Miracle-dz/UniFAR-FTUs huggingface dataset:
A Methodology for the Analysis of Verb Usage Examples in a Context of Lexical Knowledge Acquisition from Dictionary Entries

This paper presents the development of a methodology the last goal of which would be to help the linguist or lexicographer when defining the subcategorisation pattern of a verb. As a starting point we have applied this methodology over the verb entries examples of an ordinary dictionary in machine readable version. The methodology consists of the following steps: morphological analysis, resolution of morphological ambiguities, syntactic function assignment, detection of verb chains and phrasal units, and the design and implementation of an SGML data structure that represents the verb entries examples, and a query system to exploit the information contained in this data structure. 1 Motivation: Why Analyse Verb
Model‐Based Assessment of Plasma Citrate Flux Into the Liver: Implications for NaCT as a Therapeutic Target

Cytoplasmic citrate serves as an important regulator of gluconeogenesis and carbon source for de novo lipogenesis in the liver. For this reason, the sodium‐coupled citrate transporter (NaCT), a plasma membrane transporter that governs hepatic influx of plasma citrate in human, is being explored as a potential therapeutic target for metabolic disorders. As cytoplasmic citrate also originates from intracellular mitochondria, the relative contribution of these two pathways represents critical information necessary to underwrite confidence in this target. In this work, hepatic influx of plasma citrate was quantified via pharmacokinetic modeling of published clinical data. The influx was then compared to independent literature estimates of intracellular citrate flux in human liver. The results indicate that, under normal conditions, <10% of hepatic citrate originates from plasma. Similar estimates were determined experimentally in mice and rats. This suggests that NaCT inhibition will have a limited impact on hepatic citrate concentrations across species.
Developmental Pathways in the Assimilation of Non-geometric Information for Orientation in Children : a Neurorobotic Model

The performance of children in an orientation task involving geometric and nongeometric spatial cues presents an interesting pathway during development. At an early stage, children are able to exploit the first, but do not use the information provided by the second. This surprising result has been interpreted resorting to the presence of a geometric module in vertebrates’ brain whose limitation can be overcome with the acquisition of language (Hermer and Spelke, 1996). But the described set of results is not always verified: Learmonth and colleagues (2001, 2002) have shown that children, under certain conditions, can use the information provided by landmarks. In accordance with what has been suggested in the cited study by Learmonth (2001), a crucial factor to allow the use of non-geometric information is the stability of the cue presence. In the present work we have tried to address this question training artificial organisms, namely simulated robots, to solve the two tasks. Results show that if the nongeometric features is always present in the training procedure, the artificial organisms can use them to orient. Nonetheless, if the non-geometric information is present only for a certain period of the training, the percentage of artificial organisms that can exploit this information source varies proportionally to the length of exposure to non-geometric features. Manipulating this variable, it has also been possible to observe different developmental pathways and, under certain conditions, to reproduce the developmental pattern observed in children.
Ultrawideband tightly coupled array for multiband communications at S-X frequencies

In satellite-borne platforms where the reduction of size, weight and power are very critical design factors. To pursuing to this goal, we present a design for ultrawideband tightly coupled antenna array (TCDA) with wide angle scanning and low cross polarization. Although TCDAs possess the merit of wideband, wide-scanning performance, they need a balanced feeding structure which introduces several practical challenges. In this paper, we demonstrate a low-cost wideband integrated balun to incorporate with array and increase overall bandwidth. The final array is capable of working simultaneously on numerous communication bands, including S, C, and lower-X bands (2-10GHz). Besides, the array shows ±45° scanning in all planes, and less than - 15dB cross-polarization. To validate the design, an 8 × 8 TCDA prototype is fabricated and measured.
Overview of 3-D Reconstruction from Images

This article summarizes recent advancements of the theories and techniques for 3-D reconstruction from multiple images. We start with the description of the camera imaging geometry as perspective projection in terms of homogeneous coordinates and the definition of the intrinsic and extrinsic parameters of the camera. Next, we described the epipolar geometry for two, three, and four cameras, introducing such concepts as the fundamental matrix, epipolars, epipoles, the trifocal tensor, and the quadrifocal tensor. Then, we present the self-calibration technique based on the stratified reconstruction approach, using the absolute dual quadric constraint. Finally, we give the definition of the ane camera model and a procedure for 3-D reconstruction based on it.
A Planning Approach to the Recognition of Multiple Goals

