Miracle-dz/UniFAR-FTUs huggingface dataset:
Matrix of Polynomials Model Based Polynomial Dictionary Learning Method for Acoustic Impulse Response Modeling

We study the problem of dictionary learning for signals that can be represented as polynomials or polynomial matrices, such as convolutive signals with time delays or acoustic impulse responses. Recently, we developed a method for polynomial dictionary learning based on the fact that a polynomial matrix can be expressed as a polynomial with matrix coefficients, where the coefficient of the polynomial at each time lag is a scalar matrix. However, a polynomial matrix can be also equally represented as a matrix with polynomial elements. In this paper, we develop an alternative method for learning a polynomial dictionary and a sparse representation method for polynomial signal reconstruction based on this model. The proposed methods can be used directly to operate on the polynomial matrix without having to access its coefficients matrices. We demonstrate the performance of the proposed method for acoustic impulse response modeling.
Solution of large complex problems in computational electromagnetics using higher-order basis in MoM with out-of-core solvers

In a recent invited paper in the IEEE Antennas and Propagation Magazine, some of the challenging problems in computational electromagnetics were presented. One of the objectives of this note is to simply point out that challenging to one may be simple to another. This is demonstrated through an example cited in that article. The example chosen is a Vivaldi antenna array. What we discuss here also applies to the other examples presented in that article, but we have chosen the Vivaldi antenna array to help us make our point. It is shown in this short article that a higher-order basis using a surface integral equation a la a PMCHWT (Poggio-Miller-Chu-Harrington-Wu-Tsai) method-of-moments formulation may still be the best weapon that one have in today's arsenal to deal with challenging complex electromagnetic analysis problems. Here, we have used the commercially available code WIPL-D to carry out all the computations using laptop/desktop systems. The second objective of this paper is to present an out-of-core solver. The goal is to demonstrate that an out-of-core 32-bit-system-based solver can be as efficient as a 64-bit in-core solver. This is quite contrary to the popular belief that an out-of-core solver is generally much slower than an in-core solver. This can be significant, as the difference in the cost of a 32-bit system can be 1/30 of a 64-bit system of similar capabilities using current computer architectures. For the 32-bit system, we consider a Pentium 4 system, whereas for the 64-bit system, we consider an Itanium 2 system for comparison. The out-of-core solver can go beyond the 2 GB limitation for a 32-bit system and can be run on ordinary laptop/desktop; hence, we can simultaneously have a much lower hardware investment while better performance for a sophisticated and powerful electromagnetic solver. The system resources and the CPU times are also outlined.
A Framework for Mining Enterprise Risk and Risk Factors from News Documents

Any real world events or trends that can affect the company’s growth trajectory can be considered as risk. There has been a growing need to automatically identify, extract and analyze risk related statements from news events. In this demonstration, we will present a risk analytics framework that processes enterprise project management reports in the form of textual data and news documents and classify them into valid and invalid risk categories. The framework also extracts information from the text pertaining to the different categories of risks like their possible cause and impacts. Accordingly, we have used machine learning based techniques and studied different linguistic features like n-gram, POS, dependency, future timing, uncertainty factors in texts and their various combinations. A manual annotation study from management experts using risk descriptions collected for a specific organization was conducted to evaluate the framework. The evaluation showed promising results for automated risk analysis and identification.
Deriving Item Features Relevance from Past User Interactions

Item-based recommender systems suggest products based on the similarities between items computed either from past user preferences (collaborative filtering) or from item content features (content-based filtering). Collaborative filtering has been proven to outperform content-based filtering in a variety of scenarios. However, in item cold-start, collaborative filtering cannot be used directly since past user interactions are not available for the newly added items. Hence, content-based filtering is usually the only viable option left.
Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review.

