Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of discourse structure for spoken dialogue systems

Language exhibits structure beyond the sentence level (e.g. the syntactic structure of a sentence). In particular, dialogues, either human-human or human-computer, have an inherent structure called the discourse structure. Models of discourse structure attempt to explain why a sequence of random utterances combines to form a dialogue or no dialogue at all. Due to the relatively simple structure of the dialogues that occur in the information-access domains of typical spoken dialogue systems (e.g. travel planning), discourse structure has often seen limited application in such systems. In this research, we investigate the utility of discourse structure for spoken dialogue systems in more complex domains, e.g. tutoring. This work was driven by two intuitions. First, we believed that the "position in the dialogue" is a critical information source for two tasks: performance analysis and characterization of dialogue phenomena. We define this concept using transitions in the discourse structure. For performance analysis, these transitions are used to create a number of novel factors which we show to be predictive of system performance. One of these factors informs a promising modification of our system which is implemented and compared with the original version of the system through a user study. Results show that the modification leads to objective improvements. For characterization of dialogue phenomena, we find statistical dependencies between discourse structure transitions and two dialogue phenomena which allow us to speculate where and why these dialogue phenomena occur and to better understand system behavior. Second, we believed that users will benefit from direct access to discourse structure information. We enable this through a graphical representation of discourse structure called the Navigation Map. We demonstrate the subjective and objective utility of the Navigation Map through two user studies. Overall, our work demonstrates that discourse structure is an important information source for designers of spoken dialogue systems.
Variation in Macronuclear Genome Content of Three Ciliates with Extensive Chromosomal Fragmentation: A Preliminary Analysis

ABSTRACT. The genome architecture of ciliates, including features such as nuclear dualism and large‐scale genome rearrangements, impacts gene and genome evolution in these organisms. To better understand the structure of macronuclear chromosomes in ciliates with extensively processed chromosomes, a sample of complete macronuclear chromosomes was sequenced from three ciliate species: Metopus es (Class [Cl]: Armophorea), Nyctotherus ovalis (Cl: Armophorea), and Chilodonella uncinata (Cl: Phyllopharyngea). By cloning whole macronuclear chromosomes into a plasmid vector, we generated nine clones from each of M. es and C. uncinata, and 37 clones from N. ovalis. Analysis of these macronuclear chromosomes provides insight into the evolution of genome features such as chromosome content, gene structure, and genetic code. Phylogenetic patterns can be found in telomere structure and codon usage, which are both more similar in M. es and N. ovalis than C. uncinata. In addition, we provide evidence of lateral transfer of a bacterial endo‐β‐mannanase gene onto a M. es chromosome and report the discovery of a 42‐bp conserved sequence motif within N. ovalis untranslated regions.
APPLICATION OF COMPRESSIVE SENSING BASED BEAMFORMING IN AEROACOUSTIC EXPERIMENT

Compressive sensing (CS) is a newly emerging method in information technology that could reduce sampling efforts extensively by conducting L1 optimization. In this work, CS is extended to array beamforming applications and two algorithms (CSB-I and CSB-II) are presented with the assumption of spatially sparse and incoherent sound sources. The two algorithms are examined using both simulation and aeroacoustic experiments. The simulation case clearly shows that the CSB-I algorithm is quite sensitive to the sensing noise. The CSB-II algorithm, on the other hand, is more robust to noisy measurements. In addition, aeroacoustic tests of an airplane model demonstrate the good performance in terms of resolution and sidelobe rejection of CSB-II algorithm.
Taking the best from the Crowd:Learning Question Passage Classification from Noisy Data

In this paper, we propose methods to take into account the disagreement between crowd annotators as well as their skills for weighting instances in learning algorithms. The latter can thus better deal with noise in the annotation and produce higher accuracy. We created two passage reranking datasets: one with crowdsource platform, and the second with an expert who completely revised the crowd annotation. Our experiments show that our weighting approach reduces noise improving passage reranking up to 1.47% and 1.85% on MRR and P@1, respectively.
Prototyping and end user involvement in early stages of mobile applications development

: The development of mobile applications includes some different requirements compared to the development of PC software since the mobile applications are used in a different context. The user is generally being mobile or doing some special tasks while using the application. Therefore it is important to involve the user during the development of the applications in order to understand the way that the user is acting and to develop a product that better fits to his wants and needs. The tool that we propose in this case is prototyping. For this purpose we first did a literature review in order to gain an overview on the previous work and summarize it. Based on our literature review we built four hypotheses and then conducted an online survey in order to prove our hypotheses. Our survey showed that the use of prototypes is a good tool to involve the end users in the development of mobile applications and that in this way the developed applications better fulfil the user needs and requirements.
Supporting Scalable, Persistent Semantic Web Applications

