Miracle-dz/UniFAR-FTUs huggingface dataset:
Production and maintenance environments for interactive audio-visual stories

1. I N T R O D U C T I O N Storytelling is a pervasive aspect within our life because it helps to shape our experience by structuring events encountered in our everyday reality. Narrating means making a comment about a certain event, following an idea about the medium and form of presentation, which is grounded in one's own motivational and psychological attributes. Narrating is a targeted phenomenon. There is a receiver and the narrator's perception of him or her may have an impact on the outcome of the story. Moreover, both narrator and receiver do not exist in a vacuum but share a social environment, which adds extra structures to the narrational process. Thus, narration is a dynamic process of interaction in a partly given social context, where 'the interaction encompasses . the communicator, the content, the audience and the situation' [12, p. 209].
A Role for Complement in the Enhanced Susceptibility of Steatotic Livers to Ischemia and Reperfusion Injury1

Hepatic steatosis typically renders the donor organ unusable, as donor organs with >30% steatosis are more likely to develop graft failure. The mechanisms leading to failure are not well defined, but steatosis enhances hepatic susceptibility to ischemia reperfusion injury (IRI). We investigated the role of complement in hepatic IRI in lean and steatotic (diet-induced) mice. Steatotic mice were significantly more susceptible to total warm hepatic IRI than lean mice as determined by serum alanine aminotransferase, histopathologically assessed damage, and 24-h survival. C3 deficiency protected both lean and steatotic mice from IRI, as determined by all measured outcomes. Furthermore, treatment of wild-type mice with the complement inhibitor CR2-Crry provided protection equivalent to that seen in C3-deficient mice. Importantly, although steatotic livers were much more susceptible to IRI than lean livers, by most measures there was no statistical difference between the level of IRI to steatotic or lean livers when complement was inhibited. To investigate the clinical relevance of these findings in the context of transplantation, we treated recipients of lean or steatotic liver grafts with saline or CR2-Crry. There was a marked reduction in graft inflammation and injury and significantly improved 7-day survival in CR2-Crry-treated recipients of either lean or steatotic grafts. These data indicate that complement plays a key role in the enhanced susceptibility of steatotic livers to IRI and suggest that complement inhibition represents a potential strategy to reduce the donor shortage by allowing the more routine use of marginal steatotic donor livers.
Towards Describing Perceived Complexity of Songs: Computational Methods and Implementation

Providing valuable semantic descriptors of multimedia content is a topic of high interest for music content processing. Such descriptors should merge the two predicates of (1) being useful for different operations such as retrieval, visual representation of collections, classification, etc., and (2) being automatically extractable from the source. In this paper the semantic descriptor concept music complexity is introduced, and the advantages of their usage for music retrieval and for automated music recommendation are addressed. The authors provide a critical review of existing related proposals and also prospect new methods for automated music complexity estimation.
Speech Separation and Perception by Human-Machine Collaboration Everyday

Everyday, we encounter situations where our abilities to separate and understand speech are taxed to the limit and beyond: streets, trains, coffee shops, etc. Hearing damage or the natural decline in hearing ability with age can make these circumstances frustrating and dangerous, and there are many applications in which it would be valuable to 'hear out' one voice embedded in a complex, natural environment. Current automatic systems fair very poorly in such conditions. This project seeks to develop a system consisting of acoustic sensors, machine processing, and a human operator, that will handle these scenarios far better than any existing approach. The collaboration between human and machine is crucial: the unflagging, high-precision calculations of the machine will benefit from the complex, abstract knowledge of the operator to create a system in which the complementary skills of human and machine each ameliorate the other's weaknesses. To be successful, this system must be fully informed both by the most current algorithmic and signal processing approaches, and by the best understanding of the capabilities and details of human audition and speech perception. Thus, the project brings together experts in human psychophysics, machine learning, and sound and speech recognition, to contribute their particular skills to the common goal. Methods: By using sophisticated 'virtual acoustics' techniques, a corpus of highly realistic complex acoustic environments will be synthesized that duplicate the most demanding speech-separation conditions encountered in daily life, that include crowds, mechanical and other nonspeech noise, and reverberation. The control afforded by this synthetic approach (which will be verified against limited field recordings) will enable human perceptual experiments revealing the intelligibility abilities and limitations of listeners in such conditions. The nature and results of these experiments will intermesh with the selection and development of machine algorithms; the project seeks to integrate the hitherto distinct areas of blind source separation and spatial filtering, and computational auditory scene analysis in which models of the source separation strategies employed by listeners are implemented on machines. Carefully designed and controlled evaluations will quantify the benefits of the work in both objective and subjective tests. Intellectual Merit: The unique combination of skills in this project, spanning several different approaches to machine processing and incorporating deep expertise in human auditory perception, will foster the creation of new source separation technologies of crucial importance to applications including speech recognition, speaker identification, hearing-assistance technology, and audio coding and indexing. The psychological investigations conducted …
Approximation Theory of Matrix Rank Minimization and Its Application to Quadratic Equations