CONTEXT The quality of consumer health information on the World Wide Web is an important issue for medicine, but to date no systematic and comprehensive synthesis of the methods and evidence has been performed. OBJECTIVES To establish a methodological framework on how quality on the Web is evaluated in practice, to determine the heterogeneity of the results and conclusions, and to compare the methodological rigor of these studies, to determine to what extent the conclusions depend on the methodology used, and to suggest future directions for research. DATA SOURCES We searched MEDLINE and PREMEDLINE (1966 through September 2001), Science Citation Index (1997 through September 2001), Social Sciences Citation Index (1997 through September 2001), Arts and Humanities Citation Index (1997 through September 2001), LISA (1969 through July 2001), CINAHL (1982 through July 2001), PsychINFO (1988 through September 2001), EMBASE (1988 through June 2001), and SIGLE (1980 through June 2001). We also conducted hand searches, general Internet searches, and a personal bibliographic database search. STUDY SELECTION We included published and unpublished empirical studies in any language in which investigators searched the Web systematically for specific health information, evaluated the quality of Web sites or pages, and reported quantitative results. We screened 7830 citations and retrieved 170 potentially eligible full articles. A total of 79 distinct studies met the inclusion criteria, evaluating 5941 health Web sites and 1329 Web pages, and reporting 408 evaluation results for 86 different quality criteria. DATA EXTRACTION Two reviewers independently extracted study characteristics, medical domains, search strategies used, methods and criteria of quality assessment, results (percentage of sites or pages rated as inadequate pertaining to a quality criterion), and quality and rigor of study methods and reporting. DATA SYNTHESIS Most frequently used quality criteria used include accuracy, completeness, readability, design, disclosures, and references provided. Fifty-five studies (70%) concluded that quality is a problem on the Web, 17 (22%) remained neutral, and 7 studies (9%) came to a positive conclusion. Positive studies scored significantly lower in search (P =.02) and evaluation (P =.04) methods. CONCLUSIONS Due to differences in study methods and rigor, quality criteria, study population, and topic chosen, study results and conclusions on health-related Web sites vary widely. Operational definitions of quality criteria are needed.
Policy Implications Derived from a Study of Rural and Urban Marriages.

Comparing a sample of rural husbands and wives with a sample of urban husbands and wives over a range of variables that are fundamental to contemporary marriage and family, the joint issues of differences by county of residence and by sex are explored. It turns out that the most significant differences emerge over education and gender role preferences-rural women and men are less well educated and more gender role traditional than urban women and men. Thus, in planning programs to aid rural families andlor to counsel them, the family professional may wish to focus on the potential benefits to rural women (and men) of expanding their range of gender role-related options, alongside increasing access to those options.
Annexin V-Directed Enzyme Prodrug Therapy Plus Docetaxel for the Targeted Treatment of Pancreatic Cancer

Objectives The bleak prognosis associated with pancreatic cancer (PDAC) drives the need for the development of novel treatment methodologies. Here, we evaluate the applicability of 3 enzyme prodrug therapies for PDAC, which are simultaneously targeted to the tumor, tumor vasculature, and metastases via annexin V. In these therapies, annexin V is fused to an enzyme, creating a fusion protein that converts nontoxic drug precursors, prodrugs, into anticancer compounds while bound to the tumor, therefore mitigating the risk of side effects. Methods The binding strength of fusion proteins to the human PDAC cell lines Panc-1 and Capan-1 was measured via streptavidin-horseradish peroxidase binding to biotinylated fusion proteins. Cytotoxic efficacy was evaluated by treatment with saturating concentrations of fusion protein followed by varying concentrations of the corresponding prodrug plus docetaxel. Results All fusion proteins exhibited strong binding to PDAC cells, with dissociation constants between 0.02 and 1.15 nM. Cytotoxic efficacy was determined to be very good for 2 of the systems, both of which achieved complete cell death on at least 1 cell line at physiologically attainable prodrug concentrations. Conclusions Strong binding of fusion proteins to PDAC cells and effective cytotoxicity demonstrate the potential applicability of enzyme prodrug therapy to the treatment of PDAC.
How to Present Game Difficulty Choices?: Exploring the Impact on Player Experience

Matching game difficulty to player ability is a crucial step toward a rewarding player experience, yet making difficulty adjustments that are effective yet unobtrusive can be challenging. This paper examines the impact of automatic and player-initiated difficulty adjustment on player experience through two studies. In the first study, 40 participants played the casual game THYFTHYF either in motion-based or sedentary mode, using menu-based, embedded, or automatic difficulty adjustment. In the second study, we created an adapted version of the commercially available game fl0w to allow us to carry out a more focused study of sedentary casual play. Results from both studies demonstrate that the type of difficulty adjustment has an impact on perceived autonomy, but other player experience measures were not affected as expected. Our findings suggest that most players express a preference for manual difficulty choices, but that overall game experience was not notably impacted by automated difficulty adjustments.
Combining ensembles algorithms of symbolic learners

In this research work an ensemble of bagging, boosting, rotation forest, decorate and random subspace methods with 5 symbolic sub-classifiers in each one is presented. Then a voting methodology is used for the final prediction. In order to decrease training time, before building the ensemble redundant features were removed using a slight filter feature selection method. A comparison with simple bagging, boosting, rotation forest, decorate and random subspace methods ensembles with 25 symbolic sub-classifiers is performed, as well as other well-known combining methods, on standard benchmark datasets. The proposed technique is shown to be more accurate than other related methods in most cases.
Half-diminished reality image using three RGB-D sensors for remote control robots

