Miracle-dz/UniFAR-FTUs huggingface dataset:
The Numerical Solution of Underwater Acoustic Propagation Problems Using Finite Difference and Finite Element Methods

Abstract : This report discusses various aspects of the numerical solution of underwater acoustic wave propagation problems. In the first part of the report, a model propagation problem based on the two-dimensional Helmholtz equation with a variable sound speed is considered. A finite element computer code for solving such problems was implemented at NRL on the VAX 11/780. A distinctive feature of the code is the implementation of a recently developed iterative method for solving the resulting large, sparse, indefinite, non-self-adjoint system of equations. This allowed for the efficient solution of over 35,000 complex equations on a relatively small computer. Some of the results obtained after applying this code to the model problem are described. Furthermore, additional modifications that can be made to the code to improve its efficiency and extend its applicability to more general propagation models are discussed. In the second part of this report, the general situation of the coupled acoustic/ elastic wave equation in two and three dimensions is considered. For example, this may correspond to an ocean environment in which there is ice on the surface as well as an irregularly shaped bottom structure. Finite difference and finite element methods for solving both the time harmonic and time dependent models are discussed. Various issues are considered that are important in determining the size of the problem that can be adequately treated. This includes the computer power as well as the mathematical and modeling techniques available.
A Generalization of Generalized Arc Consistency : From Constraint Satisfaction to Constraint-Based Inference

Arc consistency and generalized arc consistency are two of the most important local consistency techniques for binary and non-binary classic constraint satisfaction problems (CSPs). Based on the Semiring CSP and Valued CSP frameworks, arc consistency has also been extended to handle soft constraint satisfaction problems such as fuzzy CSP, probabilistic CSP, max CSP, and weighted CSP. This extension is based on an idempotent or strictly monotonic constraint combination operator. In this paper, we present a weaker condition for applying the generalized arc consistency approach to constraint-based inference problems other than classic and soft CSPs. These problems, including probability inference and maximal likelihood decoding, can be processed using generalized arc consistency enforcing approaches. We also show that, given an additional monotonic condition on the corresponding semiring structure, some of constraintbased inference problems can be approximately preprocessed using generalized arc consistency algorithms.
Comparison between DNA Detection in Trigeminal Nerve Ganglia and Serology to Detect Cattle Infected with Bovine Herpesviruses Types 1 and 5

Bovine herpesviruses (BoHVs) types 1 (BoHV-1) and 5 (BoHV-5) are alphaherpesviruses of major importance to the bovine production chain. Such viruses are capable of establishing latent infections in neuronal tissues. Infected animals tend to develop a serological response to infection; however, such response—usually investigated by antibody assays in serum—may eventually not be detected in laboratory assays. Nevertheless, serological tests such as virus neutralization (VN) and various enzyme-linked immunosorbent assays (ELISAs) are widely employed to check individual or herd status of BoHV infections. The correlation between detection of antibodies and the presence of viral nucleic acids as indicatives of infection in infected cattle has not been deeply examined. In order to investigate such correlation, 248 bovine serum samples were tested by VN to BoHV-1 and BoHV-5, as well as in a widely employed (though not type-differential) gB ELISA (IDEXX IBR gB X2 Ab Test) in search for antibodies to BoHVs. Immediately after blood withdrawal, cattle were slaughtered and trigeminal ganglia (TG) excised for DNA extraction and viral nucleic acid detection (NAD) by nested PCR. Neutralizing antibodies to BoHV-1 and/or BoHV-5 were detected in 44.8% (111/248) of sera, whereas the gB ELISA detected antibodies in 51.2% (127/248) of the samples. However, genomes of either BoHV-1, BoHV-5, or both, were detected in TGs of 85.9% (213/248) of the animals. These findings reveal that the assays designed to detect antibodies to BoHV-1 and/or BoHV-5 employed here may fail to detect a significant number of latently infected animals (in this study, 35.7%). From such data, it is clear that antibody assays are poorly correlated with detection of viral genomes in BoHV-1 and BoHV-5-infected animals.
C-terminal tail of human immunodeficiency virus gp41: functionally rich and structurally enigmatic

The human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) pandemic is amongst the most important current worldwide public health threats. While much research has been focused on AIDS vaccines that target the surface viral envelope (Env) protein, including gp120 and the gp41 ectodomain, the C-terminal tail (CTT) of gp41 has received relatively little attention. Despite early studies highlighting the immunogenicity of a particular CTT sequence, the CTT has been classically portrayed as a type I membrane protein limited to functioning in Env trafficking and virion incorporation. Recent studies demonstrate, however, that the Env CTT has other important functions. The CTT has been shown to additionally modulate Env ectodomain structure on the cell and virion surface, affect Env reactivity and viral sensitivity to conformation-dependent neutralizing antibodies, and alter cell–cell and virus–cell fusogenicity of Env. This review provides an overview of the Env structure and function with a particular emphasis on the CTT and recent studies that highlight its functionally rich nature.
Dissecting phylogenetic signal and accounting for bias in whole-genome data sets: a case study of the Metazoa