Matrix rank minimization problems are gaining a plenty of recent attention in both mathematical and engineering fields. This class of problems, arising in various and across-discipline applications, is known to be NP-hard in general. In this paper, we aim at providing an approximation theory for the rank minimization problem, and prove that a rank minimization problem can be approximated to any level of accuracy via continuous optimization (especially, linear and nonlinear semidefinite programming) problems. One of the main results in this paper shows that if the feasible set of the problem has a minimum rank element with the least F-norm (i.e., Frobenius norm), then the solution of the approximation problem converges to the minimum rank solution of the original problem as the approximation parameter tends to zero. The tractability under certain conditions and convex relaxation of the approximation problem are also discussed. The methodology and results in this paper provide a new theoretical basis for the development of some efficient computational methods for solving rank minimization problems. An immediate application of this theory to the system of quadratic equations is presented in this paper. It turns out that the condition for such a system without a nonzero solution can be characterized by a rank minimization problem, and thus the proposed approximation theory can be used to establish some sufficient conditions for the system to possess only zero solution.
A Novel Fisheye-Lens-Based Photoacoustic System

This paper presents a novel fisheye-lens-based photoacoustic (PA) system. In conventional PA systems, mechanical motors are utilized to obtain the target information due to the small fields of view of such systems. The use of such motors introduces mechanical noise, which is difficult to remove when processing the echo signals. A fisheye lens system offering a wide field of view would effectively reduce the motor effects (i.e., the noise) and enable the system to have a wide field of view. Therefore, in this work, we propose a novel fisheye lens scheme and describe a PA system based on the developed lens scheme. In addition, to confirm the feasibility of the fisheye-lens-based PA system, we present the typical pulse-echo responses obtained using a 20 MHz single element immersion transducer and the echo signals measured from bull’s eye tissue samples separated by approximately 4, 6, 8, and 10 cm diagonally and 2 cm vertically from the fisheye lens. The experimental results demonstrate that the echo signal amplitudes, their center frequencies, and the −6 dB bandwidths obtained using red, green, and blue lights and a fisheye lens are acceptable when the fisheye lens is separated from a sample both diagonally and vertically. Therefore, fisheye-lens-based PA systems could be a potential method of achieving wide fields of view while reducing the mechanical motor effects.
The Effect of Trialable Advertising on the Durable Goods Pricing

The consumer by facing the future generates an expectation characterised by the utility of a product innovation introduced through trialable advertising, which at present length of time squeezes down the durable price. The willingness to replace the durable in the future, on the one hand, increases the slope of the high income consumer demand curve and, on the other hand, decreases the slope of the low income consumer demand curve.
Sustainable Forest Management Techniques

Forests being an indispensable resource play an important role in maintaining the earth's ecological balance. The major contributors of deforestation are logging off of trees (legal or illegal), tree theft, forest fire etc. Large scale deforestation has negative impact on the atmosphere resulting in global warming, flash floods, landslides, drought etc. Due to these adverse effects, forest management department all over the countries have taken steps for monitoring the forest to prevent deforestation. Several surveillance techniques have been employed for monitoring and prevention; they are broadly classified as Ground-based sensing techniques and Remote sensing techniques. Surveillance plays an important role in forest management. It had been used in the past and is still being used for monitoring and information collection. Ground-based techniques generally include surveillance by on-site security staff and mobile patrols monitoring the property by water, land and air (Magrath et al., 2007). Some complementary systems such as Fixed Earth System are also used with observation towers located at strategic points with specialized personnel for observing and detecting the presence of fire. All these systems are expensive and time consuming, requiring a lot of resources. Nowadays, remote sensing technologies are also used like, aerial photographs, automatic video surveillance, wireless surveillance systems and satellite imagery. Satellite imagery is very costly for use in monitoring any illegal activity like trespassers, tree theft and deforestation (if they are able to detect at all). On the other hand, with the technological advancements in wireless communication, various low power, and low cost, small-sized sensors nodes are available which can be readily deployed to monitor environment over vast areas. Wireless Sensor Networks (WSNs) technology is being used widely for monitoring and controlling applications. Currently three main wireless standards are used namely: WiFi, Bluetooth and ZigBee. Amongst them, ZigBee is the most promising standard owing to its low power consumption and simple networking configuration. Wireless sensor network based surveillance systems for remote deployment and control are more cost effective and are easy to deploy at location of interest. They can even reach those areas where satellite signals are not available. Moreover, they can be configured to monitor large areas and they have secure mode of data transmission. Environmentally, WSNs finds immense application in land management, agriculture management, lake water quality management, forest fire detection, tree theft prevention and also in the prevention of deforestation. In addition, WSN system has also been used for strain monitoring in railway bridges. (Bischoff et al., 2009), developed an event based strain
Active vision and feature selection in evolutionary behavioral systems

