Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge Representation in Learning Classifier Systems: A Review

Knowledge representation is a key component to the success of all rule based systems including learning classifier systems (LCSs). This component brings insight into how to partition the problem space what in turn seeks prominent role in generalization capacity of the system as a whole. Recently, knowledge representation component has received great deal of attention within data mining communities due to its impacts on rule based systems in terms of efficiency and efficacy. The current work is an attempt to find a comprehensive and yet elaborate view into the existing knowledge representation techniques in LCS domain in general and XCS in specific. To achieve the objectives, knowledge representation techniques are grouped into different categories based on the classification approach in which they are incorporated. In each category, the underlying rule representation schema and the format of classifier condition to support the corresponding representation are presented. Furthermore, a precise explanation on the way that each technique partitions the problem space along with the extensive experimental results is provided. To have an elaborated view on the functionality of each technique, a comparative analysis of existing techniques on some conventional problems is provided. We expect this survey to be of interest to the LCS researchers and practitioners since it provides a guideline for choosing a proper knowledge representation technique for a given problem and also opens up new streams of research on this topic.
An Empirical Investigation of the Adversarial Activity Model

Multiagent research provides an extensive literature on formal Belief-Desire-Intention (BDI) based models describing the notions of teamwork and cooperation, but adversarial and competitive relationships have received very little formal BDI treatment. Moreover, one of the main roles of such models is to serve as design guide-lines for the creation of agents, and while there is work illustrating that role in cooperative interaction, there has been no empirical work done to validate competitive BDI models. In this work we use the Adversarial Activity model, a BDI-based model for bounded rational agents that are operating in a general zero-sum environment, as an architectural guideline for building bounded rational agents in two adversarial environments: the Connect-four game (a bilateral environment) and the Risk strategic board game (a multilateral environment). We carry out extensive simulations that illustrate the advantages and limitations of using this model as a design specification.
Automatic Segmentation of Multiparty Dialogue

In this paper, we investigate the problem of automatically predicting segment boundaries in spoken multiparty dialogue. We extend prior work in two ways. We first apply approaches that have been proposed for predicting top-level topic shifts to the problem of identifying subtopic boundaries. We then explore the impact on performance of using ASR output as opposed to human transcription. Examination of the effect of features shows that predicting top-level and predicting subtopic boundaries are two distinct tasks: (1) for predicting subtopic boundaries, the lexical cohesion-based approach alone can achieve competitive results, (2) for predicting top-level boundaries, the machine learning approach that combines lexical-cohesion and conversational features performs best, and (3) conversational cues, such as cue phrases and overlapping speech, are better indicators for the toplevel prediction task. We also find that the transcription errors inevitable in ASR output have a negative impact on models that combine lexical-cohesion and conversational features, but do not change the general preference of approach for the two tasks.
Bulgarian Democracy ’ s Organizational Weapon

63 O ne of the most remarkable—and least celebrated and understood—political stories of the postcommunist region is the relative success of democratization in Bulgaria. Not only has democratization taken place but democracy has taken hold. Bulgaria has avoided the slide toward authoritarianism that occurred in Russia, Ukraine, Belarus, Albania, Armenia, and all the countries of Central Asia in the second half of the 1990s. Explaining Bulgaria's experience is difficult. Most of the usual explanations for success do not work. Bulgaria does not have a hardy democratic tradition. The brand of Sovietism practiced in Bulgaria was similar to that found in the USSR. Dissent was dealt with harshly. In contrast with Hungary or Poland, no substantial political or economic liberalization occurred during the 1970s or 1980s. At the onset of the regime change, Bulgaria was poor even by regional standards, and the economic trauma it endured during the early years of transition was as severe as that experienced by Russia and Ukraine. Neighborhood effects cannot be considered particularly auspicious. Bulgaria shares a long border with Serbia, and Sofia is located close to that border. To its south, Bulgaria is bounded by Greece and Turkey; it is the only country to share a border with both. Bulgaria does not border a West or Central European country. Nor does it have an ethnically homogeneous population. It has a large Turkish minority, geographically concentrated in the south, as well as substantial populations of Roma and Pomaks. The precommunist history of relations between Bulgarians and Turks was bloodier than that between Serbs and the people now called Bosnian Muslims, and relations between the two groups in Bulgaria were much worse during the Soviet era than those between the two groups in Yugoslavia. In short, Bulgaria did not enter the postcommunist era as a leading candidate for robust democratization. Yet democracy came nonetheless, and it appears to be holding, perhaps even deepening. After the beginning of the regime change at the end of the 1980s, Bulgaria did develop one noteworthy asset: an array of reasonably strong political parties. Like Romania and Mongolia, arguably the postcommunist region's two other pleasant surprises in the realm of democratization, Bulgaria has had a relatively high rate of popular participation in parties. Seven percent of voting-age Bulgarians, 12 percent of Romanians, and 20 percent of Mongolians belong to parties. The numbers are all high by post-communist standards and are far greater …
Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games