This paper presents a method to compose half-diminished reality images for remote control robots using three RGB-D sensors. Robots are designed to perform the work of humans during a disaster response to reduce secondary disasters. In these case, a operator controls the robot with the aid of images from a mounted camera. However, operating efficiency decreases significantly when the robot arm occludes target work objects in those images. Recently, the Half-Diminished Reality technique has been proposed in the field of computer vision. This technique is used for seeing through foreground objects and viewing occluded backgrounds. Accordingly, composing half-diminished reality images can enable the operator to see the target work objects occluded by the robot arm in only one image, which results in increased the operating efficiency.
Channel-Aware Access for Cognitive Radio Networks

This paper addresses the problem of designing channel-aware access control (CAAC) algorithms for cognitive radio networks. To protect the primary transmission, the access probabilities of secondary users are adjusted based on the channel-state information and the measured interference temperature. It is shown that the proposed CAAC algorithm always converges to a fixed point. Furthermore, the CAAC algorithm can be interpreted as a noncooperative game. Then, the game model is extended to include general access utilities, unsuccessful transmission discount, and interference constraints. Sufficient conditions are established to guarantee the uniqueness of the Nash equilibrium (NE) of the proposed general game model, and a distributed iteration algorithm is proposed to find the unique NE. The convergence properties of this algorithm in continuous-time iteration, as well as in the discrete-time version, are proved under some sufficient conditions. Simulation results demonstrate the convergence and effectiveness of the distributed channel-access algorithms.
DNA Vaccine Using Mycobacterium bovis Ag85B Antigen Induces Partial Protection against Experimental Infection in BALB/c Mice

ABSTRACT Bovine tuberculosis is a major cause of economic loss in countries where it is endemic, and in some countries, it may be a significant zoonotic disease problem. Therefore, new strategies for vaccine development are required, and among them, genetic immunization has potential value. The main goal of this study was to test the Mycobacterium bovis Ag85B gene as a DNA vaccine following challenge with an M. bovis virulent strain (ATCC 19274). Groups of BALB/c mice (n = 10) were immunized four times intramuscularly with the pCI-Ag85B construct or the pCI vector alone as the control. High titers of total immunoglobulin G (IgG), IgG1, and IgG2a anti-Ag85B were measured in pCI-Ag85B immunized mice when compared to the pCI control group. Regarding cellular immunity, significant levels of gamma interferon (IFN-γ) (1,100 ± 157 pg/ml) and tumor necrosis factor alpha (650 ± 42 pg/ml) but not interleukin-4 were detected in splenocyte culture supernatants of pCI-Ag85B-vaccinated mice following stimulation with recombinant Ag85B. Further, the main source of IFN-γ is CD8+ T cells, as demonstrated by intracellular cytokine staining. As far as protection, a significant reduction in bacterial load in spleens (P < 0.05) was detected in pCI-Ag85B-immunized mice compared to the pCI vector control group. The results obtained here suggest that use of the Ag85B DNA vaccine is a promising strategy to control M. bovis infection due to its ability to induce a Th1 type of immune response. However, protective efficacy needs to be improved, since partial protection was achieved in spleens but not in lungs of vaccinated mice.
An Exact Solution to Support Vector Mixture

— This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.
A CONIC INTERIOR POINT DECOMPOSITION APPROACH FOR LARGE SCALE SEMIDEFINITE PROGRAMMING

We describe a conic interior point decomposition approach for solving a large scale semidefinite program (SDP) whose primal feasible set is bounded. The idea is to solve such an SDP using existing primal-dual interior point methods, in an iterative fashion between a master problem and a subproblem. In our case, the master problem is a mixed conic problem over linear and smaller sized semidefinite cones. The subproblem is a smaller structured semidefinite program that either returns a column or a small sized matrix depending on the multiplicity of the minimum eigenvalue of the dual slack matrix associated with the semidefinite cone. We motivate and develop our conic decomposition methodology on semidefinite programs and also discuss various issues involved in an efficient implementation. Computational results on several well known classes of semidefinite programs are presented.
Services of Adults With Significant Intellectual and Developmental Disabilities Examining the Experiences and Decisions of Parents / Guardians : Participant Directing the Supports and

Participant direction is a service delivery model in which the consumer of public benefits, or his or her surrogate decision maker, exercises some level of choice and control over the consumer’s supports and services. In this case study, the authors examined the decisions and experiences of parents/guardians who directed supports and services for an adult with significant intellectual and developmental disabilities (SIDD). Respondents included the parents/guardian of the adult as well as others in the circle of support identified by the parents/guardians. Data analysis revealed an overarching theme in which respondents perceived participant direction as a means to achieve an end, with the end being their desired outcomes for the adult with SIDD. Implications for policy include developing and providing supportive services to adults with SIDD and their parents/guardians due to the increased responsibilities associated with directing supports and services for the adult with a SIDD.
Laplace-Beltrami spectra for shape comparison of surfaces in 3D using the closest point method

