Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical techniques for performance estimation of processors

Performance estimation of processor is important to select the right processor for an application. Poorly chosen processors can either under perform very badly or over perform but with high cost. Most previous work on performance estimation are based on generating the development tools, i.e., compilers, assemblers etc from a processor description file and then additionally generating an instruction set simulator to get the performance. In this work we present a simpler strategy for performance estimation. We propose an estimation technique based on the intermediate format of an application. The estimation process does not require the generation of all the development tools as in the prevalent methods. As a result our method is not only cheaper but also faster.
Identifying Topic-Sensitive Influential Spreaders in Social Networks

Identifying influential spreaders is an important issue in understanding the dynamics of information diffusion in social networks. It is to find a small subset of nodes, which can spread the information or influence to the largest number of nodes. The conventional approaches consider information diffusion through the network in a coarse-grained manner, without taking into account the topical features of information content and users. However, for messages with different topics, the target influential spreaders may vary largely. In this paper, we propose to harness historical propagation data to learn the information diffusion probabilities on topic-level, based on which we use a greedy algorithm to iteratively select a set of influential nodes for a given topic. Specially, we design a three-stage algorithm named TopicRank to mine the most influential spreaders with respect to a specific topic. Given observed propagation data, we first use Latent Dirichlet Allocation (LDA) model to learn a topic mixture for each propagation message. Then, the topic-level diffusion probability of an edge is computed by exploiting the propagation actions occurred to it and the topic distribution of these propagation messages. Last, based on the learned topic-level diffusion probabilities, we apply optimized greedy algorithm CLEF to identify influential nodes with respect to a specific topic. Experimental results show that our method significantly outperforms state-of-the-art methods when used for topic-sensitive information spread maximization.
Autonomous vehicle sequencing algorithm at isolated intersections

In this paper, we study a theoretical traffic control problem with the consideration of vehicle-to-infrastructure communications. During the control process, vehicles approaching the intersection inform the control center their data, then the control center authorizes each vehicle a precise time to cross intersection by analyzing the received information. Our objective is to minimize the time of evacuating all autonomous vehicles at intersection and the key point is to decide an optimal vehicle passing order. An dynamic programming algorithm is proposed to solve this problem.
Wave turbulence in incompressible Hall magnetohydrodynamics

We investigate the steepening of the magnetic fluctuation power law spectra observed in the inner Solar wind for frequencies higher than 0.5 Hz. This high frequency part of the spectrum may be attributed to dispersive nonlinear processes. In that context, the long-time behavior of weakly interacting waves is examined in the framework of three-dimensional incompressible Hall magnetohydrodynamic (MHD) turbulence. The Hall term added to the standard MHD equations makes the Alfvén waves dispersive and circularly polarized. We introduce the generalized Elsässer variables and, using a complex helicity decomposition, we derive for three-wave interaction processes the general wave kinetic equations; they describe the nonlinear dynamics of Alfvén, whistler and ion cyclotron wave turbulence in the presence of a strong uniform magnetic field $B_0 \^{e}_{\Vert}$. Hall MHD turbulence is characterized by anisotropies of different strength: (i) for wavenumbers $\textit{kd}_{\rm i}\,{\gg}\,1$ ($d_{\rm i}$ is the ion inertial length) nonlinear transfers are essentially in the direction perpendicular ($\perp$) to ${\bf B}_0$; (ii) for $\textit{kd}_{\rm i}\,{\ll}\,1$ nonlinear transfers are exclusively in the perpendicular direction; (iii) for $\textit{kd}_{\rm i} \sim 1$, a moderate anisotropy is predicted. We show that electron and standard MHD turbulence can be seen as two frequency limits of the present theory but the standard MHD limit is singular; additionally, we analyze in detail the ion MHD turbulence limit. Exact power law solutions of the master wave kinetic equations are given in the small- and large-scale limits for which we have, respectively, the total energy spectra $E(k_{\perp},k_{\Vert}) \sim k_{\perp}^{-5/2} |k_{\Vert}|^{-1/2}$ and $E(k_{\perp},k_{\Vert}) \sim k_{\perp}^{-2}$. An anisotropic phenomenology is developed to describe continuously the different scaling laws of the energy spectrum; one predicts $E(k_{\perp},k_{\Vert}) \sim k_{\perp}^{-2} |k_{\Vert}|^{-1/2} (1+k_{\perp}^2d_{\rm i}^2)^{-1/4}$. Non-local interactions between Alfvén, whistler and ion cyclotron waves are investigated; a non-trivial dynamics exists only when a discrepancy from the equipartition between the large-scale kinetic and magnetic energies happens.
Lack of Innate Interferon Responses during SARS Coronavirus Infection in a Vaccination and Reinfection Ferret Model