Transcriptome-enabled phylogenetic analyses have dramatically improved our understanding of metazoan phylogeny in recent years, although several important questions remain. The branching order near the base of the tree is one such outstanding issue. To address this question we assemble a novel data set comprised of 1,080 orthologous loci derived from 36 publicly available genomes and dissect the phylogenetic signal present in each individual partition. The size of this data set allows for a closer look at the potential biases and sources of non-phylogenetic signal. We assessed a range of measures for each data partition including information content, saturation, rate of evolution, long-branch score, and taxon occupancy and explored how each of these characteristics impacts phylogeny estimation. We then used these data to prepare a reduced set of partitions that fit an optimal set of criteria and are amenable to the most appropriate and computationally intensive analyses using site-heterogeneous models of sequence evolution. We also employed several strategies to examine the potential for long-branch attraction to bias our inferences. All of our analyses support Ctenophora as the sister lineage to other Metazoa, although support for this relationship varies among analyses. We find no support for the traditional view uniting the ctenophores and Cnidaria (jellies, anemones, corals, and kin). We also examine phylogenetic placement of myriapods (centipedes and millipedes) and find it more sensitive to the type of analysis and data used. Our study provides a workflow for minimizing systematic bias in whole genome-based phylogenetic analyses.
Written languaging with indirect feedback in writing revision: is feedback always effective?

Abstract Recent studies have shown that languaging contributes to second language skill development. Feedback is often used in combination with languaging as a prompt of verbalization during writing revision, and this combination has shown the effect of increasing the quality of writing. The present study tested whether and how indirect feedback helps learners engage in languaging, and whether the effects continued with the second new writing on the same topic. Forty participants engaged in a three-stage writing task: writing a first draft, revision with languaging with/without feedback on specific grammatical or lexical errors, and writing the second draft. Writing was multidimensionally assessed in terms of syntactic complexity, grammatical accuracy, and fluency. The results showed that the participants focused more on grammar when they were given feedback and succeeded in more error correction than when they did not receive feedback. Learners improved in fluency and slightly in accuracy, but not in complexity, regardless of the existence of indirect feedback. Importantly, written languaging with feedback did not show superiority to written languaging without feedback in skill development. The findings suggest that even metalinguistic correction induced by feedback is not always necessarily effective, but languaging may have a positive effect on overall writing quality.
Physical Activity in 3–6 Year Old Children Measured by SenseWear Pro®: Direct Accelerometry in the Course of the Week and Relation to Weight Status, Media Consumption, and Socioeconomic Factors

Background Data on objectively measured physical activity (PA) in preschoolers are controversial. Direct accelerometry was performed in children aged 3–6 years, and differences in PA patterns over the course of the week were evaluated. Data were analyzed with gender, BMI, lifestyle, and socioeconomic parameters as covariates. Methods PA was measured in 119 children by the SensewearPro® accelerometer and analyzed in the 92 (40 girls) that wore it for at least 4 days including one day of the weekend. Median measuring time in this group was 7 consecutive days (median/mean daily measuring time: 23.5 h/d and 21.8 h/d, respectively), corresponding to 834,000 analyzed minutes. PA questionnaires were completed by 103 parents and 87 preschool teachers to collect anthropometric, lifestyle, and socioeconomic data. Results Median daily PA (MET>3) was 4.3 hours (mean: 4.4 hours). Boys spent an estimated 52 min/week more being very active (MET>6) than girls (95% CI [6, 96] min/week, p = 0.02). PA was lower during the weekend (3.7 h/d) compared to weekdays (4.5 h/d), p = 3×10−6), where a 95% CI for the difference is [0.5, 1.0] h/d. PA levels did not differ between overweight/obese children (median 4.7 h/d) and normal-weight peers (median 4.2 h/d). Daily media consumption increased with decreasing social class on weekdays (p = 0.05) and during the weekend (p = 0.01), but was not related to the amount of daily PA. A multivariate regression with BMI-SDS as independent variable and gender, age, amount of PA>6 MET, parental BMI, media time and socioeconomic status as explanatory variables revealed that only SES had a significant contribution. Conclusion The negative impact of obesity-promoting factors in older children is rather low for preschoolers, but there is evidently a gradient in PA between weekdays and weekends already in this age group. Weight status of preschoolers is already considerably influenced by SES, but not physical activity levels.
On quantum Galois theory

