Miracle-dz/UniFAR-FTUs huggingface dataset:
Norges Teknisk-naturvitenskapelige Universitet Iterative Numerical Methods for Sampling from High Dimensional Gaussian Distributions Iterative Numerical Methods for Sampling from High Dimensional Gaussian Distributions

Many applications require efficient sampling from Gaussian distributions. The method of choice depends on the dimension of the problem as well as the structure of the covariance-(Σ) or precision matrix (Q). The most common black-box routine for computing a sample is based on Cholesky factorisation. In high dimensions, computing the Cholesky factor of Σ or Q may be prohibitive due to massive fill-in. We compare different methods for computing the samples iteratively adapting ideas from numerical linear algebra. These methods assume that matrix-vector products, Qv, are fast to compute. We show that some of the methods are competitive and faster than Cholesky sampling and that a parallel version of one method on a Graphical Processing Unit (GPU) using CUDA can introduce a speed-up of up to 30x. Moreover, one method is used to sample from the posterior distribution of petroleum reservoir parameters in a North Sea field, given seismic reflection data on a large 3D grid.
FUNDAMENTAL STUDY, AND EQUIPMENT FOR SINTERING AND TESTING OF CERMET BODIES, I–III

Cermet bodies, † composed of metals and oxides, are being developed for high-temperature service. Part I covers the theoretical aspects of experiments of a fundamental chemistry nature which accompanied the laboratory development of test specimens. Compacts of metal powders (Xi, Fe, Co, Cr, and Cr-B) were fired at 2880° to 3500°F. on pure Al2O3 tile in various controlled atmospheres. The results indicate that a controlled layer of oxide on the surfaces of the metal-powder grains is essential for good bonding. Special furnaces, described in Part II, were necessary for the fundamental study and for sintering cermet specimens. Equipment for determining instantaneous modulus of rupture and tensile rupture, and longtime stress-rupture in bending at temperatures up to 2400°F. , is described in Part III.
A low power Dirac basis compressed sensing framework for EEG using a Meyer wavelet function dictionary

The energy required for Electroencephalography (EEG) transmission at the sensor node, in Wireless Body Area Networks (WBANs), is high relative to the sensor's battery size. The power consumption is dominated by sensing, processing and data transmission of the EEG. Many successful solutions based on Compressed Sensing (CS) and other techniques have been proposed. The transmission of a lower number of bits elongates the battery life of the sensor but results in high errors in the reconstructed signals at the receiver side. In this paper, we use CS to reduce the energy at the sensor. We also acquire the signal using a random sampling circuit (simulating a Dirac sensing matrix) which eliminates the use of a microcontroller at the sensor node. At the receiver end, we propose to recover the signal using a basis dictionary, which has a multiple band-pass Meyer wavelet. This is shown to result in low signal recovery error. The proposed dictionary promotes optimal sparse basis and optimal incoherence with the Dirac sensing Matrix. The proposed technique is shown to achieve low decompression errors at high compression rates such as 10:1. It also achieves ultra-low power consumption as the Meyer wavelet is incoherent with the random Dirac basis used for sampling. We show an analysis that indicates significant power consumption reduction.
Mining The Stock Market : Which Measure Is Best ?

In recent years, there has been a lot of interest in the database community in mining time series data. Surprisingly, little work has been done on verifying which measures are most suitable for mining of a given class of data sets. Such work is of crucial importance, since it enables us to identify similarity measures which are useful in a given context and therefore for which efficient algorithms should be further investigated. Moreover, an accurate evaluation of the performance of even existing algorithms is not possible without a good understanding of the data sets occurring in practice. In this work we attempt to fill this gap by studying similarity measures for clustering of similar stocks (which, of course, is an interesting problem on its own). Our approach is to cluster the stocks according to various measures (including several novel ones) and compare the results to the ”groundtruth” clustering based on the Standard and Poor 500 Index. Our experiments reveal several interesting facts about the similarity measures used for stock-market data.
Interleukin 10 and interferon gamma regulation of experimental Trypanosoma cruzi infection

