Miracle-dz/UniFAR-FTUs huggingface dataset:
Intact Gram-Negative Helicobacter pylori, Helicobacter felis, and Helicobacter hepaticus Bacteria Activate Innate Immunity via Toll-Like Receptor 2 but Not Toll-Like Receptor 4

ABSTRACT Molecular and genetic studies have demonstrated that members of the Toll-like receptor (TLR) family are critical innate immune receptors. TLRs are recognition receptors for a diverse group of microbial ligands including bacteria, fungi, and viruses. This study demonstrates that distinct TLRs are responsible for the recognition of Helicobacter lipopolysaccharide (LPS) versus intact Helicobacter bacteria. We show that the cytokine-inducing activity of Helicobacter LPS was mediated by TLR4; i.e., TLR4-deficient macrophages were unresponsive to Helicobacter pylori LPS. Surprisingly, the cytokine response to whole Helicobacter bacteria (H. pylori, H. hepaticus, and H. felis) was mediated not by TLR4 but rather by TLR2. Studies of HEK293 transfectants revealed that expression of human TLR2 was sufficient to confer responsiveness to intact Helicobacter bacteria, but TLR4 transfection was not sufficient. Our studies further suggest that cag pathogenicity island genes may modulate the TLR2 agonist activity of H. pylori as cagA+ bacteria were more active on a per-cell basis compared to cagA mutant bacteria for interleukin-8 (IL-8) cytokine secretion. Consistent with the transfection studies, analysis of knockout mice demonstrated that TLR2 was required for the cytokine response to intact Helicobacter bacteria. Macrophages from both wild-type and TLR4-deficient mice produced a robust cytokine secretion response (IL-6 and MCP-1) when stimulated with intact Helicobacter bacteria. In contrast, macrophages from TLR2-deficient mice were profoundly unresponsive to intact Helicobacter stimulation, failing to secrete cytokines even at high (100:1) bacterium-to-macrophage ratios. Our studies suggest that TLR2 may be the dominant innate immune receptor for recognition of gastrointestinal Helicobacter species.
Doped polycrystalline 3C–SiC films with low stress for MEMS: part I. Deposition conditions and film properties

This paper details the development of low-stress, heavily-doped polycrystalline 3C–SiC films suitable for microelectromechanical systems applications. The films were deposited on 100 mm-diameter silicon (Si) and silicon dioxide (SiO2)-coated Si wafers in a large-volume, low-pressure chemical vapor deposition furnace using dichlorosilane (DCS) (SiH2Cl2) and acetylene (C2H2) as precursors and ammonia (NH3) as the dopant source gas. The effects of NH3 and deposition pressure on the deposition rate, film residual stress and electrical resistivity were studied. Deposition parameters optimized for a combination of resistivity and residual stress yielded an average resistivity of 0.02 Ω cm and a residual tensile stress of 59 MPa as measured using wafer-scale methods. X-ray photoelectron spectroscopy indicated that the nitrogen concentration in the films was less than 0.5 at%. Variations in the flow rate of NH3 did not affect the surface roughness of the films, but changes in deposition pressure had an obvious effect on the surface roughness.
Structural and Functional Characterizations of SsgB, a Conserved Activator of Developmental Cell Division in Morphologically Complex Actinomycetes*

SsgA-like proteins (SALPs) are a family of homologous cell division-related proteins that occur exclusively in morphologically complex actinomycetes. We show that SsgB, a subfamily of SALPs, is the archetypal SALP that is functionally conserved in all sporulating actinomycetes. Sporulation-specific cell division of Streptomyces coelicolor ssgB mutants is restored by introduction of distant ssgB orthologues from other actinomycetes. Interestingly, the number of septa (and spores) of the complemented null mutants is dictated by the specific ssgB orthologue that is expressed. The crystal structure of the SsgB from Thermobifida fusca was determined at 2.6 Å resolution and represents the first structure for this family. The structure revealed similarities to a class of eukaryotic “whirly” single-stranded DNA/RNA-binding proteins. However, the electro-negative surface of the SALPs suggests that neither SsgB nor any of the other SALPs are likely to interact with nucleotide substrates. Instead, we show that a conserved hydrophobic surface is likely to be important for SALP function and suggest that proteins are the likely binding partners.
Quantification of Na+,K+ pumps and their transport rate in skeletal muscle: Functional significance

