Miracle-dz/UniFAR-FTUs huggingface dataset:
Symbolic Nearest Mean Classifiers

The minimum-distance classifier summarizes each class with a prototype and then uses a nearest neighbor approach for classification. Three drawbacks of the original minimum-distance classifier are its inability to work with symbolic attributes, weigh attributes, and learn more than a single prototype for each class. The proposed solutions to these problems include defining the mean for symbolic attributes, providing a weighting metric, and learning several possible prototypes for each class. The learning algorithm developed to tackle these problems, SNMC, increases classification accuracy by 10% over the original minimum-distance classifier and has a higher average generalization accuracy than both C4.5 and PEBLS on 20 domains from the UCI data repository.
Path planning and tracking of a 4WD4WS vehicle to be driven under force control

The aim of this paper is to investigate the possibility of developing a system where forces at the wheels of a ground vehicle are controlled to guide the vehicle along a predetermined path. Any deviations from the desired path is handled using Bézier curve segments that put the vehicle back on track. The Bézier curve segments determine the necessary forces at the wheels. The future aim is to implement independent force control at each of the drive/steering modules of the vehicle. The vehicle is considered to be a rigid body with known inertia and mass. The paper presents path generation using Bézier curves, the extraction of desired forces and the determination of desired steering and propulsion to achieve the desired forces at the wheels of the vehicle. The forces and the control inputs such as the steering angles are then applied to a four wheel driven and four wheel steered vehicle subjected to slip in an open loop setting. Note that this paper does not address the force control issues. Simulation data are generated to validate the proposed methodology.
Adenovirus-mediated expression of ribozymes in mice

Ribozymes are a new pharmaceutical class of reagents that offer potential in treating a number of different medical disorders, including infectious diseases and cancer. As a first step towards using ribozymes for the treatment of liver disorders such as viral hepatitis, adenovirus vectors that contain a ribozyme expression cassette under the control of different promoters directed against human growth hormone (hGH) were constructed and infused into transgenic mice that produce hGH from the gastrointestinal tract and liver. Adenovirus-mediated transfer of expressed ribozymes resulted in up to a 96% reduction of hepatic hGH mRNA over a period of several weeks in the transgenic mouse model. Furthermore, the concentration of ribozyme RNA correlated with the degree of hGH mRNA reduction. This study clearly demonstrates that ribozymes can function during the period of expression in an intact organ after somatic gene transfer.
Chemical treatment and improved charge storage properties of cellular polypropylene electret film

Chemical treatment of cellular polypropylene (PP) films was carried out. Their charge storage properties were investigated using the open circuit thermally stimulated discharge (TSD) current spectra and charge TSD spectra. The charge storage thermal stability of the HF-treated samples is significantly improved, as shown by a very strong high temperature peak at about 176/spl deg/C. The charge stability of treated films is improved further by appropriately prolonging HF treatment time at RT. It was found that the reaction rate of HF with the oxidized surface layer is obviously enhanced by light radiation or treating temperature. However, charge storage stability becomes worse even than the virginal film prolonging HF-treating time under light radiation. An in situ TSD charge spectrum contains combined information on the changes of the mean charge depth and the deposited charge value. The dynamic change of the mean charge depth during heating was investigated by the in situ TSD charge spectra.
The University of Indonesia's Participation in IMAGE-CLEF 2005

We present a report on our participation in the English-Indonesian image ad-hoc task of the 2005 Cross-Language Evaluation Forum (CLEF). We chose to translate the Indonesian query set into English using a commercial machine translation tool called Transtool. We show that some improvement in retrieval effectiveness can be obtained using a query expansion technique. We used an approach that combines the retrieval results of the query on text and on image.
Timbral Qualities of Semantic Structures of Music

The rapid expansion of social media in music has provided the field with impressive datasets that offer insights into the semantic structures underlying everyday uses and classification of music. We hypothesize that the organization of these structures are rather directly linked with the ”qualia” of the music as sound. To explore the ways in which these structures are connected with the qualities of sounds, asemanticspacewasextractedfromalargecollection of musical tags with latent semantic and cluster analysis. The perceptual and musical properties of 19 clusters were investigated by a similarity rating task that used spliced musical excerpts representing each cluster. The resulting perceptual space denoting the clusters correlated high with selected acoustical features extracted from the stimuli. The first dimension related to the high-frequency energy content, the second to the regularity of the spectrum, and the third to the fluctuations within the spectrum. These findings imply that meaningful organization of music may be derived from low-level descriptions of the excerpts. Novel links with the functions of music embedded into the tagging information included within the social media are proposed.
Optimization of Mycelia Selenium Polysaccharide Extraction from Agrocybe cylindracea SL-02 and Assessment of their Antioxidant and Anti-Ageing Activities

