Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing a Sport Organization: The Impact of Recruiting, Selecting, and Retaining Elite Level Coaches in Sport

Hockey clubs in Edmonton, Alberta, Canada are a fascinating setting to study as they merge issues related to youth sport participation and volunteerism with elite level sport development. We examine the management of elite level hockey clubs, through interviews, to understand how the organizations develop and implement processes that enable them to obtain and maintain a positive reputation through the development of elite level hockey players. The results of our analyses show that hockey clubs view the coach as a vital part of creating and maintaining a successful organizational reputation. This study makes two contributions to the sport management literature; first we extend the literature on recruitment, selecting, and retention to the sport setting by understanding how hockey clubs acquire and retain the services of the most successful and qualified volunteer hockey coaches. Second, we provide a foundation for sport managers, working in a volunteer sport participation environment, to understand how they can compete for a limited pool of successful and qualified coaches.
UVES observations of a damped Ly-alpha system at z_abs = 4.466 towards the quasar APM BR J0307-4945

We present the first high-resolution (6.2 to 7.7 km/s FWHM) spectra of the APM BR J0307-4945 quasar at z_em = 4.73 obtained with UVES on the 8.2m VLT Kueyen telescope. We focus our analysis on a damped Ly-alpha (DLA) system at z_abs = 4.466 with a neutral hydrogen column density N(HI) = (4.68 +/- 0.97) 10^{20} cm^{-2}. It is the most distant DLA system known to the present date, observed when the age of the universe was only 1.3 Gyr. It shows complex low- and high-ionization line profiles spanning ~240 and 300 km/s in velocity space respectively. We derive accurate abundances for N, O, Al, Si and Fe, and place a lower limit on C and an upper limit on Ni: [N/H] = -3.07 +/- 0.15, [O/H] = -1.63 +/- 0.19, [Al/H] = -1.79 +/- 0.11, [Si/H] = -1.54 +/- 0.11, [Fe/H] = -1.97 +/- 0.19, [C/H] > -1.63 and [Ni/H] < -2.35. The derived high metallicity, 1/90 solar, shows that this very young absorber (< 1.3 Gyr) has already experienced a significant metal enrichment. The [O/Si] ratio is nearly solar suggesting a limited amount of dust, the relative [Si,O/Fe] abundance ratios show a similar enhancement as observed in the Milky Way stars with comparable metallicities, and the [N/O] ratio is very low. All these results point to an enrichment pattern dominated by Type II supernovae which suggests a Milky Way type evolutionary model.
Long-Run Abnormal Stock Performance: Some Additional Evidence

In this research we study the specification and the power of classic test statistics used in long-term event studies analysis. Using simulations in random samples, we show that test statistics based on an arbitrary benchmark are well specified and as powerful as the ones based on the size and book-to-market benchmark. However, when conditioning the samples on past stock returns performance, we show that a good matching procedure is required in order to obtain well specified and powerful tests. Finally, we examine the specification and the power of calendar-time portfolios. The crosssectional standardized t-stat is well specified in random samples in which the frequency of the events is random or depends on the past market returns performance. However, when the frequency of events is conditioned on past market returns performance and the stocks are selected among the most extreme returns misspecified test statistics are obtained.
Automatic query expansion based on tag recommendation

We here propose a new method for expanding entity related queries that automatically filters, weights and ranks candidate expasion terms extracted from Wikipedia articles related to the original query. Our method is based on state-of-the-art tag recommendation methods that exploit heuristic metrics to estimate the descriptive capacity of a given term. Originally proposed for the context of tags, we here apply these recommendation methods to weight and rank terms extracted from multiple fields of Wikipedia articles according to their relevance for the article. We evaluate our method comparing it against three state-of-the-art baselines in three collections. Our results indicate that our method outperforms all baselines in all collections, with relative gains in MAP of up to 14% against the best ones.
Development of a support group using a virtual space for cancer patients

We report findings from a chat log analysis of a support group in which two to five patients and one or two facilitators chatted in a virtual space; weekly sessions lasted 1.5 hrs. each, and we followed them over five years. In the virtual space, participants were represented by avatars with emotional expressions. Chat messages were analysed with a text-mining tool, exploring whether positive emotion words (e.g., 'happy'), medicine-related words (e.g., 'symptoms'), and informational/emotional-support messages (giving and receiving) would increase over time. We found that frequency of positive emotion words increased in Years 1-3 and remained constant thereafter; medical-related words did not increase until Year 5. Support messages increased from Years 1 to 3. Analysis of messages indicated that the patients' and facilitators' conversational roles changed as a sense of community emerged. The virtual support group appeared to promote positive emotions, trust among members, and mutual supportive relationships within the group.
sEMG-based torque estimation for robot-assisted lower limb rehabilitation