Studies were undertaken to determine whether interleukin 10, (IL-10) a cytokine shown to inhibit interferon gamma (IFN-gamma) production, was involved in Trypanosoma cruzi infections in mice. Exogenous IFN-gamma protects mice from fatal infection with T. cruzi. Furthermore, resistant B6D2 mice developed fatal T. cruzi infections when treated with neutralizing anti-IFN-gamma monoclonal antibody (mAb). Thus, endogenous as well as exogenous IFN-gamma is important in mediating resistance to this parasite. Because both T. cruzi-susceptible (B6) and -resistant (B6D2) mouse strains produced IFN-gamma during acute infection, we looked for the concomitant production of mediators that could interfere with IFN-gamma-mediated resistance to T. cruzi. We found that IL-10-specific mRNA was produced in the spleens of mice with acute T. cruzi infections. In addition, spleen cell culture supernatants from infected B6 mice, and to a lesser extent B6D2 mice, elaborated an inhibitor(s) of IFN-gamma production. This inhibitor(s) was neutralized by anti-IL-10 mAb. These experiments demonstrated the production of biologically active IL-10 during T. cruzi infection. In further studies in vitro, it was shown that IL-10 blocked the ability of IFN-gamma to inhibit the intracellular replication of T. cruzi in mouse peritoneal macrophages. Thus, in addition to its known ability to inhibit the production of IFN-gamma, IL-10 (cytokine synthesis inhibitory factor), may also inhibit the effects of IFN-gamma. These experiments demonstrate that IL-10 is produced during infection with a protozoan parasite and suggest a regulatory role for this cytokine in the mediation of susceptibility to acute disease.
Enhancing the TDT Tracking Evaluation

Abstract Topic Detection and Tracking (TDT) is a DARPA-sponsored initiative concerned with finding groups of stories on the same topic (tdt, 1998). The goal is to build systems that can segment, detect, and track incoming news stories (possibly from multiple continuous feeds) with respect to pre-defined topics. While the detection task detects the first story on a particular topic, the tracking task determines, for each story, which topic it is relevant to. This paper will discuss the algorithm currently used for evaluating systems for the tracking task, present some of its limitation, and propose a new algorithm that enhances the current evaluation.
A Distributed Document Management Approach for Workflow Support in the DBSA Architecture

Large and distributed organizations have to face a com-plex management problem: keeping track of state informa-tion of every “entity” (person, property, project, etc.). A tra-ditional centralized database is not well suited if the com-munication between parts of the organization is not reli-able or not “always-on’. In this paper we present an archi-tecture, largely based on the distribution of formally struc-tured documents, designed to support the tracking of “statechanges” inside the organization.KeywordsDocument management, workﬂow, integration, distributedsystems, software architecture.
The Optimal Extraction Path of Exhaustible Resource with Environment Cost

Assuming in the perfectly competitive market, using the optimal control theory and making the social welfare as the maximization target, the paper studies on environment cost which impacts the optimal extraction path of exhaustible resource. The special case result shows that: the time of optimal exhaustion increases with the addition of marginal environmental cost, the price has negative linear correlation with the marginal environmental cost, and the optimal extraction has positive linear correlation with the marginal environmental cost.
Channel sounding technique using MIMO software radio architecture

This paper presents a novel channel sounding system based on MIMO software defined radio architecture. It was developed for the evaluation of the beyond 4 G mobile communication systems operating at 11 GHz in which the multi-link MIMO technology will be adopted. 4Ô4 MIMO channel sounder was developed as the first prototype, and the advantages and issues are discussed based on the several performance tests. As a results, the fundamental performance of the prototype sounder was assessed, hence the validity of proposed channel sounding technique was verified.
Characterization of insertion sites and development of locus-specific assays for three broiler-derived subgroup E avian leukosis virus proviruses

This report deals with the identification of novel elements belonging to a family of endogenous retroviruses, designated endogenous avian leukosis virus-type proviral elements (ALVE), that reside in the genome of the chicken and are closely related to exogenous avian leukosis viruses. The study of ALVE elements in the chicken genome serves as a model system for understanding the interplay between endogenous viruses and their vertebrate hosts in general, including humans. In this report, we characterize the insertion sites and describe locus-specific, diagnostic polymerase chain reaction-based assays for three previously discovered, but as yet not localized, ALVE elements. In addition, we assess the proviral integrity, provide the complete element sequence and examine the genomic environs of the three broiler-derived elements.
Statistical rate monotonic scheduling

Statistical rate monotonic scheduling (SRMS) is a generalization of the classical RMS results of C. Liu and J. Layland (1973) for periodic tasks with highly variable execution times and statistical QoS requirements. The main tenet of SRMS is that the variability in task resource requirements could be smoothed through aggregation to yield guaranteed QoS. This aggregation is done over time for a given task and across multiple tasks for a given period of time. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. SRMS feasibility test ensures that it is possible for a given periodic task set to share a given resource without violating any of the statistical QoS constraints imposed on each task in the set. The SRMS scheduling algorithm consists of two parts: a job admission controller and a scheduler. The SRMS scheduler is a simple, preemptive, fixed priority scheduler. The SRMS job admission controller manages the QoS delivered to the various tasks through admit/reject and priority assignment decisions. In particular it ensures the important property of task isolation, whereby tasks do not infringe on each other.
Genetic Characterization and Virulence Role of the RALP3/LSA Locus Upstream of the Streptolysin S Operon in Invasive M1T1 Group A Streptococcus

