Miracle-dz/UniFAR-FTUs huggingface dataset:
A new perspective to the keepaway soccer: the takers

Keepaway is a sub-problem of RoboCup Soccer Simulator in which 'the keepers' try to maintain the possession of the ball, while 'the takers' try to steal the ball or force it out of bounds. By using Reinforcement Learning as a learning method, a lot of research has been done in this domain. In these works, there has been a remarkable success for the intelligent keepers part, however most of these keepers are trained and tested against simple hand-coded takers. We tried to address this part of the problem by using Sarsa(λ) as a Reinforcement Learning method with linear tile-coding as function approximation and used two different state spaces that we specially designed for the takers. As the results of the experiments confirm, we outperformed the hand-coded taker which results in creating a better trainer and tester for the keepers. Also when designing the new state space, we noticed that smaller state spaces can also be successful for this part of the problem.
Study on ellipse fitting problem for vision-based autonomous landing of an UAV

In this paper, we studied for the ellipse fitting problem when an unmanned aerial vehicle (UAV) reaches near a landing marker for vision-based autonomous landing. Due to limited field of view of a camera, the entire shape of the landing marker cannot be captured as the vehicle approaches it. Also, depending on the vehicle's pose, the shape of the maker is shown distortedly. In order to overcome these problems, we designed the novel landing marker using concentric circles and the letter `H'. By calculating the conic parameters from portions of ellipse curves, we can estimate accurate relative navigation for the precise autonomous landing. Several basic image processing algorithms are employed to find the ellipse curves before estimating the ellipse parameters and the center of the marker using the direct least square method. From indoor experiments, we analyzed the ellipse fitting performance based on well-fitted and ill-fitted ellipses. Additionally, we studied how we can improve the ill-fitted case.
Prioritized inverse kinematics using QR and cholesky decompositions

This paper proposes new methods for the prioritized inverse kinematics (PIK) by using the QR decomposition (QRD) and the Cholesky decomposition (CLD) on the purpose of separation between orthogonalization and inversion processes that are essential parts of the PIK. The distinctive approach eliminates the interference between two processes which usually induces inaccuracy and sometimes instability on the prioritized inverse solutions. Two degenerate properties of using the QRD are explained and the remedies are provided as the modified damped least-squares pseudoinverse and the numerical reconditioning. The effectiveness are examined by the kinematic simulations with the n-link manipulators in the two-dimensional case and the KUKA LWR in the three-dimensional case.
Enhanced early developmental expression of the metabotropic glutamate receptor mGluR5 in rat brain: Protein, mRNA splice variants, and regional distribution

Glutamate stimulates phosphatidyl inositol hydrolysis and mobilizes intracellular calcium through the mediation of metabotropic glutamate receptors (mGluRs), in particular the “Group I” receptors mGluRs, mGluR1, and mGluR5. This activity is markedly enhanced in developing brain relative to the adult. To determine whether this may be due to an increased amount of mGluR5 present in the developing brain, we examined mGluR5 expression using western blotting to measure mGluR5 protein, reverse transcription polymerase chain reaction (RT‐PCR) to measure mGluR5 mRNA, and immunocytochemistry to assess the regional distribution of mGluR5 morphologically. Western blotting revealed that in all brain regions examined there is more mGluR5 protein present in developing brain than in the adult. In most regions, the developmental decrease was over two‐fold. Total mGluR5 mRNA also decreased with development in most regions, but to a much lesser extent than the protein, suggesting that there is considerable post‐transcriptional regulation of the expression of this receptor. RT‐PCR analysis also demonstrated that in most regions the mGluR5a splice variant is most abundant in the young animals but mGluR5b predominates in the adult. Light microscopic immunocytochemistry indicated that expression is widespread in developing brain, and that the developmental decrease in receptor concentration is due to both an increased growth of receptor‐poor tissue regions and decreased expression within receptor‐rich regions. © 1996 Wiley‐Liss, Inc.
Information architecture

This paper introduces to the field of information architecture. It starts with an problem oriented view on cognitive overload followed by a short introduction and definition of information architecture. I will describe different types of user information seeking behavior to understand how an information architecture must support information retrieval. A short introduction into a user centered development process of an effective information architecture follows. The main part of this paper discusses the components of information architecture, how organization, labeling and navigation systems are set up. Further components such as search system and controlled vocabularies for an semantic search are described. This paper finishes with an short outlook on the implications of a Next-Generation-User-Centered-InformationManagement to information architecture.
A randomized, double‐blind, placebo‐controlled, dose‐escalation first‐in‐man study (phase 0) to assess the safety and efficacy of topical cytosolic phospholipase A2 inhibitor, AVX001, in patients with mild to moderate plaque psoriasis