Partial monitoring games are repeated games where the learner receives feedback that might be different from adversary's move or even the reward gained by the learner. Recently, a general model of combinatorial partial monitoring (CPM) games was proposed \cite{lincombinatorial2014}, where the learner's action space can be exponentially large and adversary samples its moves from a bounded, continuous space, according to a fixed distribution. The paper gave a confidence bound based algorithm (GCB) that achieves $O(T^{2/3}\log T)$ distribution independent and $O(\log T)$ distribution dependent regret bounds. The implementation of their algorithm depends on two separate offline oracles and the distribution dependent regret additionally requires existence of a unique optimal action for the learner. Adopting their CPM model, our first contribution is a Phased Exploration with Greedy Exploitation (PEGE) algorithmic framework for the problem. Different algorithms within the framework achieve $O(T^{2/3}\sqrt{\log T})$ distribution independent and $O(\log^2 T)$ distribution dependent regret respectively. Crucially, our framework needs only the simpler "argmax" oracle from GCB and the distribution dependent regret does not require existence of a unique optimal action. Our second contribution is another algorithm, PEGE2, which combines gap estimation with a PEGE algorithm, to achieve an $O(\log T)$ regret bound, matching the GCB guarantee but removing the dependence on size of the learner's action space. However, like GCB, PEGE2 requires access to both offline oracles and the existence of a unique optimal action. Finally, we discuss how our algorithm can be efficiently applied to a CPM problem of practical interest: namely, online ranking with feedback at the top.
Adaptive developmental plasticity in growing nestlings: sibling competition induces differential gape growth

Sibling competition has been shown to affect overall growth rates in birds. However, growth consists on the coordinated development of a multitude of structures, and there is ample scope for developmental plasticity and trade-offs among these structures. We would expect that the growth of structures that are used in sibling competition, such as the gape of altricial nestlings, should be prioritized under intense competition. We conducted an experiment in the spotless starling (Sturnus unicolor), cross-fostering nestlings to nests with different levels of sibling competition. We predicted that nestlings subjected to higher levels of sibling competition should develop larger gapes than control birds. We found that, halfway through the nestling period, overall size (a composite index of mass, wing, tarsus and bill) was reduced in nests with intense sibling competition, whereas gape width remained unaffected. At the end of the nestling period, experimental nestlings had wider gapes than controls. Additionally, a correlative study showed that nestling gape width increased when feeding conditions worsened and overall size decreased. These patterns could either be due to increased growth of gape flanges or to delayed reabsorption of this structure. Our results show that birds can invest differentially in the development of organs during growth, and that the growth of organs used in sibling competition is prioritized over structural growth.
Slicing object-oriented java programs

This paper presents a new approach to represent dependence for object-oriented (OO) Java software. The program dependence graph (PDG) consists of a set of PDGs with tags that are not connected. This new approach distinguishes data members for different objects and represents the effects of polymorphism and dynamic bindings. Based on this model, we introduce the concepts of partial slicing, class slicing and object slicing. In our slicing algorithm, we slice not only statements but also data members in classes, and inter-method slicings are transformed to intra-method slicings.
Critical analysis of WSD algorithms

Word Sense Disambiguation is the core of many natural language processing (NLP) tasks. WSD is a significant technique and has been an interest and concern for the various researchers from the long time. WSD is considered as a successful technique in the last several years. Though success rate of WSD technique is quiet high it has certain limitation of unavailability of standardized evaluation system. The basic aim of the paper is to investigate the critical aspects of various WSD approaches. The paper will also provide a detail of the success rate of the various approaches and also their usage in various application areas.
Diagnostic Significance of Reduced IgA in Children

Introduction: The finding of reduced value of immunoglobulin A (IgA) in children is frequent in daily medical practice. It is important to correctly interpret the findings as adequate further diagnostic evaluation of the patient in order to make the determination on the significance of such findings. In children younger than 4 years always consider the transient impairment of immunoglobulins, maturation of child and his immune system can lead to an improvement in the clinical picture. In older children decreased IgA may lead to serious illnesses that need to be recognize and acknowledge through the appropriate diagnostic methods. Material and methods: Research was realized at the University Clinical Center Tuzla. Children with suspected deficient immune response due to reduced values of IgA observed and, goes through further diagnostic evaluation at the Polyclinic for Laboratory Medicine, Department of Immunology and Department of Microbiology, as well as the Clinic of Radiology. In the period of year 2013, there were a total of 91 patients with reduced values of IgA, age up to 13 years, of which 55 boys and 36 girls. Results: Our study followed 91 patients, for the year 2013, through their medical charts and made evaluation of diagnostic and screening tests. The significance of this paper is to draw attention to the importance of diagnostic approach to IgA deficient pediatric patient and relevance of knowledge of individual diagnostic methods as well as to the proper interpretation of the results thereof.
Longitudinal Relationships Among Perceived Injunctive and Descriptive Norms and Marijuana Use.

