Miracle-dz/UniFAR-FTUs huggingface dataset:
Rao–Blackwellization for Bayesian Variable Selection and Model Averaging in Linear and Binary Regression: A Novel Data Augmentation Approach

Choosing the subset of covariates to use in regression or generalized linear models is a ubiquitous problem. The Bayesian paradigm addresses the problem of model uncertainty by considering models corresponding to all possible subsets of the covariates, where the posterior distribution over models is used to select models or combine them via Bayesian model averaging (BMA). Although conceptually straightforward, BMA is often difficult to implement in practice, since either the number of covariates is too large for enumeration of all subsets, calculations cannot be done analytically, or both. For orthogonal designs with the appropriate choice of prior, the posterior probability of any model can be calculated without having to enumerate the entire model space and scales linearly with the number of predictors, p. In this article we extend this idea to a much broader class of nonorthogonal design matrices. We propose a novel method which augments the observed nonorthogonal design by at most p new rows to obtain a design matrix with orthogonal columns and generate the “missing” response variables in a data augmentation algorithm. We show that our data augmentation approach keeps the original posterior distribution of interest unaltered, and develop methods to construct Rao–Blackwellized estimates of several quantities of interest, including posterior model probabilities of any model, which may not be available from an ordinary Gibbs sampler. Our method can be used for BMA in linear regression and binary regression with nonorthogonal design matrices in conjunction with independent “spike and slab” priors with a continuous prior component that is a Cauchy or other heavy tailed distribution that may be represented as a scale mixture of normals. We provide simulated and real examples to illustrate the methodology. Supplemental materials for the manuscript are available online.
Poster abstract: Gesture recognition via continuous maximum entropy training on accelerometer data

In this work, we present a gesture recognition system via continuous MaxEnt training on accelerometer data. We are working on embedding feature selection into MaxEnt model training to more intelligently narrow the feature set. We are also working to simplify the modeling process so developers can more easily build sensor-based applications. Finally, we are exploring the use of MaxEnt to model higher-level activities.
The Tissue-Engineered Vascular Graft—Past, Present, and Future

Cardiovascular disease is the leading cause of death worldwide, with this trend predicted to continue for the foreseeable future. Common disorders are associated with the stenosis or occlusion of blood vessels. The preferred treatment for the long-term revascularization of occluded vessels is surgery utilizing vascular grafts, such as coronary artery bypass grafting and peripheral artery bypass grafting. Currently, autologous vessels such as the saphenous vein and internal thoracic artery represent the gold standard grafts for small-diameter vessels (<6 mm), outperforming synthetic alternatives. However, these vessels are of limited availability, require invasive harvest, and are often unsuitable for use. To address this, the development of a tissue-engineered vascular graft (TEVG) has been rigorously pursued. This article reviews the current state of the art of TEVGs. The various approaches being explored to generate TEVGs are described, including scaffold-based methods (using synthetic and natural polymers), the use of decellularized natural matrices, and tissue self-assembly processes, with the results of various in vivo studies, including clinical trials, highlighted. A discussion of the key areas for further investigation, including graft cell source, mechanical properties, hemodynamics, integration, and assessment in animal models, is then presented.
Developing proximity of possible disciplinary selves in narratives: An alternative approach to explore the representation of individual in context

This article adopts a Systemic Functional Linguistics framework of appraisal theory to interpret the behavioural and attitudinal resources in written narratives and proposes the idea of proximity as an alternative representation to explain the meaning-making process of Chinese students’ possible selves in a less examined context of UK-based transnational university in China, by focusing on the lexical and semantic explanation of how these Chinese students use and are mediated by contextual resources in discourse. Six written narratives were collected from six Chinese students from the School of International Communications at the University of Nottingham Ningbo China (UNNC). The overall findings revealed that all six Chinese students from different years shaped proximal past, current and future possible disciplinary selves through repeated engagement and positive alignment with the contextual values, although they had differentiated developmental processes of using and being mediated by the contextual recourses. This article concludes by arguing for a need to investigate the Chinese learners in the current changing world by looking at their repertoire experience of disciplinary learning and reservoir context.
Transient perturbation of endothelial integrity induced by natural antibodies and complement

The barrier function of blood vessels is though to be regulated at least in part by endothelium. This concept is supported by the dramatic loss of barrier function occurring in the hyperacute rejection of vascularized grafts mediated by anti-endothelial cell (EC) antibodies and complement. In this process, the endothelium is not destroyed but instead loses the ability to retain blood cells and plasma proteins within capillaries. The noncytotoxic mechanism that allows this change in EC function has been unknown. Here we report that within 10 to 20 min of exposure to human xenoreactive natural antibodies and complement, porcine EC undergo alterations in cell shape and in the cytoskeleton that disrupt monolayer integrity and lead to formation of intercellular gaps. Gap formation is not associated with cell death but requires the complement complex C5b67. The gaps induced by anti-EC antibodies and complement are transient; gap closure requires formation of C5b-9 complexes on the cells and the rate of recovery depends on the release of cellular products into the medium. Preincubation of EC with dibutyryl cAMP (0.5 mM) prevents gap formation and disruption of the cytoskeleton caused by antibodies and complement. These results provide evidence that the integrity of endothelium is regulated by components of the complement system and suggest a mechanism that may explain the prominent loss of endothelial integrity seen in humoral immune responses.
On the Regularizing Power of Multigrid-type Algorithms

We consider the deblurring problem of noisy and blurred images in the case of known space invariant point spread functions with four choices of boundary conditions. We combine an algebraic multigrid previously defined ad hoc for structured matrices related to space invariant operators (Toeplitz, circulants, trigonometric matrix algebras, etc.) and the classical geometric multigrid studied in the partial differential equations context. The resulting technique is parameterized in order to have more degrees of freedom: a simple choice of the parameters allows us to devise a quite powerful regularizing method. It defines an iterative regularizing method where the smoother itself has to be an iterative regularizing method (e.g., conjugate gradient, Landweber, conjugate gradient for normal equations, etc.). More precisely, with respect to the smoother, the regularization properties are improved and the total complexity is lower. Furthermore, in several cases, when it is directly applied to the system $A{\bf f}={\bf g}$, the quality of the restored image is comparable with that of all the best known techniques for the normal equations $A^TA{\bf f}=A^T{\bf g}$, but the related convergence is substantially faster. Finally, the associated curves of the relative errors versus the iteration numbers are "flatter" with respect to the smoother (the estimation of the stop iteration is less crucial). Therefore, we can choose multigrid procedures which are much more efficient than classical techniques without losing accuracy in the restored image (as often occurs when using preconditioning). Several numerical experiments show the effectiveness of our proposals.
A Scalable Security Protocol for Wireless Sensor Networks

Since sensor nodes suffer from limited resources, in memory storage, computing power, energy capabilities, and transmission rates, available network security protocols are inadequate. Symmetric algorithms cannot provide the same degree of security as public-key algorithms, the fact of which has led us to devise a new algorithm, SHESP, which uses public keys within the limitations of sensor nodes. This paper aims to present a way to utilize existing public-key algorithms in the field of wireless sensor network security by dividing the network into clusters. Our algorithm supplies data confidentiality, node authentication and data integrity while remaining within acceptable memory, time and energy constraints. Also, an important feature we opted to establish, which was lacking in most security protocols, was enabling secure node-to-node communication, without the need to route through a distant base station. We provide theoretical as well as experimental evidence to validate our algorithm.
Route Optimization Techniques in Network Mobility (NEMO)

This paper targets to analyze network mobility issues and requirements in the context of next generation networks (NGN's). The aim is to explore the idea of route optimization (RO) in NEMO. After discussing the need of route optimization in NEMO, different solution thus far provided are discussed and analyzed. Still a lot of work is required to be done in the field of route optimization in NEMO. All these issues are explained to provide a future course of research in this field.
Long-range interactions and nonextensivity in ferromagnetic spin models.

The Ising model with ferromagnetic interactions that decay as $\frac{1}{{r}^{\ensuremath{\alpha}}}$ is analyzed in the nonextensive regime $0l~\ensuremath{\alpha}l~d$, where the thermodynamic limit is not defined. In order to study the asymptotic properties of the model in the $N\ensuremath{\rightarrow}\ensuremath{\infty}$ limit ($N$ being the number of spins) we propose a generalization of the Curie-Weiss model, for which the $N\ensuremath{\rightarrow}\ensuremath{\infty}$ limit is well defined for all $\ensuremath{\alpha}g~0$. We conjecture that mean-field theory is exact in the last model for all $0l~\ensuremath{\alpha}l~d$. This conjecture is supported by Monte Carlo heat-bath simulations in the $d=1$ case. Moreover, we confirm a recently conjectured scaling by Tsallis that allows for a unification of extensive ($\ensuremath{\alpha}gd$) and nonextensive ($0l~\ensuremath{\alpha}l~d$) regimes.
Discovery of an X-Ray Synchrotron Nebula Associated with the Radio Pulsar PSR B1853+01 in the Supernova Remnant W44

We report the detection, using data from the Advanced Satellite for Cosmology and Astrophysics (ASCA), of a hard X-ray source in the vicinity of the radio pulsar PSR B1853+01, which is located within the supernova remnant (SNR) W44. PSR B1853+01, a 267 ms pulsar, has to date been detected only in the radio band. Previous observations at soft X-ray energies (e.g., with ROSAT HRI) have failed to detect any significant X-ray emission (pulsed or unpulsed) from the pulsar. In addition, no high-energy emission (≳4 keV) has been detected previously from W44. Over the 0.5-4.0 keV band, the ASCA data show soft thermal emission from W44, with a morphology very similar to that observed earlier by Einstein and ROSAT. In the high-energy band (4.0-9.5 keV), the SNR is, for the most part, invisible, although a source coincident with the position of PSR B1853+01 is evident. The observed ASCA spectra are consistent with a power-law origin (photon index ~2.3) for the X-ray emission from this source at a flux level (flux density ~0.5 μJy at 1 keV) consistent with previous upper limits. The maximum allowed size for the source is determined directly from the ASCA data (<5'), while the minimum size is derived from the nondetection of a point source in the ROSAT HRI data (≳30''). Timing analysis of the hard X-ray source failed to detect pulsations at the pulsar's period. Based on these lines of evidence, we conclude that the new hard source in W44 represents an X-ray synchrotron nebula associated with PSR B1853+01, rather than the beamed output of the pulsar itself. This discovery adds W44 to the small group of previously known plerionic SNRs. This nebula lies at the low end of, but is consistent with, the correlation between X-ray luminosity and pulsar spin-down energy loss found for such objects, lending further support to our interpretation.
Optimizing the operating voltage of tunnel FET-based SRAM arrays equipped with read/write assist circuitry

This paper deals with obtaining the minimum operating voltage of memory arrays based on TFET SRAM cells. First, we compare the I-V characteristics of two TFETs and one FDSOI using SPICE simulations. The results reveal that TFET devices exhibit high ON/OFF current ratios at different power supply voltage levels. This observation suggests a higher stability for SRAM cells based on these devices. Next, the characteristics of 6T SRAM cells implemented using minimum sized transistors based on these three device structures are compared. The comparison, which considers two TFET cell structures, i.e., inward and outward SRAMs, is performed at different supply voltages. The results for the hold static noise margin show that at low supply voltages (i.e., below 300mV), the FDSOI SRAM cell cannot hold data whereas both the inward and outward structures of TFET have acceptable noise margins at all supply voltages. Among the two TFET structures, the outward cell is selected because of higher speed especially for the write operation. TFET SRAMs suffer from long read access latency at ultra-low supply voltages (e.g., 150mV). The problem, however, may be overcome by using the negative GND read-assist technique. The results show that for a 32×32 TFET outward SRAM array, the minimum energy consumption (energy-delay product) may be achieved at the supply voltage of 200mV (300mV) with 1.32GHz (4.55GHz) as the read access frequency.
The Unique Potential of SKA Radio Observations of Gamma-Ray Bursts.