ABSTRACT Group A Streptococcus (GAS) is a leading human pathogen associated with a wide spectrum of mucosal and invasive infections. GAS expresses a large number of virulence determinants whose expression is under the control of several transcriptional regulatory networks. Here we performed the first mutational analysis of a genetic locus immediately upstream of the streptolysin S biosynthetic operon in several GAS genome sequences, including that of the M1T1 serotype, the leading isolates associated with serious invasive disease. The locus consists of a predicted RofA-like stand-alone transcriptional regulator (RALP3) and the largest open reading frame in the GAS genome, encoding a predicted LPXSG motif cell wall-anchored protein we have named LSA (for “large surface-anchored” protein). Comparative reverse transcription-PCR analysis of wild-type M1T1 GAS and an isogenic RALP3-deficient mutant identifies RALP3 as a global transcriptional regulator affecting expression of numerous virulence factor genes, including those for strong repression of the hyaluronic acid capsule and cysteine protease production. RALP3 contributed to GAS epithelial cell invasion and bloodstream survival. LSA was found to be under negative regulation by RALP3 and to influence GAS-epithelial cell interactions and GAS antimicrobial peptide sensitivity. Isogenic M1T1 GAS mutants lacking either RALP3 or LSA were attenuated in a murine model of systemic infection, indicating that this locus plays a role in the virulence potential of the organism.
TEXTURE AND STRUCTURE OF CRISPY‐PUFFED FOOD PRODUCTS PART II: MECHANICAL PROPERTIES IN PUNCTURE

A puncture test was used to describe the mechanical and textural behavior of crispy-puffed food extrudates. Four criteria were identified from the force-time curves: (1) the average puncturing force, F m , (2) the spatial frequency of structural ruptures, N wr , (3) the average specific force of structural ruptures, f wr , and (4) the crispness work, W c . The discriminating power of these criteria was shown through the effects of moisture content and recipe composition in the extrusion-cooking process. Relationships between puncture criteria were also studied. The effect of water activity showed that the force related criteria described well the mechanical behavior of expanded extrudates.
ProRata: A quantitative proteomics program for accurate protein abundance ratio estimation with confidence interval evaluation.

A profile likelihood algorithm is proposed for quantitative shotgun proteomics to infer the abundance ratios of proteins from the abundance ratios of isotopically labeled peptides derived from proteolysis. Previously, we have shown that the estimation variability and bias of peptide abundance ratios can be predicted from their profile signal-to-noise ratios. Given multiple quantified peptides for a protein, the profile likelihood algorithm probabilistically weighs the peptide abundance ratios by their inferred estimation variability, accounts for their expected estimation bias, and suppresses contribution from outliers. This algorithm yields maximum likelihood point estimation and profile likelihood confidence interval estimation of protein abundance ratios. This point estimator is more accurate than an estimator based on the average of peptide abundance ratios. The confidence interval estimation provides an "error bar" for each protein abundance ratio that reflects its estimation precision and statistical uncertainty. The accuracy of the point estimation and the precision and confidence level of the interval estimation were benchmarked with standard mixtures of isotopically labeled proteomes. The profile likelihood algorithm was integrated into a quantitative proteomics program, called ProRata, freely available at www.MSProRata. org.
The Surrey Emergency Care System: a countywide initiative for change

Modernisation is at the core of government policy. Within the NHS it has variously focused on accident and emergency, coronary heart disease, clinical governance and information technology although each strand has tended to operate in isolation. The Surrey Emergency Care System is a programme combining the strands into a single countywide initiative and that lays the technical and clinical foundations of a future integrated unscheduled care network. This paper describes the programme, its potential impact, and offers some insight into the barriers to change that the project has met so far.
Gathering lexical linked data and knowledge patterns from FrameNet

FrameNet is an important lexical knowledge base featuring cognitive plausibility, and grounded in a large corpus. Besides being actively used by the NLP community, frames are a great source of knowledge patterns once converted into a knowledge representation language. In this paper we present our experience in converting the 1.5 XML version of FrameNet into RDF datasets published on the Linked Open Data cloud, which are interoperable with WordNet and other resources. In the conversion we have used Semion, a new tool that allows a rule-based, customized pipeline from XML to RDF and OWL data. In addition, we introduce a method to select and refactor part of the information related to frames as full-fledged OWL knowledge patterns. This last result has required non-trivial assumptions on how to interpret FrameNet relations as formal knowledge.
Degradation of polycyclic aromatic hydrocarbons in the presence of synthetic surfactants

