Miracle-dz/UniFAR-FTUs huggingface dataset:
Incrementality and intention-recognition in utterance processing

Ever since dialogue modelling first developed relative to broadly Gricean assumptions about utter-ance interpretation (Clark, 1996), it has remained an open question whether the full complexity of higher-order intention computation is made use of in everyday conversation. In this paper we examine the phenomenon of split utterances, from the perspective of Dynamic Syntax, to further probe the necessity of full intention recognition/formation in communication: we do so by exploring the extent to which the interactive coordination of dialogue exchange can be seen as emergent from low-level mechanisms of language processing, without needing representation by interlocutors of each other’s mental states, or fully developed intentions as regards messages to be conveyed. We thus illustrate how many dialogue phenomena can be seen as direct consequences of the grammar architecture, as long as this is presented within an incremental, goal-directed/predictive model.
Crossing a categorical boundary: the implications of switching from non-kosher wine production in the Israeli wine market

With growing interest in the penalties associated with straddling market categories, it is important to develop a stock of evidence about the relative importance of consideration and valuation penalties in different empirical settings. In this chapter, we isolate the possible adverse implications for currently kosher Israeli wine producers that were established as non-kosher producers. Our analysis suggests that crossing the kosher categorical boundary exposes these producers to experience-based penalties that are reflected in lower product quality ratings. However, we find no evidence of additional penalties associated either with consideration (i.e., market access) or with the possession of a convoluted organizational identity.
Aerial localization of an RF source in NLOS condition

In this paper a particle filter approach to the localization of an RF source, such as a cell phone in a search and rescue mission, with unknown power and None Line Of Sight (NLOS) condition has been introduced. Two basic methods based on the Received Strength Signal Indicator (RSSI) and Angle of Arrival (AOA) using particle filters have been implemented. Two new approaches have been proposed to benefit from both RSSI and AOA methods. In the first approach the transmit power of the source has been estimated to improve the localization method. To reduce the number of particles while maintaining good accuracy, a differential method is proposed which combines the advantages of both RSSI and AOA methods, while keeping the number of particles low and keeping the accuracy acceptable. The methods have been implemented in simulation, and the results prove the efficiency of the proposed methods. The results show that even a low resolution AOA sensor can reduce NLOS propagation effects on RSSI based approaches. Furthermore, the proposed hybrid approaches did not add significant computational load to the localization process, making it suitable for real time applications.
Investigation of Phenolic Acids in Suspension Cultures of Vitis vinifera Stimulated with Indanoyl-Isoleucine, N-Linolenoyl-L-Glutamine, Malonyl Coenzyme A and Insect Saliva

Vitis vinifera c.v. Muscat de Frontignan (grape) contains various high valuable bioactive phenolic compounds with pharmaceutical properties and industrial interest which are not fully exploited. The focus of this investigation consists in testing the effects of various biological elicitors on a non-morphogenic callus suspension culture of V. vinifera. The investigated elicitors: Indanoyl-isoleucine (IN), N-linolenoyl-L-glutamine (LG), insect saliva (IS) and malonyl coenzyme A (MCoA) were aimed at mimicking the influence of environmental pathogens on plants in their natural habitats and at provoking exogenous induction of the phenylpropanoid pathway. The elicitors’ indanoyl-isoleucine (IN), N-linolenoyl-L-glutamine (LG) and insect saliva (IS), as well as malonyl coenzyme A (MCoA), were independently inoculated to stimulate the synthesis of phenylpropanoids. All of the enhancers positively increased the concentration of phenolic compounds in grape cells. The highest concentration of phenolic acids was detected after 2 h for MCoA, after 48 h for IN and after 24 h for LG and IS respectively. At the maximum production time, treated grape cells had a 3.5-fold (MCoA), 1.6-fold (IN) and 1.5-fold (IS) higher phenolic acid content compared to the corresponding control samples. The HPLC results of grape cells showed two major resveratrol derivatives: 3-O-Glucosyl-resveratrol and 4-(3,5-dihydroxyphenyl)-phenol. Their influences of the different elicitors, time of harvest and biomass concentration (p < 0.0001) were statistically significant on the synthesis of phenolic compounds. The induction with MCoA was found to demonstrate the highest statistical effect corresponding to the strongest stress response within the phenylpropanoid pathway in grape cells.
Rateless coded hybrid amplify/decode-forward cooperation for wireless multicast

We consider a cooperative wireless multicast channel with no channel state information available at the transmitters, and where all wireless links undergo independent identically distributed quasi-static Rayleigh fading. For cooperation, we propose a rateless coded approach and identify its benefits over a conventional fixed-rate two-hop strategy. In addition to providing robust communications under fading conditions, rateless coding is able to exploit the cooperation benefits to a greater degree. A hybrid rateless coded cooperation scheme is proposed which employs amplify-and-forward (AF) in conjunction with decode-and-forward (DF) strategy. Results based on Monte-Carlo simulations indicate that the rateless coded hybrid scheme is able to significantly outperform two-hop cooperation, as well as the individual AF and DF strategies.
A Candidate Molecular Biomarker Panel for the Detection of Bladder Cancer

