Miracle-dz/UniFAR-FTUs huggingface dataset:
Є-Samples for Kernels

We study the worst case error of kernel density estimates via subset approximation. A kernel density estimate of a distribution is the convolution of that distribution with a fixed kernel (e.g. Gaussian kernel). Given a subset (i.e. a point set) of the input distribution, we can compare the kernel density estimates of the input distribution with that of the subset and bound the worst case error. If the maximum error is e, then this subset can be thought of as an e-sample (aka an e-approximation) of the range space defined with the input distribution as the ground set and the fixed kernel representing the family of ranges. Interestingly, in this case the ranges are not binary, but have a continuous range (for simplicity we focus on kernels with range of [0, 1]); these allow for smoother notions of range spaces. It turns out, the use of this smoother family of range spaces has an added benefit of greatly decreasing the size required for e-samples. For instance, in the plane the size is
Fast chromatin immunoprecipitation assay

Chromatin immunoprecipitation (ChIP) is a widely used method to explore in vivo interactions between proteins and DNA. The ChIP assay takes several days to complete, involves several tube transfers and uses either phenol–chlorophorm or spin columns to purify DNA. The traditional ChIP method becomes a challenge when handling multiple samples. We have developed an efficient and rapid Chelex resin-based ChIP procedure that dramatically reduces time of the assay and uses only a single tube to isolate PCR-ready DNA. This method greatly facilitates the probing of chromatin changes over many time points with several antibodies in one experiment.
Discriminant Analysis and Statistical Pattern Recognition

Provides a systematic account of the subject area, concentrating on the most recent advances in the field. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are: regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule and extensions of discriminant analysis motivated by problems in statistical image analysis. Includes over 1,200 references in the bibliography.
Dynamic simulation of hydrodynamically interacting particles

A general method for computing the hydrodynamic interactions among N suspended particles, under the condition of vanishingly small particle Reynolds number, is presented. The method accounts for both near-field lubrication effects and the dominant many-body interactions. The many-body hydrodynamic interactions reproduce the screening characteristic of porous media and the ‘effective viscosity’ of free suspensions. The method is accurate and computationally efficient, permitting the dynamic simulation of arbitrarily configured many-particle systems. The hydrodynamic interactions calculated are shown to agree well with available exact calculations for small numbers of particles and to reproduce slender-body theory for linear chains of particles. The method can be used to determine static (i.e. configuration specific) and dynamic properties of suspended particles that interact through both hydrodynamic and non-hydrodynamic forces, where the latter may be any type of Brownian. colloidal, interparticle or external force. The method is also readily extended to dynamically simulate both unbounded and bounded suspensions.
Separation of stereo speech signals based on a sparse dictionary algorithm

We address the problem of source separation in echoic and anechoic environments, with a new algorithm which adaptively learns a set of sparse stereo dictionary elements, which are then clustered to identify the original sources. The atom pairs learned by the algorithm are found to capture information about the direction of arrival of the source signals, which allows to determine the clusters. A similar approach is also used here to extend the dictionary learning K singular value decomposition (K-SVD) algorithm, to address the source separation problem, and results from the two methods are compared. Computer simulations indicate that the proposed adaptive sparse stereo dictionary (ASSD) algorithm yields good performance in both anechoic and echoic environments.
History merging as a mechanism for concurrency control in cooperative environments

Cooperative applications need proper transactional support for coordinating joint activities, sharing of data, and semantically correct exchange of information of collaborating users. Conventional transaction models based on the ACID properties do not meet the typical requirements of cooperative applications. The CoACT model (M. Rusinkiewicz et al., 1995) is designed for supporting cooperative work in multi user environments. CoACT includes a novel algorithm implementing the semantically correct exchange of information among concurrent activities of cooperating users by means of merging histories of user activities. This technique of merging activity histories is applicable in various fields beyond CSCW systems, e.g., in the area of mobile computing to manage disconnected operation.
Epipolar Visual Servoing for Multirobot Distributed Consensus