The biodegradation of polycyclic aromatic hydrocarbons (PAH) often is limited by low water solubility and dissolution rate. Nonionic surfactants and sodium dodecyl sulfate increased the concentration of PAH in the water phase because of solubilization. The degradation of PAH was inhibited by sodium dodecyl sulfate because this surfactant was preferred as a growth substrate. Growth of mixed cultures with phenanthrene and fluoranthene solubilized by a nonionic surfactant prior to inoculation was exponential, indicating a high bioavailability of the solubilized hydrocarbons. Nonionic surfactants of the alkylethoxylate type and the alkylphenolethoxylate type with an average ethoxylate chain length of 9 to 12 monomers were toxic to a PAH-degrading Mycobacterium sp. and to several PAH-degrading mixed cultures. Toxicity of the surfactants decreased with increasing hydrophilicity, i.e., with increasing ethoxylate chain length. Nontoxic surfactants enhanced the degradation of fluorene, phenanthrene, anthracene, fluoranthene, and pyrene.
Distributed Shared Memory for Roaming Large Volumes

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming
Multiclass semantic video segmentation with object-level active inference

We address the problem of integrating object reasoning with supervoxel labeling in multiclass semantic video segmentation. To this end, we first propose an object-augmented dense CRF in spatio-temporal domain, which captures long-range dependency between supervoxels, and imposes consistency between object and supervoxel labels. We develop an efficient mean field inference algorithm to jointly infer the supervoxel labels, object activations and their occlusion relations for a moderate number of object hypotheses. To scale up our method, we adopt an active inference strategy to improve the efficiency, which adaptively selects object subgraphs in the object-augmented dense CRF. We formulate the problem as a Markov Decision Process, which learns an approximate optimal policy based on a reward of accuracy improvement and a set of well-designed model and input features. We evaluate our method on three publicly available multiclass video semantic segmentation datasets and demonstrate superior efficiency and accuracy.
Multifilar hemispherical helical antennas

This investigation examines the radiation characteristics of a new bifilar hemispherical helical antenna. Directivity, E- and H-plane radiation patterns, axial ratio and input impedance of a few example designs are calculated. It is shown that the bifilar hemispherical helix provides a nearly constant gain over the measured bandwidth of about 14% and generally elliptical polarization with near circular polarization in limited cases.
Robust detection of P. aeruginosa and S. aureus acute lung infections by secondary electrospray ionization-mass spectrometry (SESI-MS) breathprinting: from initial infection to clearance

Before breath-based diagnostics for lung infections can be implemented in the clinic, it is necessary to understand how the breath volatiles change during the course of infection, and ideally, to identify a core set of breath markers that can be used to diagnose the pathogen at any point during the infection. In the study presented here, we use secondary electrospray ionization-mass spectrometry (SESI-MS) to characterize the breathprint of Pseudomonas aeruginosa and Staphylococcus aureus lung infections in a murine model over a period of 120 h, with a total of 86 mice in the study. Using partial least squares-discriminant analysis (PLS-DA) to evaluate the time-course data, we were able to show that SESI-MS breathprinting can be used to robustly classify acute P. aeruginosa and S. aureus mouse lung infections at any time during the 120 h infection/clearance process. The variable importance plot from PLS indicates that multiple peaks from the SESI-MS breathprints are required for discriminating the bacterial infections. Therefore, by utilizing the entire breathprint rather than single biomarkers, infectious agents can be diagnosed by SESI-MS independent of when during the infection breath is tested.
Wi-Fi Mobility Classification on a Mobile Phone for Energy Efficient Activity Tracking

Tracking user location and physical activity is quite common especially among fitness and utility applications on modern smartphones. However, use of GPS and accelerometer sensors to obtain such data is energy consuming and in general cannot be used for extended periods of time. In this paper we describe an approach to detect mobility states and thus turn on and off these energy consuming sensors using Wi-Fi analysis, which compared to GPS and accelerometer is much less power consuming. This allows us not only to save battery life but also to perform activity measurements throughout the whole day.
The Influence of Circulation Quenching on Temper Brittleness of Steel EA4T

In this paper, for the purpose of seeking the control methods of temper brittleness of steel EA4T, doing some experiments on steel EA4T by circulation quenching process . Then do some research about the influence of circulation quenching on temper brittleness of steel EA4T.The result proves that circulation quenching can render grain refinement and restrain the temper brittleness of steel EA4T, thus contract the temperature range of carbide precipitation in high temperature tempering; the result indicate that Circulation quenching restrain the temper brittleness of steel EA4T at 550°C.