Miracle-dz/UniFAR-FTUs huggingface dataset:
CRII : RI : Learning Skills from First Person Demonstrations

Project Summary Wearable (first person) cameras such as Snapchat Sunglasses and GoPro open up a new opportunity to closely record our candid and unscripted interactions with surroundings. In particular, as following the visual attention of the camera wearer, it can measure subtle eye-hand coordination, e.g., head location, gaze direction, and finger configuration. Such subtlety has been largely ignored in prior studies of object interaction due to limited resolution of third person cameras (surveillance camera or robot mounted camera). In this research proposal, the PI proposes to develop a theory and algorithm to learn skills such as playing tennis or violin from first person cameras. However, understanding first person videos is challenging because state-of-the-art computer vision systems built upon third person videos do not apply. The first person view is highly dynamic, local, and person-biased due to severe head movements, which produces larger variations of visual data. The PI will address this challenge by building a 3D reconstruction algorithm of interactions with surrounding objects, which enables effectively learning first person demonstrations using an imitation learning framework. This computational model of interactions with environments will offer a new opportunity to train and teach robots in an intuitive, cost effective, and scalable way. It will also enable quantitative skill assessment and training.
Solving Complexity and Resource-Constrained Project Scheduling Problem in Aircraft Heavy Maintenance

Aircraft heavy maintenance consists of complex sets of interrelated activities that must be performed in a given period of time regarding the maintenance schedule. However, delays of aircraft delivery, particularly in heavy maintenance, seem to be a common problem for aviation industry due to its complexity and a vast number of tasks to carry out with limited resources. This paper presents an approach to solve the complexity of the interrelated activities and the resourceconstrained project scheduling problem (RCPSP) of the aircraft heavy maintenance. It applies DSM to sequence the interrelated activities in proper order. The priority rules-based heuristic is employed to solve the RCPSP with the minimum makespan. Regarding the maintenance schedule and the stochastic data sets of the actual duration, a simulation model is therefore conducted to evaluate the system of the aircraft heavy maintenance.
Torque Mapping Low Level Torque ControlTrunkTask Gravity Compensation Momentum Based Disturbance Observer + Whole-Body Optimization Planner User Input Foot Scheduler Whole-Body Controller Terrain Estimator State Estimator

We present experimental results using a passive whole-body control approach for quadruped robots that achieves dynamic locomotion while compliantly balancing the robot’s trunk. We formulate the motion tracking as a Quadratic Program (QP) that takes into account the full robot rigid body dynamics, the actuation limits, the joint limits and the contact interaction. We analyze the controller’s robustness against inaccurate friction coefficient estimates and unstable footholds, as well as its capability to redistribute the load as a consequence of enforcing actuation limits. Additionally, we present practical implementation details gained from the experience with the real platform. Extensive experimental trials on the 90 kg Hydraulically actuated Quadruped (HyQ) robot validate the capabilities of this controller under various terrain conditions and gaits. The proposed approach is superior for accurate execution of highly dynamic motions with respect to the current state of the art.
Bank concentration and retail interest rates q

The recent wave of mergers in the euro area raises the question whether the increase in concentration has offset the increase in competition in European banking through deregulation. We test this question by estimating a simple Cournot model of bank pricing. We construct country and product specific measures of bank concentration and find that for loans and demand deposits increasing concentration may have resulted in less competitive pricing by banks, whereas for savings and time deposits, the model is rejected, suggesting increases in contestability and/or efficiency in these markets. Finally, the paper discusses some implications for tests of the effect of concentration on monetary policy transmission. 2002 Elsevier Science B.V. All rights reserved. JEL classification: G21; D43
Simultaneous proximal-type epithelioid sarcoma of the chest wall and primary pulmonary adenocarcinoma : a case report and literature review

Epithelioid sarcoma (ES) is a rare and aggressive soft-tissue neoplasm that is divided into distal-type ES and proximal-type ES. Due to this tumor's infrequent occurrence, uncertain differentiation, and atypical histological pictures, diagnosis of epithelioid sarcoma in its early stages has become extremely difficult. This present study reports, in detail, a rare case of proximal-type ES of the chest wall with primary pulmonary adenocarcinoma, simultaneously, in a 54-year-old man. To the best of our knowledge, this is the first case of simultaneous proximal-type epithelioid sarcoma of the chest wall with primary pulmonary adenocarcinoma.
Three-segmented hopping leg for the analysis of human running locomotion