To realize the vision of the Semantic Web, efficient storage and retrieval of large RDF data sets is required. A common technique for persisting RDF data (graphs) is to use a single relational database table, a triple store. But, we believe a single triple store cannot scale for large-scale applications. This paper describes storing and querying persistent RDF graphs in Jena, a Semantic Web programmers’ toolkit. Jena augments the triple store with property tables that cluster multiple property values in a single table row. We also describe two tools to assist in designing application-specific RDF storage schema. The first is a synthetic data generator that generates RDF graphs consistent with an underlying ontology. The second mines an RDF graph or an RDF query log for frequently occurring patterns. These patterns can be applied to schema design or caching strategies to improve performance. We also briefly describe Jena inferencing and a new approach to context in RDF which we call snippets.
Axillary versus femoral arterial cannulation in type A acute aortic dissection: evidence from a meta-analysis of comparative studies and adjusted risk estimates.

OBJECTIVES There is a growing perception that femoral arterial cannulation (FAC), by reversing the flow in the thoracoabdominal aorta, may increase the risk of retrograde brain embolization, dissection and organ malperfusion in type A aortic dissection. Axillary artery cannulation (AXC) has been reported to improve operative outcomes by allowing antegrade blood flow. However, FAC still remains largely utilized as a consensus for the routine use of AXC has not yet been reached. METHODS A meta-analysis on comparative studies reporting operative outcomes using AXC versus FAC was performed. Pooled weighted incidence rates for end points of interest (both adjusted and unadjusted) have been computed using an inverse variance model. RESULTS Overall, a total of 8 studies including 793 patients were analysed (AXC = 396, FAC = 397). AXC was associated with reduced risk for in-hospital mortality [risk ratio (RR): 0.41; 95% confidence interval (CI): 0.29-0.58; P < 0.001] and permanent neurological deficit (PND) (RR: 0.59; 95% CI: 37.-0.93; P = 0.02) when compared with FAC. Pooled adjusted estimates confirmed that AXC was independently associated with a significantly reduced incidence of in-hospital mortality (adjusted OR: 0.54; 95% CI: 0.36-0.82; P = 0.004; I(2) = 57%) and PND (adjusted OR: 0.19; 95%CI: 0.07-0.54; P = 0.002; I(2) = 0%). CONCLUSIONS The present meta-analysis demonstrated that AXC is superior to FAC in reducing in-hospital mortality and the incidence of PND in patients operated on for type A acute aortic dissection.
Content characteristics of formal information technology strategy as implementation predictors in Norwegian organisations

The need for improved implementation of information technology strategy has been emphasised in both empirical and prescriptive research studies. In this study, ten content characteristics of formal information technology strategy are identified from the research literature as potential implementation predictors. These are descriptions of: i) resources needed for the implementation; ii) user involvement during the implementation; iii) analyses of the organisation; iv) anticipated changes in the environment; v) solutions to potential resistance during the implementation; vi) information technology to be implemented; vii) projects’ relevance to the business plan; viii) responsibility for the implementation; ix) management support for the implementation; and x) clearity of the documentation. The survey was conducted in Norway whereupon the return of 471 completed questionnaires resulted in a satisfactory response rate of 43%. Formal IT strategy was reported in 40% of these organisations. The two significant predictors in the testing of hypotheses proved to be description of responsibility for the implementation and description of user involvement during the implementation. Suggestions for further research are concerned with adding richness by searching for other explanations of IT strategy implementation beyond characteristics of the plan itself and including contingency variables.
A MAC protocol for UWB Very Low Power Mobile Ad-hoc Networks based on Dynamic Channel Coding with Interference Mitigation

We propose a MAC protocol for very low radiated power (1 microwatt) ultra-wide band (UWB) mobile ad-hoc networks. Unlike traditional approaches, our protocol fully utilizes the specific nature of the physical layer of UWB. This makes it possible to reach a reasonably high bit rate per source in spite of the low power, while being fully distributed. We use dynamic channel coding as an efficient way to adapt to varying channel conditions due to mobility and interference. Our design is based on existing theoretical findings that state that it is optimal to allow interfering sources to transmit simultaneously, as long as they are outside a well-defined exclusion region around a destination, and to adapt the channel code to this interference; in contrast, interference from inside the exclusion region should be combatted. We use pulse position modulation, as is commonly done with UWB. The very low power assumption implies that pulses are infrequent. This property, together with a demodulation scheme that cancels much of the interfering energy, allows us to mitigate interference from nodes in the exclusion region. This scheme is entirely local to a destination and involves no protocol action. In addition, sources constantly adjust their channel codes (thus their bit rates) and send incremental redundancy as required. Contention between sources sending to the same destination is solved by a private MAC protocol, i.e., a set of interactions that involve only the nodes that want to talk to the same destination. Carrier sensing is not used, as it is practically impossible with UWB. We show by simulation that we achieve a significant increase in network throughput, compared to traditional MAC protocols that are separated from the physical layer.
Algorithm acceleration on LEON-2 processor using a reconfigurable bit manipulation unit

