Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the finite-length performance of generalized LDPC codes

In this paper, we analyze the performance of finite-length generalized LDPC (GLDPC) block codes constructed from protographs when transmission takes place over the binary erasure channel (BEC). A generalized peeling decoder is proposed and we derive a system of differential equations that gives the expected evolution of the graph degree distribution during decoding. We then show that the finite-length performance of a GLDPC code can be estimated by means of a simple scaling law, where a single scaling parameter represents the finite-length properties of the code. We also show that, as we consider stronger component codes, both the asymptotic threshold and the finite-length scaling parameter are improved.
Enhancing reality in the operating room

Three dimensional computer models of the anatomy generated from volume acquisitions of computed tomography and magnetic resonance imaging are useful adjuncts to 2D images. This paper describes a system that merges the computer generated 3D models with live video to enhance the surgeon's understanding of the anatomy beneath the surface. The system can be used as a planning aid before the operation and provide additional information during an operation. The application of the system to a brain operation is described. <<ETX>>
An Efficient Algorithm for Partially Matched Web Services Based on Consumer's QoS Requirements

With the fast growing number of web services and consumers, selecting a suitable service for the consumer is becoming a crucial issue. Quality of Service (QoS) plays a significant role for both service and consumer in determining requirements. A number of models have been proposed for service selection by considering QoS parameters. In this paper we propose a service selection algorithm by considering multiple consumer criteria and allowing partially matched services to be counted as a candidate for the selection process. Based on consumer criteria, the algorithm returns a list of recommended services. Experimental results from real world web services shows our algorithm has a significant improvement in the quality of recommended web services.
Derivative-Free Optimization of Expensive Functions with Computational Error Using Weighted Regression

We propose a derivative-free algorithm for optimizing computationally expensive functions with computational error. The algorithm is based on the trust region regression method by Conn, Scheinberg, and Vicente [A. R. Conn, K. Scheinberg, and L. N. Vicente, IMA J. Numer. Anal. , 28 (2008), pp. 721--748] but uses weighted regression to obtain more accurate model functions at each trust region iteration. A heuristic weighting scheme is proposed that simultaneously handles (i) differing levels of uncertainty in function evaluations and (ii) errors induced by poor model fidelity. We also extend the theory of $\Lambda$-poisedness and strong $\Lambda$-poisedness to weighted regression. We report computational results comparing interpolation, regression, and weighted regression methods on a collection of benchmark problems. Weighted regression appears to outperform interpolation and regression models on nondifferentiable functions and functions with deterministic noise.
Two algorithms for general list matrix partitions

List matrix partitions are restricted binary list constraint satisfaction problems which generalize list homomorphisms and many graph partition problems arising, e.g., in the study of perfect graphs. Most of the existing algorithms apply to concrete small matrices, i.e., to partitions into a small number of parts. We focus on two general classes of partition problems, provide algorithms for their solution, and discuss their implications.The first is an <i>O</i>(<i>n</i><sup>r+2</sup>)-algorithm for the list <i>M-</i>partition problem where <i>M</i> is any <i>r</i> by <i>r</i> matrix over subsets of {0, 1}, which has the "bisplit property". This algorithm can be applied to recognize so-called <i>k</i>-bisplit graphs in polynomial time, yielding a solution of an open problem from [2]. The second is an algorithm running in time (<i>rn</i>)<sup><i>O</i>(log <i>r</i> log <i>n</i>/log log <i>n</i>)</sup><i>n</i><sup><i>O</i></sup>(log<sup>2</sup><i>r</i>) for the list <i>M</i>-partition problem where <i>M</i> is any <i>r × r</i> matrix over subsets of {0,1,. ,<i>q</i>- 1}, with the "incomplete property". This algorithm applies to all non-NP-complete list <i>M</i>-partition problems with <i>r</i> = 3, and it improves the running time of the quasi-polynomial algorithm for the "stubborn problem" from [5], and for the "edge-free three-coloring problem" from [12].
Movement, Gesture, and Meaning: A Sensiromotor Model for Audience Engagement with Dance

Philosophers of art draw a distinction between two broad sets of concerns: questions about aesthetic responses to artworks and questions about interpretation, including questions about the formal strategies artists use to express emotions and ideas. Recent research in philosophy and neuroscience addresses the nature of aesthetic responses to dance, suggesting that they are embodied, grounded in the human mirror system and action observation network, and involve either some form of tacit motor simulation (Calvo-Merino et al 2008) or proprioceptive sensibility (Montero, 2006). Recent literature does not address interpretative responses to dance. However, a model for the way that dance is used to express emotions and ideas can be derived from the literature on aesthetic response. Langer (1953) and Beardsley (1982) argued that dance is a gestural language in which ordinary movements are used as “virtual gestures” to express the intentions of choreographers and dancers (e.g., the ideas and emotions constitutive of the content of a dance). Recent discussions suggest that areas of the premotor and parietal cortices associated with the action observation network play a significant role in our capacity to recognize and understand the intentions (Gallese & Goldman, 1998; Hamilton & Grafton, 2006) and emotional states (Carr et al, 2003; Iacoboni & Dapretto, 2006) of others. In this paper I propose a sensiromotor model for interpretive responses to dance which integrates Langer and Beardsley’s intuitions about the role of gesture in dance with discussions of the role played by the action observation network in social cognition.
Developmental Perspectives on Nutrition and Obesity From Gestation to Adolescence