The goals of the present paper are to initiate a program to systematically study and rigorously establish what a physicist might refer to as the “operator content of orbifold models. ” To explain what this might mean, and to clarify the title of the paper, we will assume that the reader is familiar with the algebraic formulation of 2-dimensional CFT in the guise of vertex operator algebras (VOA), see [B], [FLM] and [DM] for more information on this point. In the paper [DVVV], several ideas are proposed concerning the structure of a holomorphic orbifold. In other words, if V is a holomorphic VOA and if G is a finite group of automorphisms of V, then the sub VOA V G of G-invariants is itself a VOA and the subject of [DVVV] is very much concerned with speculation on the nature of the V -modules. It turns out to be more useful − at least for purpose of inductive proofs − to take V to be a simple VOA. We will then see that V G is also simple whenever G is a finite group of automorphisms of V. One consequence of our main results is the following:
Image tampering detection by blocking periodicity analysis in JPEG compressed images

Since JPEG image format has been a popularly used image compression standard, tampering detection in JPEG images now plays an important role. The artifacts introduced by lossy JPEG compression can be seen as an inherent signature for compressed images. In this paper, we propose a new approach to analyse the blocking periodicity by, 1) developing a linearly dependency model of pixel differences, 2) constructing a probability map of each pixelpsilas belonging to this model, and 3) finally extracting a peak window from the Fourier spectrum of the probability map. We will show that, for single and double compressed images, their peakspsila energy distribution behave very differently. We exploit this property and derive statistic features from peak windows to classify whether an image has been tampered by cropping and recompression. Experimental results demonstrate the validity of the proposed approach.
The moderating effect of a firm's internal climate for innovation on the impact of public R&D support programmes

This study investigates the influence of a firm's internal climate for innovation on the relationship between public R&D support and the innovation behaviour of the firm. We hypothesise that, if there is a positive relationship between public R&D support and a firm's innovation activities, this phenomenon is more likely to be observed in firms with an internal climate that promotes innovation, rather than in firms with a restrictive one. Based on a sample of 135 manufacturing firms in Singapore, we discover the significant moderating effect of a firm's internal climate for innovation on the impact of public R&D support on several measures of a firm's innovation input, output and collaboration behaviour. We identify two distinct dimensions of internal climate for innovation (organisational policies and individual attitudes), which exhibit different moderating effects.
Visualizing the Impact of Geographical Variations on Multivariate Clustering

Traditional multivariate clustering approaches are common in many geovisualization applications. These algorithms are used to define geodemographic profiles, ecosystems and various other land use patterns that are based on multivariate measures. Cluster labels are then projected onto a choropleth map to enable analysts to explore spatial dependencies and heterogeneity within the multivariate attributes. However, local variations in the data and choices of clustering parameters can greatly impact the resultant visualization. In this work, we develop a visual analytics framework for exploring and comparing the impact of geographical variations for multivariate clustering. Our framework employs a variety of graphical configurations and summary statistics to explore the spatial extents of clustering. It also allows users to discover patterns that can be concealed by traditional global clustering via several interactive visualization techniques including a novel drag & drop clustering difference view. We demonstrate the applicability of our framework over a demographics dataset containing quick facts about counties in the continental United States and demonstrate the need for analytical tools that can enable users to explore and compare clustering results over varying geographical features and scales.
Reaching in Depth: Hand Position Dominates over Binocular Eye Position in the Rostral Superior Parietal Lobule

Neural activity was recorded in area PE (dorsorostral part of Brodmann's area 5) of the posterior parietal cortex while monkeys performed arm reaching toward memorized targets located at different distances from the body. For any given distance, arm movements were performed while the animal kept binocular eye fixation constant. Under these conditions, the activity of a large proportion (36%) of neurons was modulated by reach distance during the memory period. By varying binocular eye position (vergence angle) and initial hand position, we found that the reaching-related activity of most neurons (61%) was influenced by changing the starting position of the hand, whereas that of a smaller, although substantial, population (13%) was influenced by changes of binocular eye position (i.e., by the angle of vergence). Furthermore, the modulation of the neural activity was better explained expressing the reach movement end-point, corresponding to the memorized target location, in terms of distance from the initial hand position, rather than from the body. These results suggest that the activity of neurons in area PE combines information about eye and hand position to encode target distance for reaching in depth predominantly in hand coordinates. This encoding mechanism is consistent with the position of PE in the functional gradient that characterizes the parieto-frontal network underlying reaching.
The organizational effect of collective teacher efficacy: A study of student test scores and high schools with large concentrations of minority students