sEMG (surface electromyography) signals have been used as human-machine interface to control robots or prostheses in recent years. sEMG-based torque estimation is a widely research methodology to obtain human motion intention. Most researches focus on improving the accuracy of sEMG-torque models, which often makes them complicated and confined in the laboratory research. However, an accurate estimation of muscle torque could be unnecessary to perform the robot-assisted rehabilitation training. This paper proposes a practical method to estimate the net muscle torques of lower limbs using sEMG, which can be used to implement a real-time coordinated active training with iLeg-a horizontal exoskeleton for lower limb rehabilitation developed at our laboratory. Two three-layer back propagation (BP) neural networks are built to estimate the net muscle torques at hip and knee joints respectively. Experimental results show that the well-trained neural networks estimate the user's motion intention in real-time, and can assist the user to perform an active training with iLeg.
MIRROR NEURONS: TESTS AND TESTABILITY

Commentators have tended to focus on the conceptual framework of our article, the contrast between genetic and associative accounts of mirror neurons, and to challenge it with additional possibilities rather than empirical data. This makes the empirically focused comments especially valuable. The mirror neuron debate is replete with ideas; what it needs now are system-level theories and careful experiments – tests and testability.
Recent improvements in topology and shape optimisation and the integration into the virtual product development process

Due to the demand to decrease the time-to-market of new products while maintaining a high quality level and reducing overall product development costs, structural optimisation tools have become of significant importance in the virtual product development process. These tools like topology and shape optimisation have reached wide spread acceptance as stand-alone applications in the CAE environment, but a closer integration in the product development chain is still desirable. To achieve this, FE-Design is leader of a subproject with industry partners like Porsche, Audi, Bosch and Keiper within the German research project “Integrated Virtual Product Creation”.
Combining Laplacian eigenmaps and vesselness filters for vessel segmentation in X-ray angiography

Automatic vessel outline delineation from X-ray angiography is highly useful to cardiologists during interventional procedures, especially to measure clinical indices such as vessel diameters, perimeters and areas. The challenges of obtaining a fully automatic segmentation are plentiful: radiographic noise, irregular injection of contrast agent, vessel overlap, etc. While vesselness filters were proposed to detect probable vessel-like shapes, such techniques often fail to recover prominent vessels in a cluttered background, and may obtain irregular shapes when artifacts are present. In this study, we propose a novel approach to segment vessel-like structures, which combines vesselness filters and Laplacian eigenmaps. Our technique finds automatically a global optimum solution for the image segmentation problem. By using both vesselness and Laplacian features, this approach can recognize vessel-like shapes in the background, while preserving the regularity of the extracted shapes. A visual and quantitative evaluation of the proposed approach, on both simulated images and pediatric patient X-ray angiography data, demonstrates its usefulness and efficiency.
Using Virtual Reality to Analyze Sports Performance

Improving performance in sports can be difficult because many biomechanical, physiological, and psychological factors come into play during competition. A better understanding of the perception-action loop employed by athletes is necessary. This requires isolating contributing factors to determine their role in player performance. Because of its inherent limitations, video playback doesn't permit such in-depth analysis. Interactive, immersive virtual reality (VR) can overcome these limitations and foster a better understanding of sports performance from a behavioral-neuroscience perspective. Two case studies using VR technology and a sophisticated animation engine demonstrate how to use information from visual displays to inform a player's future course of action.
Food Intakes by Preschool Children in Flanders Compared with Dietary Guidelines

The objective of this study was to compare food group intakes among preschool children with food-based dietary guidelines (FBDG) and to determine the proportion of children meeting these guidelines. Food consumption of preschool children (2.5–6.5 years) living in Flanders (Belgium) were assessed in a cross-sectional study, using proxy reported 3d estimated dietary records (EDR) (n 696). Statistical modelling was used to account for within-individual variation in the 3d EDR. Mean daily intakes of most food groups (beverages, vegetables, fruit and milk) were below the minimum recommendations. Only ‘grains and potatoes’ and ‘meat products’ were in line with the recommendations and ‘bread and cereals’ showed borderline intakes. Mean intakes of energy-dense and low-nutritious foods, which are discouraged within a healthy diet (like snacks and sugared drinks), were high. Furthermore, the percentage of children complying with the different food-based dietary guidelines was for most food groups extremely low (ranging from approximately 4% for fluid and vegetable intakes up to 99% for potato intakes). Boys had in general higher mean intakes of the recommended food groups. In conclusion, preschool children in Flanders follow eating patterns that do not meet Flemish FBDG. Although the impact of these eating habits on preschooler’s current and future health should be further investigated, it is clear that nutrition education and intervention are needed among preschool children and their parents in Flanders.
Advanced virtual humanoid animation framework based on the MPEG-4 SNHC standard