Cytosolic phospholipase A2 (cPLA2α) is an enzyme suggested as a therapeutic target in inflammatory skin diseases. AVX001, a cPLA2α inhibitor, was investigated in a randomized, double‐blind, placebo‐controlled, split‐design, first‐in‐man study in patients with mild to moderate psoriasis.
Salivary Testosterone and Cortisol Responses to Cycle Ergometry in Basketball Players with Different Training Volume

Abstract This study analyzes the degree to which different amounts of training during a 4-month period affects salivary testosterone (Tsal), salivary cortisol (Csal) responses, and changes in the salivary testosterone/cortisol ratio (Tsal/Csal ratio) following acute physical effort. Two professional basketball teams with similar fitness levels carried out a maximal cycle ergometry at the beginning and in the middle of the sports season. In both sessions, saliva samples were collected to determine Tsal and Csal, and mood was assessed. Training was registered daily, total training volume being almost two-fold higher in Team 1 than in Team 2. No significant differences between the teams in anthropometric characteristics, mood, or cycle ergometer performance were found. The Tsal/Csal ratio response to ergometry decreased after training in Team 1 and increased in Team 2, whereas Tsal response did not change significantly and the Csal response to ergometry increased in Team 1 and decreased in Team 2. Results ob.
An Analysis of Clique Formation and Structure in Organizations.

The organizational literature has long acknowledged the effects of various formal organizational variables on informal structure. Nevertheless, very few systematic and empirically testable propositions have been formulated specifying relationships in this area. In this article a number of testable propositions are developed which relate the variables of compliance, mobility and size to motivation for clique formation and to constraints within which cliques form. A typology of five clique types (1) coercive cliques, (2) normative cliques, (3) high-mobility utilitarian cliques, (4) seniority utilitarian cliques, and (5) no-mobility utilitarian cliques, is discussed.
An Efficient Learning Based Smartphone Playback Attack Detection Using GMM Supervector

Playback attack detection (PAD) is essentially a binary classification task which is used to identify the authentic recordings from the playback recordings. For PAD problem, the difference of the acoustic feature between the authentic and playback recordings mainly comes from the recording channel and the ambient noise. Motivated by the excellent performance of the Gaussian Mixture Model-Universal Background Model (GMM-UBM) in modeling the characteristics of speaker and the GMM supervector (GSV) in characterizing speech utterances, this paper proposes an efficient learning based smartphone PAD system using the GSV feature and kernel support vector machine (SVM) (termed as GSV-SVM-PAD). To facilitate the performance of our proposed PAD system, a playback attack detection database (PADD) is designed where more than 14,000 utterances of 100 speakers have been recorded. Extensive experimental results show that the proposed GSV-SVM-PAD system offers a great performance and the lowest number of error classification (NEC) with the increasing tested speakers and utterances. Besides, the NEC of GSV-SVM-PAD is even less than 5 when 7694 utterances of 100 speakers are tested.
Growing neural network for acquisition of 2-layer structure

Neural networks are broadly used to approximate non-linear functions. However, it is difficult to decide an appropriate structure for a given problem. In this paper, "growing neural network" is proposed as an extension of backpropagation (BP) learning. The propagated error signal is diffused from a target neuron as a substance. The axon of a growing neuron grows according to the concentration gradient of the substance. In a simulation, it was examined that the simplest problems, "AND" and "OR", could be solved by the neural network and 2-layer structure was properly obtained.
Decay of Correlations for Sparse Graph Error Correcting Codes

The subject of this paper is transmission over a general class of binary-input memoryless symmetric channels using error correcting codes based on sparse graphs, namely, low-density generator-matrix and low-density parity-check codes. The optimal (or ideal) decoder based on the posterior measure over the code-bits and its relationship to the suboptimal belief propagation decoder are investigated. We consider the correlation (or covariance) between two code-bits, averaged over the noise realizations, as a function of the graph distance for the optimal decoder. Our main result is that this correlation decays exponentially fast for given low-density generator-matrix codes and a high enough noise parameter and also for given low-density parity-check codes and a low enough noise parameter. This has many consequences. Appropriate performance curves—called generalized extrinsic information transfer (GEXIT) functions—of the belief propagation and optimal decoders match in high/low noise regimes. This means that i.
Very Large-Scale Integrated Processor

Many-core processors are designed for improving thread-level parallelism (TLP) across the cores and for keeping instruction-level parallelism (ILP) in each core. However, each application has its own characteristic TLP and ILP. Therefore, a "pre-fabricated" chip multiprocessor (CMP) cannot tolerate a wide range of applications. Recent works attempted to reconfigure the CMP in order to fit the processor to the applications. This paper proposes a scalable processor that is able to up scale and down scale the data path of the adaptive processor. The scaling is based on a chaining interconnection networks between segments. The adaptive processor uses a linear topology to form a stack structure. In order to map the array to a two-dimensional array, a new topology, which we call an S-topology which scales well is also proposed. We assessed costs in terms of area and delay on the S-topology applied to the adaptive processor, and peak performances.
Symmetry and reduction in collectives: cyclic pursuit strategies