Legged locomotion is an interesting subject because it may contribute to our understanding of the biomechanics of human walking and running, as well as to the developement of legged mobile robots. Here, a planar model for a hopping three-segmented single leg with an associated control concept is introduced. The overall model is capable of passive hopping motion by means of torsional springs in the joints, and it can be used for the analysis of some aspects of running motion, such as ground-foot impact, energy efficiency or balancing. The control actions are realized by actuator torques in the ankle and knee joints and in the hip, which is coupled to a reaction wheel. We show that stable periodic motion exists, which imitates human locomotion.
Seasonal Dependence of Geometrical and Optical Properties of Tropical Cirrus Determined from Lidar, Radiosonde, and Satellite Observations over the Polluted Tropical Indian Ocean (Maldives)

Cirrus clouds detected with a six-wavelength aerosol lidar in the tropical region of the Maldives (4.1° N, 73.3° E) were characterized in terms of seasonal geometrical, optical, and thermal properties. The dataset was collected during the Indian Ocean Experiment between February 1999 and March 2000. Cirrus visible optical depth, mean extinction coefficient, and lidar ratio were derived from the 532–nm elastic–backscatter lidar signals. Temperature information from radiosondes launched frequently at the lidar site was used to characterize the thermal structure of the tropical troposphere and the temperature dependence of the optical and geometrical cirrus properties. Descending stratospheric Kelvin waves were observed which seem to influence cirrus formation close to the tropopause. Deep convection is most likely responsible for the formation of cirrus below 14 km height. Cirrus clouds were detected during 51% of the time at altitudes between 7 and 18 km, but were on average located below altitudes reported in other tropical cirrus studies. Trajectories and satellite data providing outgoing longwave radiation and aerosol optical depth were used to characterize the source regions of the cirrus clouds and suggested that clouds were probably affected by anthropogenic pollution. An impact of pollution on the cirrus optical properties could not be quantified. Zusammenfassung Zirren, gemessen mit einem Sechswellenlängenlidar auf den tropischen Malediven (4.1° N, 73.3° O), wurden anhand ihrer saisonalen geometrischen, optischen und thermischen Eigenschaften charakterisiert. Der Datensatz entstand zwischen Februar 1999 und März 2000 bei Messungen im Rahmen des Indian Ocean Experiment. Optische Dicken, mittlere Extinktionskoeffizienten und Extinktion-zu-Rückstreuverhältnisse der Zirren wurden aus dem elastischen Lidarrückstreusignal bei 532 nm bestimmt. Von der Lidarstation aus gestartete Radiosonden lieferten Temperaturprofile, die zur Charakterisierung der tropischen Troposphäre und der Temperaturabhängigkeit der optischen und geometrischen Zirruseigenschaften verwendet wurden. Absinkende stratosphärische Kelvinwellen wurden beobachtet, die scheinbar die Bildung von Zirren in Tropopausennähe beeinflussen. In Höhen unter 14 km ist höchstwahrscheinlich hochreichende Konvektion für die Zirrusbildung verantwortlich. In 51% der Messzeit wurden Zirren beobachtet, die sich üblicherweise in Höhen zwischen 7 und 18 km befanden, jedoch im Mittel tiefer lagen, als in anderen Studien über tropische Zirren berichtet wird. Anhand von Trajektorien und Satellitendaten, die Informationen zu ausgehender langwelliger Strahlung und optischen Dicken des Aerosols lieferten, wurden Quellregionen der Zirren charakterisiert und Indizien gefunden, die einen Einfluss von anthropogener Verschmutzung auf Zirren vermuten lassen. Ein quantitativer Nachweis für den Einfluss von Verschmutzung auf die optischen Zirruseigenschaften konnte nicht gefunden werden.
ENVIRONMENTAL FACTORS CONTROLLING CILIATES IN SHALLOW LAKES OF THE DANUBE DELTA – SPATIAL AND TEMPORAL

