Competitive ratio of List Scheduling on uniform machines andrandomized heuristics

We study online scheduling on m uniform machines, where m−1 of them have a reference speed 1 and the last one a speed s with 0≤s≤1. The competitive ratio of the well-known List Scheduling (LS) algorithm is determined. For some values of s and m=3, LS is proven to be the best deterministic algorithm. We describe a randomized heuristic for m machines. Finally, for the case m=3, we develop and analyze the competitive ratio of a randomized algorithm which outperforms LS for any

La détection de périodicités cachées

This thesis is a small part of the preparation of the launch of the Gaia mission, a satellite of the European Space Agency (ESA). One of the goals of the mission is to perform a classification among variable stars considering different attributes. Periodic behavior in the observed light curve is such an attribute. It is of importance to determine these hidden cycles with as high an accuracy as possible. A key difficulty is connected to the fact that observations are taken at irregularly distributed time points. Classical methods of frequency analysis do not work in this situation. In a first step, we made a catalogue of potential solutions and applied them to real and simulated data. The performances have been compared in order to select the best method. In a second step, we considered the asymptotic performance of estimators based on regression methods. We derived the asymptotic distribution under the hypothesis that the observation model contains a periodic signal with period P0 > 0, continuous and square integrable on [0; P0), with Gaussian correlated errors. The irregular sampling has to satisfy the asymptotic property that the whole interval [0, P0) can be observed. We have also considered the special case of a periodic signal with period P0 > 0, piecewise constant on [0; P0) and the asymptotic distribution of the estimator. If an irregular sampling scheme does not satisfy the asymptotic property that the signal can be fully observed, the period can still be estimated reliably. We determined the asymptotic distribution of an estimator in a particular situation and under the assumption that the observation model contains a periodic signal with period P0 > 0, continuous and square integrable on [0; P0), and is observed with additive errors that are independent and identically distributed

Micro−transducteur ultrasonique capacitif à membrane de nanotubes de carbone : Perspectives pour le suivi immergé de la durabilité des matériaux cimentaires

Nous présentons des éléments de la conception, la réalisation et la caractérisation d'un micro−transducteur ultrasonique capacitif haute-fréquence dont la membrane vibrante est faite de nanotubes de carbone alignés. Le dispositif est conçu spécifiquement pour l'instrumentation immergée de la microporosité des matériaux cimentaires. La modélisation élasto−acoustique du dispositif valide préliminairement son intérêt applicatif pour la métrologie de la microporosité

Aligned carbon nanotube based ultrasonic microtransducers for durability monitoring in civil engineering

International audienceStructural health monitoring of porous materials such as concrete is becoming a major component in our resource-limited economy, as it conditions durable exploitation of existing facilities. Durability in porous materials depends on nanoscale features which need to be monitored in situ with nanometric resolution. To address this problem, we put forward an approach based on the development of a new nanosensor, namely a capacitive micrometric ultrasonic transducer whose vibrating membrane is made of aligned single-walled carbon nanotubes (SWNT). Such sensors are meant to be embedded in large numbers within a porous material in order to provide information on its durability by monitoring in situ neighboring individual micropores. In the present paper, we report on the feasibility of the key building block of the proposed sensor: we have fabricated well-aligned, ultra-thin, dense SWNT membranes that show above-nanometer amplitudes of vibration over a large range of frequencies spanning from 100 kHz to 5 MHz

A CD31-derived peptide prevents angiotensin II-induced atherosclerosis progression and aneurysm formation.

International audienceAIMS: The loss of the inhibitory receptor CD31 on peripheral T lymphocytes is associated with the incidence of atherosclerotic complications such as abdominal aortic aneurysms (AAA) in patients and plaque thrombosis in mice. However, we have recently discovered that a small fragment of extracellular CD31 remains expressed on the surface of the apparently 'CD31-negative' T-cells and that it is possible to restore the CD31-mediated T-cell inhibition in vivo by using a synthetic CD31-derived peptide. Here, we wanted to evaluate the therapeutic potential of the peptide in an experimental model of accelerated atherosclerosis and AAA formation. METHODS AND RESULTS: The effect of the murine CD31-derived peptide (aa 551-574, 1.5 mg/kg/day, sc) was evaluated on the extent of atherosclerotic plaques and the incidence of AAA in 28-week-old apolipoprotein E knockout mice (male, n ≥ 8/group) submitted to chronic angiotensin II infusion. The therapeutic mechanisms of the peptide were assessed by evaluating its effect on immune cell functions in vivo and in vitro. The prevalence of angiotensin II-induced AAA correlated with the loss of extracellular CD31 on T-cells. CD31 peptide treatment reduced both aneurysm formation and plaque size (P < 0.05 vs. control). Protection was associated with reduced perivascular leucocyte infiltration and T-cell activation in vivo. Functional in vitro studies showed that the peptide is able to suppress both T-cell and macrophage activation. CONCLUSION: CD31 peptides could represent a new class of drugs intended to prevent the inflammatory cell processes, such as those underlying progression of atherosclerosis and development of AAA

Optical control of pain in vivo with a photoactive mGlu5 receptor negative allosteric modulator

Light-operated drugs constitute a major target in drug discovery, since they may provide spatiotemporal resolution for the treatment of complex diseases (i.e. chronic pain). JF-NP-26 is an inactive photocaged derivative of the metabotropic glutamate type 5 (mGlu5) receptor negative allosteric modulator raseglurant. Violet light illumination of JF-NP-26 induces a photochemical reaction prompting the active-drug's release, which effectively controls mGlu5 receptor activity both in ectopic expressing systems and in striatal primary neurons. Systemic administration in mice followed by local light-emitting diode (LED)-based illumination, either of the thalamus or the peripheral tissues, induced JF-NP-26-mediated light-dependent analgesia both in neuropathic and in acute/tonic inflammatory pain models. These data offer the first example of optical control of analgesia in vivo using a photocaged mGlu5 receptor negative allosteric modulator. This approach shows potential for precisely targeting, in time and space, endogenous receptors, which may allow a better management of difficult-to-treat disorders

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe