amodal symbols. We discuss DL capability for modeling cognition on multiple levels of abstraction. PSS is extended toward interaction between cognition and language. Experimental predictions of the theory are discussed. They might influence experimental psychology and impact future theoretical developments in cognitive science, including knowledge representation, and mechanisms of interaction between perception, cognition, and language. All mathematical equations are also discussed conceptually, so mathematical understanding is not required. Experimental evidence for DL and PSS in brain imaging is discussed as well as future research directions.
Molecular cloning and characterization of a broad substrate terpenoid oxidoreductase from Artemisia annua.

From Artemisia annua L. , a new oxidoreductase (Red 1) was cloned, sequenced and functionally characterized. Through bioinformatics, heterologous protein expression and enzyme substrate conversion assays, the elucidation of the enzymatic capacities of Red1 was achieved. Red1 acts on monoterpenoids, and in particular functions as a menthone:neomenthol oxidoreductase. The kinetic parameter k(cat)/K(m) was determined to be 939-fold more efficient for the reduction of (-)-menthone to (+)-neomenthol than results previously reported for the menthone:neomenthol reductase from Mentha x piperita. Based on its kinetic properties, the possible use of Red1 in biological crop protection is discussed.
CellSense: A Probabilistic RSSI-Based GSM Positioning System

Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this paper, we present CellSense, a probabilistic RSSI-based fingerprinting location determination system for GSM phones. We discuss the challenges of implementing a probabilistic fingerprinting localization technique in GSM networks and present the details of the CellSense system and how it addresses the challenges. To evaluate our proposed system, we implemented CellSense on Android-based phones. Results for two different testbeds, representing urban and rural environments, show that CellSense provides at least 23.8% enhancement in accuracy in rural areas and at least 86.4% in urban areas compared to other RSSI-based GSM localization systems. This comes with a minimal increase in computational requirements. We also evaluate the effect of changing the different system parameters on the accuracy-complexity tradeoff.
Mitochondrial replacement in an iPSC model of Leber's hereditary optic neuropathy

Cybrid technology was used to replace Leber hereditary optic neuropathy (LHON) causing mitochondrial DNA (mtDNA) mutations from patient-specific fibroblasts with wildtype mtDNA, and mutation-free induced pluripotent stem cells (iPSCs) were generated subsequently. Retinal ganglion cell (RGC) differentiation demonstrates increased cell death in LHON-RGCs and can be rescued in cybrid corrected RGCs.
Effects of levodopa on forward and backward gait patterns in persons with Parkinson's disease.

INTRODUCTION Backward walking is difficult for persons with Parkinson's disease (PD). It is unknown how levodopa influences backward gait patterns, especially when compared to forward gait patterns. PURPOSE Investigate the effects of levodopa on forward and backward gait patterns in individuals with PD. DESIGN A repeated measures design was used. METHODS The sample consisted of 21 individuals with PD (15 males, 6 females). Their mean age was 70.24 ± 8.69 yr. The average time since diagnosis was 11.81 ± 5.49 years. The median of the Hoehn and Yahr stage while 'ON' medication was 2.57. Gait patterns during forward and backward walking at a self-selected comfortable speed were recorded before and after taking levodopa on the same day. RESULTS Levodopa significantly increased gait speed and stride length and decreased the percent of the gait cycle (%GC) spent in double support. Gait speed and stride length were greater and the %GC spent in double support was less during forward walking compared with backward walking. Cadence was not changed by levodopa or walking direction. CONCLUSIONS Levodopa improved gait characteristics during backward walking in a manner similar to that during forward walking in persons with PD.
Using Design Science Research to develop Online Enhanced Pharmaceutical Care Services

The ePharmaCare project aims at assessing the potential of eHealth services for the provision of pharmaceutical services interacting actively with patients. The results presented here focus on the first three steps of Design Science Research Methodology. A mixed methods approach was used with an online survey to collect data on use of information technologies in community pharmacy, followed by an exploratory observational time and business processes study, which use the shadowing method to identify and assess the opportunity to lunch online services. Combining this with the Service Experiment Blueprint and the Dáder method an enhanced pharmaceutical service was designed. Next, an artifact is developed and a prototype is implemented to demonstrate the value of online pharmaceutical services' delivery. This new service could represent a new perspective for pharmaceutical services integration within the health system.