The Danube Delta Biosphere Reserve encompasses a complex of aquatic ecosystems with a mosaic of structural and functional features, that influence significantly the biological communities. Ciliata group plays an important role as part of the zooplankton communities, being a key factor in nutrient cycling within the microbial loop. The microbial food web gained lately a wide recognition, especially in eutrophic and hypertrophic systems (such as the Danube Delta) as circulation pathway of organic matter within the planktonic trophic networks and reintroduction of inorganic forms of nutrients in the water, rendering them available again to primary producers. In 2013, an intensive study was carried out, covering a seasonal sampling program (spring, summer, autumn) in four large deltaic lake complexes. This paper focuses on the characterization of ciliate community, highlighting also the biotic and abiotic factors that control this community in the investigated lakes. A number of 30 genera and species were identified, the highest diversity being reached in the marine part of the delta (23 in complex Roşu – Puiu, and 20 in Matiţa – Merhei), and the lowest in the fluvial complex Şontea – Fortuna (7). The abundance varied in a large spatial and temporal range, in all the four lake complexes: in Roşu – Puiu, it fluctuated between 38 ind Lin summer and a minimum of 0.28 ind L in Mândra, in spring; in Gorgova Isac, it varied between 27.60 ind L in Gorgostel, in October, and 0.22 ind L in Uzlina, in July; in Matiţa – Merhei, it fluctuated between 48 ind Lin Merheiul Mic, in October, and 0.30 ind L in Matiţa, in May, while in Şontea-Fortuna complex it ranged between 1.60 in Ligheanca, and 0.24 in Lake No name, both in summer. In terms of spatial distribution of Ciliata abundance, the maximum averages were recorded in Roşu Puiu complex (7.61 ind L) and the minimum in ŞonteaFortuna (0.81). Anova single factor analysis reveals no statistically significant differences in terms of abundance in the 4 lake complexes (p>0.05, Fcrit>F). The corelation of ciliate development according to the season has been tested with single factor ANOVA and revealed that seasons affected statistically significant this community (p<0.05, F3, 128 = 4.591). An important biotic factor controlling ciliates development was phytoplankton biomass (estimated as total chlorophyll a concentration (r=0.46, p<0.0001). In particular, two phytoplankton groups had a significant influence on the ciliates: Cyanobacteria (r= 0.269, p<0.05) and Chlorophyceae (0.38, p<0.01). Among the physical-chemical factors that had a significant influence on the ciliate community were: pH (r=0.29, p<0.05), conductivity (r=0.31, p<0.01 ), turbidity (r=0.293, p<0.01), the redox potential (r=0.304 , p<0.05), DO (r=0.35 , p<0.05) and TP concentration (r=0.245 , p<0.05).
Fair value measurement disclosure regulation and the manufacturing sector

This study examines the effect of FASB Accounting Standards Codification on Fair Value Measurements (ASC 820-10) on distressed and non-distressed firms in the manufacturing sector. The manufacturing sector took a considerable hit in production aided by the decreased global liquidity caused by the major financial crisis of 2007. This study aims to shed light on the effects of corporate disclosure regulation and its effects on firms with a perceived incentive to bias financial reporting. Initial results indicate that ASC 820-10 did improve financial reporting quality however the requirement did have a differential effect on distressed and non-distressed firms.
Real-Time Fuzzy Identification of Twin Rotor MIMO System

This paper presents identification of laboratory Twin Rotor MIMO System (TRMS) using fuzzy logic. The TRMS is a challenging system to control since it is a non-minimum phase system and is a laboratory bench mark system for air vehicles like helicopters. This system has two degrees of freedom with strong cross-coupling between the vertical and horizontal axes. For optimal tuning of the fuzzy system parameters, the gradient descent algorithm is employed in this paper. In order to reduce the computation complexity and at the same time to increase robustness of the fuzzy model, the online learning method is used here. Experimental results show effectiveness of the proposed approach.
The Dynamics of Concealment