Obesity results from a complex combination of factors that act at many stages throughout a person's life. Therefore, examining childhood nutrition and obesity from a developmental perspective is warranted. A developmental perspective recognizes the cumulative effects of factors that contribute to eating behavior and obesity, including biological and socioenvironmental factors that are relevant at different stages of development. A developmental perspective considers family, school, and community context. During gestation, risk factors for obesity include maternal diet, overweight, and smoking. In early childhood, feeding practices, taste acquisition, and eating in the absence of hunger must be considered. As children become more independent during middle childhood and adolescence, school nutrition, food marketing, and social networks become focal points for obesity prevention or intervention. Combining a multilevel approach with a developmental perspective can inform more effective and sustainable strategies for obesity prevention.
Mutual coupling effects on the capacity of multielement antenna systems

A study of the capacity of multiple element antenna systems is presented, with particular emphasis on the effect that mutual coupling between the antenna elements has on the capacity. The results presented here show, contrary to some earlier claims, that correlation between different channel coefficients as a function of antenna spacing, can in fact decrease when the mutual coupling effect is accounted for. As a consequence, capacity also improves. A realistic channel model is used to perform simulations to support these claims.
A biologically inspired navigation concept based on the Landmark-Tree map for efficient long-distance robot navigation

Graphical Abstract Map-based navigation is a crucial task for any mobile robot. Usually, in an unknown environment, this problem is addressed by applying Simultaneous Localization and Mapping based on metric grid-maps. However, such maps are in general rather computational expensive and do not scale well. Insects are able to cover large distances and reliably find back to their nests, although they are quite limited in their resources. Inspired by theories on insect navigation, we developed a data structure which is highly scalable and efficiently adapts to the available memory during run-time. Positions in space are memorized as snapshots, which are unique configurations of landmarks. Unlike conventional snapshot or visual map approaches, we do not simply store the landmarks as a set, but we arrange them in a tree-like structure according to the relevance of their information. The resulting navigation solely relies on the direction measurements of arbitrary landmarks. In this work, we present the concept of the Landmark-Tree (LT) map and apply it to a mobile platform equipped with an omnidirectional camera. We verify the reliability and robustness of the LT-map concept in simulations as well as by experiments with the robotic platform.
Dependences of the X-ray luminosity and pulsar wind nebula on different parameters of pulsars and the evolutionary effects

Dependences of the X-ray luminosity (L$_x$) of single pulsars, due to ejection of relativistic particles, on electric field intensity, rate of rotational energy loss (\.{E}), magnetic field, period, and the energy spectra of the ejected particles are discussed. Influence of the magnetic field and effects of some other parameters of neutron stars on the L$_x$-\. {E} and the L$_x$-$\tau$ (characteristic time) dependences are considered. Evolutionary factors also play an important role in our considerations. We find that only the pulsars with L$_{2-10keV}$$>10^{33}$ erg/s have pulsar wind nebula around them. The pulsars from which $\gamma$-ray radiation has been observed have low X-ray luminosities in general.
Frequency-Dependent Streaming Potentials: A Review

The interpretation of seismoelectric observations involves the dynamic electrokinetic coupling, which is related to the streaming potential coefficient. We describe the different models of the frequency-dependent streaming potential, mainly Packard's and Pride's model. We compare the transition frequency separating low-frequency viscous flow and high-frequency inertial flow, for dynamic permeability and dynamic streaming potential. We show that the transition frequency, on a various collection of samples for which both formation factor and permeability are measured, is predicted to depend on the permeability as inversely proportional to the permeability. We review the experimental setups built to be able to perform dynamic measurements. And we present some measurements and calculations of the dynamic streaming potential.
Ultrafast Hybrid-Integrated Symmetric Mach-Zehnder All-Optical Switch and Its 168 Gbps Error-Free Demultiplexing Operation