The aim of the present study was to optimize the purification of mycelia selenium polysaccharides (MSPS) from Agrocybe cylindracea SL-02 and characterize their in vitro antioxidant and in vivo anti-ageing activities. The Box-Behnken experimental design (BBD) was evaluated, which showed that the optimum conditions included an extraction temperature of 94.99°C, a pH of 9 and a precipitation temperature of 12°C, and the predicted yield was 11.036 ± 0.31%. The in vitro antioxidant assay demonstrated that MSPS had potential effects on scavenging and enhanced the reducing power of reactive oxygen species. The in vivo anti-ageing evaluation showed that MSPS significantly reduced the malonaldehyde (MDA) contents and total cholesterol (CHOL) levels, and remarkably improved the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and total antioxidant capacity (T-AOC) in mice in response to D-galactose-induced ageing. Furthermore, the characteristic analysis of MSPS indicated a selenium content of 1.76 ± 0.10 mg/g at a concentration of 6 μg/mL in liquid media and a monosaccharide composition of rhamnose, arabinose, mannose, glucose and galactose at a molar ratio of 29:3:1:18.8:2.7. These results suggest that MSPS might be suitable for functional foods and natural drugs on preventing the ageing progress induced by toxic chemicals.
Niki and Julie: a robot and virtual human for studying multimodal social interaction

We demonstrate two agents, a robot and a virtual human, which can be used for studying factors that impact social influence. The agents engage in dialogue scenarios that build familiarity, share information, and attempt to influence a human participant. The scenarios are variants of the classical “survival task,” where members of a team rank the importance of a number of items (e.g., items that might help one survive a crash in the desert). These are ranked individually and then re-ranked following a team discussion, and the difference in ranking provides an objective measure of social influence. Survival tasks have been used in psychology, virtual human research, and human-robot interaction. Our agents are operated in a “Wizard-of-Oz” fashion, where a hidden human operator chooses the agents’ dialogue actions while interacting with an experiment participant.
Optimal Filters with Multiple Packet Losses and its Application in Wireless Sensor Networks

This paper is concerned with the filtering problem for both discrete-time stochastic linear (DTSL) systems and discrete-time stochastic nonlinear (DTSN) systems. In DTSL systems, an linear optimal filter with multiple packet losses is designed based on the orthogonal principle analysis approach over unreliable wireless sensor networks (WSNs), and the experience result verifies feasibility and effectiveness of the proposed linear filter; in DTSN systems, an extended minimum variance filter with multiple packet losses is derived, and the filter is extended to the nonlinear case by the first order Taylor series approximation, which is successfully applied to unreliable WSNs. An application example is given and the corresponding simulation results show that, compared with extended Kalman filter (EKF), the proposed extended minimum variance filter is feasible and effective in WSNs.
Bayesian Anomaly Detection (BAD v0.1)

Prior experiments with Bayesian rule generation produced a scalable anytime learner. At its core, that tool computes the likelihood of new events as the product of frequencies of old events. Orrego and Menzies applied that tool to logs of an F-15 flight simulator and showed that the same tool can detect anomalous events which have not been seen previously. This paper checks the external validity of that prior experiment. In twenty-five data sets, anomalous new situations could be identified with high probabilities of detection (average pd over 80%) and low probabilities of false alarm (usually, pf ≤ 5%). These results strongly suggest that we can detect anomalous events, even among very large data sets.
Spliced exons of adenovirus late RNAs colocalize with snRNP in a specific nuclear domain

Posttranscriptional steps in the production of mRNA include well characterized polyadenylation and splicing reactions, but it is also necessary to understand how RNA is transported within the nucleus from the site of its transcription to the nuclear pore, where it is translocated to the cytoplasmic compartment. Determining the localization of RNA within the nucleus is an important aspect of understanding RNA production and may provide clues for investigating the trafficking of RNA within the nucleus and the mechanism for its export to the cytoplasm. We have previously shown that late phase adenovirus-infected cells contain large clusters of snRNP and non-snRNP splicing factors; the presence of these structures is correlated with high levels of viral late gene transcription. The snRNP clusters correspond to enlarged interchromatin granules present in late phase infected cells. Here we show that polyadenylated RNA and spliced tripartite leader exons from the viral major late transcription unit are present in these same late phase snRNP-containing structures. We find that the majority of the steady state viral RNA present in the nucleus is spliced at the tripartite leader exons. Tripartite leader exons are efficiently exported from the nucleus at a time when we detect their accumulation in interchromatin granule clusters. Since the enlarged interchromatin granules contain spliced and polyadenylated RNA, we suggest that viral RNA may accumulate in this late phase structure during an intranuclear step in RNA transport.
Towards a More Systematic Approach to Secure Systems Design and Analysis