The ISO/IEC 14496 standard issued in December 2000 specifies a normative framework and a set of tools to animate virtual avatar. Efficiency of such a standardized face and human body description and animation has been widely demonstrated all along the standardization process [1] and more recently in specific applications developed and implemented by several companies [2], [3]. However, achieving realistic animations requires a lot of efforts during the modeling stage, specifically for accurately and efficiently handling 3D object deformations. As all the animation parameters have to be explicitly defined and transmitted for each frame, such a flexibility as instantiating and transmitting only key frame animation parameters, is not supported. In addition, a high level animation description, as provided by a gesture analysis system [4], [5], involving a subset of the animation parameters cannot be specified within the standard.
"The Returns to Attending a Prestigious Law School." Working Paper, 2009.

We measure the returns to attending a highly ranked law school using the “After the JD” survey of lawyers …rst passing the Bar Exam in 2000. In 2002 and 2007, those lawyers that went to top 10 law schools made, on average, 25% more than those that went to schools ranked 11-20 and over 50% more than those that went to schools ranked 21-100. Graduates of Top 10 schools were also much more likely to work in large law …rms in leading law markets. We use two methods to assess the degree of selection in the law school prestige premium – the methods developed by Altonji, Elder, and Taber (2005), who focus on the relationship between observable and unobservable variables, and propensity score matching. We …nd that at least a third of the large returns to law school reputation are due to selection, but this selection is almost entirely on a single variable –quality of the undergraduate institution attended. Selection on other background characteristics is trivial. Whatever unobservables lead to selection into top undergraduate schools may also lead to selection into top law schools. Our results are consistent
Cultivating the Appearance of Neutrality : Autocratic Propaganda in Africa and Asia ∗

How do autocrats manipulate the beliefs of their citizens during political crises? We argue that they cultivate a reputation for neutrality so that, during moments of crisis, their proregime arguments have some measure of credibility. To test the argument, we employ a corpus of 24 state-affiliated newspapers from Africa and Asia. Using a differences-in-differences estimation strategy, we find that propaganda in autocracies is generally indistinguishable from state-affiliated newspapers in democracies, save for the 15 days prior to an election, when positive coverage of the autocrat and the ruling party triples. This increase, we show, is driven not by more effusive articles, but an increase in the share of articles about the regime. Consequently, the aggregate volume of pro-regime coverage increases, but the per article positive coverage does not. By contrast, autocratic propaganda generally avoids defaming the opposition. State-affiliated newspapers in democracies exhibit generally neutral coverage.
On the Stability Region of Two-User Slotted ALOHA with Cooperative Relays

In this work, we analyze the stability region of the slotted ALOHA random access network with cooperative users. With cooperation, the packets corresponding to each user can be transmitted to the destination through the multiple relaying paths formed by the other users. The diversity introduced by the multi-path relaying reduces significantly the probability of outage. We propose two queuing strategies for the cooperative system. In the first strategy, we assume that each user is equipped with two buffers: a source buffer, to record its own packets, and the relay buffer, to store the packets received from its partner. When both buffers are non-empty, the user chooses randomly among the two buffers based on a predetermined probability. An inner bound of the stability region is derived and is shown to outperform the non-cooperative system. In the second case, we assume that each user utilizes only one buffer to store all packets. The relaying packets are stored at the front of the queue at the cooperative user upon arrival. The second scheme outperforms the non-cooperative case only for certain channel conditions and arrival rates. However, the scheme has low complexity and can be implemented with little changes to the original system.
AN ANT COLONY OPTIMIZATION METHOD WITH LOCAL SEARCH FOR STABILITY ANALYSIS OF LINEAR TIME-INVARIANT TIME-DELAY SYSTEMS

A hybrid search method based on Ant Colony Optimization for Continuous Domains ( ACO (cid:92) ) and the Nelder-Mead Simplex algorithm is proposed to calculate the stability margin of linear time-invariant time-delay systems. The effectiveness of the Nelder-Mead Simplex procedure is combined with the global search power of the ACO (cid:92) method to obtain the stability margin of linear time-invariant time-delay systems. Also, the problem is formulated in a way that results in a constant-dimension search space (the complex plane) regardless of the order of the system. Simulation results indicate successful assessment of stability for the systems under examination.
The Problem of Limited Inter-rater Agreement in Modelling Music Similarity