During excitation, muscle cells gain Na+ and lose K+, leading to a rise in extracellular K+ ([K+]o), depolarization, and loss of excitability. Recent studies support the idea that these events are important causes of muscle fatigue and that full use of the Na+,K+-ATPase (also known as the Na+,K+ pump) is often essential for adequate clearance of extracellular K+. As a result of their electrogenic action, Na+,K+ pumps also help reverse depolarization arising during excitation, hyperkalemia, and anoxia, or from cell damage resulting from exercise, rhabdomyolysis, or muscle diseases. The ability to evaluate Na+,K+-pump function and the capacity of the Na+,K+ pumps to fill these needs require quantification of the total content of Na+,K+ pumps in skeletal muscle. Inhibition of Na+,K+-pump activity, or a decrease in their content, reduces muscle contractility. Conversely, stimulation of the Na+,K+-pump transport rate or increasing the content of Na+,K+ pumps enhances muscle excitability and contractility. Measurements of [3H]ouabain binding to skeletal muscle in vivo or in vitro have enabled the reproducible quantification of the total content of Na+,K+ pumps in molar units in various animal species, and in both healthy people and individuals with various diseases. In contrast, measurements of 3-O-methylfluorescein phosphatase activity associated with the Na+,K+-ATPase may show inconsistent results. Measurements of Na+ and K+ fluxes in intact isolated muscles show that, after Na+ loading or intense excitation, all the Na+,K+ pumps are functional, allowing calculation of the maximum Na+,K+-pumping capacity, expressed in molar units/g muscle/min. The activity and content of Na+,K+ pumps are regulated by exercise, inactivity, K+ deficiency, fasting, age, and several hormones and pharmaceuticals. Studies on the α-subunit isoforms of the Na+,K+-ATPase have detected a relative increase in their number in response to exercise and the glucocorticoid dexamethasone but have not involved their quantification in molar units. Determination of ATPase activity in homogenates and plasma membranes obtained from muscle has shown ouabain-suppressible stimulatory effects of Na+ and K+.
Decentralised minimal-time consensus

This study considers the discrete-time dynamics of a network of agents that exchange information according to the nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the consensus value of the whole network in finite time using only the minimal number of successive values of its own history. We show that this minimal number of steps is related to a Jordan block decomposition of the network dynamics and present an algorithm to obtain the minimal number of steps in question by checking a rank condition on a Hankel matrix of the local observations. Furthermore, we prove that the minimal number of steps is related to other algebraic and graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the underlying graph topology.
Adaptive signal analysis of immunological data

This paper aims to investigate whether both supervised and unsupervised signal analysis can contribute to the interpretation of immunological data. For this pur- pose a data base was set up containing cellular data from bmnchoalveolar lavage fluid which was obtained from 37 children with pulnionary diseases. The children were di- chotomized into two groups: 20 children suffered from chronic bronchitis whereas 17 children had an interstitial lung disease. A selforganizing map (SOM) and linear in- dependent component analysis were utilized to test higher- order correlations between cellular subsets and the patient gmups. Furthermore, a supervised approach with a per- ceptron trained to the patients' diagnosis was applied. The SOM confirmed rhe results that were expected from previ- ous statistical analyses. The results of the 1CA were rather weak, which liespresumably in the fact that a linear mixing model of independent sources does not hold; neverrheless, we couldfind parameters of high diagnosis influence that were confirmed by the perceptmn. The supervised percep- tron learning afterprincipal component analysis for dimen- sion reduction turned aut to be highly successful by linearly separating the patients into two groups with different diag- noses. The simplicity of the perceptmn made it easy to ex- tract diagnosis rules, which partly were known already and can now readily be tested on largerdata sets. In conclusion, neural network signal nnalysisprovidespmmising tools for rhe analysis of highly complex immunological data.
Towards a theory of cache-efficient algorithms

We present a model that enables us to analyze the running time of an algorithm on a computer with a memory hierarchy with limited associativity, in terms of various cache parameters. Our cache model, an extension of Aggarwal and Vitter's I/O model, enables us to establish useful relationships between the cache complexity and the I/O complexity of computations. As a corollary, we obtain cache-efficient algorithms in the single-level cache model for fundamental problems like sorting, FFT, and an important subclass of permutations. We also analyze the average-case cache behavior of mergesort, show that ignoring associativity concerns could lead to inferior performance, and present supporting experimental evidence.We further extend our model to multiple levels of cache with limited associativity and present optimal algorithms for matrix transpose and sorting. Our techniques may be used for systematic exploitation of the memory hierarchy starting from the algorithm design stage, and for dealing with the hitherto unresolved problem of limited associativity.
Learning a joint discriminative-generative model for action recognition

An action consists of a sequence of instantaneous motion patterns whose temporal ordering contains critical information especially for distinguishing fine-grained action categories. However, existing action recognition methods are dominated by discriminative classifiers such as kernel machines or metric learning with Bag-of-Words (BoW) action representations. They ignore the temporal structures of actions in exchange for robustness against noise. Although such temporal structures can be modelled explicitly using dynamic generative models such as Hidden Markov Models (HMMs), these generative models are designed to maximise the likelihood of the data therefore providing no guarantee on suitability for discrimination required by action recognition. In this work, a novel approach is proposed to explore the best of both worlds by discriminatively learning a generative action model. Specifically, our approach is based on discriminative Fisher kernel learning which learns a dynamic generative model so that the distance between the log-likelihood gradients induced by two actions of the same class is minimised. We demonstrate the advantages of the proposed model over the state-of-the-art action recognition methods using two challenging benchmark datasets of complex actions.
Control of induction motors for wide speed range for electric vehicle drives