Background: Bladder cancer is among the five most common malignancies worldwide, and due to high rates of recurrence, one of the most prevalent. Improvements in noninvasive urine-based assays to detect bladder cancer would benefit both patients and health care systems. In this study, the goal was to identify urothelial cell transcriptomic signatures associated with bladder cancer. Methods: Gene expression profiling (Affymetrix U133 Plus 2.0 arrays) was applied to exfoliated urothelia obtained from a cohort of 92 subjects with known bladder disease status. Computational analyses identified candidate biomarkers of bladder cancer and an optimal predictive model was derived. Selected targets from the profiling analyses were monitored in an independent cohort of 81 subjects using quantitative real-time PCR (RT-PCR). Results: Transcriptome profiling data analysis identified 52 genes associated with bladder cancer (P ≤ 0.001) and gene models that optimally predicted class label were derived. RT-PCR analysis of 48 selected targets in an independent cohort identified a 14-gene diagnostic signature that predicted the presence of bladder cancer with high accuracy. Conclusions: Exfoliated urothelia sampling provides a robust analyte for the evaluation of patients with suspected bladder cancer. The refinement and validation of the multigene urothelial cell signatures identified in this preliminary study may lead to accurate, noninvasive assays for the detection of bladder cancer. Impact: The development of an accurate, noninvasive bladder cancer detection assay would benefit both the patient and health care systems through better detection, monitoring, and control of disease. Cancer Epidemiol Biomarkers Prev; 21(12); 2149–58. ©2012 AACR.
Inductive knowledge acquisition usingfeedforward neural networks with rule-extractionRichi

At the present state of art, generating a rule base is one of the main challenges in the area of knowledge-based systems. The present work attempts to automate the parts of the process of knowledge acquisition by using neural networks with rule extraction techniques. This paper presents a methodology composed of four phases to generate a representation formalism based on quantiied rules of n-ary predicates, facts and type hierarchy. Predicate rules extracted from neural networks have been used successfully to initialise SHRUTI reasoning system. The automated knowledge base enables the greater explanatory capabilities by allowing user interaction. Moreover, empirical results demonstrate that these predicate rules extracted from neural networks have a high accuracy.
Macroeconomic Uncertainty and the Impact of Oil Shocks

This paper evaluates whether macroeconomic uncertainty changes the impact of oil shocks on the oil price. Using a structural threshold VAR model, we endogenously identify different regimes of uncertainty in which we estimate the effects of oil demand and supply shocks. The results show that higher macroeconomic uncertainty, as measured by higher world industrial production volatility, significantly increases the responsiveness of oil prices to oil shocks. This implies a lower price elasticity of oil demand and supply in the uncertain regime, or in other words, that both oil curves become steeper when uncertainty is high. The difference in oil demand elasticities is both statistically and economically meaningful. Accordingly, varying uncertainty about the macroeconomy can explain time variation in the oil price elasticity and hence in oil price volatility. Also the impact of oil shocks on economic activity appears to be significantly stronger in uncertain times.
A LITERATURE SURVEY ON OBJECT TRACKING

The goal of this article is to review the state of the art of tracking methods, classify them into different categories, and identify new useful tracking methods . Many difficulties arise in object tracking due to camera motion, occlusions, non rigid object structures, abrupt changes in the appearance patters of both the object and the scene, therefore object tracking is a challenging problem. In this paper we present different object representations, their detection and categorize different tracking methods on the basis of the object and motion representation used.
Real-Time Tracking Using Edge and Color Feature

Visual surveillance system is an important tool used for monitoring a scene in order to detect any suspicious behavior. Recently, due to the increasing number of cameras, most of the researchers have shown more interest on how to track objects across the cameras. However, the existing algorithms that have been proposed by earlier researchers still offer some trade-off. As the tracking accuracy increases, the speed will be affected and vice-versa. Thus, this paper presents a novel approach for tracking moving objects which provides the most optimal trade-off in terms of its accuracy and speed. In this paper, a novel computational algorithm for dominant color to deal with the changes of objects' viewpoints is presented. Though, color cue alone is insufficient to provide a reliable tracking since in realistic environment, specifically outdoors, variation of illumination may affect the object appearance. Additional feature that is invariant to this imaging feature, namely edge is used in this project to compensate with the shortcoming. The tracking performance of the algorithm based on each individual feature and the fusion of the edge and color features are presented. Experimental results show that the proposed algorithm is reliable for real-time operation.
DDoS intrusion detection using Generalized Grey Self-organizing Maps

