Miracle-dz/UniFAR-FTUs huggingface dataset:
Can a Virtual Listener Replace a Human Listener in Active Listening Conversation?

The elderly who live alone are increasing rapidly in these years. For their mental health, it is reported useful to maintain their social life with others. Active listening is a communication technique that the listener listens to the speaker carefully and attentively by confirming or asking for more details about what they heard. Our project is aiming to develop a computer graphics animated agent who can engage active listening dialog with the elderly users. However, there is a research issue exists in this task: whether the CG animated virtual listener can be really perceived as a human active listeners even if they perform the same behaviors. This paper presents the experiment results in investigating this issue. We conducted an experiment which collects active listening teleconferences in two conditions, human-human and human-agent. In the human-agent condition, the human listener's video is substituted with a CG character performing the same behaviors. We then compared the impression in these two conditions base on the evaluation done by the participants themselves. The results showed that generally there were no significant differences between these two conditions. This means that a virtual listener can engage active listening at the level similar to human listeners if their behaviors are appropriately modeled.
A Task Scheduling Algorithm Based on PSO for Grid Computing

Grid computing is a high performance computing environment to solve larger scale computational demands. Grid computing contains resource management, task scheduling, security problems, information management and so on. Task scheduling is a fundamental issue in achieving high performance in grid computing systems. However, it is a big challenge for efficient scheduling algorithm design and implementation. In this paper, a heuristic approach based on particle swarm optimization algorithm is adopted to solving task scheduling problem in grid environment. Each particle is represented a possible solution, and the position vector is transformed from the continuous variable to the discrete variable. This approach aims to generate an optimal schedule so as to get the minimum completion time while completing the tasks. The results of simulated experiments show that the particle swarm optimization algorithm is able to get the better schedule than genetic algorithm.
Sequence Classification Based on Delta-Free Sequential Patterns

Sequential pattern mining is one of the most studied and challenging tasks in data mining. However, the extension of well-known methods from many other classical patterns to sequences is not a trivial task. In this paper we study the notion of δ-freeness for sequences. While this notion has extensively been discussed for itemsets, this work is the first to extend it to sequences. We define an efficient algorithm devoted to the extraction of δ-free sequential patterns. Furthermore, we show the advantage of the δ-free sequences and highlight their importance when building sequence classifiers, and we show how they can be used to address the feature selection problem in statistical classifiers, as well as to build symbolic classifiers which optimizes both accuracy and earliness of predictions.
The Arabidopsis receptor kinase STRUBBELIG undergoes clathrin-dependent endocytosis

Abstract Signaling mediated by cell surface receptor kinases is central to the coordination of growth patterns during organogenesis. Receptor kinase signaling is in part controlled through endocytosis and subcellular distribution of the respective receptor kinase. For the majority of plant cell surface receptors, the underlying trafficking mechanisms are not characterized. In Arabidopsis, tissue morphogenesis requires the atypical receptor kinase STRUBBELIG (SUB). Here, we studied the endocytic mechanism of SUB. Our data revealed that a functional SUB–enhanced green fluorescent protein (EGFP) fusion is ubiquitinated in vivo. We further showed that plasma membrane-bound SUB:EGFP becomes internalized in a clathrin-dependent fashion. We also found that SUB:EGFP associates with the trans-Golgi network and accumulates in multivesicular bodies and the vacuole. Co-immunoprecipitation experiments revealed that SUB:EGFP and clathrin are present within the same protein complex. Our genetic analysis showed that SUB and CLATHRIN HEAVY CHAIN (CHC) 2 regulate root hair patterning. By contrast, genetic reduction of CHC activity ameliorates the floral defects of sub mutants. Taken together, the data indicate that SUB undergoes clathrin-mediated endocytosis, that this process does not rely on stimulation of SUB signaling by an exogenous agent, and that SUB genetically interacts with clathrin-dependent pathways in a tissue-specific manner.
Kernel Functions and Meshless Methods

The basic LU factorization with row pivoting, applied to a rectangular Vandermonde-like matrix of an admissible mesh on a multidimensional compact set, extracts from the mesh the so-called Discrete Leja Points, and provides at the same time a Newton-like interpolation formula. Working on the mesh, we obtain also a good approximate estimate of the interpolation error.
Analysis of non-idealities in direct and indirect matrix converters

This paper compares the voltage transfer characteristics of direct and indirect matrix converter topologies. Knowledge of the real voltage transfer capability of a converter is essential, especially in sensorless motor drives in low speed region. The comparison is based on the analysis of non-idealities caused by real semiconductor devices and safe commutation methods. The effects of on-state voltage losses and commutation methods are modelled with equations. The analysis is verified in measurements and simulations. The direct matrix converter follows the reference more accurately than the indirect matrix converter. Thus direct topology is also found to be a more suitable converter solution for sensorless motor drives if no compensation methods of voltage inaccuracies are used. The results show that analysis of voltage transfer inaccuracies in direct and indirect matrix converter topologies can be used as a basis to develop the compensation methods needed in high performance motor drives without speed sensors
Survey on VSPN: VANET-Based Secure and Privacy-Preserving Navigation