One of the central goals of Music Information Retrieval (MIR) is the quantification of similarity between or within pieces of music. These quantitative relations should mirror the human perception of music similarity, which is however highly subjective with low inter-rater agreement. Unfortunately this principal problem has been given little attention in MIR so far. Since it is not meaningful to have computational models that go beyond the level of human agreement, these levels of inter-rater agreement present a natural upper bound for any algorithmic approach. We will illustrate this fundamental problem in the evaluation of MIR systems using results from two typical application scenarios: (i) modelling of music similarity between pieces of music; (ii) music structure analysis within pieces of music. For both applications, we derive upper bounds of performance which are due to the limited inter-rater agreement. We compare these upper bounds to the performance of state-of-the-art MIR systems and show how the upper bounds prevent further progress in developing better MIR systems.
How Arts Integration Has Helped K–2 Teachers to Boost the Language Development of English-Language Learners

This study looks at the impact of a cost-effective professional development model in which teaching artists helped early elementary teachers master arts-based strategies for boosting the oral language development of English-language learners (ELLs). Teaching artists visited K–2 classrooms for 50 minutes weekly for 28 weeks. Student scores on the listening and speaking sections of the California English Language Development Test were used to determine the impact on language development. The experimental group consisted of 267 students; the comparison group consisted of 2,981 students. The analysis of the listening and speaking scores, fall 2010 to fall 2011, showed significantly more improvement for students in the experimental group. This research has implications for school leaders who, in times of tight budgets, seek professional development opportunities that can assist teachers in addressing the language development needs of English-language learners.
Euclidean-space measures of robotic joint failures

Robotic joint failures are directly characterized and measured in joint space. A locking failure, for example, is one for which a joint cannot move, and it gives an error equal to the desired value minus the locked value. This article extends the joint-space characterization to Euclidean space by measuring a failure's effect there. The approach is based on a primitive measure of point error that can be defined to be distance or path length. It is used to form comprehensive measures through weighted integration over Euclidean-space regions. For kinematically redundant manipulators, minimizing the measures can be used to induce failure tolerance by either reducing the likelihood of collision-induced damage before a failure or reducing end-effector error after a failure. Examples for both cases are given.
Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System

A key part of effective teaching is adaptively selecting pedagogical activities to maximize long term student learning. In this poster we report on ongoing work to both develop a tutoring strategy that leverages insights from the partially observable Markov decision process (POMDP) framework to improve problem selection relative to state-of-the-art intelligent tutoring systems, and evaluate the computed strategy in the classroom. We also highlight some of the challenges in data mining related to automatically constructing pedagogical strategies.
Cylindrical Homomorphisms and Lawson Homology

We use the cylindrical homomorphism and a geometric construction introduced by J. Lewis to study the Lawson homology groups of certain hypersurfaces $X\subset \mathbb{P}^{n+1}$ of degree $d\leq n+1$. As an application, we compute the rational semi-topological K-theory of a generic cubic of dimension 5, 6 and 8 and, using the Bloch-Kato conjecture, we prove Suslin's conjecture for these varieties. Using the generic cubic sevenfolds, we show that there are smooth projective varieties with the lowest non-trivial step in their s-filtration infinitely generated and undetected by the Abel-Jacobi map.
Energy Efficient Object Tracking in Sensor Networks by Mining Temporal Moving Patterns

Object tracking sensor networks (OTSNs) have received extensive attentions for researches in recent years due to the wide applications. One important research issue in OTSNs is the energy saving strategy in considering the limited power of sensor nodes. The past studies on energy saving in OTSNs usually considered the movement behavior of objects as randomness. However, in some real applications, the object movement behavior often carries certain patterns instead of randomness completely. In this paper, we propose an efficient data mining algorithm named TMP-Mine with a special data structure named TMP-Tree for efficiently discovering the temporal movement patterns of objects in sensor networks. Moreover, we propose novel location prediction strategies that employ the discovered temporal movement patterns so as to reduce the prediction errors for energy saving. Through empirical evaluation on simulated, TMP-Mine and the proposed prediction strategies are shown to deliver excellent performance in terms of scalability, accuracy and energy efficiency.
A survey on sentence fusion techniques of abstractive text summarization

Sentence fusion is one of the tasks of automatic text summarization that has wide spread applications in the field of computer science. It is currently used in automatic text summarization and question answering systems. It is also used in natural language generation systems in the name of sentence aggregation. The task of sentence fusion poses various challenges like deciding whether two sentences can be combined or not, which part of a sentence should be selected for combination, how these parts can be combined and how to fit the combinations in a grammatically correct sentence structure. In this paper we discuss about the research done on sentence fusion and various challenges that are yet to be met. Index Terms─ Automatic text summarization, Abstractive text summarization, Natural language processing, Sentence fusion.