Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating HILDA in the CODA Project: A Case Study in Question Generation Using Automatic Discourse Analysis

Recent studies on question generation identify the need for automatic discourse analysers. We evaluated the feasibility of integrating an available discourse analyser called HILDA for a specific question generation system called CODA; introduce an approach by extracting a discourse corpus from the CODA parallel corpus; and identified future work towards automatic discourse analysis in the domain of question generation.
USING ROBOTS TO ACCESS PLAY AT DIFFERENT DEVELOPMENTAL LEVELS FOR CHILDREN WITH SEVERE DISABILITIES: A PILOT STUDY

Children who have severe physical disabilities may have difficulty participating in play activities. The use of robots can promote and facilitate play for children with disabilities. Robot play could give insight to the developmental level of play of children with disabilities who are difficult to assess with standardized tests. The purpose of this study was to develop scenarios with and without a robot where children could demonstrate play at different developmental levels. Validation of the scenarios was done through direct observation of 10 typically developing children playing with and without a robot with conventional toys and unstructured materials. A play coding system was used to classify the levels of play (no play, functional play or pretend play). Analysis showed that the scenarios could elicit play as expected (young children did more functional play and older children did more pretend play). However, children presented less pretend play with the robot than they did without the robot. This could be because typically developing children are accustomed to manipulating toys directly and the robot posed a higher level of cognitive difficulty. Next steps will be to address the effect of the robot, and trial the scenarios with children with disabilities.
Epigenetic Editing: targeted rewriting of epigenetic marks to modulate expression of selected target genes

Despite significant advances made in epigenetic research in recent decades, many questions remain unresolved, especially concerning cause and consequence of epigenetic marks with respect to gene expression modulation (GEM). Technologies allowing the targeting of epigenetic enzymes to predetermined DNA sequences are uniquely suited to answer such questions and could provide potent (bio)medical tools. Toward the goal of gene-specific GEM by overwriting epigenetic marks (Epigenetic Editing, EGE), instructive epigenetic marks need to be identified and their writers/erasers should then be fused to gene-specific DNA binding domains. The appropriate epigenetic mark(s) to change in order to efficiently modulate gene expression might have to be validated for any given chromatin context and should be (mitotically) stable. Various insights in such issues have been obtained by sequence-specific targeting of epigenetic enzymes, as is presented in this review. Features of such studies provide critical aspects for further improving EGE. An example of this is the direct effect of the edited mark versus the indirect effect of recruited secondary proteins by targeting epigenetic enzymes (or their domains). Proof-of-concept of expression modulation of an endogenous target gene is emerging from the few EGE studies reported. Apart from its promise in correcting disease-associated epi-mutations, EGE represents a powerful tool to address fundamental epigenetic questions.
A low-cost stereo system for 3D object recognition

In this paper, we present a low-cost stereo vision system designed for object recognition with FPFH point feature descriptors. Image acquisition is performed using a pair of consumer market UVC cameras costing less than 80 Euros, lacking synchronization signal and without customizable optics. Nonetheless, the acquired point clouds are sufficiently accurate to perform object recognition using FPFH features. The recognition algorithm compares the point cluster extracted from the current image pair with the models contained in a dataset. Experiments show that the recognition rate is above 80% even when the object is partially occluded.
An Algebraic Approach to Generalized Measures of Information

