Miracle-dz/UniFAR-FTUs huggingface dataset:
Power laws and the AS-level internet topology

In this paper, we study and characterize the topology of the Internet at the autonomous system (AS) level. First, we show that the topology can be described efficiently with power laws. The elegance and simplicity of the power laws provide a novel perspective into the seemingly uncontrolled Internet structure. Second, we show that power laws have appeared consistently over the last five years. We also observe that the power laws hold even in the most recent and more complete topology with correlation coefficient above 99% for the degree-based power law. In addition, we study the evolution of the power-law exponents over the five-year interval and observe a variation for the degree-based power law of less than 10%. Third, we provide relationships between the exponents and other topological metrics.
Generalized Free Choice and Missing Alternatives

In this article I propose that there are unembedded disjunctions which receive a conjunctive interpretation via recursive implicature computation. This is unexpected: since disjunction competes with conjunction, implicature computation will usually result in the negation of the conjunctive alternative. I argue that certain disjunctions do not compete with a conjunctive alternative, due to a constraint on the assertability of scalar alternatives. As a result, recursive implicature computation can strengthen matrix or into and in these cases. I discuss the pragmatic factors driving recursive implicature computation, as well as the scope of the proposed assertability condition on alternatives.
The magnetic structure of our Galaxy: a review of observations

Abstract The magnetic structure in the Galactic disk, the Galactic center and the Galactic halo can be delineated more clearly than ever before. In the Galactic disk, the magnetic structure has been revealed by starlight polarization within 2 or 3 kpc of the Solar vicinity, by the distribution of the Zeeman splitting of OH masers in two or three nearby spiral arms, and by pulsar dispersion measures and rotation measures in nearly half of the disk. The polarized thermal dust emission of clouds at infrared, mm and submm wavelengths and the diffuse synchrotron emission are also related to the large-scale magnetic field in the disk. The rotation measures of extragalactic radio sources at low Galactic latitudes can be modeled by electron distributions and large-scale magnetic fields. The statistical properties of the magnetized interstellar medium at various scales have been studied using rotation measure data and polarization data. In the Galactic center, the non-thermal filaments indicate poloidal fields. There is no consensus on the field strength, maybe mG, maybe tens of μG. The polarized dust emission and much enhanced rotation measures of background radio sources are probably related to toroidal fields. In the Galactic halo, the antisymmetric RM sky reveals large-scale toroidal fields with reversed directions above and below the Galactic plane. Magnetic fields from all parts of our Galaxy are connected to form a global field structure. More observations are needed to explore the untouched regions and delineate how fields in different parts are connected.
Laplacian Mesh Processing

Surface representation and processing is one of the key topics in computer graphics and geometric modeling, since it greatly affects the range of possible applications. In this paper we will present recent advances in geometry processing that are related to the Laplacian processing framework and differential representations. This framework is based on linear operators deﬁned on polygonal meshes, and furnishes a variety of processing applications, such as shape approximation and compact representation, mesh editing, watermarking and morphing. The core of the framework is the deﬁnition of differential coordinates and new bases for efﬁcient mesh geometry representation, based on the mesh Laplacian operator.
Nonsmooth Optimization Techniques for Semisupervised Classification

We apply nonsmooth optimization techniques to classification problems, with particular reference to the transductive support vector machine (TSVM) approach, where the considered decision function is nonconvex and nondifferentiable, hence difficult to minimize. We present some numerical results obtained by running the proposed method on some standard test problems drawn from the binary classification literature.
Reducing Error in Context-Sensitive Crowdsourced Tasks

Most research in quality control in crowdsourced workflows has focused on microtasks, wherein quality can be improved by assigning tasks to multiple workers and interpreting the output as a function of workers' agreement. Not all work fits into microtask frameworks, however, especially work that requires significant training or time per task. In such a context-heavy crowd work system with limited budget for task redundancy, we propose three novel techniques for reducing task error: (1) A self-policing crowd hierarchy in which trusted workers review, correct, and improve entry-level workers' output (2) predictive modeling of task error that improves data quality through targeted redundancy, and (3) holistic modeling of worker performance that supports crowd management strategies designed to improve average crowd worker quality and allocate training to the workers that need the most assistance.
A Generalized Kernel Approach to Structured Output Learning