Plan recognition is a ubiquitous task in artificial intelligence and pervasive computing research. The multigoal recognition problem presents a major challenge in the real world of plan recognition. Users often pursue several goals in a concurrent and interleaving manner, where the pursuit of goals may spread over different parts of an activity sequence and may be pursued in parallel. Existing approaches for multigoal problems are probabilistic approaches. They all assume the existence of plan libraries, which require a lot of human efforts in predicting and formalizing plans and may be impractical in many cases. In this paper, we present a novel logic‐based approach to solve the multigoal recognition problem efficiently, without the need of plan libraries, using a state‐of‐the‐art heuristic search planner LAMA. In particular, we first propose the formulation of a multigoal recognition problem based on automated planning. Then we present a bilevel probabilistic plan recognition approach that deals with both concurrent and interleaving goals from observed activity sequences. Experimental results over several domains show that our method has great flexibility and scalability.
Semeval-2016 Task 4 : Sentiment Analysis in Twitter

The aim of this paper is to produce a methodology for analyzing sentiments of selected Twitter messages, better known as Tweets. This project elaborates on two experiments carried out to analyze the sentiment of Tweets from SemEval-2016 Task 4 Subtask A and Subtask B. Our method is built from a simple unigram model baseline with three main feature enhancements incorporated into the model: 1) emoticon retention, 2) word stemming, and 3) token saliency calculation. Our results indicate an increase in classification accuracy with the addition of emoticon retention and word stemming, while token saliency shows mixed performance. These results elucidate a possible classification feature model that could aid in the sentiment analysis of Twitter feeds and other microblogging environments.
Text Reuse Detection using a Composition of Text Similarity Measures

Detecting text reuse is a fundamental requirement for a variety of tasks and applications, ranging from journalistic text reuse to plagiarism detection. Text reuse is traditionally detected by computing similarity between a source text and a possibly reused text. However, existing text similarity measures exhibit a major limitation: They compute similarity only on features which can be derived from the content of the given texts, thereby inherently implying that any other text characteristics are negligible. In this paper, we overcome this traditional limitation and compute similarity along three characteristic dimensions inherent to texts: content, structure, and style. We explore and discuss possible combinations of measures along these dimensions, and our results demonstrate that the composition consistently outperforms previous approaches on three standard evaluation datasets, and that text reuse detection greatly benefits from incorporating a diverse feature set that reflects a wide variety of text characteristics.
CEO job security and risk-taking

We use the length of employment contracts to estimate CEO turnover probability and its effects on risk-taking. Protection against dismissal should encourage CEOs to pursue riskier projects. Indeed, we show that firms with lower CEO turnover probability exhibit higher return volatility, especially idiosyncratic risk. An increase in turnover probability of one standard deviation is associated with a volatility decline of 17 basis points. This reduction in risk is driven largely by a decrease in investment and is not associated with changes in compensation incentives or leverage.
Report on the International Provenance and Annotation Workshop: (IPAW'06) 3-5 May 2006, Chicago

The provenance of a data item refers to its origins and processing history, while annotation is a term that refers to the process of adding notes or data to an existing structure. Because these terms are broad, and are used in slightly different ways by different communities, confusion is rampant. For example, consider that (1) annotating a data set with its provenance information, and (2) finding the provenance of a specific data annotation are both perfectly reasonable concepts.
A comparative study on sign recognition using sEMG and inertial sensors

Decision tree and random forest algorithm are introduced to the field of gesture recognition, and the gestures are classified by the fusion information of sEMG and inertial sensor. Experiments show that gesture recognition based on multi fusion information is more accurate than only using surface EMG or inertial signals. Taking the common 12 kinds of gestures as an example, the average recognition rate is 93.6%, some can even reach 100%. The cross validation indicate that the random forest is better than the decision tree in gesture recognition. Finally, the gesture recognition methods based on multi fusion information are used in the family service robot of our laboratory. By using hand gestures to control the service robot, a new human-computer interaction was explored.
Managing change in general practice: a step by step guide.