This study examined collective teacher efficacy along with student mathematics and reading test scores on a nationally representative sample of high school students and their schools. Collective teacher efficacy is defined as a group of teachers' shared belief in their ability to promote learning and positive student outcomes. For this study, this construct is conceptualized as an aspect of the informal organization of schools, whereas other factors, such as curriculum tracking, are considered to be an aspect of the formal organization of schools. Prior research into collective teacher efficacy as an organizational construct found evidence of a positive relationship with student achievement scores, though peer-reviewed studies have not been done on a national sample of students. In addition, there has been no research on the possible moderating effects of collective teacher efficacy. I used a national dataset, the National Longitudinal Survey of 1988, and hierarchical linear modeling as the quantitative method. Contrary to prior research, I found no evidence that collective teacher efficacy had any effect on high school mathematics or reading test scores. It was not associated with either outcome, nor did it moderate the effect of the school's minority enrollment. Moreover, the largest predictor of high school test scores was prior achievement, which suggests that future research should examine school effects for young children. While this study confirmed the existence of an achievement gap between minority and majority students within schools, this gap did not vary between schools and thus, could not be modeled as a function of school characteristics. One school measure, academic press, had an impact only after controlling for average prior achievement. Additional efforts should be made to develop better measures of school organization, particularly the informal aspects of schooling, such as a school's academic press.
APPLICATION OF A RECURRENT NEURAL NETWORK IN ON- LINE MODELLING OF REAL-TIME SYSTEMS ∗

Given the universal approximation properties, simplicity as well its intrinsic analogy to the non-linear state space form, a recurrent Elman network is derived and applied for modelling non-linear plants. Learning is implemented on-line, based on input and output data and using a truncated backpropagation through time algorithm. Regarding its structural simplicity, previous knowledge based on a linear description of the plant to be modelled might be used for initialising the network weights. The main goal of this work is to emphasise the potential benefits of this architecture for real-time identification. Experimental results collected from a laboratory heating system, for several operating conditions, confirm the viability and effectiveness of the proposed methodology.
On the Quality of Spectral Separators

Computing graph separators is an important step in many graph algorithms. A popular technique for finding separators involves spectral methods. However, there has not been much prior analysis of the quality of the separators produced by this technique; instead it is usually claimed that spectral methods "work well in practice. " We present an initial attempt at such an analysis. In particular, we consider two popular spectral separator algorithms and provide counterexamples showing that these algorithms perform poorly on certain graphs. We also consider a generalized definition of spectral methods that allows the use of some specified number of the eigenvectors corresponding to the smallest eigenvalues of the Laplacian matrix of a graph, and we show that if such algorithms use a constant number of eigenvectors, then there are graphs for which they do no better than using only the second smallest eigenvector. Furthermore, using the second smallest eigenvector of these graphs produces partitions that are poor with respect to bounds on the gap between the isoperimetric number and the cut quotient of the spectral separator. Even if a generalized spectral algorithm uses $n^\epsilon$ for \mbox{$0 < \epsilon < \frac{1}{4}$} eigenvectors, there exist graphs for which the algorithm fails to find a separator with a cut quotient within \mbox{$n^{\frac{1}{4} - \epsilon} - 1$} of the isoperimetric number. We also introduce some facts about the structure of eigenvectors of certain types of Laplacian and symmetric matrices; these facts provide the basis for the analysis of the counterexamples. Finally, we discuss some developments in spectral partitioning that have occurred since these results first appeared.
Foreground Object Detection and Tracking for Visual Surveillance System: A Hybrid Approach

Foreground detection is one of the fundamental preprocessing steps in many image processing and computer vision applications. In spite of significant efforts, however, slowly moving foregrounds or temporarily stationary foregrounds remains challenging problem. To address these problems, this paper presents a hybrid approach, which combines background segmentation and long-term tracking with selective tracking and reducing search area, we robustly and effectively detect the foreground objects. The evaluation of realistic sequences from i-LIDS dataset shows that the proposed methodology outperforms with most of the state-of-the-art methods.
Control of Invasive Salmonella Disease in Africa: Is There a Role for Human Challenge Models?

Invasive Salmonella disease in Africa is a major public health concern. With evidence of the transcontinental spread of the Salmonella Typhi H58 haplotype, improved estimates of the burden of infection and understanding of the complex interplay of factors affecting disease transmission are needed to assist with efforts aimed at disease control. In addition to Salmonella Typhi, invasive nontyphoidal Salmonella are increasingly recognized as an important cause of febrile illness and mortality in sub-Saharan Africa. Human experimental oral challenge studies with Salmonella can be used as a model to offer unique insights into host–pathogen interactions as well as a platform to efficiently test new diagnostic and vaccine candidates. In this article, we review the background and use of human challenge studies to date and discuss how findings from these studies may lead to progress in the control of invasive Salmonella disease in Africa.