In terms of its highly pathogenic nature, there remains a significant need to further define the immune pathology of SARS-coronavirus (SARS-CoV) infection, as well as identify correlates of immunity to help develop vaccines for severe coronaviral infections. Here we use a SARS-CoV infection-reinfection ferret model and a functional genomics approach to gain insight into SARS immunopathogenesis and to identify correlates of immune protection during SARS-CoV-challenge in ferrets previously infected with SARS-CoV or immunized with a SARS virus vaccine. We identified gene expression signatures in the lungs of ferrets associated with primary immune responses to SARS-CoV infection and in ferrets that received an identical second inoculum. Acute SARS-CoV infection prompted coordinated innate immune responses that were dominated by antiviral IFN response gene (IRG) expression. Reinfected ferrets, however, lacked the integrated expression of IRGs that was prevalent during acute infection. The expression of specific IRGs was also absent upon challenge in ferrets immunized with an inactivated, Al(OH)3-adjuvanted whole virus SARS vaccine candidate that protected them against SARS-CoV infection in the lungs. Lack of IFN-mediated immune enhancement in infected ferrets that were previously inoculated with, or vaccinated against, SARS-CoV revealed 9 IRG correlates of protective immunity. This data provides insight into the molecular pathogenesis of SARS-CoV and SARS-like-CoV infections and is an important resource for the development of CoV antiviral therapeutics and vaccines.
The Use of Multithreaded Processors in DASH

DASH is a scalable shared memory multiprocessor architecture which employs directory based cache coherence. Due to the physical distribution of the memory in DASH, there is potential for long memory latency. Although a number of latency reducing and hiding techniques such caching, a weaker memory consistency model, and pre-fetching are employed by DASH, the use of Multithreaded processors is not currently included in the design. In this paper, the use of Multithreaded processors in the DASH architecture is examined. A processor architecture which incorporates multithreading with superscalar capabilities is proposed, and a general discussion of issues regarding multithreading as well as the incorporation of the proposed multithreaded processor into the existing DASH architecture is presented.
Robust Multi-Source Localization Over Planar Arrays Using MUSIC-Group Delay Spectrum

Subspace-based source localization methods utilize the spectral magnitude of the MUltiple SIgnal Classification (MUSIC) method. However, in all these methods, a large number of sensors are required to resolve closely spaced sources. A novel method for high resolution source localization based on the group delay of MUSIC is described in this work. The method can resolve both the azimuth and elevation angles of closely spaced sources using a minimal number of sensors over a planar array. At the direction of arrival (DOA) of the desired source, a transition is observed in the phase spectrum of MUSIC. The negative differential of the phase spectrum also called group delay, results in a peak at the DOA. The proposed MUSIC-Group delay spectrum defined as product of MUSIC-Magnitude (MM) and group delay spectra, resolves spatially close sources even under reverberation owing to its spatial additive property. This is illustrated by performing spectral analysis of the MUSIC-Group delay function under reverberant environments. A mathematical proof for the spatial additive property of group delay spectrum is also provided. Source localization error analysis, sensor perturbation analysis, and Cramér-Rao bound (CRB) analysis are then performed to verify the robustness of the MUSIC-Group delay method. Experiments on speech enhancement and distant speech recognition are also conducted on spatialized TIMIT and MONC databases. Experimental results obtained using objective performance measures and word error rates (WER) indicate reasonable robustness when compared to conventional source localization methods in literature.
Nonlinear Poisson–Nernst–Planck equations for ion flux through confined geometries