I propose an algebraic framework in which to study measures of information. One immediate consequence is a new proof of the classification of branching entropies on a Boolean algebra. Common constructions in the theory of entropy such as the conditional entropy and the mutual information arise naturally in this framework. A generalized theory of information can be interpreted in a category-theoretic context as a natural transformation between two functors. In 1948, Claude E. Shannon established the statistical theory of entropy (Shannon 1948), which offered deep insights into coding theory and compression. Since then researchers have been generalizing the axiomatic structure of the Shannon entropy so that they might bring it to bear on other mathematical questions. One such generalization is the notion of a branching inset entropy (Kannappan & Sander 2004). In 1983, J. Aczel named the problem of classifying inset information measures on a list of unsolved problems in the theory of functional equations at the Twenty-First Symposium on Functional Equations. The problem was solved (Ebanks 1986, B́.R. Ebanks & Ng 1990), but the proof is 20 pages long and involves checking over a dozen special cases. Below we introduce an algebraic object, the partition algebra, and we identify the space of branching entropies as the dual of this object. In addition to producing a new and simple algebraic proof of the classification of branching entropies, this construction endows the space of branching entropies with a rich algebraic structure with information theoretic interpretations and leads to a notion of a generalized information theory. 1. Definition of the partition algebra We fix an arbitrary base ring k, but for most applications we can consider k = R. For any boolean algebra F , we consider the space of formal linear combinations of elements of F with coefficients in k, where we take the element ∅ ∈ F to be zero. We can extend the intersection operation “ ∩ ” bilinearly to define a multiplication of formal sums. This k-module, along with the multiplication, is a k-algebra denoted k0F . Define the k-algebra AkF to be the quotient of k0F by the ideal generated by expressions of the form a ∪ b+ a ∩ b− a− b for all a, b ∈ F . In other words AkF is the space of formal linear combinations of elements of F , but where we consider a ∪ b = a + b whenever a, b ∈ F are disjoint. We refer to AkF as the “algebra of simple functions on F”, because if F is a boolean algebra of subsets of some set X , then AkF is just the algebra of k-valued functions on X whose range is a finite set in k and whose level sets are elements of F . We see this by identifying the formal element E ∈ F ⊆ AkF with the indicator function χE for all subsets E ∈ F . Denote the surjection onto the quotient algebra πF : k0F → AkF . This surjection is natural in the sense that if φ : F → G is a map of boolean algebras, then there is a
Remodeling Grounded Theory

In diesem Beitrag verdeutliche ich meine Besorgnis uber zahlreiche Umformungen der Grounded Theory (GT), die mit deren Rezeption durch Methodologien der qualitative Datenanalyse (QDA) einhergehen, und hieraus folgende Erosionen. Ich skizziere zunachst einige Beispiele hierfur, um danach die essentiellen Bestandteile der klassischen GT-Methodologie zusammenzufassen. Ich hoffe, dass dieser Beitrag meine Besorgnis uber die wachsende, aber meines Erachtens missverstandene Einvernahme von GT durch QDA-Methodologien veranschaulicht und zugleich als einfuhrender Leitfaden fur Novizen und Novizinnen dient, die daran interessiert sind, die grundlegenden Prinzipien der GT nachzuvollziehen. URN: urn:nbn:de:0114-fqs040245
Title : A neurocomputational model of automatic sequence production Abbreviated title : Automaticity in sequence production

Most behaviors unfold in time and include a sequence of sub-movements or cognitive activities. In addition, most behaviors are automatic and repeated daily throughout life. Yet, relatively little is known about the neurobiology of automatic sequence production. Past research suggests a gradual transfer from the associative striatum to the sensorimotor striatum, but a number of more recent studies challenge this role of the basal ganglia in automatic sequence production. In this article, we propose a new neurocomputational model of automatic sequence production in which the main role of the basal ganglia is to train cortical-cortical connections within the premotor areas that are responsible for automatic sequence production. The new model is used to simulate four different data sets from human and non-human animals, including (1) behavioral data (e.g., response times), (2) electrophysiology data (e.g., single-neuron recordings), (3) macro-structure data (e.g., transcranial magnetic stimulation), and (4) neurological circuit data (e.g., inactivation studies). We conclude with a comparison of the new model with existing models of automatic sequence production and discuss a possible new role for the basal ganglia in automaticity and its implication for Parkinson’s disease.
A Survey of Monte-Carlo Techniques in Games Master ’ s Scholarly Paper

The way computer programs play strategy games is quite different from the way humans play. In perfect-information games like chess and checkers, a game-tree search is the core technique in a computer program’s arsenal, augmented by good evaluation functions and clever secondary strategies. In other perfect-information games such as go and clobber, there is very little intuition as to how good a position is, and consequently constructing a good evaluation function is not easy. Furthermore, go has a high branching factor. It turns out that Monte-Carlo simulations, i.e. producing repeated random samples and considering their average in making a decision, work surprisingly well in these games. In imperfect-information games such as bridge and scrabble (the latter game has inherent randomness associated with it as well), Monte-Carlo simulations once again turn out to be useful. This paper examines the use of Monte-Carlo simulations in bridge, scrabble, go, clobber, and backgammon, and reports on how this technique impacts each of these games.
A New Look at Electron Localization

two-particle density for electrons of parallel spin, a function of two electrons’ coordinates (x, y , z and x’, y‘ , z‘) which gives the joint probability of finding one electron at position x , y , z and another electron of the same spin at position x’, y’ , z‘. The analysis showed that electrons of parallel spin restrict themselves to separate regions of space, and hence follows the notion of localized electron pairs. A well-known application of these concepts are the Gillespie and Nyholm
Dual oscillators and Quantum Pendulum spectrum