Radio observations with the Square Kilometer Array (SKA) provide the agility, sensitivity, and spectral coverage to trace the evolution of the size, shape and spectra of gamma-ray burst (GRB) remnants from the earliest moments on. In the first hours to days after the burst a major, and unique tool, will be provided through the study of dynamically evolving radio spectra, caused by diffractive and refractive scintillation in the local ISM. Simultaneous observations from optically thin to optically thick frequencies will provide strong constraints on any model for the GRB remnant. SKA will also allow for extremely rapid (within minutes, if not seconds) follow-up observations by electronic steering of the array. SKA observations have the sensitivity to detect GRB afterglows out to redshifts of 10 or greater. They therefore allow studies of the high redshift universe, and measure the massive star formation (and massive star death rate! ) history of the universe, unbiased by optical obscuration. Wide field surveys may detect thousands of GRBs within a few days of observing (depending on the amount of collimation, the width of the GRB luminosity function, the number of GRBs like GRB 980425/SN1998bw). There would be new ones, but many more would be old, fading afterglows, allowing the determination of the multivariate GRB-optical-radio luminosity function of GRBs. This should elucidate the relation of the ‘faint’ ones, like GRB980425, to the luminous ones like GRB970508. Such surveys will also tell us whether GRB fireballs (and which ones) are collimated into jets.
Applications of combinatorial designs in computer science

The theory of combinatorial designs has been used in widely different areas of computation concerned with the design and analysis of both algorithms and hardware. Combinatorial designs capture a subtle balancing property that is inherent in many difficult problems and hence can provide a sophisticated tool for addressing these problems. The role of combinatorial designs in solving many problems that are basic to the field of computing is explored in this paper. Case studies of many applications of designs to computation are given; these constitute a first survey, which provides a representative sample of uses of designs. More importantly, they suggest paradigms in which designs can be used profitably in algorithm design and analysis.
Prevalence of Abdominal Obesity in Spanish Children and Adolescents. Do We Need Waist Circumference Measurements in Pediatric Practice?

Background Evidence indicates that central adiposity has increased to a higher degree than general adiposity in children and adolescents in recent decades. However, waist circumference is not a routine measurement in clinical practice. Objective This study aimed to determine the prevalence of abdominal obesity based on waist circumferences (WC) and waist to height ratio (WHtR) in Spanish children and adolescents aged 6 to 17 years. Further, the prevalence of abdominal obesity (AO) among normal and overweight individuals was analyzed. Design Data were obtained from a study conducted from 1998 to 2000 in a representative national sample of 1521 children and adolescents aged 6 to 17 years (50.0% female) in Spain. WC and WHtR measurements were obtained in addition to BMI. AO was defined as WHtR ≥0.50 (WHtR-AO), sex and age specific WC≥90th percentile (WC-AO1), and sex and age specific WC cut-off values associated with high trunk fat measured by by dual-energy X-ray absorptiometry (WC-AO2). Results IOTF- based overweight and obsity prevalence was 21.5% and 6.6% in children and 17.4% and 5.2% in adolescents, respectively. Abdominal obesity (AO) was defined as WHtR≥0.50 (WHtR-AO), sex- and age-specific WC≥90th percentile (WC-AO1), and sex- and age-specific WC cut-off values associated with high trunk fat measured by dual-energy X-ray absorptiometry (WC-AO2). The respective prevalence of WHtR-AO, WC-AO1, and WC-AO2 was 21.3% (24.6% boys; 17.9% girls), 9.4% (9.1% boys; 9.7% girls), and 26.8% (30.6% boys;22.9% girls) in children and 14.3% (20.0% boys; 8.7% girls), 9.6% (9.8% boys; 9.5% girls), and 21.1% (28.8% boys; 13.7% girls) in adolescents. Conclusion The prevalence of AO in Spanish children and adolescents is of concern. The high proportion of AO observed in young patients who are normal weight or overweight indicates a need to include waist circumference measurements in routine clinical practice.
General criteria for the stochastic sum of measured harmonics at plant busses