The mathematical modelling and simulation of ion transport through biological and synthetic channels (nanopores) is a challenging problem, with direct application in biophysics, physiology and chemistry. At least two major effects have to be taken into account when creating such models: the electrostatic interaction of ions and the effects due to size exclusion in narrow regions. While mathematical models and methods for electrostatic interactions are well-developed and can be transferred from other flow problems with charged particles, e.g. semiconductor devices, less is known about the appropriate macroscopic modelling of size exclusion effects. Recently several papers proposed simple or sophisticated approaches for including size exclusion effects into entropies, in equilibrium as well as off equilibrium. The aim of this paper is to investigate a second potentially important modification due to size exclusion, which often seems to be ignored and is not implemented in currently used models, namely the modification of mobilities due to size exclusion effects. We discuss a simple model derived from a self-consisted random walk and investigate the stationary solutions as well as the computation of conductance. The need of incorporating nonlinear mobilities in high density situations is demonstrated in an investigation of conductance as a function of bath concentrations, which does not lead to obvious saturation effects in the case of linear mobility.
Parity space hybrid system diagnosis under model uncertainty

In this paper, diagnosis for hybrid systems using a parity space approach that considers model uncertainty is proposed. The hybrid diagnoser is composed of modules which carry out the mode recognition and diagnosis tasks both based on residuals generated using a model. Both tasks interact each other since the diagnosis module adapts himself according to the current mode of the hybrid system. Moreover, the methodology takes into account the parameter uncertainty using a passive robust strategy. An adaptive threshold for residual evaluation is generated and the parity space approach is used to design a set of residuals for each mode. The proposed fault diagnosis approach for hybrid systems is illustrated on a part of the Barcelona sewer network.
Peer Review History Title (provisional) Preventing Renal and Cardiovascular Risk by Renal Function Assessment: Insights from a Cross- Sectional Study in Low-income Countries and the Us

BMJ Open publishes all reviews undertaken for accepted manuscripts. Reviewers are asked to complete a checklist review form (see an example) and are provided with free text boxes to elaborate on their assessment. These free text comments are reproduced below. Some articles will have been accepted based in part or entirely on reviews undertaken for other BMJ Group journals. These will be reproduced where possible.
Factors Associated with the Acquisition and Severity of Gestational Listeriosis

Gravid mammals are more prone to listeriosis than their nongravid counterparts. However, many features of the disease in gravid animals are not well defined. We determined, in mice, that increased susceptibility to lethal infection following oral inoculation begins surprisingly early in pregnancy and extends through embryonic development. Pregnancy did not demonstrably increase the spread of listeriae from the intestine to the liver and spleen in the initial 96 h period post inoculation. Consequently, it appeared that gravid animals were competent to contain an enteric infection, but in those instances where escape did occur, a lethal outcome was more likely. Interestingly, colonic colonization level and prevalence, measured 96 h post inoculation, was significantly higher in gravid individuals. In terms of human risk factors for listeriosis, our results suggest that the window of listeriosis susceptibility afforded by pregnancy may be open longer than previously appreciated. Our results also suggest that while gravid animals are competent to contain an enteric infection, enteric carriage rate may be more of a factor in defining disease incidence than previously considered.
Relevance and application of sortase and sortase-dependent proteins in lactic acid bacteria