BMJ 1992;304:231-4 Over the past five years general practitioners have been challenged by proposals from both the government and the Royal College of General Practitioners to funda? mentally change the administrative structure and day to day running of general practice.15 Changes range from individual practice based innovations, such as developing structured surveillance for chronic dis? orders and improving the provision of preventive services, to broader initiatives, such as performance review and an emphasis on medical audit. Though much attention has been paid to the content of such change, less energy has been directed towards establishing how change can be managed most effec? tively. Experience in industry suggests that even the most rational change can be obstructed if its imple? mentation is either badly planned or inadequately negotiated. Several models have been developed to assist the successful management of change,67 some of which have been applied to various aspects of the NHS.8"10 We discuss how one such model, which was first developed in industry, has been usefully applied in general practice settings. We worked with a management consultant (RC), who has considerable industrial experience, to develop and adapt a model for managing change for general practice; the model emphasises a team approach. We have applied this model to different situations in general practice, including introducing screening ser? vices and surveillance of chronic disorders, incorporat? ing new technology into practice administration, and improving liaison and effective working relationships between different professional groups.1112 The model can be used either by a practice that already functions as a cohesive team or by a person within the practice who wishes to move towards a team based decision in introducing change. In practices that already function well as a team, with regular meetings of the whole team in which each member's contribution is recognised and respected, the process of shared decision making about an innova? tion can be started with few of the preliminary steps described here. However, more often an innovation is sponsored by a single person. In this case the strategies described can be used to introduce an idea to other team members, to negotiate agreement and imple? mentation, if appropriate, in such a way that it strengthens the team and has maximum chance of success.
A sufism-inspired model for embodied interaction design

This paper presents a concise overview of argumentations about the body and the concept of embodiment in the field of technology by also referencing to the similar debates in philosophy, critical theory and social studies. In view of the observation that advances in technology call for a re-definition of embodiment, and in many different fields of life embodied approaches are increasingly looked for, it briefly revisits Modernity's ideal of disembodiment, which for those of us who live in modern societies, still dominates our approach to life and our understanding of existence, and as a corollary, our daily interactions with technologies as well. Then drawing from Sufism, the mystical tradition of Islam, and from a phenomenological interpretation of its approach to human body, the authors finally propose a four-layer understanding of embodiment as a model to be implemented in embodied interaction design.
Position Paper: Representation Search through Generate and Test

Learning representations from data is one of the fundamental problems of artificial intelligence and machine learning. Many different approaches exist for learning representations, but what constitutes a good representation is not yet well understood. In this work, we view the problem of representation learning as one of learning features (e.g., hidden units of neural networks) such that performance of the underlying base system continually improves. We study an important case where learning is done fully online (i.e., on an example-by-example basis) from an unending stream of data, and the computational cost of the learning element should not grow with time or cannot be much more than that of the performance element. Few methods can be used effectively in this case. We show that a search approach to representation learning can naturally fit with this setting. In this approach good representations are searched by generating different features and then testing them for utility. We develop new representation-search methods and show that the generate-and-test approach can be utilized in a simple and effective way for continually improving representations. Our methods are fully online and add only a small fraction to the overall computation. We believe online representation search constitutes an important step toward effective and inexpensive solutions to representation learning problems.
Additional information paper Forecasting and Analyzing Insurance Companies ’ Ratings by

The quality of the model fit is assessed by the negative log likelihood. In information criteria, one often uses the model deviance, which is twice the negative log likelihood, as a main indicator. In the case of ordinary least squares regression, the deviance is closely related to the sum squared error. The deviance) between the full model M1 (with inputs 1, . . . , i−1, i, i+1, . . . ,m) and the reduced model M0 without the corresponding input (inputs 1, . . . , i − 1, i + 1, . . . ,m) are compared. The Bayes factor B10 is approximated via
Continuous speech recognizer for low-end embedded devices

This paper discusses the implementation of continuous speech recognition system for low-cost bare-metal platform. The applied algorithms are well known, however they are optimized for constrained embedded environment. System is very flexible since it uses publicly available acoustic and language models, and dictionaries, and as a result of recognition produces readable ASCII string through serial port. Performance measurements show that it is slower compared to the same algorithm running on desktop, but it keeps its recognition accuracy.
Representation of Instantaneous and Short-Term Loudness in the Human Cortex

Acoustic signals pass through numerous transforms in the auditory system before perceptual attributes such as loudness and pitch are derived. However, relatively little is known as to exactly when these transformations happen, and where, cortically or sub-cortically, they occur. In an effort to examine this, we investigated the latencies and locations of cortical entrainment to two transforms predicted by a model of loudness perception for time-varying sounds: the transforms were instantaneous loudness and short-term loudness, where the latter is hypothesized to be derived from the former and therefore should occur later in time. Entrainment of cortical activity was estimated from electro- and magneto-encephalographic (EMEG) activity, recorded while healthy subjects listened to continuous speech. There was entrainment to instantaneous loudness bilaterally at 45, 100, and 165 ms, in Heschl's gyrus, dorsal lateral sulcus, and Heschl's gyrus, respectively. Entrainment to short-term loudness was found in both the dorsal lateral sulcus and superior temporal sulcus at 275 ms. These results suggest that short-term loudness is derived from instantaneous loudness, and that this derivation occurs after processing in sub-cortical structures.
Using Active Relocation to Aid Reinforcement Learning