The task of designing secure software systems is fraught with uncertainty, as data on uncommon attacks is limited, costs are difficult to estimate, and technology and tools are continually changing. Consequently, experts may interpret the security risks posed to a system in different ways, leading to variation in assessment. This paper presents research into measuring the variability in decision making between security professionals, with the ultimate goal of improving the quality of security advice given to software system designers. A set of thirty nine cyber-security experts took part in an exercise in which they independently assessed a realistic system scenario. This study quantifies agreement in the opinions of experts, examines methods of aggregating opinions, and produces an assessment of attacks from ratings of their components. The authors show that when aggregated, a coherent consensus view of security emerges which can be used to inform decisions made during systems design.
Institutional Entrepreneurship in Emerging Fields: HIV/AIDS Treatment Advocacy in Canada

In a qualitative study of the emerging field of HIV/AIDS treatment advocacy in Canada, we found that institutional entrepreneurship involved three sets of critical activities: (1) the occupation of “subject positions” that have wide legitimacy and bridge diverse stakeholders, (2) the theorization of new practices through discursive and political means, and (3) the institutionalization of these new practices by connecting them to stakeholders’ routines and values.
Unifying Framework for Rule Semantics: Application to Gene Expression Data

The notion of rules is very popular and appears in different flavors, for example as association rules in data mining or as functional dependencies in databases. Their syntax is the same but their semantics widely differs. In the context of gene expression data mining, we introduce three typical examples of rule semantics and for each one, we point out that Armstrong's axioms are sound and complete. In this setting, we propose a unifying framework in which any "well-formed" semantics for rules may be integrated. We do not focus on the underlying data mining problems posed by the discovery of rules, rather we prefer to discuss the expressiveness of our contribution in a particular application domain: the understanding of gene regulatory networks from gene expression data. The key idea is that biologists have the opportunity to choose - among some predefined semantics - or to define the meaning of their rules which best fits into their requirements. Our proposition has been implemented and integrated into an existing open-source system named MeV of the TIGR environment devoted to microarray data interpretation. An application has been performed on expression profiles of a sub-sample of genes from breast cancer tumors.
Psychopathy versus psychopathies in classifying criminal offenders

Purpose. Psychopathy has been shown to be related to the onset, frequency, and course of antisocial behaviour in criminal offenders. The purpose of the present study was to use cluster analysis to explore the existence of subtypes of criminal offenders in male inmates, based on the two empirically validated dimensions of psychopathy and several other dimensions previously proposed for differentiating offender groups. Methods. Two hundred male inmates participated in the study. Scores on the two dimensions of the Psychopathy Checklist–Revised (Hare, 1991), the Interpersonal Measure of Psychopathy (Kosson, Steuerwald, Forth, & Kirkhart, 1997), DSM-IV diagnoses for alcohol and drug abuse/dependence, and anxiety were standardized and were included in two different types of cluster analyses. Both Ward's hierarchical method and K-means non-hierarchical method revealed the presence of four subtypes of criminal offenders in the sample. The four-cluster solution was replicated when the sample was split in half and identical cluster analyses were performed on the two subsamples. Results. Two types of cluster analyses identified four subtypes of criminal offenders in two samples of jail inmates. Two of the clusters resembled primary and secondary psychopaths described in the literature, the third group exhibited some antisocial and psychopathic features, and the fourth group was non-psychopathic. Conclusions. Findings suggest that considering the individual contributions of the two dimensions of psychopathy in lieu of the construct as a whole may prove useful in identifying relatively homogeneous groups of criminal offenders.
Predictors of disordered eating in adolescence and young adulthood

We investigated longitudinal predictors for disordered eating from early adolescence to young adulthood (12–34 years) across gender and different developmental phases among Norwegian young people. Survey data from a population-based sample were collected at four time points (T) over a 13-year time span. A population-based sample of 5,679 females and males at T1 and T2, 2,745 at T3 and 2,718 at T4 were included in analyses, and linear regression and random intercept models were applied. In adolescence, initial disordered eating and parental overprotectiveness were more strongly related to disordered eating among females, whereas loneliness was a stronger predictor for adolescent males. Initial disordered eating during early adolescence predicted later disordered eating more strongly in late- than mid-adolescence. In young adulthood, no significant gender-specific risk factors were found. The findings provide support for both shared and specific risk factors for the developmental psychopathology of disordered eating.
High resolution SAR imaging using random pulse timing