We re-derive the nonlinear transformation in the path integral representation for partition function bringing the duality between one-dimensional oscillators with stable and unstable shapes of potential. This duality transformation realizes the equivalence between spectra of a Hermitian and a non-Hermitian Hamiltonians. It is exploited to calculate the spectra of quantum rotators .
A time-frequency analysis of event-related desynchronization/synchronization based on Gabor filter

An alternative method is proposed based on Gabor filter to make a time-frequency analysis of the event-related (de)synchronization (ERD/ERS). To develop an alternative time-frequency method for better extracting the feature information underlying the ERD/ERS during motor imagery, the Gabor filter is used in the algorithm to extract the amplitude information of the EEG in each frequency band. Then the inter-trail variance method is used to quantify the ERD/ERS. At last, the time-frequency map is shown to make a comprehensive analysis of hand motor imagery. The result shows a contralateral dominant alpha and beta ERD, and a beta ERS bilaterally. The present method is tested with EEG data from BCI competition III dataset IIIa. The feasibility of this method is proved and a compare with band-pass filter-based method is presented.
Background data format optimization for efficient sub-word parallel program generation

This paper illustrates the strong interaction between background data format organization and foreground data in the context of speed and power efficient Sub-Word level Parallel (SWP) program generation. Such interaction, if not considered well, results in an excess of (un)packing operations that are typically required to match the format of data stored in memory to the one required by the sub-word parallel processing units. To avoid this overhead a careful selection of the data format for background storage is needed. We propose a conceptual methodology for efficiently exploiting such degree of freedom. The approach is demonstrated on two real-life application kernels, where source code level data format transformations are applied to the data in background memory such that a substantially better exploitation of the sub-word level functional units can be achieved by the compiler. A significant reduction in packing instruction overhead, data (up to a factor 4) and instruction memory accesses (up to 50%) is obtained. This results in a substantial reduction of power consumed by the register file (less (un)packing operations), the data bus (less bus transactions), the data memory hierarchy (less accesses) and the instruction memory hierarchy (less accesses and more compact code). Also the execution time for the optimized application running on a TriMedia TM1300 evaluation board shows substantial gains.
ENVIRONMENTAL REGULATION OF POLLUTING FIRMS: PORTER'S HYPOTHESIS REVISITED

This paper provides a theoretical explanation for a regulation-driven win-win situation along the lines of Porter's hypothesis. Using a Cournot duopoly with polluting firms we show that in the absence of government intervention there exist parameter values such that, in the resulting Nash equilibrium, both firms choose the old, high polluting technology even though the adoption of a new, low polluting technology yields higher profits for both firms (prisoner's dilemma). We then show that gobernment intervention in the form of direct emission controls can eliminate the prisoner's dilemma situation and induce both firms to adopt the modern, low polluting technology provided that the regulation is sufficiently strict. In this case, the reduction in market size for polluting firms is storng enough to reduce profits. By investing in a new, low polluting technology, firms avoid any quantity restrictions on output and enjoy higher profits despite the initial cost of investing in the new technology.
New coding strategies for the relay channel

This paper studies coding strategies for a three-node relay channel. We first review the basic coding strategies of Cover and El Gamal for the relay channel. Next, two new coding strategies superimposing cooperation and facilitation are developed. One of the coding strategies is shown to include the generalized strategy of Cover and El Gamal. For certain parameters of the Gaussian relay channel, the two new strategies give higher achievable rates than the generalized strategy of Cover and El Gamal
Methods for the numerical solution of the nonlinear Schroedinger equation

Optimal L2 rates of convergence are established for several fully-discrete schemes for the numerical solution of the nonlinear Schroedinger equation. Both finite differences and finite elements are considered for the discretization in space, while the integration in time is treated either by the leap-frog technique or by a modified Crank-Nicolson procedure, which generalizes the one suggested by Delfour, Fortin and Payne and possesses two useful conserved quantities.
Effect of parallel processing and optimization techniques in molecular dynamics

Molecular dynamics (MD) has been studied long time due to its attractive function of predicting structure of molecules. Though many studies reported improved algorithms, it is unclear to an end-user of MD software tool to choose appropriate computer architecture, type of parallel processing, and optimization options to compile and execute the tool. In this study, we tested various combinations of parallel processing and optimization options on four different computer architectures, i.e. a vector supercomputer, multi-processor supercomputer with shared and distributed memories, and a PC cluster. Experimental results revealed superiority of PC cluster against other expensive supercomputers.
Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.
New Trend of Protein Secondary Structure Prediction