We specify and analyse models that capture the geometry of purposeful motion of a collective of mobile agents, with a focus on planar motion, dyadic strategies and attention graphs which are static, directed and cyclic. Strategies are formulated as constraints on joint shape space and are implemented through feedback laws for the actions of individual agents, here modelled as self-steering particles. By reduction to a labelled shape space (using a redundant parametrization to account for cycle closure constraints) and a further reduction through time rescaling, we characterize various special solutions (relative equilibria and pure shape equilibria) for cyclic pursuit with a constant bearing (CB) strategy. This is accomplished by first proving convergence of the (nonlinear) dynamics to an invariant manifold (the CB pursuit manifold), and then analysing the closed-loop dynamics restricted to the invariant manifold. For illustration, we sketch some low-dimensional examples. This formulation—involving strategies, attention graphs and sensor-driven steering laws—and the resulting templates of collective motion, are part of a broader programme to interpret the mechanisms underlying biological collective motion.
Conceptual frameworks and emancipatory research in social gerontology

It is argued that conflicts arise in social gerontology because conceptual frameworks are not sufficiently developed. Taking a broad definition of conceptual frameworks that includes political awareness, I argue that the theoretical works of Anne Phillips and Nancy Fraser have much to offer when applied to social gerontology. It is, however, essential first to theorise later life in terms of difference and diversity and the potential for conflict between concepts. The main argument is that when researching a devalued group such as elders, the political aspects of research cannot be ignored even when researchers aim to be ‘apolitical’, and that research will be helped by considering the politics of equality under the headings of: universalism and particularism; convergence and recognition; cultural valorisation and redistribution; and redress and transformation. These categories are not completely separate and may overlap. Just as aspects of disadvantage are complex and interact, so are the remedies or theorisations that can be deployed.
Multifaceted analysis of international environmental policy

The systematic analysis of international environmental policy is based on certain methodological and theoretical approaches. In this paper, five of these approaches are considered: the levels, foreign policy, mediation, international regime and structural system approaches. These approaches are seen as com plementary and interlocking elements of an analytical network for conducting methodologically advanced comparative research.
Being a Stepparent: Live-in and Visiting Stepchildren.

Quantitative and qualitative data are presented to document certain aspects of the experience of stepparenting in a subsample of 109 stepparents. A focus is placed on the locale of residence of stepchildren as a variable affecting stepparents' marital life, attachment to stepchildren, and stepchildren 's relationships with stepparents' own children. For this sample, the stepparenting experience, particularly for stepmothers, was a more positive one with live-in stepchildren than with those who live elsewhere. Stepsiblings' relations were also more positive when they lived together rather than visited. The arrival of a child born to the remarried couple had a different impact on the stepparent-stepchild relationship, depending on the gender of the stepparent and the stepchild's locale of residence.
Bifurcation Analysis of Current Coupled BVP oscillators

The Bonhoffer-van der Pol (BVP) oscillator is a simple circuit implementation describing neuronal dynamics. Lately the diffusive coupling structure of neurons attracts much attention since the existence of the gap-junctional coupling has been confirmed in the brain. Such coupling is easily realized by linear resistors for the circuit implementation, however, there are not enough investigations about diffusively coupled BVP oscillators, even a couple of BVP oscillators. We have considered several types of coupling structure between two BVP oscillators, and discussed their dynamical behavior in preceding works. In this paper, we treat a simple structure called current coupling and study their dynamical properties by the bifurcation theory. We investigate various bifurcation phenomena by computing some bifurcation diagrams in two cases, symmetrically and asymmetrically coupled systems. In symmetrically coupled systems, although all internal elements of two oscillators are the same, we obtain in-phase, anti-phase solution and some chaotic attractors. Moreover, we show that two quasi-periodic solutions are disappeared simultaneously by the homoclinic bifurcation on the Poincare map and that a large quasi-periodic solution is generated by the coalescence of these quasi-periodic solutions, but it is disappeared by the heteroclinic bifurcation on the Poincare map. In the other case, we confirm the existence a conspicuous chaotic attractor in the laboratory experiments.
The Relationship Between Spatial Transformations and Iconic Gestures