This paper describes the application of G2SOM (generalized grey self-organizing maps) to the DDoS(denial of service) intrusion detection. Generalized grey relational coefficients (G2RC), which characterize and stresses the whole correlation relationships between the input pattern and the weights of all the nodes that participate in competition, are explicitly introduced into the learning rule of the traditional SOM. In addition, SOM is generalized by the designed three G2RC functions, namely generalized grey self-organizing maps. Finally, the experiments on the DDOS datasets confirm their validities and feasibilities over the G2SOM in this paper. The dataset used is DARPA/KDD-99 publicly available dataset of features from network packets classified into normal and four DDoS attack categories.
Passive Component Network for Antenna Isolation in MIMO Systems for Handheld Terminals

This paper presents an improved method to isolate the ports for a MIMO antenna in hand-held devices using lumped components. It has been analyzed through simulation and measurement. The total efficiency and the envelope correlation have been evaluated. Compared to the case with no decoupling mechanism, the efficiency from the scattering parameters increases significantly and the envelope correlation coefficient decreases dramatically. Nevertheless, when choosing the components, the ohmic losses must receive extra consideration in order to maximize the system's total efficiency. Furthermore, the use of lumped components has the potential to make the presence of other components in the mobile device or the user, less harmful to the decoupling mechanism.
Quality of service management in hybrid optical-LTE access networks

In this work we show how to manage the integration between wireless and wired networks. In particular, as wireless technology LTE (Long Term Evolution) was chosen for its characteristics of bandwidth, point-to-multipoint, nomadic and mobile characteristics. We show how to extend the wired network performances, in terms of bandwidth and QoS, to the wireless access assuming different access and backhaul configurations: point-to-point, point to multipoint (or Passive Optical Networks, PON) and Wavelength Division Multiplexing (WDM) PON. The investigation has been carried out by means of OPNET simulations. We will show how it can be ensured the QoS of specific services by working both directly in the cell LTE and in the optical network with techniques DiffServ over MPLS.
Modelling Overlay Networks for Autonomous Supply Chain Systems

In logistics, different kinds of overlay systems are used to solve problems in processing and handling massively distributed information. One of the major challenges is to build overlay systems with effective routing mechanisms working efficiently in dynamically changing distributed environments, like a supply chain. Therefore, scalable and flexible information dissemination solutions are considered crucial. This article presents overlay networks, particularly Peer-to-Peer systems, as carriers of electronic data interchange in the growing global e-marketplace. Here, novel algorithms are utilized to build/relinquish connections among nodes of a supply network, as well as perform supply chain operations according to the SCOR reference model autonomously. The ultimate goal of doing so is to improve the Quality of Service (QoS) among nodes in a supply chain, especially in relation to the customer, since all modern supply chains are customer oriented. These algorithms can be used to facilitate decision making in supply chain management. In this article the necessary design decisions for the implementation of coordinated autonomous systems as cornerstones of a logistics platform for future e-marketplaces are discussed.
Leverage , Excess Leverage and Future Stock Returns

* We thank John Graham for making his data available. We also thank David Aboody and Ruihao Ke for helpful comments. Abstract We examine the relation between leverage and future stock returns while simultaneously considering the dynamic nature of firm's leverage. Using Graham's (2000) " kink " measure as a proxy for excess leverage, we find supportive evidence that firm's leverage can be characterized by a partial adjustment model. Excess leverage predicts not only future changes in leverage, but also other fundamentals such as investment and profitability. The market does not seem to fully understand the information contained in excess leverage about future fundamentals (especially investments), and under-levered firms earn superior risk adjusted returns through unexpected growth. The anomalous finding by Penman, Richardson and Tuna (2007), that the relation between leverage and future returns is negative, is subsumed by the negative relation between excess leverage and future returns. 2 1.
Modelling aspectual choice in Polish modal constructions

Much effort has been put into clarifying the relation between modality and other verbal properties, in particular mood and tense. Until recently the relation between modality and aspect received much less attention, however. For Slavic languages this situation is particularly unfortunate as Slavic languages mark the imperfective versus perfective distinction on all verbal forms, so there is no avoiding aspectual choice. Moreover, the hypothesis that directed much of the research, i.e. that imperfective aspect prevails in modal constructions or that the imperfective is used to express epistemic or alethic modality whereas perfective aspect renders deontic meanings, does not seem to hold for Slavic data: it has long been recognized that, if anything, the perfective would used more frequently in modal constructions in general (cf. Rassudova 1968, Forsyth 1970) and the imperfective aspect would be preferred in deontic contexts (Padučeva 2006, Šmelev & Zalizniak 2006, Wiemer ms.).
Stellar abundance gradients in galactic discs — I. Method and spectral line gradients