We study the problem of structured output learning from a regression perspective. We first provide a general formulation of the kernel dependency estimation (KDE) approach to this problem using operator-valued kernels. Our formulation overcomes the two main limitations of the original KDE approach, namely the decoupling between outputs in the image space and the inability to use a joint feature space. We then propose a covariance-based operator-valued kernel that allows us to take into account the structure of the kernel feature space. This kernel operates on the output space and only encodes the interactions between the outputs without any reference to the input space. To address this issue, we introduce a variant of our KDE method based on the conditional covariance operator that in addition to the correlation between the outputs takes into account the effects of the input variables. Finally, we evaluate the performance of our KDE approach on three structured output problems, and compare it to the state-of-the-art kernel-based structured output regression methods.
Direct Metagenomic Detection of Viral Pathogens in Nasal and Fecal Specimens Using an Unbiased High-Throughput Sequencing Approach

With the severe acute respiratory syndrome epidemic of 2003 and renewed attention on avian influenza viral pandemics, new surveillance systems are needed for the earlier detection of emerging infectious diseases. We applied a “next-generation” parallel sequencing platform for viral detection in nasopharyngeal and fecal samples collected during seasonal influenza virus (Flu) infections and norovirus outbreaks from 2005 to 2007 in Osaka, Japan. Random RT-PCR was performed to amplify RNA extracted from 0.1–0.25 ml of nasopharyngeal aspirates (N = 3) and fecal specimens (N = 5), and more than 10 µg of cDNA was synthesized. Unbiased high-throughput sequencing of these 8 samples yielded 15,298–32,335 (average 24,738) reads in a single 7.5 h run. In nasopharyngeal samples, although whole genome analysis was not available because the majority (>90%) of reads were host genome–derived, 20–460 Flu-reads were detected, which was sufficient for subtype identification. In fecal samples, bacteria and host cells were removed by centrifugation, resulting in gain of 484–15,260 reads of norovirus sequence (78–98% of the whole genome was covered), except for one specimen that was under-detectable by RT-PCR. These results suggest that our unbiased high-throughput sequencing approach is useful for directly detecting pathogenic viruses without advance genetic information. Although its cost and technological availability make it unlikely that this system will very soon be the diagnostic standard worldwide, this system could be useful for the earlier discovery of novel emerging viruses and bioterrorism, which are difficult to detect with conventional procedures.
Ordered Cloned DNA Map of the Genome ofVibrio cholerae 569B and Localization of Genetic Markers

ABSTRACT By using a low-resolution macrorestriction map as the foundation (R. Majumder et al., J. Bacteriol. 176:1105–1112, 1996), an ordered cloned DNA map of the 3.2-Mb chromosome of the hypertoxinogenic strain 569B of Vibrio cholerae has been constructed. A cosmid library the size of about 4,000 clones containing more than 120 Mb ofV. cholerae genomic DNA (40-genome equivalent) was generated. By combining landmark analysis and chromosome walking, the cosmid clones were assembled into 13 contigs covering about 90% of theV. cholerae genome. A total of 92 cosmid clones were assigned to the genome and to regions defined by NotI,SfiI, and CeuI macrorestriction maps. Twenty-seven cloned genes, 9 rrn operons, and 10 copies of a repetitive DNA sequence (IS1004) have been positioned on the ordered cloned DNA map.
H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus

Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body’s resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient’s data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.
Meeting acts: a labeling system for group interaction in meetings

We describe a new system for labeling speech corpora with high-level group interaction tags, called “meeting acts. ” The system was motivated by a need to assess work seeking to automatically detect meeting style using dialog act information. We present information about the relationships seen between dialog act sequences and meeting style to motivate the labeling process. We provide a summary of the annotation system and labeling procedure, as well as preliminary inter-annotator reliability statistics on the ICSI Meeting Recorder Corpus.
Concept of a Work Management System in Nokia: Focusing on Goals Instead of Process Phases