OBJECTIVE The current study uses longitudinal data to examine the relative influence of perceived descriptive and injunctive norms for proximal and distal referents on marijuana use. METHOD Participants were 740 undergraduate students (67% female) who completed web-based surveys at two time points 12 months apart. Time 1 measures included reports of marijuana use, approval, perceived descriptive norms, and perceived injunctive norms for the typical student, close friends, and parents. At Time 2, students reported on their marijuana use. RESULTS Results of a path analysis suggest that, after we controlled for Time 1 marijuana use, greater perceived friend approval indirectly predicted Time 2 marijuana use as mediated by personal approval. Greater perceived parental approval was both indirectly and directly associated with greater marijuana use at follow-up. Perceived typical-student descriptive norms were neither directly nor indirectly related to Time 2 marijuana use. CONCLUSIONS The findings support the role of proximal injunctive norms in predicting college student marijuana use up to 12 months later. The results indicate the potential importance of developing normative interventions that incorporate the social influences of proximal referents.
Alcohol and Tobacco Use Among Undergraduate and Postgraduate Medical Students in India: A Multicentric Cross-sectional Study

Background: Substance use among medical fraternity is a well-known phenomenon among both undergraduate (UG) and postgraduate (PG) medical students. Yet, there have been very few multi-centric studies to estimate the actual burden of this problem in this important population group in India. This study was conducted to estimate the prevalence of alcohol and tobacco use, assess the knowledge and attitudes towards this issue, and identify factors associated with substance use among UG and PG medical students in India. Methods: A pre-tested, self-report, anonymous questionnaire was administered to medical undergraduates and post graduate medical residents of eight medical colleges across India. This study used a convenience sample of medical colleges with random selection of study participants within each college for each group, UG and PG. Results: Prevalence of alcohol and tobacco use among UG students was 16.6%, 95% CI [14.5, 18.9] and 8.0%, 95% CI [6.4, 9.6], respectively, whereas prevalence was 31.5%, 95% CI [26.3, 37.0] and 14.5%, 95% CI [10.7, 18.9], respectively for PGs. For both substances, males had a higher prevalence of use compared to females in both groups (p < 0.001). Positive family history of substance use (p < 0.001 for both groups) and early age of initiation (p = 0.011 for tobacco; p > 0.05 for alcohol) were associated with a greater difficulty to quit the habit. Over 90% of study participants felt that substance use adversely affected their skills and reported not using substances prior to managing their patients. Conclusions: Since substance use is a relatively common phenomenon among UG and PG medical students in India, future prospective studies and interventions are required to better understand the pattern of substance use and reduce its prevalence.
Compact and Broadband CPW-to-RWG Transition Using Stub Resonators

This paper proposes a broadband coplanar waveguide (CPW)-to-rectangular waveguide (RWG) transition using stub resonators. The reflection coefficient of the proposed transition is less than -20 dB in the frequency band ranging from 8.6 to 12.6 GHz, which almost covers the whole X-band (8.2-12.4 GHz). As compared with the miniaturized CPW-to-RWG transition using the inductance-compensated slotline, the reflection coefficient is reduced from -15 to -20 dB and the size is maintained at 8.6 mm. In order to reduce the circuit size, a compact CPW-to-RWG transition using right-angled stub resonators is proposed. The circuit size is reduced from 8.6 to 7.8 mm while the broadband response of the -20-dB reflection coefficient is maintained. In order to verify the simulation results, three back-to-back CPW-to-RWG transitions are fabricated and measured by which the measurement results agree with the simulation results.
Cell-specific synaptic plasticity induced by network oscillations

Gamma rhythms are known to contribute to the process of memory encoding. However, little is known about the underlying mechanisms at the molecular, cellular and network levels. Using local field potential recording in awake behaving mice and concomitant field potential and whole-cell recordings in slice preparations we found that gamma rhythms lead to activity-dependent modification of hippocampal networks, including alterations in sharp wave-ripple complexes. Network plasticity, expressed as long-lasting increases in sharp wave-associated synaptic currents, exhibits enhanced excitatory synaptic strength in pyramidal cells that is induced postsynaptically and depends on metabotropic glutamate receptor-5 activation. In sharp contrast, alteration of inhibitory synaptic strength is independent of postsynaptic activation and less pronounced. Further, we found a cell type-specific, directionally biased synaptic plasticity of two major types of GABAergic cells, parvalbumin- and cholecystokinin-expressing interneurons. Thus, we propose that gamma frequency oscillations represent a network state that introduces long-lasting synaptic plasticity in a cell-specific manner. DOI: http://dx.doi. org/10.7554/eLife.14912. 001
Small World Network Based World Representation for Scalable Reinforcement Learning