Current theories of gesture production all suggest that spatial working memory is a critical component of iconic gesture production. However, none of the models has a selection mechanism for what aspect of spatial working memory is gestured. We explored how expert and journeyman scientists gestured while discussing their work. Participants were most likely to make iconic gestures about change over time (spatial transformations), less likely to gesture about spatial relations and locations (geometric relations), and far less likely to gesture about the magnitude of spatial entities. We also found that experts were especially likely to have a high degree of association between iconic gestures and spatial transformations. These results show that different features of spatial language are gestured about at different rates. We suggest that current gesture production models need to be expanded to include selection mechanisms to account for these differences.
Using objects for systems analysis

nated as a programming and software design discipline offering advantages such as reusability, extendibility and portability. Recently, object thinking has been applied extensively to systems analysis [1, 3, 4, 8, 10]. It has even been claimed that “the real payoff (of the object-oriented approach) comes from addressing front-end conceptual issues, rather than back-end implementation issues” [10]. However, in this evolution, programming concepts have crept into some analysis methods. This is demonstrated by statements such as: “Objects serve two purposes: They promote understanding of the real world and provide a practical basis for computer implementation” [10] or “An object is any thing, real or abstract, about which we store data and those methods that manipulate the data” [8]. We believe that improper adaptation of programming concepts has impeded the successful application of object-oriented systems analysis. Systems analysis involves modeling a domain. It is therefore fundamentally different from software design, which is implementation-oriented. According to Kilov and Ross [7], “the library of generic programming concepts is at too low a level for analysis. ” Of course, object-oriented analysis provides input for designing software. Accordingly, software design objectives such as modularity and reuse could be seen as relevant during analysis. We argue, however, that this perspective may interfere with understanding the domain by drawing attention to implementation considerations. This can be detrimental to system success, since “focusing on implementation issues too early . often leads to an inferior product” [10]. By drawing on distinctive models of representation we are able to analyze the role of objects in domain modeling. This method leads to a clearer understanding of various aspects of the OO approach. Using Objects for Systems Analysis
Opportunities and Challenges for Privacy-Preserving Visualization of Electronic Health Record Data

In this paper, we reflect on the use of visualization techniques for analyzing electronic health record data with privacy concerns. Privacy-preserving data visualization is a relatively new area of research compared to the more established research areas of privacy-preserving data publishing and data mining. We describe the opportunities and challenges for privacy-preserving visualization of electronic health record data by analyzing the different disclosure risk types, and vulnerabilities associated with commonly used visualization techniques.
Resisting Sybil Attack By Social Network and Network Clustering

Peer to peer (P2P) systems are extremely vulnerable to Sybil attacks, in which a malicious user controls a large number of Sybil peers to collude to break the system laws. This paper proposes a distributed algorithm, named Sybil Resisting Network Clustering (SRNC), to resist the Sybil attack by preventing honest peers from communicating with Sybil Peers. SRNC is based on a social network model. In this model, honest peers and Sybil peers can be largely classified into two clusters, connected by a small number of edges, called attack edges. SRNC tries to explicitly detect attack edges, and then prohibits the communication over the detected edges. The performance of SRNC is evaluated by theoretical analysis and simulations. In particular, SRNC ensures theoretically that honest peers totally accept O(jAEj) Sybil peers. This is a O(log(n)) times improvement over SybilLimit, one of the conventional representative Sybil resisting algorithms, where n is the number of peers and jAEj is the number of attack edges in the system. The performance is then evaluated by simulations on data sets of real world social networks.
Lexicon Acquisition with a large-coverage unification-based grammar

We describe how unknown lexical entries are processed in a unification-based framework with large-coverage grammars and how from their usage lexical entries are extracted. To keep the time and space usage during parsing within bounds, information from external sources like Part of Speech (PoS) taggers and morphological analysers is taken into account when information is constructed for unknown words.
The relation between alignment covariance and background-averaged epistasis

Epistasis, or the context-dependence of the effects of mutations, limits our ability to predict the functional impact of combinations of mutations, and ultimately our ability to predict evolutionary trajectories. Information about the context-dependence of mutations can essentially be obtained in two ways: First, by experimental measurement the functional effects of combinations of mutations and calculating the epistatic contributions directly, and second, by statistical analysis of the frequencies and co-occurrences of protein residues in a multiple sequence alignment of protein homologs. In this manuscript, we derive the mathematical relationship between epistasis calculated on the basis of functional measurements, and the covariance calculated from a multiple sequence alignment. There is no one-to-one mapping between covariance and epistatic terms: covariance implies epistasis, but epistasis does not necessarily lead to covariance, indicating that covariance in itself is not the directly relevant quantity for functional prediction. Having calculated epistatic contributions from the alignment, we can directly obtain a functional prediction from the alignment statistics by applying a Walsh-Hadamard transform, fully analogous to the transformation that reconstructs functional data from measured epistatic contributions. This embedding into the Hadamard framework is directly relevant for solidifying our theoretical understanding of statistical methods that predict function and three-dimensional structure from natural alignments.