VANET provide facility for the vehicles on roads to communicate for driving safety. The basic idea is to allow arbitrary vehicles to broadcast ad hoc messages to other vehicles. However, this raises the issue of security and privacy. Here, we have described various existing solutions/protocols that are used in order to satisfy the security and privacy requirement of the vehicular ad hoc network. We have also described security issues and challenges in VANET. We have presented various security attributes that may be considered as criteria to measure security such as availability, confidentiality, integrity, authentication and non-repudiation. This paper also give the detail information of some of the schemes such as RAISE ,IBV with their pros and cons.
Tight Bounds for Planar Strongly Connected Steiner Subgraph with Fixed Number of Terminals (and Extensions)

Given a vertex-weighted directed graph G = (V, E) and a set T = {t1, t2, . tk} of k terminals, the objective of the Strongly Connected Steiner Subgraph (SCSS) problem is to find a vertex set H ⊆ V of minimum weight such that G[H] contains a ti → tj path for each i ≠ j. The problem is NP-hard, but Feldman and Ruhl (FOCS '99; SICOMP '06) gave a novel nO(k) algorithm for the SCSS problem, where n is the number of vertices in the graph and k is the number of terminals. We explore how much easier the problem becomes on planar directed graphs. • Our main algorithmic result is a 2O(k log k) · nO(√k) algorithm for planar SCSS, which is an improvement of a factor of O(√k) in the exponent over the algorithm of Feldman and Ruhl. • Our main hardness result is a matching lower bound for our algorithm: we show that planar SCSS does not have an f(k) · no(√k) algorithm for any computable function f, unless the Exponential Time Hypothesis (ETH) fails. The algorithm eventually relies on the excluded grid theorem for planar graphs, but we stress that it is not simply a straightforward application of treewidth-based techniques: we need several layers of abstraction to arrive to a problem formulation where the speedup due to planarity can be exploited. To obtain the lower bound matching the algorithm, we need a delicate construction of gadgets arranged in a grid-like fashion to tightly control the number of terminals in the created instance. The following additional results put our upper and lower bounds in context: • Our 2O(k log k) · nO(√k) algorithm for planar directed graphs can be generalized to graphs excluding a fixed minor. • In general graphs, we cannot hope for such a dramatic improvement over the nO(k) algorithm of Feldman and Ruhl: assuming ETH, SCSS in general graphs does not have an f(k) · no(k/logk) algorithm for any computable function f. • Feldman and Ruhl generalized their nO(k) algorithm to the more general Directed Steiner Forest (DSF) problem; here the task is to find a subgraph of minimum weight such that for every source si there is a path to the corresponding terminal ti. We show that that, assuming ETH, there is no f(k) · no(k) time algorithm for DSF on acyclic planar graphs.
Contributing Knowledge to Organizational Repositories: The Role of Governance Mechanisms

Two mechanisms employed by organizations to ensure information quality in organizational knowledge repositories is using experts to control or edit users’ contributions (such as in a refereed repository), or using a community of users to review, rate, or edit existing contributions (such as in a community-driven wiki). The goal of this paper is to explore these two mechanisms and study their impact on knowledge contributions by organizational members. Propositions are suggested by drawing upon self-determination theory.
Long term variability of Cygnus X-1. I. X-ray spectral-temporal correlations in the hard state

We present the long term evolution of the timing properties of the black hole candidate Cygnus X-1 in the 0.002-128 Hz frequency range as monitored from 1998 to 2001 with the Rossi X-ray Timing Explorer (RXTE). For most of this period the source was in its hard state. The power spectral density (PSD) is well modeled as the sum of four Lorentzians, which describe distinct broad noise components. Before 1998 July, Cyg X-1 was in a "quiet" hard state characterized primarily by the first three of these broad Lorentzians being dominant. Around 1998 May, this behavior changed: the total fractional rms amplitude decreased, the peak frequencies of the Lorentzians increased, the average time lag slightly increased, and the X-ray spectrum softened. The change in the timing parameters is mainly due to a strong decrease in the amplitude of the third Lorentzian. Since this event, an unusually large number of X-ray flares have been observed, which we classify as "failed state transitions". During these failed state transitions, the X-ray power spectrum changes to that of the intermediate state. Modeling this PSD with the four Lorentzians, we find that the first Lorentzian component is suppressed relative to the second and third Lorentzian during the state transitions. We also confirm our previous conclusion that the frequency-dependent time lags in- crease significantly in the 3.2-10 Hz band during these transitions. We confirm the interpretation of the flares as failed state transitions with observations from the 2001 January and 2001 October soft states. Both the behavior of the PSD and the X-ray lag suggest that some or all of the Lorentzian components are associated with the accretion disk corona responsible for the hard state spectrum. We discuss the physical interpretation of our results.
Reasoning for Intelligent System-User Interactions with Enterprise Resource Planning Systems ∗