Synthetic Aperture Radar (SAR) is a fundamental technology with significant impact in remote sensing applications. SAR relies on the motion of the radar platform to synthesize a large aperture, and achieve high resolution imaging of a large area. However, current strip-map SAR designs, relying on uniform pulsing, suffer from a fundamental trade-off between the azimuth resolution and the range coverage length. In this paper we overcome this trade-off using a randomized pulsing scheme combined with non-linear compressive sensing (CS) reconstruction. Our experimental results demonstrate significant improvement in the azimuth resolution using the proposed approach, without compromise on the range length of the imaged area.
Psychological, physical, and interpersonal correlates of emotional expressiveness, conflict, and control

This article examines the relations between emotional expression, conflict over expression, and emotional control and psychological and physical distress. Fifty married couples completed two mail‐in surveys containing the Emotional Expressiveness Questionnaire (EEQ), the Ambivalence Over Emotional Expression Questionnaire (AEQ), and the Emotional Control Questionnaire (ECQ), as well as measures of psychological and physical well‐being. They also made expressiveness and well‐being ratings of their spouses. AEQ and ECQ scores were significantly positively correlated with measures of psychological distress and questionnaire measures of physical discomfort. In addition, AEQ scores for items dealing explicitly with anger predicted visits to health‐care provider for illness. EEQ scores did not predict either psychological distress or physical symptoms. AEQ scores were also positively correlated with spouse's symptoms and alcohol use. Wives' expressiveness ratings for their husbands were negatively correlated with a number of indices of psychological distress, while husbands' ratings of wives' expressiveness were positively correlated with measures of distress. Generally, expressiveness, inhibition, and conflict over expression in one spouse did not consistently predict well‐being of the other. Implications of these findings for future research in the area of emotion and illness as well as in relationship satisfaction are discussed.
An analytical approach to study educational inequalities: 10 hypothesis tests in PIRLS 2006

The paper draws on the work of Willms [2006. Learning divides: Ten policy questions about the performance and equity of schools and schooling systems. Montreal: UNESCO Institute for Statistics] to present an analytical approach to the study of academic achievement disparities related to family socioeconomic status. The approach is illustrated by evaluating 10 hypotheses with two-level and three-level hierarchical linear models using data from the Progress in International Reading Literacy Study 2006. For each hypothesis, the underlying theory, statistical model, and critical model test are presented and the results are discussed. The analytical approach can be generalized to other studies and data sets. The results help to understand how inequalities are configured at the within-country and between-country levels.
eHealth communication and behavior change: promise and performance

Traditional health communication interventions have often failed to show significant changes in people's behaviors. Guidance from social semiotic frameworks suggests that health communication interventions can be improved by incorporating greater participation by the intended audiences of users, paying greater attention to social contexts, and increasing broad use of integrated multimedia dissemination strategies. The use of eHealth communication has great promise to influence behavioral health outcomes, given its enhanced features of interactivity, multimodality, mass customization, and the opportunity for users to also be producers. The first 15 years of scientific evidence about the use of eHealth interventions suggests that, overall, such strategies are gaining rapid acceptance worldwide, improve user engagement, and often show significant positive effects on health behaviors in diverse populations and across a wide range of health conditions. Challenges remain, however, to learn how to best use eHealth communication to improve information access for vulnerable populations, to effectively leverage the power of new media channels, and to discover the longer-term effects of eHealth communication on public health. This article reviews key issues and evidence from eHealth studies and recommends a greater application of strategic semiotic principles in future eHealth communication research and interventions.
Gaining Access to Intrafirm Knowledge: An Internal Market Perspective on Knowledge Sharing

This study explores how account managers—employees who operate as entrepreneurial customer boundary spanners—obtain intrafirm knowledge (organizational and expertise knowledge) from diverse colleagues so as to develop tailor-made solutions for their customers. Access to intrafirm knowledge is obtained through two independent knowledge-based exchanges within internal knowledge markets: account managers invest in different activities in order to signal communal and deal-maker reputations. In exchange, colleagues share organizational and expertise knowledge that ultimately contribute to account managers' performance. The types of knowledge shared by colleagues depend on the reputations of account managers.
Optimal Robot Path Planning with Cellular Neural Network

This paper presents a new methodology based on neural dynamics for optimal robot path planning by drawing an analogy between cellular neural network CNN and path planning of mobile robots. The target activity is treated as an energy source injected into the neural system and is propagated through the local connectivity of cells in the state space by neural dynamics. By formulating the local connectivity of cells as the local interaction of harmonic functions, an improved CNN model is established to propagate the target activity within the state space in the manner of physical heat conduction, which guarantees that the target and obstacles remain at the peak and the bottom of the activity landscape of the neural network. The proposed methodology cannot only generate real-time, smooth, optimal, and collision-free paths without any prior knowledge of the dynamic environment, but it can also easily respond to the real-time changes in dynamic environments. Further, the proposed methodology is parameter-independent and has an appropriate physical meaning.