pinecone/core-2020-05-10-deduplication huggingface dataset:
The Formation of the First Massive Black Holes

Supermassive black holes (SMBHs) are common in local galactic nuclei, and
SMBHs as massive as several billion solar masses already exist at redshift z=6.
These earliest SMBHs may grow by the combination of radiation-pressure-limited
accretion and mergers of stellar-mass seed BHs, left behind by the first
generation of metal-free stars, or may be formed by more rapid direct collapse
of gas in rare special environments where dense gas can accumulate without
first fragmenting into stars. This chapter offers a review of these two
competing scenarios, as well as some more exotic alternative ideas. It also
briefly discusses how the different models may be distinguished in the future
by observations with JWST, (e)LISA and other instruments.Comment: 47 pages with 306 references; this review is a chapter in "The First
  Galaxies - Theoretical Predictions and Observational Clues", Springer
  Astrophysics and Space Science Library, Eds. T. Wiklind, V. Bromm & B.
  Mobasher, in pres
Evolutionary synthesis models as a tool and guide towards the first
  galaxies

We summarize the principles and fundamental ingredients of evolutionary
synthesis models, which are stellar evolution, stellar atmospheres, the IMF,
star-formation histories, nebular emission, and also attenuation from the ISM
and IGM. The chapter focusses in particular on issues of importance for
predictions of metal-poor and Population III dominated galaxies.
  We review recent predictions for the main physical properties and related
observables of star-forming galaxies based on up-to-date inputs. The predicted
metallicity dependence of these quantities and their physical causes are
discussed. The predicted observables include in particular the restframe
UV-to-optical domain with continuum emission from stars and the ionized ISM, as
well as emission lines from H, He, and metals.
  Based on these predictions we summarize the main observational signatures
(emission line strengths, colors etc.), which can be used to distinguish
"normal" stellar populations from very metal-poor objects or even Pop III.
  Evolutionary synthesis models provide an important and fundamental tool for
studies of galaxy formation and evolution, from the nearby Universe back to
first galaxies. They are used in many applications to interpret existing
observations, to predict and guide future missions/instruments, and to allow
direct comparisons between state-of-the-art galaxy simulations and
observations.Comment: 32 pages, 19 figures. Chapter to appear in "The First Galaxies -
  Theoretical Predictions and Observational Clues", Eds. T. Wiklind, V. Bromm,
  B. Mobasher, Springer Verla
Deciding which skill to learn when: Temporal-Difference Competence-Based Intrinsic Motivation (TD-CB-IM)

Intrinsic motivations, the topic of this paper, can be defined by contrasting them to extrinsic motivations. Extrinsic motivations are directed to drive and guide the learning of behaviour directed to satisfy homeostatic regulations related to the organisms\u27 survival and repro- duction. Intrinsic motivations, instead, are motivations that serve the evolutionary function of acquiring knowledge (e.g., the capacity to pre- dict) and competence (i.e. the capacity to do) in the absence of extrinsic motivations: this knowledge and competence can be later exploited for producing behaviours that enhance biological fitness. While knowledge- based intrinsic motivation mechanisms have been widely modelled and studied, competence-based intrinsic motivation mechanisms (CB-IM), usable for guiding learning on the basis of competence level or improve- ment, have been much less investigated. The goal of this paper is to clarify the nature and possible roles of CB-IM mechanisms for learning, in particular in relation to the cumulative acquisition of a repertoire of skills underlying the capacity to accomplish multiple tasks in the environ- ment, and then to review a specific CB-IM mechanism. This mechanism (TD-CB-IM) measures the improvement rate of competence on the ba- sis of the Temporal-Difference learning signal (TD-error) used in several reinforcement learning (RL) models. The effectiveness of the mechanism is supported by reporting the results of some experiments where the TD- CB-IM mechanism is successfully exploited by a hierarchical RL model controlling a simulated navigating robot to decide when to train different skills in different environmental conditions. The mechanism is one of the few CB-IM mechanisms proposed in the computational literature
Functions and mechanisms of intrinsic motivations: the knowledge versus competence distinction

Mammals, and humans in particular, are endowed with an exceptional capacity for cumulative learning. This capacity crucially de- pends on the presence of intrinsic motivations, i.e. motivations that are not directly related to an organism\u27s survival and reproduction but rather to its ability to learn. Recently, there have been a number of attempts to model and reproduce intrinsic motivations in artificial systems. Different kinds of intrinsic motivations have been proposed both in psychology and in machine learning and robotics: some are based on the knowl- edge of the learning system, while others are based on its competence. In this contribution we discuss the distinction between knowledge-based and competence-based intrinsic motivations with respect to both the functional roles that motivations play in learning and the mechanisms by which those functions are implemented. In particular, after arguing that the principal function of intrinsic motivations consists in allowing the development of a repertoire of skills (rather than of knowledge), we suggest that at least two different sub-functions can be identified: (a) discovering which skills might be acquired and (b) deciding which skill to train when. We propose that in biological organisms knowledge-based intrinsic motivation mechanisms might implement the former function, whereas competence-based mechanisms might underly the latter one
On the Finite Dimensional Laws of Threshold GARCH Processes