The curse of dimensionality plagues practical uses of reinforcement learning. Temporal abstraction approaches have been proposed to overcome this problem, but typically they require a priori design of the hierarchy and lack the compact representation needed for large sized problems, so their practical uses are still limited. Inspired by recent research in complex networks, we present a compact selforganizing, growing network for world representation to scale up reinforcement learning. Continuous state space is represented with a compact self-organizing network, and the network is augmented to have small world property without a priori knowledge. Experimental results with various problem sizes show that the average path length between nodes of this network scales subpolynomially with the size of the network, and the convergence of reinforcement learning is accelerated significantly.
An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images

We have developed an algorithm for the rigid-body registration of a CT volume to a set of C-arm images. The algorithm uses a gradient-based iterative minimization of a least-squares measure of dissimilarity between the C-arm images and projections of the CT volume. To compute projections, we use a novel method for fast integration of the volume along rays. To improve robustness and speed, we take advantage of a coarse-to-fine processing of the volume/image pyramids. To compute the projections of the volume, the gradient of the dissimilarity measure, and the multiresolution data pyramids, we use a continuous image/volume model based on cubic B-splines, which ensures a high interpolation accuracy and a gradient of the dissimilarity measure that is well defined everywhere. We show the performance of our algorithm on a human spine phantom, where the true alignment is determined using a set of fiducial markers.
Tokamak burn cycle study: a data base for comparing long pulse and steady-state power reactors

Several distinct operating modes (conventional ohmic, noninductive steady state, internal transformer, etc.) have been proposed for tokamaks. Our study focuses on capital costs and lifetime limitations of reactor subsystems in an attempt to quantify sensitivity to pulsed operation. Major problem areas considered include: thermal fatigue on first wall, limiter/divertor; thermal energy storage; fatigue and eddy current heating in toroidal field coils; electric power supply costs; and noninductive driver costs. We assume a high availability and low cost of energy will be mandatory for a commercial fusion reactor, and we characterize improvements in physics (current drive efficiency) and engineering (superior materials) which will help achieve these goals for different burn cycles.
Resveratrol and Ophthalmic Diseases

Resveratrol, a naturally occurring plant polyphenol found in grapes, is the principal biologically active component in red wine. Clinical studies have shown that resveratrol due to its potent anti-oxidant and anti-inflammatory properties are cardio-protective, chemotherapeutic, neuroprotective, and display anti-aging effects. Oxidative stress and inflammation play a critical role in the initiation and progression of age-related ocular diseases (glaucoma, cataract, diabetic retinopathy and macular degeneration) that lead to progressive loss of vision and blindness. In vitro and in vivo (animal model) experimental studies performed so far have provided evidence for the biological effects of resveratrol on numerous pathways including oxidative stress, inflammation, mitochondrial dysfunction, apoptosis, pro-survival or angiogenesis that are implicated in the pathogenesis of these age-related ocular disorders. In this review, we provide a brief overview of current scientific literature on resveratrol, its plausible mechanism(s) of action, its potential use and current limitations as a nutritional therapeutic intervention in the eye and its related disorders.
Effects of low-chloride solutions on action potentials of sheep cadiac purkinje fibers

The rapid repolarization during phase 1 of the action potential of sheep cardiac purkinje fibers has been attributed to a time- and voltage-dependent chloride current. In part, this conclusion was based on experiments that showed a substantial slowing of phase 1 when larger, presumably impermeant, anions were substituted for chloride in tyrode’s solution. We have re- examined the electrical effects of low-chloride solutions. We recorded action potentials of sheep cardiac purkinje fibers in normal tyrode’s solution and in low-chloride solutions made by substituting sodium propionate, acetylglycinate, methylsulfate, or methanesulfonate for the NaCl of Tyrode’s solution. Total calcium was adjusted to keep calcium ion activity of test solutions equal to that of control solutions. Propionate gave qualitatively variable results in preliminary experiments; it was not tested further. Low-chloride solutions made with the other anions gave much more consistent results: phase 1 and the notch that often occurs between phases 1 and 2 were usually unaffected, and the action potential duration usually increased. The only apparent change in the resting potential was a transient 3-6 mV depolarization when low-chloride solution was first admitted to the chamber, and a symmetrical transient hyperpolarization when chloride was returned to normal. If a time- and voltage-dependent chloride current exists in sheep cardiac purkinje fibers, our results suggest that it plays little role in generating phase 1 of the action potential.