A control scheme for induction motors suitable for electric vehicles is presented. The proposed scheme allows the motor to exploit the maximum torque capability in the whole speed range, shows a weak dependence on the motor parameters and is robust against fast variations of the dc-link voltage. It is based on a control algorithm that decreases the rotor flux as the requested voltage tends to overcome the available voltage. The proposed scheme produces a smooth transition into and out of the flux weakening region and a fast torque response. The feasibility of the whole control scheme is confirmed by experimental tests.
A Survey on Knowledge Extraction Techniques for Semantic Web

Nowadays the Web has demonstrated as a wealthy, remarkable and marvellous data source of information. More than one domains can be viewed and mined in the web. Data mining in web is known as web mining. Objectives of web data mining is taken in searching relevant and reliable and meaningful knowledge from web learn about the particular user and web synthesis also. Extracting the exact information from a large volume repository of unstructured [9-10] or semi structured web is a big challenge. Still researchers are having interest in web data mining. From the various solution of this problem one is Semantic Web. Semantic web is enhancement of current web in where information is provided along with meaning also, hence it enable computers and human being to work together in better coordination. The main deal in web mining techniques is to extract the exact information from web data. This article provides an overview of various Semantic web mining techniques.
On establishing evaluation standards for ECG biometrics

Electrocardiogram (ECG) biometrics are becoming increasingly popular. Numerous approaches to ECG processing have been proposed over the past years and the field has drawn significant attention from the biometrics community. However, less attention has been paid to developing a standard for ECG biometric testing for the evaluation of such algorithms. This paper proposes a set of standards for ECG signal recording and presents the UofT ECG Database (UofTDB) in order to evaluate the performance of various ECG biometric methods. Compared to existing databases, the UofTDB has three important characteristics namely, large population size (1012 individuals), varying body postures, physical exercise and acquisition over a long period. A promising equal error rate of under 5% is also reported.
An approach to identify microRNAs involved in neuropathic pain following a peripheral nerve injury

Peripheral nerve injury alters the expression of hundreds of proteins in dorsal root ganglia (DRG). Targeting some of these proteins has led to successful treatments for acute pain, but not for sustained post-operative neuropathic pain. The latter may require targeting multiple proteins. Since a single microRNA (miR) can affect the expression of multiple proteins, here, we describe an approach to identify chronic neuropathic pain-relevant miRs. We used two variants of the spared nerve injury (SNI): Sural-SNI and Tibial-SNI and found distinct pain phenotypes between the two. Both models induced strong mechanical allodynia, but only Sural-SNI rats maintained strong mechanical and cold allodynia, as previously reported. In contrast, we found that Tibial-SNI rats recovered from mechanical allodynia and never developed cold allodynia. Since both models involve nerve injury, we increased the probability of identifying differentially regulated miRs that correlated with the quality and magnitude of neuropathic pain and decreased the probability of detecting miRs that are solely involved in neuronal regeneration. We found seven such miRs in L3-L5 DRG. The expression of these miRs increased in Tibial-SNI. These miRs displayed a lower level of expression in Sural-SNI, with four having levels lower than those in sham animals. Bioinformatic analysis of how these miRs could affect the expression of some ion channels supports the view that, following a peripheral nerve injury, the increase of the seven miRs may contribute to the recovery from neuropathic pain while the decrease of four of them may contribute to the development of chronic neuropathic pain. The approach used resulted in the identification of a small number of potentially neuropathic pain relevant miRs. Additional studies are required to investigate whether manipulating the expression of the identified miRs in primary sensory neurons can prevent or ameliorate chronic neuropathic pain following peripheral nerve injuries.
Thoracoscopic resection of extralobar sequestration in a neonate.