In this chapter we establish bounds for the finite dimensional laws of a threshold GARCH process, X, with generating process Z. In this class of models the conditional standard deviation has different reactions according to the sign of past values of the process. So, we firstly find lower and upper bounds for the law of \left ({X}_{1}^{+},-{X}_{1}^{+},\ldots,{X}_{n}^{+},-{X}_{n}^{+}\right), in certain regions of R^{2n}, and use them to find bounds of the law of \left ({X}_{1},\ldots,{X}_{n}\right). Some of these bounds only depend on the parameters of the model and on the distribution function of the independent generating process, Z. An application of these bounds to control charts for time series is presented
Carbon, water and energy fluxes of terrestrial ecosystems in Italy

In this chapter the Eddy Covariance network of Italy is presented, with a short introduction to each of the 29 sites that were active during the CarboItaly project. These sites provided a unique dataset for a better study and understanding of the carbon cycle of terrestrial ecosystems and the links between carbon sink capacity and the main environmental factors. After a number of examples of Eddy Covariance time series where it is possible to see the effect of interannual climate variability and disturbances and managements practices, an analysis of the role of the Carbon Uptake Period in the total Net Ecosystem Exchange (NEE) definition and a study of the effect of temperature and precipitation on the interannual variability of NEE are presented in order to show the way these data can contribute to a better understanding of the role and response of ecosystems to climate change
Rich internet application for semi-automatic annotation of semantic shots on keyframes

This paper describes a system developed for the semi-automatic annotation of keyframes in a broadcasting company. The tool aims at assisting archivists who traditionally label every keyframe manually by suggesting them an automatic annotation that they can intuitively edit and validate. The system is valid for any domain as it uses generic MPEG-7 visual descriptors and binary SVM classifiers. The classification engine has been tested on the multiclass problem of semantic shot detection, a type of metadata used in the company to index new content ingested in the system. The detection performance has been tested in two different domains: soccer and parliament. The core engine is accessed by a Rich Internet Application via a web service. The graphical user interface allows the edition of the suggested labels with an intuitive drag and drop mechanism between rows of thumbnails, each row representing a different semantic shot class. The system has been described as complete and easy to use by the professional archivists at the companyPostprint (published version
Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM

International audienceWe implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order selection, we combine the CEM algorithm with the hierarchical agglomeration strategy and a model order selection criterion called Integrated Completed Likelihood (ICL). We exploit amplitude statistics in a Finite Mixture Model (FMM), and a Multinomial Logistic (MnL) latent class label model for a mixture density to obtain spatially smooth class segments. We test our algorithm on TerraSAR-X data
Real-Time Specification Patterns and Tools

An issue limiting the adoption of model checking technologies by the industry
is the ability, for non-experts, to express their requirements using the
property languages supported by verification tools. This has motivated the
definition of dedicated assertion languages for expressing temporal properties
at a higher level. However, only a limited number of these formalisms support
the definition of timing constraints. In this paper, we propose a set of
specification patterns that can be used to express real-time requirements
commonly found in the design of reactive systems. We also provide an integrated
model checking tool chain for the verification of timed requirements on TTS, an
extension of Timed Petri Nets with data variables and priorities.Comment: An extended version of this paper appears as Research Report LAAS No.
  11364, June 2011. 17th International Workshop on Formal Methods for
  Industrial Critical Systems, FMICS 2012, Paris : France (2012
OrderBased labeling scheme for dynamic XML query processing

Need for robust and high performance XML database systems increased due to growing XML data produced by today's applications. Like indexes in relational databases, XML labeling is the key to XML querying. Assigning unique labels to nodes of a dynamic XML tree in which the labels encode all structural relationships between the nodes is a challenging problem. Early labeling schemes designed for static XML document generate short labels; however, their performance degrades in update intensive environments due to the need for relabeling. On the other hand, dynamic labeling schemes achieve dynamicity at the cost of large label size or complexity which results in poor query performance. This paper presents OrderBased labeling scheme which is dynamic, simple and compact yet able to identify structural relationships among nodes. A set of performance tests show promising labeling, querying, update performance and optimum label size. © 2012 IFIP International Federation for Information Processing
The Projection Games Conjecture and the NP-Hardness of ln n-Approximating Set-Cover