Enterprise Resource Planning (ERP) systems are recognized as having unintuitive interfaces and being difficult to use. At least part of the reason for these problems comes from the complexity of the processes they support and the need for generic interfaces that can be adapted for use by a wide range of industries. We examine here the application of usage logs and AI planning to strengthen the ability of the system to act as a collaborative partner providing individualized support to its users, particularly in resolving errors. This work is part of a larger project investigating if the usability of ERP systems can be improved by adopting humancomputer collaboration as a paradigm for system design.
ONLINE SOCIAL NETWORKS AND THE PRIVACY PARADOX: A RESEARCH FRAMEWORK

There is a paradox of privacy within social networking sites such as Facebook and MySpace. Users join these sites for any number of reasons, from professional networking to keeping in touch with family and every reason in-between. Studies show that it is likely that users are not always as aware of privacy issues on the Internet, and probably share more information than they would if they were aware of their potential exploitation when their supposedly private data is accessed without permission. This paper will look the privacy issues that surround social networking sites and offer a research framework specifically focusing on the characteristics of an online social networker and the motivating factors that guide them as they communicate through a social networking website.
Brain Mechanisms for Social Perception

In this review, we summarize our research program, which has as its goal charting the typical and atypical development of the social brain in children, adolescents, and adults with and without autism. We highlight recent work using virtual reality stimuli, eye tracking, and functional magnetic resonance imaging that has implicated the superior temporal sulcus (STS) region as an important component of the network of brain regions that support various aspects of social cognition and social perception. Our work in typically developing adults has led to the conclusion that the STS region is involved in social perception via its role in the visual analysis of others' actions and intentions from biological‐motion cues. Our work in high‐functioning adolescents and adults with autism has implicated the STS region as a mechanism underlying social perception dysfunction in this neurodevelopmental disorder. We also report novel findings from a study of biological‐motion perception in young children with and without autism.
TGF-b and 'Adaptive' Foxp3 þ Regulatory T cells

In naive T cells transforming growth factor-beta (TGF-b) induces Foxp3, a transcription factor essential for programming and developing T regulatory cells (Treg cells). This finding reveals a physiological factor which can turn on the Foxp3 gene and establishes an experimental approach to induce antigen-specific Treg cells as a potential therapy for human diseases. While this role for TGF-b is well confirmed, several critical questions remain largely unanswered and await further investigation. In this regard, it is imperative to understand the molecular pathways by which TGF-b signaling initiates and regulates Foxp3 expression. It is also important to elucidate which factors and/or cytokines influence the TGF-b-mediated conversion of naive T cells and how to create an immunologically regulatory milieu to facilitate Treg cell generation in vivo. In this short article, we will highlight the key findings and recent progress in the field, discuss the molecular mechanisms underlying the TGF-b-mediated induction of Foxp3, and attempt to outline the challenges ahead.
A Review of Temporomandibular Disorder and an Analysis of Mandibular Motion

This study quantified mandibular motion of asymptomatic subjects upon jaw opening and closing. Five males, mean age of 28 years, agreed to participate; they showed no sign or symptom of temporomandibular disorder (TMD) on clinical examination or by anamnestic history. Mandibular motion for each subject was measured with a tracking system and software utilizing the Screw Displacement Axis (SDA), which is a mathematical approach to analyzing and quantifying the movement of an object in three dimensions. Rotation and translation were calculated, as well as twoand three-dimensional charting of condylar path and sagittal condylar intercepts. Furthermore, analyses examined error propagation, change in error amplitude with varying test conditions, and a comparison between theoretical and experimental data. The mean maximum rotation around the screw displacement axes was 25.0 ̊ (sd = 4.0 ̊). Mean translation along the screw displacement axes was 2.3 mm (sd = 0.68 mm). The SDA intersection plots showed that the paths of motion for all subjects were posterior and inferior to the condyle. During opening, paths start nearer to the condyle and travel inferiorly and anteriorly. Jaw closing followed the reverse path (superior and posterior) with the final position approximating the area of the initial axis. Mean SDA intercepts with the sagittal plane of the condyle were positioned posterior and inferior of the selected center of the condyle. SDA v position and orientation parameters were inversely related to the rotational increment. As rotational increments approached 5 ̊, there was little change in the uncertainty values, indicating that data should be processed at increments of at least 4 ̊ to 5 ̊. Coordinate data obtained with the tracking system displayed an error that was not present when the targets were stationary, nor did its amplitude change with a change in velocity. These observations led to the idea that the error associated with the tracking system relied purely on target position. The only way to counter this system error was to raise the rotational increments in data processing and find an area in the sensor’s viewing field that produces the least error. The closest the targets could be brought to the camera while maintaining a viewing area large enough to test jaw motion was in the range of 150-200 mm from the sensor. The experimental data obtained from the SDA intercepts at 10 ̊ iterations showed a path similar to theoretical expectations. The screw displacement axis method does have limitations. If only translational motion occurs, the SDA is undefined. The SDA method is also very prone to measurement error. At low rotational increments, large error of the SDA parameters can be encountered due to small measurement inaccuracies. However, small rotational increments are necessary to reliably approximate the continuous movement through a series of finite calculations. A balance is therefore required between these two opposing error sources.
Evolution and Functional Implications of the Tricarboxylic Acid Cycle as Revealed by Phylogenetic Analysis