We describe the technique of absorption-line imaging of galaxy discs using the Taurus Tunable Filter on the Anglo-Australian Telescope and demonstrate its sensitivity to the behaviour of spectral features associated with Mg and Fe. Radial profiles of Mg 2 and Fe5270 line strengths are presented for a sample of eight face-on spiral galaxies spanning a range of Hubble types. Signatures of phenomena including merger-induced star formation, H II rings and galactic bars are also reported. This study demonstrates the capacity of tunable filters to measure Mg and Fe line strengths across the face of spiral galaxies, which can ultimately reveal clues about the star formation history and chemical evolution.
The Importance and Trickiness of Definition Strategies in Legal and Political Argumentation

This paper uses argumentation tools to show by means of analyzing nine cases from law and politics how argument strategies using persuasive definitions and quasi-definitions are powerful rhetorical tools of persuasion. By bringing to lightthe argumentation structure found in these examples, it is shown that definitions and redefinitions can have serious legal and political implications. Persuasive definitions and quasi-definitions are modeled as two distinct strategies for altering the relationship between classification and evaluation of a state of affairs. Persuasive definitions are aimed at modifying the relationship between the definiendum and its referent. In quasi-definitions some characteristics of an entity or event leading to a specific value judgment are selected and made accessible, while other conflicting ones are excluded. Reframing an issue is shown to be related to both strategies.
Decision List Algorithm for Word Sense Disambiguation for TELUGU Natural Language Processing

Word Sense Disambiguation plays a key role in Information Retrieval Applications. Telugu language contains more ambiguous words when compared to other European languages. Word complexity is high for Telugu and Information Retrieval in a Telugu language is a challenging task. This paper focus on assigning a particular sense for a word based on the context of use. Word cooccurance probability over the corpus is measured with the help of Decision list algorithm and assigned the sense. This algorithm is proven to be accurate for English text corpus about 90%. We adopted the same decision list algorithm to disambiguate sense of Telugu words with unsupervised learning process. The performance of Telugu Information Retrieval is measured with and without WSD. The results are more accurate with WSD when compared to word sense ambiguity.
Modulation Error Observation and Regulation for use in Off-line Optimal PWM Fed High Power Synchronous Motors

In synchronous motors, in the range of several mega watts, operated at low switching frequencies, it is advantageous to use off-line optimal PWM, to reduce the switching losses and undesired frequency harmonic components. But low transient performance of the system restricts the use of such commands. Considering the feed-forward structure of PWM modulators, it is tried in this paper to compensate the undesired modulation-error transients that may cause high overcurrents. An 80kW setup is used to simulate the experiments in laboratory. IGBT based, two-point voltage source inverter is used, and operated at low switching frequencies to simulate GTO-based inverters that are commonly used to feed motors in this power range
Novel pharmacologic treatment in acute binge eating disorder – role of lisdexamfetamine

Binge eating disorder (BED) is the most common eating disorder and an important public health problem. It is characterized by recurrent episodes of excessive food consumption accompanied by a sense of loss of control over the binge eating behavior without the inappropriate compensatory weight loss behaviors of bulimia nervosa. BED affects both sexes and all age groups and is associated with medical and psychiatric comorbidities. Until recently, self-help and psychotherapy were the primary treatment options for patients with BED. In early 2015, lisdexamfetamine dimesylate, a prodrug stimulant marketed for attention deficit hyperactive disorder, was the first pharmacologic agent to be approved by the US Food and Drug Administration for the treatment of moderate or severe BED in adults. This article summarizes BED clinical presentation, and discusses the pharmacokinetic profile, efficacy, and safety of lisdexamfetamine dimesylate in the treatment of BED in adults.
X1908+075: An X-Ray Binary with a 4.4 Day Period

X1908+075 is an optically unidentified and highly absorbed X-ray source that appeared in early surveys such as Uhuru, OSO 7, Ariel 5, HEAO-1, and the EXOSAT Galactic Plane Survey. These surveys measured a source intensity in the range 2-12 mcrab at 2-10 keV, and the position was localized to ~0. °5. We use the Rossi X-Ray Timing Explorer (RXTE) All-Sky Monitor (ASM) to confirm our expectation that a particular Einstein/IPC detection (1E 1908.4+0730) provides the correct position for X1908+075. The analysis of the coded mask shadows from the ASM for the position of 1E 1908.4+0730 yields a persistent intensity ~8 mcrab (1.5-12 keV) over a 3 yr interval beginning in 1996 February. Furthermore, we detect a period of 4.400 ± 0.001 days with a false-alarm probability less than 10-7. The folded light curve is roughly sinusoidal, with an amplitude that is 26% of the mean flux. The X-ray period may be attributed to the scattering and absorption of X-rays through a stellar wind combined with the orbital motion in a binary system. We suggest that X1908+075 is an X-ray binary with a high-mass companion star.