We suggest the research agenda of establishing new hardness of approximation results based on the “projection games conjecture”, i.e., an instantiation of the Sliding Scale Conjecture of Bellare, Goldwasser, Lund and Russell to projection games.
We pursue this line of research by establishing a tight NP-hardness result for the Set-Cover problem. Specifically, we show that under the projection games conjecture (in fact, under a quantitative version of the conjecture that is only slightly beyond the reach of current techniques), it is NP-hard to approximate Set-Cover on instances of size N to within (1 − α)ln N for arbitrarily small α > 0. Our reduction establishes a tight trade-off between the approximation accuracy α and the time required for the approximation 2[superscript NΩ(α)], assuming Sat requires exponential time.
The reduction is obtained by modifying Feige’s reduction. The latter only provides a lower bound of 2[superscript NΩ(α/loglogN)] on the time required for (1 − α)ln N-approximating Set-Cover assuming Sat requires exponential time (note that N[superscript 1/loglogN] = N[superscript o(1)]). The modification uses a combinatorial construction of a bipartite graph in which any coloring of the first side that does not use a color for more than a small fraction of the vertices, makes most vertices on the other side have their neighbors all colored in different colors
Sensorization and intelligent systems in energetic sustainable environments

Sustainability is an important topic of discussion in our world. However,
measuring sustainability and assessing behaviors is not always easy. Indeed, and in
order to fulfill this goal, in this work it will be proposed a multi-agent based architecture to measure and assess sustainable indicators taken from a given environment.
These evaluations will be based on past and present behaviors of the users and the
particularities of the setting, leading to the evaluation of workable indicators such
as gas emissions, energetic consumption and the users fitting with respect to the
milieu. Special attention is given to user interaction and user attributes to calculate
sustainable indicators for each type of structure, i.e., the aim of this scheme is to promote sustainability awareness and sustainable actions through the use of sustainable
markers calculated in terms of the information gathered from the environment.The research presented is partially supported by a portuguese doctoral grant,
SFRH/BD/78713/2011, issued by the Fundação da Ciência e Tecnologia (FCT) in Portugal
Autonomous Exploration Using Kinect and Laser Range Finder

Autonomous exploration has received a large attention in robotic community. Recently, the low cost RGB-D sensor Microsoft Kinect has got more and more applications in mapping and localization, since it can provide abundant depth environment information in real time. However, the robot equipped only with Kinect sensor for autonomous navigation will face safety problems in complex scenarios. In this paper, we analyze the Kinect limitations and propose a system setup equipped with both Kinect and laser range finder in order to achieve a safety navigation in dynamic indoor environments. The Kinect is used for global navigation planning including target finding, best target choosing and path planning, while the laser performs local obstacle avoidance. The performances of map building and autonomous exploration are evaluated for two robotic platforms in lab environments to validate the proposed approac
High-performance combination of low resolution tactile images using a bit-based representation

Since the seminal work of Harmon[1] through to more recent reviews such as that of Dahiya et al.[2], the focus in the field of tactile sensing has been on creating sensors with resolutions as low as 1mm . Such specifications are justified by the simplicity of manufacturing a single resolution of skin sensor for all possible applications. Unfortunately, this approach requires not only that a robot has some means of connecting to potentially millions of sensors, but more significantly that it has some means of processing the commensurately large volume of data. The work presented here reduces the volume of data that must be processed by allowing the requirement for high resolution sensors to be relaxed and by the novel use of the bitboard data structure that has been used to represent board games for computers as well as solve complex graph problems [3]
Singularity Hypotheses: An Overview

Bill Joy in a widely read but controversial article claimed that the most powerful 21st century technologies are threatening to make humans an endangered species. Indeed, a growing number of scientists, philosophers and forecasters insist that the accelerating progress in disruptive technologies such as artificial intelligence, robotics, genetic engineering, and nanotechnology may lead to what they refer to as the technological singularity: an event or phase that will radically change human civilization, and perhaps even human nature itself, before the middle of the 21st century
A Characterization of Bispecial Sturmian Words

A finite Sturmian word w over the alphabet {a,b} is left special (resp. right
special) if aw and bw (resp. wa and wb) are both Sturmian words. A bispecial
Sturmian word is a Sturmian word that is both left and right special. We show
as a main result that bispecial Sturmian words are exactly the maximal internal
factors of Christoffel words, that are words coding the digital approximations
of segments in the Euclidean plane. This result is an extension of the known
relation between central words and primitive Christoffel words. Our
characterization allows us to give an enumerative formula for bispecial
Sturmian words. We also investigate the minimal forbidden words for the set of
Sturmian words.Comment: Accepted to MFCS 201
Leveraging Task-Parallelism in Energy-Efficient ILU preconditioners

We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditioner for the solution of sparse\ud
linear systems on multi-core processors. In particular, we elaborate a theoretical model for the power dissipation, and employ it to explore the effect of the processor power states on the time-power-energy interaction\ud
for this calculation. Armed with the insights gained from this study, we then introduce two energy-saving mechanisms which, incorporated into the runtime in charge of the parallel execution of the algorithm, improve energy efficiency by 6.9%, with a negligible impact on\ud
performance.Peer ReviewedPostprint (published version
What do strokes teach us about collaborative design ?