In this paper, we give a distributed solution to the problem of making a team of nonholonomic robots reach consensus about their orientations using monocular cameras. We consider a scheme where the motions of the robots are decided using nearest-neighbor rules. Each robot is equipped with a camera and can only exchange visual information with a subset of the other robots. The main contribution of this paper is a new controller that uses the epipoles that are computed from the images provided by neighboring robots, eventually reaching consensus in their orientations without the necessity of directly observing each other. In addition, the controller only requires a partial knowledge of the calibration of the cameras in order to achieve the desired configuration. We also demonstrate that the controller is robust to changes in the topology of the network and we use this robustness to propose strategies to reduce the computational load of the robots. Finally, we test our controller in simulations using a virtual environment and with real robots moving in indoor and outdoor scenarios.
VLBI surveys

Systematic surveys of astronomical objects often lead to discoveries, but always provide invalu-able information for statistical studies of well-deﬁned samples. They also promote follow-up investigations of individual objects or classes. Surveys using a yet unexplored observing wavelength, a novel technique or a new instrument are of special importance. Signiﬁcantly improved observing parameters (e.g. sensitivity, angular resolution, monitoring capability) provide new in-sight into the morphological and physical properties of the objects studied. I give a brief overview of the important Very Long Baseline Interferometry (VLBI) imaging surveys conducted in the past. A list of surveys guides us through the developments up until the present days. I also attempt to show directions for the near future.
The Analysis of America SEC Analytic Paradigm and Its Implication——In the Perspective of Alignment between Assessment and Standard in Basic Education

As education reform efforts have moved toward a standard-based approach,and the demand of teaching is rather low.Americans are committed to developing "SEC"(Surveys of Enacted Curriculum)analytic paradigm,which aims at analyzing the ideas,procedures and methods of the alignment between assessment and curriculum standards.And this action has great effects on the curriculum assessment which is based on the curriculum standards.The analytic paradigm offers us some valuable advice on our curriculum evaluation reform.
Control of electrical drives based on fuzzy logic

The paper presents the theory of control systems for electrical drives based on fuzzy logic, from the author's point of view. The paper offers practical answers at questions related to the design of speed control systems based on fuzzy PI speed controller: what is the adequate structure of fuzzy controller, the number of rules fuzzy values, how to assure stability, implementation, control system quality criteria. The conventional design method for the linear speed control systems is presented as a comparison base. An example of fuzzy control systems for d.c. drives is given, with its modelling, simulation, design, transient characteristics and quality criteria.
Explicit Logic Circuits Discriminate Neural States

The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems.
Task taxonomy for graph visualization

Our goal is to define a list of tasks for graph visualization that has enough detail and specificity to be useful to: 1) designers who want to improve their system and 2) to evaluators who want to compare graph visualization systems. In this paper, we suggest a list of tasks we believe are commonly encountered while analyzing graph data. We define graph specific objects and demonstrate how all complex tasks could be seen as a series of low-level tasks performed on those objects. We believe that our taxonomy, associated with benchmark datasets and specific tasks, would help evaluators generalize results collected through a series of controlled experiments.
Subdomain Location of Mutations in Cardiac Actin Correlate with Type of Functional Change

Determining the molecular mechanisms that lead to the development of heart failure will help us gain better insight into the most costly health problem in the Western world. To understand the roles that the actin protein plays in the development of heart failure, we have taken a systematic approach toward characterizing human cardiac actin mutants that have been associated with either hypertrophic or dilated cardiomyopathy. Seven known cardiac actin mutants were expressed in a baculovirus system, and their intrinsic properties were studied. In general, the changes to the properties of the actin proteins themselves were subtle. The R312H variant exhibited reduced stability, with a T m of 53.6°C compared to 56.8°C for WT actin, accompanied with increased polymerization critical concentration and Pi release rate, and a marked increase in nucleotide release rates. Substitution of methionine for leucine at amino acid 305 showed no impact on the stability, nucleotide release rates, or DNase-I inhibition ability of the actin monomer; however, during polymerization, a 2-fold increase in Pi release was observed. Increases to both the T m and DNase-I inhibition activity suggested interactions between E99K actin molecules under monomer-promoting conditions. Y166C actin had a higher critical concentration resulting in a lower Pi release rate due to reduced filament-forming potential. The locations of mutations on the ACTC protein correlated with the molecular effects; in general, mutations in subdomain 3 affected the stability of the ACTC protein or affect the polymerization of actin filaments, while mutations in subdomains 1 and 4 more likely affect protein-protein interactions.
A general performance model interchange format