A newly developed hybrid-integrated Symmetric Mach-Zehnder (HI-SMZ) all-optical switch is reported. For integration, we chose the Symmetric Mach-Zehnder (SMZ) structure rather than the Polarization-Discriminating Symmetric Mach-Zehnder (PD-SMZ) structure which is similar to SMZ but more often used in experiments using discrete optical components. We discuss advantages and disadvantages of SMZ and PD-SMZ to show that SMZ is more suitable for integration. We also discuss about the use of SOAs as nonlinear elements for all-optical switches. We conclude that, although the ultrafast switching capability of SMZ is limited by the gain compression of SOAs, the very low switching energy is more important for practical devices. We then describe the HI-SMZ all-optical switch. This integration scheme has advantages which include low loss, low dispersion silica waveguides for high speed operation and ease in large scale integration of many SMZs with other optical, electrical, and opto-electrical devices. We show that a very high dynamic extinction ratio is possible with HI-SMZ. We also examine HI-SMZ with 1 ps pulses to show its ultrafast capability. Finally, we describe a 168 to 10.5Gbps error-free demultiplexing experiment which is to our best knowledge the fastest experiment with an integrated device. key words: all-optical switch, nonlinear optics, optical commu-
The Three-Point Correlation Function of the Cosmic Microwave Background in Inflationary Models

We analyze the temperature three–point correlation function and the skewness of the Cosmic Microwave Background (CMB), providing general relations in terms of multipole coefficients. We then focus on applications to large angular s anisotropies, such as those measured by the COBE DMR, calculating the contribution to these quantities from primordial, inflation generated, scalar perturbations, via the Sachs–Wolfe effect. Using the techniques of stochastic inflation we are able to provide a universal expression for the ensemble averaged three–point function and for the corresponding skewness, which accounts for all primordial second–order effects. These general expressions would moreover apply to any situation where the bispectrum of the primordial gravitational potential has a hierarchical form. Our results are then specialized to a number of relevant models: power–law inflation driven by an exponential potential, chaotic inflation with a quartic and quadratic potential and a particular case of hybrid inflation. In all these cases non–Gaussian effects are small: as an example, the mean skewness is much smaller than the cosmic rms skewness implied by a Gaussian temperature fluctuation field.
New Bounds and Constructions for Granular Media Coding

Improved lower and upper bounds on the size and the rate of grain-correcting codes are presented. The lower bound is Gilbert-Varshamov-like combined with a construction by Gabrys et al., and it improves on the previously best known lower bounds on the asymptotic rate of ⌈τn⌉-grain-correcting codes of length n on the interval [0, 0.0668]. One of the two newly presented upper bounds improves on the best known upper bounds on the asymptotic rate of ⌈τn⌉-grain-correcting codes of length n on the interval τ ∈ (0, 1/8] and meets the lower bound of 1/2 for τ ≥ 1/8. Moreover, in a nonasymptotic regime, both upper bounds improve on the previously best known results on the largest size of t-grain-correcting codes of length n, for certain values of n and t. Constructions of 1-grain-correcting codes based on a partitioning technique are presented for lengths up to 18. Finally, a lower bound of 1/2 log2 n on the minimum redundancy of ∞-grain-detecting codes of length n is presented.
ESO Very Large Telescope Optical Spectroscopy of BL Lacertae Objects. II. New Redshifts, Featureless Objects, and Classification Assessments

We report on ESO Very Large Telescope optical spectroscopy of 42 BL Lacertae objects of unknown redshift. Nuclear emission lines were observed in 12 objects, while for another six we detected absorption features due to the host galaxy. The new high signal-to-noise ratio spectra therefore allow us to measure the redshift of 18 sources. Five of the observed objects were reclassified as either stars or quasars, and one is of uncertain nature. For the remaining 18 the optical spectra appear without intrinsic features in spite of our ability to measure rather faint (equivalent width ∼0.1 Å) spectral lines. For the latter sources a lower limit to the redshift was set, exploiting the very fact that the absorption lines of the host galaxy are undetected in the observed spectra.
A Survey of Database Inference Attack Prevention Methods

Inference attacks are notoriously hard to mitigate due to the fact that some data always needs to be made available to legitimate sources. It's di cult to prevent a determined individual from connecting available non-sensitive data and making inferences about more sensitive data. With more databases reachable from the web, this opens numerous opportunities for hackers to gain knowledge about sensitive or con dential data which they should not have. This paper attempts a thorough coverage of the advancements in methods of inference attack detection and prevention. There are a number of methods each with it's own advantages and disadvantages. There are design models which contribute to the mitigation of these attacks as well as functionality which can be added to database front-end and/or back-end. This paper pulls together information on each of the methods and models of inference detection / prevention and attempts summarize them in an easy to understand manner. I'll also discuss the usefulness of each in di erent situations and suggest where two or more methods may compliment each other well. Lastly I'll note which currently available products support any methods for implementing these techniques and how they might be used to accomplish it e ectively.
A comparative analysis of the college-choice factors of NCAA football student-athletes at a southeastern university