Advanced bit manipulation operations are not efficiently supported by standard microprocessors since they are optimized for fixed data size operations. In literature several hardware solutions are proposed to overcome this problem [1], [3] and [4]. In this work we present the experimental results of a new architecture based on LEON-2 and a simplified version of ADAPTO [1] (Adder-based Dynamic Architecture for Processing Tailored Operators), acting as a co-processor. For our experiments we run a set of Bit Manipulation Algorithms on the LEON-2 processor in presence and absence of the ADAPTO unit. This permits to measure the speed-up factor obtained using the proposed reconfigurable co-processor.
High Resolution Image Reconstruction in Shape from Focus

In the Shape from Focus (SFF) method, a sequence of images of a 3D object is captured for computing its depth profile. However, it is useful in several applications to also derive a high resolution focused image of the 3D object. Given the space-variantly blurred frames and the depth map, we propose a method to optimally estimate a high resolution image of the object within the SFF framework.
Color enhancement in the compressed domain

This paper presents a new efficient technique for color enhancement in the compressed domain. In the proposed technique the enhancement computation is performed in three steps, namely, adjustment of dynamic range of brightness values, preservation of local contrast and preservation of color with all computations involving scaling of the DCT coefficients. Further special care has been taken for reducing the blocking artifacts. The proposed algorithm provide better performances compared to some of the existing techniques in the compressed domain.
Photon-assisted transport through ultrasmall quantum dots: Influence of intradot transitions

We study transport through one or two ultrasmall quantum dots with discrete energy levels to which a time-dependent field is applied (e.g., microwaves). The ac field causes photon-assisted tunneling and also transitions between discrete energy levels of the dot. We treat the problem by introducing a generalization of the rotating-wave approximation to arbitrarily many levels. We calculate the dc current through one dot and find satisfactory agreement with recent experiments by Oosterkamp et al. [Phys. Rev. Lett. 78, 1536 (1997)]. In addition, we propose an electron pump consisting of two serially coupled single-level quantum dots with a time-dependent interdot barrier.
Mining GO Annotations for Improving Annotation Consistency

Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.
Allogeneic hematopoietic cell transplantation in adult patients with myelodysplastic/myeloproliferative neoplasms

Background In adults, the 2 main types of myelodysplastic/myeloproliferative neoplasms (MDS/MPN) are chronic myelomonocytic leukemia (CMML) and atypical chronic myeloid leukemia (aCML). Both are associated with a poor prognosis. Allogeneic hematopoietic cell transplantation (HCT) is the only known curative treatment modality for these diseases, but data on outcomes following such treatment are limited. We analyzed the outcomes of patients with MDS/MPN after allogeneic HCT. Methods This retrospective study included 10 patients with MDS/MPN who received allogeneic HCT at Asan Medical Center from 2002 to 2010. Of these 10 patients, 7 had CMML, 2 had aCML, and 1 had unclassifiable MDS/MPN. Five patients received a myeloablative conditioning (MAC) regimen (busulfan-cyclophosphamide), and 5 received reduced-intensity conditioning (RIC) regimen. Results Neutrophil engraftment was achieved in all patients. After a median follow-up of 47.5 months among surviving patients, 4 had relapsed and 5 had died. There was only 1 treatment-related death. The 5-year rates of overall, relapse-free, and event-free survival were 42.2%, 51.9%, and 46.7%, respectively. Relapse was the leading cause of treatment failure, and all relapses were observed in patients who had received RIC and who did not develop chronic graft-versus-host disease. Conclusion Allogeneic HCT can induce durable remission in patients with MDS/MPN, but RIC cannot replace MAC in patients eligible for myeloablative treatments.
sparqlPuSH: Proactive Notification of Data Updates in RDF Stores Using PubSubHubbub