Abstract Firm managers likely have more information than outsiders. If managers strategically conceal information, market uncertainty will increase. We develop a dynamic corporate disclosure model, estimating the model using the management earnings forecasts of US public companies. The model, based on the buildup of reputations by managers over time, matches key facts about forecast dynamics. We find that 80% of firms strategically manage information, that managers have superior information around half of the time, and that firms conceal information about 40% of the time. Concealment increases market uncertainty by just under 8%, a sizable information loss.
invasive ladybird Harmonia axyridis Expansion of the antimicrobial peptide repertoire in the Supplementary data tml

Supplementary data tml http://rspb.royalsocietypublishing. org/content/suppl/2012/11/15/rspb.2012. 2113.DC1. h "Data Supplement" References http://rspb.royalsocietypublishing. org/content/280/1750/20122113.full. html#ref-list-1 This article cites 39 articles, 10 of which can be accessed free This article is free to access Subject collections (13 articles) immunology  (28 articles) genomics  (1333 articles) ecology  Articles on similar topics can be found in the following collections
Feature Selection Using FCBF in Type II Diabetes Databases

— Data mining techniques have been widely applied to extract knowledge from medical databases. Data mining is the search for relationships and global patterns that exist in large databases but are `hidden' among the vast amount of data, such as a relationship between patient data and their medical diagnosis. Usually medical databases are high dimensional in nature. If a training dataset contains irrelevant and redundant features (i.e., attributes), classification analysis may produce less accurate results. In order for data mining algorithms to perform efficiently and effectively on high-dimensional data, it is imperative to remove irrelevant and redundant features. Data pre-processing is required to prepare the data for data mining tasks to increase the predictive accuracy. Feature selection is one of the important and frequently used data preprocessing technique for data mining applications in medicine. This paper illustrates, the application of feature selection technique in medical databases, will enable to find small number of informative features leading to potential improvement in medical diagnosis. It is proposed to find an optimal feature subset of the PIMA Indian Diabetes Dataset using Symmetrical Uncertainty Attribute set Evaluator and Fast Correlation-Based Filter (FCBF). The approach is validated by means of performance enhancement of the Libsvm classifier.
Analysis of combustion stability and efficiency of a mesoscale combustor by means of Continuously Stirred Tank Reactor model

Miniaturization of electronics and mechanical systems has triggered the need for the development of small-scale power generation and propulsion systems. The higher energy density of hydrocarbon fuels as compared to currently available top rechargeable chemical batteries (respectively 45 MJ/kg vs. ~0.6 MJ/kg) [1] has readily focused the attention towards combustion based systems. Moreover the cube square law suggested that micro-propulsion and micro-power generation systems based on combustion could outperform macro-scale propulsion devices and chemical batteries. Nevertheless combustion in meso and micro combustor could be hindered by the high surface to volume ratio (heat losses and wall quenching issues) and by the quite short residence time (poor chemical conversion), thus a proper management and understanding of the thermo-chemical issues connected to size reduction are mandatory in order to realize operational and efficient meso-combustors [1-6]. The present work originated from an on-going research activity carried out by some of the authors on a meso-scale whirl combustor of about 254 mm in volume and burning H2, CH4 or C3H8 [7-11]. Their experimental results evidenced that under isothermal condition the mesocombustor has an internal flow field characterized by an asymmetric vortex structure, a high turbulent region near the reactants injection zone and a quite quiescent region at its center [10]. By means of the shadowgraph technique a similar flow structure has been also observed under combustion conditions [11]. These results supported the possibility to numerically investigate the meso-scale combustor by representing it as a Continuously Stirred Tank Reactor (CSTR). The CSTR approach is very attractive because compared to other complex approach (i.e. CFD simulation) it allows to quickly evaluate basic combustor performances at different operating conditions and to use detailed kinetical scheme for hydrocarbon oxidation. To this aim, the stability (blow-off) limits and the chemical efficiencies of a meso scale whirl combustor burning hydrocarbon fuels have been numerically investigated by a Continuously Stirred Tank Reactor model coupled with a detailed kinetic scheme. Analyses of the relevant numerical results and a comparison with the relevant experimental data have been also reported.
SpellRueval : the FiRSt Competition on automatiC Spelling CoRReCtion FoR RuSSian