We describe an evolutionary approach to active vision systems for dynamic feature selection. After summarizing recent work on evolution of a simulated active retina for complex shape discrimination, we describe in detail experiments that extend this approach to an all-terrain mobile robot equipped with a mobile camera. We show that evolved robots are capable of selecting simple visual features and actively maintaining them on the same retinal position, which largely simplifies the "recognition" task, in order to generate efficient navigation trajectories with an extremely simple neural control system. Analysis of evolved solutions indicates that robots develop a simple and yet very efficient version of edge detection and visual looming to detect obstacles and move away from them. Two evolved sensory-motor strategies are described, one where the mobile camera is actively used throughout the entire navigation and one where it is used only at the beginning to point towards relevant environmental features. The relationship between these two strategies are discussed in the context of the underlying visuomotor mechanisms and of the evolutionary conditions.
TransCom 3 CO2 inversion intercomparison: 2. Sensitivity of annual mean results to data choices

TransCom 3 is an intercomparison project for CO2 source inversions. Annual mean CO2 concentration data are used to estimate CO2 sources using 16 different atmospheric transport models. Here we test the sensitivity of the inversion to the concentration data. We examine data network choice, time period of data, baseline data selection and the choice of data uncertainty used. We find that in most cases regional source estimates lie within the source uncertainty range of the control inversion. This indicates that the estimated sources are relatively insensitive to the changes in data that were tested. In the data network tests, only the Australian region source estimates varied over a much larger range than that given by the control case uncertainty estimate. For the other regions, the sensitivity to data network was within or close to the uncertainty range. Most of the sensitivity was found to be associated with a small number of sites (e.g. Darwin, Easter Island). These sites are often identified by the inability of the inversion to fit the data at these locations. The model-mean inversion values are mostly insensitive to the time period of data used, with the exception of temperate North America and the tropical Indian ocean. Data selection has a small impact on source estimates for the mean across models, but individual model sensitivity can be large. The magnitude of data uncertainties controls the relative magnitude of the estimated source uncertainty and the spread in model source estimates. Smaller data uncertainties lead to larger differences in source estimates between models. Overall, the data sensitivity tests performed here support the robustness of the control inversion source estimates presented in Gurney et al. (2003. Tellus 55B, this issue). The test results also provide guidance in setting up and interpreting other inversions.
Leakage localization in water networks using fuzzy logic

This paper presents a methodology for leakage localization using FIR (Fuzzy Inductive Reasoning). A real water network situated in Barcelona has been subdivided in zones which could contain a leakage. Two sensors measure pressures on two separated points of the network. A faulty fuzzy model for each zone and sensor is generated. Test data have been used for classification of leakages in order to evaluate how this methodology helps in leakage localization. Results are compared with another isolation methodology. All the work has been done using simulations carried out by EPANET connected with Matlab. FIR applications used are programmed in Matlab too.
Daily global maps of carbon monoxide from NASA's Atmospheric Infrared Sounder

We present the first observations of tropospheric carbon monoxide (CO) by the Atmospheric Infrared Sounder (AIRS) onboard NASA's Aqua satellite. AIRS daily coverage of ∼70% of the planet represents a significant evolutionary advance in satellite trace gas remote sensing. Tropospheric CO abundances are retrieved from AIRS 4.55 μm spectral region using the full AIRS retrieval algorithm run in a research mode. The presented AIRS daily global CO maps from 22–29 September 2002 show large‐scale, long‐range transport of CO from anthropogenic and natural sources, most notably from biomass burning. The sequence of daily maps reveal CO advection from Brazil to the South Atlantic in qualitative agreement with previous observations. Forward trajectory analysis confirms this scenario and indicates much longer range transport into the southern Indian Ocean. Preliminary comparisons to in situ aircraft profiles indicate AIRS CO retrievals are approaching the 15% accuracy target set by pre‐launch simulations.
Mean-Dispersion Preferences.