At first, this paper reviews the development history of the protein secondary structure prediction. Some concerned secondary structure prediction methods are introduced. Then a novel method is proposed, which substantially improves the prediction accuracy of CB513 with 80.49% and RS126 with 82.79% respectively. In the end, this paper points out several possible trends in the protein secondary structure prediction.
New Approaches to Optical Music Recognition

We present the beginnings of a new system for optical music recognition (OMR), aimed toward the score images of the International Music Score Library Project (IMSLP). Our system focuses on measures as the basic unit of recognition. We identify candidate composite symbols (chords and beamed groups) using grammatically-formulated top-down model-based methods, while employing template matching to find isolated rigid symbols. We reconcile these overlapping symbols by seeking non-overlapping variants of the composite symbols that best account for the pixel data. We present results on a representative score from the IMSLP.
Separation Theorems for Phase-Incoherent Multiple-User Channels

We study the transmission of two correlated and memoryless sources $(U,V)$ over several multiple-user phase asynchronous channels. Namely, we consider a class of phase-incoherent multiple access relay channels (MARC) with both non-causal and causal unidirectional cooperation between encoders, referred to as phase-incoherent unidirectional non-causal cooperative MARC (PI-UNCC-MARC), and phase-incoherent unidirectional causal cooperative MARC (PI-UCC-MARC) respectively. We also consider phase-incoherent interference channels (PI-IC), and interference relay channel (PI-IRC) models in the same context. In all cases, the input signals are assumed to undergo non-ergodic phase shifts due to the channel. The shifts are assumed to be unknown to the transmitters and known to the receivers as a realistic assumption. Both necessary and sufficient conditions in order to reliably send the correlated sources to the destinations over the considered channels are derived. In particular, for all of the channel models, we first derive an outer bound for reliable communication that is defined with respect to the source entropy content (i.e., the triple $(H(U|V),H(V|U),H(U,V))$). Then, using {\em separate} source and channel coding, under specific gain conditions, we establish the same region as the inner bound and therefore obtain tight conditions for reliable communication for the specific channel under study. We thus establish a source-channel separation theorem for each channel and conclude that without the knowledge of the phase shifts at the transmitter sides, separation is optimal. It is further conjectured that separation in general is optimal for all channel coefficients.
Network-Based Data Integration for Selecting Candidate Virulence Associated Proteins in the Cereal Infecting Fungus Fusarium graminearum

The identification of virulence genes in plant pathogenic fungi is important for understanding the infection process, host range and for developing control strategies. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a ‘guilt by association’ approach. Here we study 133 genes in the globally important Ascomycete fungus Fusarium graminearum that have been experimentally tested for their involvement in virulence. An integrated network that combines information from gene co-expression, predicted protein-protein interactions and sequence similarity was employed and, using 100 genes known to be required for virulence, we found a total of 215 new proteins potentially associated with virulence of which 29 are annotated as hypothetical proteins. The majority of these potential virulence genes are located in chromosomal regions known to have a low recombination frequency. We have also explored the taxonomic diversity of these candidates and found 25 sequences, which are likely to be fungal specific. We discuss the biological relevance of a few of the potentially novel virulence associated genes in detail. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a ‘guilt by association’ approach.
Research Status and Development Trends of Cognitive Radio Technology

Cognitive Radio (CR) is a newly proposed intelligent wireless communication technology which can utilize wireless spectrum resource efficiently and improve communication system performance notably. In this paper, backgrounds, basic concepts and working principles of CR are introduced firstly. Then, based on above introduction research status of CR technology are expounded roundly and its applications and future development trends are discussed.
Formal verification of algorithms for critical systems

The authors describe their experience with formal, machine-checked verification of algorithms for critical applications, concentrating on a Byzantine fault-tolerant algorithm for synchronizing the clocks in the replicated computers of a digital flight control system. The problems encountered in unsynchronized systems and the necessity, and criticality, of fault-tolerant synchronization are described. An overview of one such algorithm and of the arguments for its correctness are given. A verification of the algorithm performed using the authors' EHDM system for formal specification and verification is described. The errors found in the published analysis of the algorithm and benefits derived from the verification are indicated. Based on their experience, the authors derive some key requirements for a formal specification and verification system adequate to the task of verifying algorithms of the type considered. The conclusions regarding the benefits of formal verification in this domain and the capabilities required of verification systems in order to realize those benefits are summarized. >