Complex systems development requires different ways of working than largely used static process oriented work. In practice, workers invent new ways of working to deal with appearing challenges. Thus, a company’s processes and tools should support these new process paths. Instead of defining a specific flow to conduct the work, several options for work processes should be allowed. This paper introduced the main findings of a case study conducted in a complex product development environment. The goal of the case study was to improve the company’s process support, based on the results of semi-structured interviews and the viewpoints of cognitive approach. The paper points out that it is important to focus on the goals for the work than the actual process phases and task descriptions. As a result of the study, the concept of a Work Management System (WMS) is proposed. The paper introduces this concept and discusses in details the main benefits of using a WMS.
Action Classification with Locality-Constrained Linear Coding

We propose an action classification algorithm which uses Locality-constrained Linear Coding (LLC) to capture discriminative information of human body variations in each spatio-temporal subsequence of a video sequence. Our proposed method divides the input video into equally spaced overlapping spatio-temporal sub sequences, each of which is decomposed into blocks and then cells. We use the Histogram of Oriented Gradient (HOG3D) feature to encode the information in each cell. We justify the use of LLC for encoding the block descriptor by demonstrating its superiority over Sparse Coding (SC). Our sequence descriptor is obtained via a logistic regression classifier with L2 regularization. We evaluate and compare our algorithm with ten state-of-the-art algorithms on five benchmark datasets. Experimental results show that, on average, our algorithm gives better accuracy than these ten algorithms.
Selection of Protease-Positive and Protease-Negative Variants of Streptococcus cremoris

Protease-negative variants were shown to outcompete the wild-type strains of Streptococcus cremoris E8, HP, and Wg2 at pH values higher than 6.0 in milk. For S. cremoris E8 this process was studied in more detail. At lower pH values the wild type had a selective advantage. This pH-dependent selection was not found in all media tested. The poor growth of the protease-negative variant at low pH was not due to lower internal pH values. By growing S. cremoris E8 and Wg2 in acidified milk (pH 5.9) the proteolytic activity of the cultures could be stabilized. In continuous cultures under amino acid limitation the wild type S. cremoris E8 and HP strains had a selective advantage over the protease-negative variants at low dilution rates (D < 0.2) at all pH values of the medium. This was apparently due to a lower affinity-constant (Ks) of the protease-positive variants for amino acids. Finally, a high fraction of protease-positive variants could be maintained in continuous cultures by using a growth medium with low concentrations of casein as a nitrogen source. At high dilution rates nearly all cells were protease positive.
An Extended Shortest Path Problem with Switch Cost Between Arcs

—Computing the shortest path in a graph is an important problem and it is very useful in various applications. The standard shortest path problem has been studied extensively and intensively, but it can’t handle the situation when there is a switch cost between arcs. For example, in a train transportation network, the switch cost between arcs contains waiting time in stations, times of transfer and so on. Obviously, the switch cost is an important factor for users to make decisions. Taking into consideration of the switch cost between arcs, we extend the standard shortest path problem and propose an algorithm and its optimized version to solve the extended single source shortest path problem. Test results show that the proposed algorithms can give reasonable and acceptable results for users.
Health Problems Presented to Family Practices in The Netherlands 1 Year Before and 1 Year After a Disaster

Background: Disasters often have negative health consequences. Studies of health problems presented in family practice before and after a disaster are rare. The present study analyzed health problems before and after a disaster and predictors of increased morbidity after the disaster as presented in family practice. Methods: A matched cohort study design with measurements 1 year before the disaster and 1 year after the disaster. Victims (N = 9183) and matched controls (N = 7066) were surveyed in the electronic medical records of 30 family practices after the explosions of a fireworks depot in The Netherlands. All health problems were registered using the International Classification of Primary Care. Results: Victims showed significantly higher prevalence rates for psychological problems after the disaster than before the disaster (422 vs133 per 1000 person-years; P < .001) and for problems of the musculoskeletal system (450 vs 401 per 1000 person-years; P < .05). Relocation because of the disaster (odds ratio, 10.65; 95% confidence interval, 8.15–13.94) and, to a lesser degree, psychological morbidity before the disaster (odds ratio, 2.31; 95% confidence interval, 1.42–3.76) were the strongest predictors of psychological problems after the disaster. Conclusion: The results suggested that forced relocation and a history of psychological problems were risk factors to post-disaster psychological problems of victims presenting to a family practice.
Numerical investigation of the recrystallization kinetics by means of the KWC phase-field model with special order parameters