We propose a new framework for aiding a reinforcement learner by allowing it to relocate, or move, to a state it selects so as to decrease the number of steps it needs to take in order to develop an effective policy. The framework requires a minimal amount of human involvement or expertise and assumes a cost for each relocation. Several methods for taking advantage of the ability to relocate are proposed, and their effectiveness is tested in two commonly-used domains.
Structural Methods Applied to the Symbolic Analysis of Petri Nets

Symbolic techniques based on Binary Decision Diagrams have emerged as one of the possible strategies to overcome the state exposition problem in the analysis of systems modeled as Petri nets. The results on structural theory of Petri nets obtained in the last few decades can be used to improve the symbolic analysis and to alleviate the state exposition problem. Structural theory provides several methods to derive efficient encoding schemes for the BDD representations of markings. It also provides mechanisms to identify conservative upper bounds to the reachable states. The unreachable state space determined by the upper bound can be used to alleviate both the calculation of the exact reachability set by breath or depth first search and the scrutiny of properties by backward traversal.
Instruction-Matrix-Based Genetic Programming

In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In this paper, we propose a new GP framework, namely, instruction-matrix (IM)-based GP (IMGP), to handle their interactions. IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from an IM and updates the IM with the information of the extracted program trees. As the IM actually keeps most of the information of the schemata of GP and evolves the schemata directly, IMGP is effective and efficient. Our experimental results on benchmark problems have verified that IMGP is not only better than those of canonical GP in terms of the qualities of the solutions and the number of program evaluations, but they are also better than some of the related GP algorithms. IMGP can also be used to evolve programs for classification problems. The classifiers obtained have higher classification accuracies than four other GP classification algorithms on four benchmark classification problems. The testing errors are also comparable to or better than those obtained with well-known classifiers. Furthermore, an extended version, called condition matrix for rule learning, has been used successfully to handle multiclass classification problems.
Extending the honey bee venome with the antimicrobial peptide apidaecin and a protein resembling wasp antigen 5

Honey bee venom is a complex mixture of toxic proteins and peptides. In the present study we tried to extend our knowledge of the venom composition using two different approaches. First, worker venom was analysed by liquid chromatography‐mass spectrometry and this revealed the antimicrobial peptide apidaecin for the first time in such samples. Its expression in the venom gland was confirmed by reverse transcription PCR and by a peptidomic analysis of the venom apparatus tissue. Second, genome mining revealed a list of proteins with resemblance to known insect allergens or venom toxins, one of which showed homology to proteins of the antigen 5 (Ag5)/Sol i 3 cluster. It was demonstrated that the honey bee Ag5‐like gene is expressed by venom gland tissue of winter bees but not of summer bees. Besides this seasonal variation, it shows an interesting spatial expression pattern with additional production in the hypopharyngeal glands, the brains and the midgut. Finally, our immunoblot study revealed that both synthetic apidaecin and the Ag5‐like recombinant from bacteria evoke no humoral activity in beekeepers. Also, no IgG4‐based cross‐reactivity was detected between the honey bee Ag5‐like protein and its yellow jacket paralogue Ves v 5.
Complexity of the Mycoplasma fermentans M64 Genome and Metabolic Essentiality and Diversity among Mycoplasmas

Recently, the genomes of two Mycoplasma fermentans strains, namely M64 and JER, have been completely sequenced. Gross comparison indicated that the genome of M64 is significantly bigger than the other strain and the difference is mainly contributed by the repetitive sequences including seven families of simple and complex transposable elements ranging from 973 to 23,778 bps. Analysis of these repeats resulted in the identification of a new distinct family of Integrative Conjugal Elements of M. fermentans, designated as ICEF-III. Using the concept of “reaction connectivity”, the metabolic capabilities in M. fermentans manifested by the complete and partial connected biomodules were revealed. A comparison of the reported M. pulmonis, M. arthritidis, M. genitalium, B. subtilis, and E. coli essential genes and the genes predicted from the M64 genome indicated that more than 73% of the Mycoplasmas essential genes are preserved in M. fermentans. Further examination of the highly and partly connected reactions by a novel combinatorial phylogenetic tree, metabolic network, and essential gene analysis indicated that some of the pathways (e.g. purine and pyrimidine metabolisms) with partial connected reactions may be important for the conversions of intermediate metabolites. Taken together, in light of systems and network analyses, the diversity among the Mycoplasma species was manifested on the variations of their limited metabolic abilities during evolution.