The starting point for this paper is the variational preference model introduced by Maccheroni et al (2006)), which includes Gilboa-Schmeidler multiple-prior preferences and Hansen-Sargent multiplier preferences. First, we show that any variational preferences admit aprimal' representation with a natural in- terpretation: amean' expected-utility of the act minus adispersion measure' that depends only on state-by-state dierences from that mean. The second term can be thought of as reecting the agent's dislike of dispersion: it is the premium (in terms of the mean utility) that the individual would be willing to pay to remove all subjective uncertainty associated with the act. The primal representation thus high- lights a key behavioral aspect of all variational preferences: the premium does not depend on the average utility of an act. That is, variational preferences exhibit constant absolute ambiguity aversion. Second, we develop a generalization of the variational preference model. The generalization is still based on a mean utility and a dispersion measure that depends only on the state-wise dierences from the mean. But the new model is only weakly separable in terms of these two summary statistics. Thus, the ambiguity premium need not be constant in this model. Mean-dispersion preferences can accommodate many existing models. We show how these correspond to dierent attitudes toward dispersion. Finally, we use the model to compare dierent notions of aversion to variation across states such as uncertainty aversion, second-order risk aversion and issue preference.
Working Papers Department of Economics University of Vienna Learning by Imitation When Playing the Field

We study the properties of learning rules based on imitation in the context of n-player games played among agents within the same population. We find that there are no (non-trivial) rules that increase (average) expected payoffs at each possible state, and for any possible game. The results highlight the complexity of learning by imitation of successful behavior displayed by conspecifics in the presence of strategic considerations within the same population.
Argument structure as a locus for binding theory

Argumentstructureasalo cusforbindingtheoryChristopherD.ManningUniversityofSydneycmanning@ucc.su. oz.au1Lo catingbindingrelationshipsThecorrectlo cus(orlo ci)ofbindingtheoryhasb eenamattermuchdiscussion.Theoriescanb eseenasvaryingalongatleasttwodimensions.The rstiswhetherbindingtheorycon gurationallydetermined(thatis,thetheoryexploitsgeometryofaphrasemarker,ap-p ealingtosuchpurelystructuralnotionsasc-commandandgovernment)orwhetherthetheorydep endsratheronexaminingtherelationsb etweenitemsselectedbyapredicate(whereselectionIamintendingtocovereverythingfromsemanticdep endenciessyntacticsub cat-egorization). Thesecondisthelevelofgrammaronwhichbindingde ned.Attemptingtoroughlyequatelevelsacrossdi erenttheories,suggestionshaveincludedthesemantics/lexicalconceptualstructure(Jackendo 1992),thematic1972,Wilkins1988),ar-gumentstructure/D-structure/initialgrammaticalrelations(Manning1994,BellettiandRizzi1988,Perlmutter1984),surfacesyntax/grammaticalrelations,logicalform,linearorder,prag-matics(Levinson1991),anddiscourse(Iida1992). Thedataissucientlyvariedcomplexthatmanytheoriesendupasmixtures,variouslyemployingacombinationofelementsalongb othdimensions(forinstance,Chomsky(1986)reliespurelyoncon gurationalnotionsfortherelationshipb etweenananaphoranditstecedent,butusesconceptsfromselectioninthede nitionofthebindingdomainananaphor). LFGhasalwaysrejectedcon gurationalaccountofbinding.Forinstance,Simpson(1991)arguesthatacon gurationaltheoryofbindinginWarlpiricannotb emaintained,amongotherreasonsb ecause niteclauseslackaVP.Thesuggestionisratherthatbindingcanb eaccountedforatthelevelofgrammaticalrelations,bynotingthatsub jectscanbindob jects.IacceptargumentsofBresnan(lectures,1985{93),Wilkins(1988),Dalrymple(1993)andPollardSag(1994)infavourofatheorybindingbasedonselectionratherthancon gurations,butIwillhavelittlemoretosayonthismatter(sincenothinginparticularnewadd). Instead,Iwanttoconcentrateontheseconddimension.Thedominantraditionwithingenerativegrammarhasb eentoassumethatthenotionofsurfaceobliquenessidenti esthesub jectofaclause(whethercon gurationallyorbyanorderingondep endents)isalsousedforthecoreconditionsonreexivebinding.InLGB(Chomsky1981),bindingtheoryisde nedonS-structure,sothatin(1),Nancycanbindherselfduetothec-commandingcon gurationthatalsomakesNancythesub ject. (1)IPNPNancyiVPVgaveNPherselfiDetaNraise1
The English Resultative as a Family of Constructions

English resultative expressions have been a major focus of research on the syntax-semantics interface. We argue in this article that a family of related constructions is required to account for their distribution. We demonstrate that a number of generalizations follow from the semantics of the constructions we posit: the syntactic argument structure of the sentence is predicted by general principles of argument linking; and the aspectual structure of the sentence is determined by the aspectual structure of the constructional subevent, which is in turn predictable from general principles correlating event structure with change, extension, motion, and paths. Finally, the semantics and syntax of resultatives explain the possibilities for temporal relations between the two subevents. While these generalizations clearly exist, there is also a great deal of idiosyncrasy involved in resultatives. Many idiosyncratic instances and small subclasses of the construction must be learned and stored individually. This account serves to justify aspects of what we share in our overall vision of grammar, whatwe might call the CONSTRUCTIONAL view. To the extent that our treatment of the resultative can be stated only within the constructional view, it serves as evidence for this view as a whole.