Lactic acid bacteria (LAB) are a diverse group of Gram-positive bacteria found in a vast array of environments including dairy products and the human gastrointestinal tract (GIT). In both niches, surface proteins play a crucial role in mediating interactions with the surrounding environment. The sortase enzyme is responsible for covalently coupling a subset of sortase-dependent proteins (SDPs) to the cell wall of Gram-positive organisms through recognition of a conserved C-terminal LPXTG motif. Genomic sequencing of LAB and annotation has allowed for the identification of sortase and SDPs. Historically, sortase and SDPs were predominately investigated for their role in mediating pathogenesis. Identification of these proteins in LAB has shed light on their important roles in mediating nutrient acquisition through proteinase P as well as positive probiotic attributes including adhesion, mucus barrier function, and immune signaling. Furthermore, sortase expression signals in LAB have been exploited as a means to develop oral vaccines targeted to the GIT. In this review, we examine the collection of studies which evaluate sortase and SDPs in select species of dairy-associated and health promoting LAB.
BRENDA , the enzyme database : updates and major new developments

BRENDA (BRaunschweig ENzyme DAtabase) represents a comprehensive collection of enzyme and metabolic information, based on primary literature. The database contains data from at least 83 000 different enzymes from 9800 different organisms, classi®ed in ~4200 EC numbers. BRENDA includes biochemical and molecular information on classi®cation and nomenclature, reaction and speci®city, functional parameters, occurrence, enzyme structure, application, engineering, stability, disease, isolation and preparation, links and literature references. The data are extracted and evaluated from ~46 000 references, which are linked to PubMed as long as the reference is cited in PubMed. In the past year BRENDA has undergone major changes including a large increase in updating speed with >50% of all data updated in 2002 or in the ®rst half of 2003, the development of a new EC-tree browser, a taxonomy-tree browser, a chemical substructure search engine for ligand structure, the development of controlled vocabulary, an ontology for some information ®elds and a thesaurus for ligand names. The database is accessible free of charge to the academic community at http://www.brenda. uni-koeln.de.
Tiny Systematic Vote Manipulations Can Swing Elections 1

We examine the effects of a type of electoral fraud easily perpetrated by someone with access to the system software for a direct-recording electronic voting system. The hypothetical attacker modifies the software to arbitrarily change a small number of votes on each voting machine. We determine the effect of this manipulation on the electoral college results of the 2000 United States Presidential election. We conclude that changing only a single vote per electronic voting machine can change the outcome of the election.
Gary Becker's: A Theory of the Allocation of Time

Becker's (1965) paper, ‘A Theory of the Allocation of Time’ revolutionised the modelling of household behaviour, by unifying Marshallian demand functions for goods with labour supply and related time use decisions within the household. In this article, we first summarise Becker's time allocation model and associated key contributions, then we show how his original framework extends to modern collective household models. Becker, G.S. (1965). ‘A theory of the allocation of time’, Economic Journal, vol. 75(299), pp. 493–517.
Luminosity Indicators in Dusty Photoionized Environments

The luminosity of the central source in ionizing radiation is an essential parameter in a photoionized environment and is one of the most fundamental physical quantities one can measure. We outline a method of determining the luminosity for any emission‐line region using only infrared data. In dusty environments, grains compete with hydrogen in absorbing continuum radiation. Grains produce infrared emission, and hydrogen produces recombination lines. We have computed a very large variety of photoionization models, using ranges of abundances, grain mixtures, ionizing continua, densities, and ionization parameters. The conditions were appropriate for such diverse objects as H ii regions, planetary nebulae, starburst galaxies, and the narrow‐ and broad‐line regions of active nuclei. The ratio of the total thermal grain emission relative to Hβ (IR/Hβ) is the primary indicator of whether the cloud behaves as a classical Strömgren sphere (a hydrogen‐bounded nebula) or whether grains absorb most of the incident continuum (a dust‐bounded nebula). We find two global limits: when IR/Hβ<100, infrared recombination lines determine the source luminosity in ionizing photons; when IR/Hβ≫100, the grains act as a bolometer to measure the luminosity.
A Randomized Complexity-theoretic Model of Bio-inspired Mobile Epidemics via Close Contact