The tricarboxylic acid (TCA) cycle, a crucial component of respiratory metabolism, is composed of a set of eight enzymes present in the mitochondrial matrix. However, most of the TCA cycle enzymes are encoded in the nucleus in higher eukaryotes. In addition, evidence has accumulated demonstrating that nuclear genes were acquired from the mitochondrial genome during the course of evolution. For this reason, we here analyzed the evolutionary history of all TCA cycle enzymes in attempt to better understand the origin of these nuclear-encoded proteins. Our results indicate that prior to endosymbiotic events the TCA cycle seemed to operate only as isolated steps in both the host (eubacterial cell) and mitochondria (alphaproteobacteria). The origin of isoforms present in different cell compartments might be associated either with gene-transfer events which did not result in proper targeting of the protein to mitochondrion or with duplication events. Further in silico analyses allow us to suggest new insights into the possible roles of TCA cycle enzymes in different tissues. Finally, we performed coexpression analysis using mitochondrial TCA cycle genes revealing close connections among these genes most likely related to the higher efficiency of oxidative phosphorylation in this specialized organelle. Moreover, these analyses allowed us to identify further candidate genes which might be used for metabolic engineering purposes given the importance of the TCA cycle during development and/or stress situations.
Special Issue in the Journal Artificial Intelligence in Medicine on Summarization and Information Extraction from Medical Documents, Comparative Experiments on Learning Information Extractors for Proteins and their Interactions

Automatically extracting information from biomedical text holds the promise of easily consolidating large amounts of biological knowledge in computer-accessible form. This strategy is particularly attractive for extracting data relevant to genes of the human genome from the 11 million abstracts in Medline. However, extraction e orts have been frustrated by the lack of conventions for describing human genes and proteins. We have developed and evaluated a variety of learned information extraction systems for identifying human protein names in Medline abstracts and subsequently extracting information on interactions between the proteins. We demonstrate that machine learning approaches using support vector machines and maximum entropy are able to identify human proteins with higher accuracy than several previous approaches. We also demonstrate that various rule induction methods are able to identify protein interactions with higher precision than manually-developed rules.
ELI⇥IR: Expertise Learning & Identification ⇥ Information Retrieval

In today’s knowledge-based economy, having the proper expertise is crucial to resolving many tasks. Expertise Finding (EF) is the area of research concerned with matching available experts to given tasks. As tandard approach is to input at ask description/proposal/paper into an EF system, and receive recommended experts as output. Mostly, EF systems operate either via a content-based approach, which uses the text of the input, as well as the text of the available experts’ profiles to determine a match, and structure-based approaches, which use the inherent relationship between experts, affiliations, papers, etc. (such as is available in citation networks). The majority of methods use one approach (content-based, "C") or the other (structure-based, "S"); though sometimes both approaches are used in tandem (C and S). The underlying data representation is fundamentally different, which makes the methods mutually incompatible. However, in previous work Watanabe et al. [34] achieved good results by converting content-based data to a structure-representation and using a structure-based approach. We posit that the reverse may also hold merit, namely, a content-based approach leveraging structure-based data converted to a content-based representation. We compare our idea to a content only-based approach, demonstrating that our method yields substantially better performance, and thereby substantiating our claim.
A Spatio-Temporal Metric for the Evaluation of Cooperative Awareness

Upcoming field trials for cooperative systems provide unique opportunities to evaluate research results in real world experiments. Amongst these research results, there are many approaches for efficient use of available communication resources. It is crucial to establish a metric for comparison, in order to identify the most suitable approaches. This metric should be usable in both, field trial experiments and preparative simulations. This paper proposes such a metric. It measures the quality of the ultimate goal of cooperative systems, the quality of cooperative awareness. The authors discuss the implementation of the metric in a simulation environment, and provide results of a simulation study on the system performance under high load. Furthermore, they explain how to realize the metric in large-scale field trials.