A common, XML-based interface between specifications of quantitative system models and programmed solutions is developed and illustrated with several examples. It is based on the PMIF (Performance Model Interchange Format), which allows queueing network models to be specified in XML and solved by calling any appropriate modelling tool, such as Qnap. The definition of PMIF specifications is generalised by considering more abstract collections of interacting nodes, using concepts compatible with the Reversed Compound Agent Theorem (RCAT). The interactions are more general in that they synchronise transitions in a pair of nodes rather than being restricted to describing traffic flows. The generalised nodes are characterised by the interactions in which they participate, together with their rates and reversed rates, which may be implicit. In this way, generalised queueing networks with negative customers and triggers can be incorporated and fixpoint models can also be handled uniformly through the use of symbolic variables.
The proximal distance algorithm

The MM principle is a device for creating optimization algorithms satisfying the ascent or descent property. The current survey emphasizes the role of the MM principle in nonlinear programming. For smooth functions, one can construct an adaptive interior point method based on scaled Bregmann barriers. This algorithm does not follow the central path. For convex programming subject to nonsmooth constraints, one can combine an exact penalty method with distance majorization to create versatile algorithms that are effective even in discrete optimization. These proximal distance algorithms are highly modular and reduce to set projections and proximal mappings, both very well-understood techniques in optimization. We illustrate the possibilities in linear programming, binary piecewise-linear programming, nonnegative quadratic programming, $\ell_0$ regression, matrix completion, and inverse sparse covariance estimation.
Systematic Energy Characterization of CMP/SMT Processor Systems via Automated Micro-Benchmarks

Microprocessor-based systems today are composed of multi-core, multi-threaded processors with complex cache hierarchies and gigabytes of main memory. Accurate characterization of such a system, through predictive pre-silicon modeling and/or diagnostic post silicon measurement based analysis are increasingly cumbersome and error prone. This is especially true of energy-related characterization studies. In this paper, we take the position that automated micro-benchmarks generated with particular objectives in mind hold the key to obtaining accurate energy-related characterization. As such, we first present a flexible micro-benchmark generation framework (MicroProbe) that is used to probe complex multi-core/multithreaded systems with a variety and range of energy-related queries in mind. We then present experimental results centered around an IBM POWER7 CMP/SMT system to demonstrate how the systematically generated micro-benchmarks can be used to answer three specific queries: (a) How to project application-specific (and if needed, phase-specific) power consumption with component-wise breakdowns? (b) How to measure energy-per-instruction (EPI) values for the target machine? (c) How to bound the worst-case (maximum) power consumption in order to determine safe, but practical (i.e. affordable) packaging or cooling solutions? The solution approaches to the above problems are all new. Hardware measurement based analysis shows superior power projection accuracy (with error margins of less than 2.3% across SPEC CPU2006) as well as maxpower stressing capability (with 10.7% increase in processor power over the very worst-case power seen during the execution of SPEC CPU2006 applications).
Shallow knowledge as an aid to deep understanding in early phase requirements engineering

Requirements engineering's continuing dependence on natural language description has made it the focus of several efforts to apply language engineering techniques. The raw textual material that forms an input to early phase requirements engineering and which informs the subsequent formulation of the requirements is inevitably uncontrolled and this makes its processing very hard. Nevertheless, sufficiently robust techniques do exist that can be used to aid the requirements engineer provided that the scope of what can be achieved is understood. In this paper, we show how combinations of lexical and shallow semantic analysis techniques developed from corpus linguistics can help human analysts acquire the deep understanding needed as the first step towards the synthesis of requirements.
Iterative filtering of phonetic transcriptions of proper nouns

This paper focuses on an approach to enhancing automatic phonetic transcription of proper nouns by using an iterative filter to retain only the most relevant part of a large set of phonetic variants, obtained by combining rule-based generation with extraction from actual audio signals. Using this technique, we were able to reduce the error rate affecting proper nouns during automatic speech transcription of the ESTER corpus of French broadcast news. The role of the filtering was to ensure that the new phonetic variants of proper nouns would not induce new errors in the transcription of the rest of the words.
Self-Regulation of Emotion, Functional Impairment, and Comorbidity Among ChildrenWith AD/HD