This paper reports on the first competition on automatic spelling correction for Russian language—SpellRuEval—held within the framework of “Dialogue Evaluation”. The competition aims to bring together groups of Russian academic researchers and IT-companies in order to gain and exchange the experience in automatic spelling correction, especially concentrating on social media texts. The data for the competition was taken from Russian segment of Live Journal. 7 teams took part in the competition, the best results were achieved by the model using edit distance and phonetic similarity for candidate search and n-gram language model for their reranking. We discuss in details the algorithms used by the teams, as well as the methodology of evaluation for automatic spelling correction.
Structured singular values for Bernoulli matrices

In this article we present the computation of lower bounds of Structured Singular Values (SSV) for a class of Bernoulli matrices. The comparison of lower bounds with the well-known MATLAB routine mussv is studied and investigated. SSV provides important tools to analyze, synthesize the robustness, performance, stability and instability analysis of feedback systems in the linear control theory as well as in structured eigenvalue perturbation theory. MSC: 40C05 • 58E25
University of Groningen Interactive example-based hatching Gerl

We present an approach for interactively generating pen-and-ink hatching renderings based on handdrawn examples. We aim to overcome the regular and synthetic appearance of the results of existing methods by incorporating human virtuosity and illustration skills in the computer generation of such imagery. To achieve this goal, we propose to integrate an automatic style transfer with user interactions. This approach leverages the potential of example-based hatching while giving users the control and creative freedom to enhance the aesthetic appearance of the results. Using a scanned-in hatching illustration as input, we use image processing and machine learning methods to learn a model of the drawing style in the example illustration. We then apply this model to semi-automatically synthesize hatching illustrations of 3D meshes in the learned drawing style. In the learning stage, we first establish an analytical description of the hand-drawn example illustration using image processing. A 3D scene registered with the example drawing allows us to infer object-space information related to the 2D drawing elements. We employ a hierarchical style transfer model that captures drawing characteristics on four levels of abstraction, which are global, patch, stroke, and pixel levels. In the synthesis stage, an explicit representation of hatching strokes and hatching patches enables us to synthesize the learned hierarchical drawing characteristics. Our representation makes it possible to directly and intuitively interact with the hatching illustration. Amongst other interactions, users of our system can brush with patches of hatching strokes onto a 3D mesh. This interaction capability allows illustrators who are working with our system to make use of their artistic skills. Furthermore, the proposed interactions allow people without a background in hatching to interactively generate visually appealing hatching illustrations. & 2012 Elsevier Ltd. All rights reserved.
M ay 2 01 5 Towards Optimal Adaptive Wireless Communications in Unknown Environments

Designing efficient channel access schemes for wireless communications withoutany prior knowledge about the nature of environments has been a very challenging issue, espe cially when the channel states distribution of all spectrum resour ces could be entirely or partially stochastic and/or adversarial at different time and locations. In this paper, we propose an adaptive channel access algorithm for wireless communicat ions in unknown environments based on the theory of multi-armed bandits (MAB) problems. By automatically tuning two control parameters, i.e., learning rate and exploration probabili ty, our algorithms are capable of finding the optimal channel access strategies and achieving the almost optimal learning perfo rmance over time under our defined four typical regimes for general unknown environments, e.g., the stochastic regime where ch annels follow some unknown i.i. d. process, the adversarial re gime where all channels are suffered by adversarial jamming attack, the mixed stochastic and adversarial regime where a subset o f channels are attacked and the contaminated stochastic regi me where occasionally adversarial events contaminate the sto chastic channel process, etc. To reduce the implementation time and space complexity, we further develop an enhanced algorithmby exploiting the internal structure of the selection of channel access strategy. We conduct extensive simulations in all these reg imes to validate our theoretical analysis. The quantitative performance studies indicate the superior throughput gain and the flexibility of our algorithm in practice, which is resilient to both oblivious and adaptive jamming attacks with different intelligence and any attacking strength that ranges from no-attack to the full-attack of all spectrum resources.