It is important that collegiate athletic department personnel are aware of student-athletes " college-choice factors so they can recruit and retain student-athletes that enhance Thus, the purpose of this study was to examine the college-choice factors of current NCAA Division I Football Bowl Subdivision (FBS) football players at a southeastern university (N = 77). Using a modified version of the Student-Athlete College-marketing and branding theories to identify strategies to attract student-athletes who are a great fit for their program analysis illustrated that athletically-related college-choice components were rated most influential by the respondents. Therefore, it is vital that administrators use these results to educate their coaches regarding techniques to enhance efficiency within the recruiting process. iv To my wife and best friend, Tabatha, for all of her love, patience, and encouragement. v ACKNOWLEDGEMENTS First and foremost I would like to give thanks to God for blessing me with the opportunity to pursue higher education at an esteemed university led by distinguished faculty and staff. Next I would like to thank my family for their persistent support and inspiration as I continue to chase my passion and contribute to the collegiate sport industry. Equally important I would like to extend my utmost gratitude to my advisor, Dr. Coyte Cooper. His countless hours of guidance and mentorship have not only developed me as a student, but continue to empower me to be a future leader as well. I am also indebted to a vast network of support that has not only contributed to the completion of my thesis, but also to my personal growth during my time in Chapel Hill. This includes my committee members Dr. Ed Shields and Dr. Deborah Stroman, additional sport administration faculty members Ms. Tufts, as well as several Athletic Department staff. Finally, I would like to acknowledge my classmates who have been invaluable resources in my life: Thanks for leading by example, pursuing excellence, and embodying the Carolina Way.
Does diversity matter? Evidence from a survey of political science faculty

ABSTRACT Does diversity in political science departments matter? In addressing the question, this article helps assess the value of increasing diversity in the discipline overall. Members of gender, race, and sexual orientation minority groups remain underrepresented in political science departments. What effects does underrepresentation have? To answer this question we rely upon a 2009 American Political Science Association (APSA)-sponsored survey of all faculty in U.S. political science departments. We study responses to questions about the number of female; racial minority; and lesbian, gay, or bisexual faculty members in political science departments. We test hypotheses about the relationship between the degree of departmental diversity and the friendliness, collegiality, and productivity of the associated faculty. We find that diversity, significantly affects intra-departmental relations, productivity, and perceptions of the treatment of female and racial/ethnic minorities. For both attitudes toward racial minorities and attitudes toward sexual minorities, greater diversity is generally associated with more positive attitudes. Women and racial/sexual minorities perceive their departments as less “friendly” than men and non-minorities. The presence of five or more women triggers a rise in the unfriendliness of a given department; this pattern does not appear for racial/sexual minorities.
Investigating the Allosteric Regulation of YfiN from Pseudomonas aeruginosa: Clues from the Structure of the Catalytic Domain

Pseudomonas aeruginosa is responsible for a plethora of biofilm mediated chronic infections among which cystic fibrosis pneumonia is the most frightening. The long-term survival strategy of P. aeruginosa in the patients lungs is based on a fine balance of virulence vs dormant states and on genetic adaptation, in order to select persistent phenotypes as the small colony variants (SCVs), which strongly correlate with antibiotic resistance and poor lung function. Recent studies have coupled SCV with increased levels of the signaling molecule cyclic di-GMP, and demonstrated the central role of the diguanylate cyclase YfiN, part of the tripartite signaling module YifBNR, in c-di-GMP dependent SCV regulation. YfiN, also called TpbB, is a multi-domain membrane enzyme connecting periplasmic stimuli to cytosolic c-di-GMP production by an allosteric inside-out signaling mechanism that, due to the lack of structural data, is still largely hypothetical. We have solved the crystal structure of the catalytic domain (GGDEF), and measured the enzymatic activity of the cytosolic portion in real-time by means of a newly developed method. Based on these results we demonstrate that, unlike other diguanylate cyclase, YfiN does not undergo product feedback inhibition, and that the presence of the HAMP domain is required for dimerization and catalysis. Coupling our structural and kinetic data with an in silico study we are now able to propose a model for the allosteric regulation of YfiN.
Maximum likelihood endpoint detection with time-domain features

In this paper we propose an effective, robust and computationally low-cost HMM-based start-endpoint detector for speech recognisers 1 . Our ﬁrst attempts follow the classical scheme feature extractor-Viterbi classiﬁer (used for voice activity detection), followed by a post-processing stage, but the ultimate goal we pursue is a pure HMM-based architecture capable of performing the endpointing task. The features used for voice activity detection are energy and zero crossing rate, together with AMDF (Average Magnitude Difference Function), which proves to be a valid alternative to energy; further, we study the impact on performance of grammar structures and training conditions. In the end, we set the basis for the investigation of pure HMM-based architectures.