In this paper we present a randomized complexity theoretic model for those epidemics propagated via short-distance close contact. We prove that the contact-based epidemics problems fall into the Randomized Polynomial (RP) complexity class. We draw an analogy between our complexity-theoretic model and the complexity-theoretic foundation of modern cryptology. Both of them are built on top of the concept of “negligible”. In the crypto model, the failure probability of a provably secure system is negligible given the input metric n, which is the crypto key length. In our model, the failure probability of the infectious sources is negligible given the input metric ρ, which is the network density (the number of network nodes per unit area). In addition, this negligibility guarantee is an asymptotic invariant in the entire system.
Nber Working Paper Series Comparative Advantage, Complexity and Volatility

We are grateful to Arnaud Costinot, Miklos Koren and workshop participants at the University of Michigan and the 2009 AEA Meetings for helpful suggestions. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. ABSTRACT Less developed countries tend to experience higher output volatility, a fact that is, in part, explained by their specialization in more volatile sectors. This paper proposes theoretical explanations for this pattern of specialization-with the complexity of the goods playing a central role. Specifically, less developed countries with low levels of human capital, or alternately, with lower institutional ability to enforce contracts, will specialize in less complex goods which are also characterized by higher levels of output volatility. We provide novel empirical evidence that less complex industries are indeed more volatile.
A Review of distributions on the string landscape

We review some basic flux vacua counting techniques and results, focusing on the distributions of properties over different regions of the landscape of string vacua and assessing the phenomenological implications. The topics we discuss include: an overview of how moduli are stabilized and how vacua are counted; the applicability of effective field theory; the uses of and differences between probabilistic and statistical analysis (and the relation to the anthropic principle); the distribution of various parameters on the landscape, including cosmological constant, gauge group rank, and supersymmetry-breaking scale; "friendly landscapes;" open string moduli; the (in)finiteness of the number of phenomenologically viable vacua; etc. At all points, we attempt to connect this study to the phenomenology of vacua which are experimentally viable.
Complex Correlation Measure as a sensitive indicator of risk for sudden cardiac death in patients with depression

Heart rate variability (HRV) is reduced in patients with Major Depressive Disorder (MDD). We examined the sensitivity of a new nonlinear parameter, the Complex Correlation Measure (CCM) in patients with depression. Two-minute ECG recordings at rest with eyes-closed were analyzed. CCM was higher (0.36±0.1) in control participants compared to MDD (0.29±0.1), indicating a decrease in temporal variability associated with decreased parasympathetic function (Cohen's d = 0.7, p=0.0008). CCM also demonstrated a larger effect size than SD1 (Cohen's d = 0.5, p =0.0005) and SD2 (Cohen's d = 0.2, p = 0.015). These results highlight that depressed patients display a dampening of oscillations between parasympathetic and sympathetic input indicative of reduced functionality and increased risk of sudden cardiac death. CCM is a more sensitive measure of HRV, which provides additional information on HRV dynamics compared to SD1 and SD2 of the Poincaré plot distribution.
On cryptography with auxiliary input

We study the question of designing cryptographic schemes which are secure even if an arbitrary function f(sk) of the secret key is leaked, as long as the secret key sk is still (exponentially) hard to compute from this auxiliary input. This setting of auxiliary input is more general than the more traditional setting, which assumes that some of information about the secret key sk may be leaked, but sk still has high min-entropy left. In particular, we deal with situations where f(sk) information-theoretically determines the entire secret key sk. As our main result, we construct CPA/CCA secure symmetric encryption schemes that remain secure with exponentially hard-to-invert auxiliary input. We give several applications of such schemes. * We construct an average-case obfuscator for the class of point functions, which remains secure with exponentially hard-to-invert auxiliary input, and is reusable. * We construct a reusable and robust extractor that remains secure with exponentially hard-to-invert auxiliary input. Our results rely on a new cryptographic assumption, Learning Subspace-with-Noise (LSN), which is related to the well known Learning Parity-with-Noise (LPN) assumption.