The need to compare separate objects arises in a wide range of applications. In one approach for comparing objects, `Shape-DNA' is constructed to give a numerical fingerprint representing an individual object. Shape-DNA is a cropped set of eigenvalues of the Laplace-Beltrami operator for the surface of the object. In this paper, we compute the Shape-DNA of surfaces using the closest point method. Our approach may be applied to a variety of surface representations including triangulations, point clouds and certain analytical shapes. A 2D multidimensional scaling plot illustrates that similar objects form groups based on the Shape-DNAs. Our method has the benefit that it may be applied to surfaces defined by dense point clouds without requiring the construction of point connectivity.
PorePy: An Open-Source Simulation Tool for Flow and Transport in Deformable Fractured Rocks

Fractures are ubiquitous in the subsurface and strongly affect flow and deformation. The physical shape of the fractures, they are long and thin objects, puts strong limitations on how the effect of this dynamics can be incorporated into standard reservoir simulation tools. This paper reports the development of an open-source software framework, termed PorePy, which is aimed at simulation of flow and transport in three-dimensional fractured reservoirs, as well as deformation of the reservoir due to shearing along fracture and fault planes. Starting from a description of fractures as polygons embedded in a 3D domain, PorePy provides semi-automatic gridding to construct a discrete-fracture-matrix model, which forms the basis for subsequent simulations. PorePy allows for flow and transport in all lower-dimensional objects, including planes (2D) representing fractures, and lines (1D) and points (0D), representing fracture intersections. Interaction between processes in neighboring domains of different dimension is implemented as a sequence of couplings of objects one dimension apart. This readily allows for handling of complex fracture geometries compared to capabilities of existing software. In addition to flow and transport, PorePy provides models for rock mechanics, poro-elasticity and coupling with fracture deformation models. The software is fully open, and can serve as a framework for transparency and reproducibility of simulations. We describe the design principles of PorePy from a user perspective, with focus on possibilities within gridding, covered physical processes and available discretizations. The power of the framework is illustrated with two sets of simulations; involving respectively coupled flow and transport in a fractured porous medium, and low-pressure stimulation of a geothermal reservoir.
Bandwidth Allocation for Video Streaming in WiMax Networks

We describe an analytical model, based on a Markov chain, suitable to study different bandwidth allocation policies for video streams over a WiMax access link. The Markov chain models an MPEG source, wireless channel conditions derived from a model compliant with WiMax specifications, and different bandwidth allocation policies. Validation with simulation results shows the correctness of the analytical model. The model permits to discuss the properties of various bandwidth allocation policies in terms of wasted slots, amount of lost data and access delays.
Structure-Function Analysis of the Coiled-Coil and Leucine-Rich Repeat Domains of the RPS 5 Disease Resistance Protein 1 [ W ] [ OA ]

The Arabidopsis (Arabidopsis thaliana) RESISTANCE TO PSEUDOMONAS SYRINGAE5 (RPS5) disease resistance protein mediates recognition of the Pseudomonas syringae effector protein AvrPphB. RPS5 belongs to the coiled-coil-nucleotide-binding site-leucine-rich repeat (CC-NBS-LRR) family and is activated by AvrPphB-mediated cleavage of the protein kinase PBS1. Here, we present a structure-function analysis of the CC and LRR domains of RPS5 using transient expression assays in Nicotiana benthamiana. We found that substituting the CC domain of RPS2 for the RPS5 CC domain did not alter RPS5 specificity and only moderately reduced its ability to activate programmed cell death, suggesting that the CC domain does not play a direct role in the recognition of PBS1 cleavage. Analysis of an RPS5-super Yellow Fluorescent Protein fusion revealed that RPS5 localizes to the plasma membrane (PM). Alanine substitutions of predicted myristoylation (glycine-2) and palmitoylation (cysteine-4) residues affected RPS5 PM localization, protein stability, and function in an additive manner, indicating that PM localization is essential to RPS5 function. The first 20 amino acids of RPS5 were sufficient for directing super Yellow Fluorescent Protein to the PM. C-terminal truncations of RPS5 revealed that the first four LRR repeats are sufficient for inhibiting RPS5 autoactivation; however, the complete LRR domain was required for the recognition of PBS1 cleavage. Substitution of the RPS2 LRR domain resulted in the autoactivation of RPS5, indicating that the LRR domain must coevolve with the NBS domain. We conclude that the RPS5 LRR domain functions to suppress RPS5 activation in the absence of PBS1 cleavage and promotes RPS5 activation in its presence.