The present paper proposes an extension to the phase-field model of Kobayashi, Warren and Carter (KWC) as described in (Warren et al 2002 Acta Mater.) to incorporate the recrystallization process which occurs during heat treatments of alloy systems with predeformed defect structure. The standard KWC model is extended by an additional order parameter for recrystallized grains and describes the general results for the steady-state moving boundary. The simulation results of the initial grain growth and recrystallization process in various systems show that the extended phase-field model is able to describe the influence of the initial grain boundaries on the recrystallization kinetics and to incorporate the misorientation dependency of the low angle grain boundary mobility which strongly influences the orientation distribution in the resulting microstructure.
Evaluating the Inferential Utility of Lexical-Semantic Resources

Lexical-semantic resources are used extensively for applied semantic inference, yet a clear quantitative picture of their current utility and limitations is largely missing. We propose system- and application-independent evaluation and analysis methodologies for resources' performance, and systematically apply them to seven prominent resources. Our findings identify the currently limited recall of available resources, and indicate the potential to improve performance by examining non-standard relation types and by distilling the output of distributional methods. Further, our results stress the need to include auxiliary information regarding the lexical and logical contexts in which a lexical inference is valid, as well as its prior validity likelihood.
Prevalence of quadruplexes in the human genome

Guanine-rich DNA sequences of a particular form have the ability to fold into four-stranded structures called G-quadruplexes. In this paper, we present a working rule to predict which primary sequences can form this structure, and describe a search algorithm to identify such sequences in genomic DNA. We count the number of quadruplexes found in the human genome and compare that with the figure predicted by modelling DNA as a Bernoulli stream or as a Markov chain, using windows of various sizes. We demonstrate that the distribution of loop lengths is significantly different from what would be expected in a random case, providing an indication of the number of potentially relevant quadruplex-forming sequences. In particular, we show that there is a significant repression of quadruplexes in the coding strand of exonic regions, which suggests that quadruplex-forming patterns are disfavoured in sequences that will form RNA.
PEAKS: identification of regulatory motifs by their position in DNA sequences

UNLABELLED Many DNA functional motifs tend to accumulate or cluster at specific gene locations. These locations can be detected, in a group of gene sequences, as high frequency 'peaks' with respect to a reference position, such as the transcription start site (TSS). We have developed a web tool for the identification of regions containing significant motif peaks. We show, by using different yeast gene datasets, that peak regions are strongly enriched in experimentally-validated motifs and contain potentially important novel motifs. AVAILABILITY http://genomics.imim. es/peaks
Eschenburg space as gravity dual of flavored = 4 Chern-Simons-matter theory

We find a 3D flavored = 4 Chern-Simons-matter theory, a kind of = 3 SCFT, has a gravity dual AdS4 × 7(t1, t2, t3) where three coprime parameters can be read off according to the number and charge of 5-branes in the dual Type IIB string setup. Because 7(t1, t2, t3) has been known in literature as Eschenburg space, we exploit some of its properties to examine the correspondence between two sides.
SaFT: Reliable Transport in Mobile Networks

End-to-end transport protocols perform poorly in mobile environments, primarily due to the frequent route breaks induced by node mobility. We present a framework for hop-by-hop transport protocols and propose a new reliable transport protocol: SaFT (store-and-forward transport). We evaluate its performance in mobile ad hoc networks vis-a-vis TCP. Overall, SaFT achieves up to 3 times faster delivery of messages in such networks. We conclude that store-and-forward protocols are suited well to provide reliable communication in mobile ad hoc networks
Limited-Use Atomic Snapshots with Polylogarithmic Step Complexity

This article presents a novel implementation of a snapshot object for n processes, with O(log2 b log n) step complexity for update operations and O(log b) step complexity for scan operations, where b is the number of updates. The algorithm uses only reads and writes. For polynomially many updates, this is an exponential improvement on previous snapshot algorithms, which have linear step complexity. It overcomes the existing Ω(n) lower bound on step complexity by having the step complexity depend on the number of updates. The key to this implementation is the construction of a new object consisting of a pair of max registers that supports a scan operation.