Objective: This study investigated the role of self-regulation of emotion in relation to functional impairment and comorbidity among children with and without AD/HD. Method: A total of 358 probands and their siblings participated in the study, with 74% of the sample participants affected by AD/HD. Parent-rated levels of emotional lability served as a marker for self-regulation of emotion. Results: Nearly half of the children affected by AD/HD displayed significantly elevated levels of emotional lability versus 15% of those without this disorder. Children with AD/HD also displayed significantly higher rates of functional impairment, comorbidity, and treatment service utilization. Emotional lability partially mediated the association between AD/HD status and these outcomes. Conclusion: Findings lent support to the notion that deficits in the self-regulation of emotion are evident in a substantial number of children with AD/HD and that these deficits play an important role in determining functional impairment and comorbidity outcomes.
sgen1: A generator of small but difficult satisfiability benchmarks

The satisfiability problem is known to be NP-Complete; therefore, there should be relatively small problem instances that take a very long time to solve. However, most of the smaller benchmarks that were once thought challenging, especially the satisfiable ones, can be processed quickly by modern SAT-solvers. We describe and make available a generator that produces both unsatisfiable and, more significantly, satisfiable formulae that take longer to solve than any others known. At the two most recent international SAT Competitions, the smallest unsolved benchmarks were created by this generator. We analyze the results of all solvers in the most recent competition when applied to these benchmarks and also present our own more focused experiments.
Global configuration stabilization for the VTOL aircraft with strong input coupling

Trajectory tracking and configuration stabilization for VTOL aircraft (vertical take off and landing) in the literature has been only considered for the case of slight or zero input coupling. In the paper, our main contribution is to address global configuration stabilization for the VTOL aircraft with a strong input coupling using a smooth static state feedback.
The Effects of a Mother's Return to Work Decision on Child Development in the UK

The last 20 years has seen a huge increase in employment among mothers in the first year after giving birth in the UK. We examine whether early maternal employment has an adverse effect on child outcomes. We analyse rich data from a cohort of children born in the UK in the early 1990s and examine the impact of early maternal employment on three outcome variables measuring child cognitive development between four and seven years of age. We also explore whether the effect varies with the mother's educational attainment, lone parent status or the type of replacement non-maternal childcare used. Copyright 2005 Royal Economic Society.
An Open Cloud Model for Expanding Healthcare Infrastructure

with the rapid improvement of computation facilities, healthcare still suffers limited storage space and lacks full utilization of computer infrastructure. That not only adds to the cost burden but also limits the possibility for expansion and integration with other healthcare services. Cloud computing which is based on virtualization, elastic allocation of resources, and pay as you go for used services, opened the way for the possibility to offer fully integrated and distributed healthcare systems that can expand globally. However, cloud computing with its ability to virtualize resources doesn't come cheap or safe from the healthcare perspective. The main objective of this paper is to introduce a new strategy of healthcare infrastructure implementation using private cloud based on OpenStack with the ability to expand over public cloud with hybrid cloud architecture. This research proposes the migration of legacy software and medical data to a secured private cloud with the possibility to integrate with arbitrary public clouds for services that might be needed in the future. The tools used are mainly OpenStack, DeltaCloud, and OpenShift which are open source adopted by major cloud computing companies. Their optimized integration can give an increased performance with a considerable reduction in cost without sacrificing the security aspect. Simulation was then performed using CloudSim to measure the design performance.
Ja n 20 02 CGPG-01 / 11-3 gr-qc / 0111067 Geometry of Generic Isolated Horizons

Geometrical structures intrinsic to non-expanding, weakly isolated and isolated horizons are analyzed and compared with structures which arise in other contexts within general relativity, e.g., at null infinity. In particular, we address in detail the issue of singling out the preferred normals to these horizons required in various applications. This work provides powerful tools to extract invariant, physical information from numerical simulations of the near horizon, strong field geometry. While it complements the previous analysis of laws governing the mechanics of weakly isolated horizons, prior knowledge of those results is not assumed.