Understanding collaborative design goes far beyond analyzing group dynamics, tasks allocations or negotiation during decision-making processes. In this paper, we focused on the collaborative sketching process, during which the intentions of designers are supported by their sketches and by specific strokes.Twelve professional designers attended an experimental design session, where they were asked to express, share, capture or interpret sketches. A qualitative and quantitative fine-grained analysis of strokes teach us (i) how designers tend to deal with representations that are not theirs; (ii) what main graphical key-features constitute the inner nature of the shared information and (iii) how and when can this graphic essence be shared with collaborators.Peer reviewe
Linearity in the non-deterministic call-by-value setting

We consider the non-deterministic extension of the call-by-value lambda
calculus, which corresponds to the additive fragment of the linear-algebraic
lambda-calculus. We define a fine-grained type system, capturing the right
linearity present in such formalisms. After proving the subject reduction and
the strong normalisation properties, we propose a translation of this calculus
into the System F with pairs, which corresponds to a non linear fragment of
linear logic. The translation provides a deeper understanding of the linearity
in our setting.Comment: 15 pages. To appear in WoLLIC 201
Improving the cAnt-MinerPB Classification Algorithm

Ant Colony Optimisation (ACO) has been successfully applied to the classification task of data mining in the form of Ant-Miner. A new extension of Ant-Miner, called cAnt-MinerPB, uses the ACO procedure in a different fashion. The main difference is that the search in cAnt-MinerPB is optimised to find the best list of rules, whereas in Ant-Miner the search is optimised to find the best individual rule at each step of the sequential covering, producing a list of best rules. We aim to improve cAnt-MinerPB in two ways, firstly by dynamically finding the rule quality function which is used while the rules are being pruned, and secondly improving the rule-list quality function which is used to guide the search. We have found that changing the rule quality function has little effect on the overall performance, but that by improving the rule-list quality function we can positively affect the discovered lists of rules
Fast restoration of Connectivity for Wireless Sensor Networks

International audienceNode failures represent a fundamental problem in wireless sensor networks. Such failures may result in partitioned networks and lose of sensed information. A network recovery approach is thus necessary in order to ensure continuous network operations. In this paper, we propose CoMN2 a scalable and distributed approach for network recovery from node failures in wireless sensor networks. CoMN2 relies on a new concept called network mapping which consists in partitioning the network into several regions of increasing criticality. The criticality is set according to the energy, the traffic distribution and the deployment of nodes. Using this network mapping, our solution CoMN2 ensures the continuous network activity by efficiently swapping nodes from low critical area to highly critical area when required. Simulation results prove the effectiveness of our approach and show that the obtained improve-ment in terms of lifetime is in the order of 40%
Business Process Data Compliance

Most approaches to business process compliance are restricted to the analysis of the structure of processes. It has been argued that full regulatory compliance requires information on not only the structure of processes but also on what the tasks in a process do. To this end Governatori and Sadiq[2007] proposed to extend business processes with semantic annotations. We propose a methodology to automatically extract one kind of such annotations; in particular the annotations related to the data schema and templates linked to the various tasks in a business process
Multi-robot Map Updating in Dynamic Environments

Multi-robot systems play an important role in many robotic applications. A prerequisite for a team of robots is the capability of building and maintaining updated maps of the environment. The simultaneous estimation of the trajectory and the map of the environment (known as SLAM) requires many computational resources. Moreover, SLAM is generally performed in environments that do not vary over time (called static environments), whereas real applications commonly require navigation services indynamic environments. This paper focuses on long term mapping operativity in presence of variations in the map, as in the case of robotic applications in logistic spaces, where rovers have to track the presence of goods in given areas. In this context classical SLAM approaches are generally not directly applicable, since they usually apply in static environments or in dynamic environments where it is possible to model the environment dynamics. This paper proposes a methodology that allows the robots to detect variations in the environment, generate maps containing only the persistent variations, propagate thiem to the team and finally merge the received information in a consistent way. The team of robots is also exploited to assure the coverage of areas not visited for long time, thus improving the knowledge on the present status of the map. The map updating process is demonstrated to be computationally light, in order to be performed in parallel with other tasks (e.g., team coordination and planning, surveillance)