With the growing numbers of status update websites and related wrappers, initiatives modelling sensor data in RDF, as well as the dynamic nature of many Linked Data exporters, there is a need for protocols enabling real-time notification and broadcasting of RDF data updates. In this paper we present a flexible approach that provides such notifications to be delivered in real-time to any RSS or Atom reader. Our framework enables the active delivery of SPARQL query results through the PubSubHubbub (PuSH) protocol upon the arrival of new information in RDF stores. Our open source implementation can be plugged on any SPARQL endpoint and can directly reuse PuSH hubs that are already deployed in scalable clouds (e.g. Google’s).
List-color-critical graphs on a fixed surface

A k-list-assignment for a graph G assigns to each vertex v of G a list L(v) of admissible colors, where |L(v)| ≥ k. A graph is k-list-colorable (or k-choosable) if it can be properly colored from the lists for every k-list-assignment. We prove the following conjecture posed by Thomassen in 1994: "There are only finitely many list-color-critical graphs with all lists of cardinality at least 5 on any fixed surface. " This generalizes the well-known result of Thomassen on the usual graph coloring case. We use this theorem and specific parts of its proof to resolve the complexity status of the following problem about k-list-coloring graphs on a fixed surface S, where k is a fixed positive integer. Input: A graph G embedded in the surface S. Question: Is G k-choosable? If not, provide a certificate (a list-color-critical subgraph and the corresponding k-list-assignment). The cases k = 3, 4 are known to be NP-hard (actually even Πp2-complete), and the cases k = 1, 2 are easy. Our main results imply that the problem is tractable for every k ≥ 5. In fact, together with our recent algorithmic result, we are able to solve it in linear time when k ≥ 5. Our proof yields even more: if the input graph is k-list-colorable, then for any k-list-assignment L, we can construct an L-coloring of G in linear time. This generalizes the well-known linear-time algorithms for planar graphs by Nishizeki and Chiba (for 5-coloring), and Thomassen (for 5-list-coloring). We also give a polynomial-time algorithm to resolve the following question: Input: A graph G in the surface S, and a k-list-assignment L, where k ≥ 5. Question: Does G admit an L-coloring? If not, provide a certificate for this. If yes, then return an L-coloring. If the graph G is k-list-colorable, then our first result gives a linear time solution. However, the second problem is more general, since it provides a coloring (or a small obstruction) for an arbitrary graph in S. We also use our main theorem to prove another conjecture that was proposed recently by Thomassen: "For every fixed surface S, there exists a positive constant c such that every 5-list-colorable graph with n vertices embedded on S, has at least c · 2n distinct 5-list-colorings for every 5-list-assignment for G. " Thomassen himself proved that this conjecture holds for usual 5-colorings. In addition to all these results, we also made partial progress towards a conjecture of Albertson concerning coloring extensions and a progress on similar questions for triangle-free graphs and graphs of larger girth.
A Family of Non-negative Matrix Factorizations for One-Class Collaborative Filtering Problems

This paper is motivated by the industrial research problem of designing a real-world recommender system for a large Information Technology (IT) company. Given historical records of client purchases, compactly represented as a sparse client-times-product “who-bought-what” binary matrix, the goal is to build a model that provides recommendations for what products should be sold next to the existing client base. Such a problem may naturally be formulated as a collaborative filtering task. However, this is a one-class setting, that is, if a client has not bought a product yet, it does not imply that the client has a low propensity to potentially buy that product later. In the absence of explicitly labeled negative examples, one may resort to considering zero-valued client-product pairs as either missing data or as surrogate negative instances. In this paper, we outline an approach to explicitly deal with this kind of ambiguity by instead treating zero-valued pairs as optimization variables. These variables are optimized in conjunction with learning a weighted, low-rank non-negative matrix factorization (NMF) of the client-product matrix. The proposed algorithm alternates NMF optimization with deterministicannealing/continuation techniques designed for global minimization of combinatorial and non-convex objective functions. Experimental results show that our approach can give significantly better recommendations in comparison to various competing alternatives on a one-class collaborative filtering task.
Multi-field Correlated Topic Modeling

Popular methods for probabilistic topic modeling like the Latent Dirichlet Allocation (LDA, [1]) and Correlated Topic Models (CTM, [2]) share an important property, i.e., using a common set of topics to model all the data. This property can be too restrictive for modeling complex data entries where multiple fields of heterogeneous data jointly provide rich information about each object or event. We propose a new extension of the CTM method to enable modeling with multi-field topics in a global graphical structure, and a mean-field variational algorithm to allow joint learning of multinomial topic models from discrete data and Gaussianstyle topic models for real-valued data. We conducted experiments with both simulated and real data, and observed that the multi-field CTM outperforms a conventional CTM in both likelihood maximization and perplexity reduction. A deeper analysis on the simulated data reveals that the superior performance is the result of successful discovery of the mapping among field-specific topics and observed data.