Criteria are presented for constructing the probability density and cumulative functions of the amplitudes and phases of the harmonic currents and voltages at plant buses when the harmonic vs. time behavior in the plant branches is detected by on field measurements. In particular, the convolution and Monte Carlo methods are applied and the relevant results compared on the basis of simulated and experimental samples. The methods do not reply on assumptions pertinent to any kind of probability function. The significance of providing harmonic quantities associated with the occurrence probability is considered. Examples of applications based on real plant measurements and comparisons of the procedures used are included. <<ETX>>
ISIM: A Program for Grand Canonical Monte Carlo Simulations of the Ionic Environment of Biomolecules

In this work we present a new software package (ISIM), which represents a flexible, computational tool for simulations of electrolyte solutions via a grand canonical Monte Carlo procedure (GCMC) with a specific capability of treating biomolecules in solution. The GCMC method provides a powerful tool for studying the ionic environments of highly charged macromolecules with attention to the atomic detail of both the solute and the mobile counterions. The ISIM software differs from previous schemes mainly by treating different ion types independently and offering a new parameterization procedure for calibrating excess chemical potentials and bulk ion concentrations. Additionally, ISIM leverages the APBS software package to provide accurate descriptions of the biomolecular electrostatic potential through the efficient solution of Poisson's equation. ISIM has been validated on a variety of test systems; we successfully reproduce elementary properties of electrolyte solutions as well as theoretical and experimental results for challenging test systems like Calmodulin and DNA.
A novel method to predict protein-protein interactions based on the information of protein sequence

Protein-protein interactions (PPIs) are crucial for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. Unfortunately, the experimental methods for identifying PPIs are both time-consuming and expensive. Therefore, it is important to develop computational approaches for predicting PPIs. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on learning algorithm-Extreme Learning Machine (ELM) combined with a novel representation of local protein sequence descriptors. The local descriptors account for the interactions between residues in both continuous and discontinuous regions of a protein sequence, thus this method enables us to extract more PPI information from the protein sequences. ELM is a kind of accurate and fast-learning innovative classification method based on the random generation of the input-to-hidden-units weights followed by the resolution of the linear equations to obtain the hidden-to-output weights. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 89.09% prediction accuracy with 89.25% sensitivity at the precision of 88.96%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Achieved results show that the proposed approach is very promising for predicting PPI, and it can be a helpful supplement for PPIs prediction.
Long Tail in Weighted Lexical Networks

Lexical networks can be used with benefit for semantic analysis of texts, word sense disambiguation (WSD) and in general for graph-based Natural Language Processing. Usually strong relations between terms (e.g.: cat --> animal) are sufficient to help for the task, but quite often, weak relations (e.g.: cat --> ball of wool) are necessary. Our purpose here is to acquire such relations by means of online serious games as other classical approaches seems impractical. Indeed, it is difficult to ask the users (non experts) to define a proper weighting for the relations they propose, and then we decided to relate weights with the frequency of their propositions. It allows us to acquire first the strongest relations, but also to populate the long tail of an already existing network. Furthermore, trying to get an estimation of our network by the very users thanks to a tip of the tongue (TOT) software, we realized that they rather tend to favor the relations of the long tail and thus promote their emergence. Developing the long tail of a lexical network with standard and non-standard relations of low weight can be of advantage for tasks such that words retrieval from clues or WSD in texts.