The authors report a case of extralobar pulmonary sequestration (ELS) located at the right costophrenic recessus and resected thoracoscopically in a 22-day-old girl. Prenatally, spontaneous resolution of a cystic adenomatoid lung lesion (CCAM) occurring independently in the upper right hemithorax was observed. ELS with preceding complete resolution of CCAM in the ipsilateral hemithorax has not been reported before. This is the first neonate reported with ELS treated by thoracoscopy.
Livestock-Associated Methicillin-Resistant Staphylococcus aureus (LA-MRSA) Isolates of Swine Origin Form Robust Biofilms

Methicillin-resistant Staphylococcus aureus (MRSA) colonization of livestock animals is common and prevalence rates for pigs have been reported to be as high as 49%. Mechanisms contributing to the persistent carriage and high prevalence rates of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) strains in swine herds and production facilities have not been investigated. One explanation for the high prevalence of MRSA in swine herds is the ability of these organisms to exist as biofilms. In this report, the ability of swine LA-MRSA strains, including ST398, ST9, and ST5, to form biofilms was quantified and compared to several swine and human isolates. The contribution of known biofilm matrix components, polysaccharides, proteins and extracellular DNA (eDNA), was tested in all strains as well. All MRSA swine isolates formed robust biofilms similar to human clinical isolates. The addition of Dispersin B had no inhibitory effect on swine MRSA isolates when added at the initiation of biofilm growth or after pre-established mature biofilms formed. In contrast, the addition of proteinase K inhibited biofilm formation in all strains when added at the initiation of biofilm growth and was able to disperse pre-established mature biofilms. Of the LA-MRSA strains tested, we found ST398 strains to be the most sensitive to both inhibition of biofilm formation and dispersal of pre-formed biofilms by DNaseI. Collectively, these findings provide a critical first step in designing strategies to control or eliminate MRSA in swine herds.
Social and psychosocial influences on sudden cardiac death, ventricular arrhythmia and cardiac autonomic function.

The importance of a better understanding of arrhythmic risk lies, in public health terms, in the prevention of sudden cardiac death. Approximately 50% of all coronary deaths are sudden, occurring within 1 h of the onset of symptoms. Most cases of sudden cardiac death have coronary artery disease present at autopsy, although in approximately 50% this will not have been clinically apparent prior to death. Sudden cardiac death is most often due to ventricular fibrillation and cardiac autonomic function may play an important role in setting the arrhythmic threshold. Figure 1 illustrates this simple model of arrhythmic risk and gives the structure for this review. Sudden cardiac death is not, however, distributed equally in society. In one study of 1608 cases of sudden cardiac death, the age-adjusted rates of sudden cardiac death were higher among those with less education, an effect which was stronger than for people dying of non-sudden cardiac death. Educational level and other markers of social position, such as occupation and income, consistently show inverse associations with the incidence of cardiovascular disease. Social status may influence coronary risk via the behavioural risk factors of smoking, exercise and diet. However, the finding that social position gradients in heart disease are observed among non-smokers and are independent of the classical risk factors of cholesterol and blood pressure suggests
Modelling of the Oxygen Transport through MIEC Membrane in Transient Stage

The transient stage is critical due to the stress induced by the chemical and thermal strain. In order to predict this strain, the oxygen activity field through the membrane needs to be known. Usually, the membrane is divided into three zones: the bulk where diffusion takes place and the two surfaces where exchanges between atmosphere and membrane take place. Oxygen bulk diffusion is well described by the Wagner theory. A consensus has not yet emerged regarding the surface exchange models proposed in the literature. Moreover, these models describe the permanent state, and cannot be extended to the transient stage. A new macroscopic surface exchange model which allows computing transient stage is proposed. This model assumed that the oxygen flux is governed by the association/dissociation of adsorbed oxygen and by the high energetic cost of oxygen reduction/oxidation. Then, the balance of transient specie only present on the surface is introduced to account for these two phenomena. The oxygen activity fields predicted by the proposed model are in agreement with the measures of chemical potential drop between the membrane and the atmosphere in permanent state. Transient stage measured during isothermal expansion test is partially reproduced.
Supervised and semi-supervised suppression of background music in monaural speech recordings

In this paper, we propose a semi-supervised algorithm based on sparse non-negative matrix factorization (NMF) to improve separation of speech from background music in monaural signals. In our approach, fixed speech basis vectors are obtained from training data whereas music bases are estimated on-the-fly to cope with spectral variability while preserving small NMF dimensionality for decreased computation effort. In a large-scale experimental evaluation with 168 speakers from the TIMIT database, we compare the semi-supervised method to supervised NMF with an explicit background music model. Our results reveal that the semi-supervised method outperforms supervised NMF at low speech-to-music ratios, and that sparsity constraints on the music spectra to enforce harmonicity can improve separation performance.
A Lyapunov function for periodic economic optimizing Model Predictive Control

Model Predictive Control (MPC) schemes are commonly using reference-tracking cost functions, which have attractive properties in terms of stability and numerical implementation. However, many control applications have clear economic objectives that can be used directly as the NMPC cost function. Such NMPC schemes are labelled Economic NMPC. Unfortunately, Economic NMPC schemes suffer from some drawbacks. In particular, stability results for economic NMPC are still very sparse. A Lyapunov function for Economic NMPC was first proposed in [1] for problems having a steady-state optimum. The present paper develops a further generalization and clarification of these results for periodic systems.