559 research outputs found
Overexpression of PD-1-related molecules is associated with lymphocyte anergy, mortality, and development of nosocomial infections in septic shock patients
Lithium-ion battery aging experiments at subzero temperatures and model development for capacity fade estimation
Lithium-ion (Li-ion) batteries widely used in electric vehicles (EVs) and hybrid EVs (HEVs) are insufficient for vehicle use after they have degraded to 70% to 80% of their original capacity. Battery lifespan is a large consideration when designing battery packs for EVs/HEVs. Aging mechanisms, such as metal dissolution, growth of the passivated surface film layer on the electrodes, and loss of both recyclable lithium ions, affect the longevity of the Li-ion battery at higherature operations. Even vehicle maneuvers at low temperatures (T<0°C)contribute to battery lifetime degradation, owing to the anode electrode vulnerability to other degradation mechanisms such as lithium plating. Nowadays, only a few battery thermal management schemes have properly considered lowerature degradation. This is due to the lack of studies on aging of Li-ion batteries at sub-zero temperature. This paper investigates how load cycle and calendar life properties affect the lifetime and aging processes of Li-ion cells at low temperatures. Accelerated aging tests were used to determine the effect of the ambient temperature on the performance of three 100-Ah LiFeMnP04 Li-ion cells. Two of them were aged through a normalized driving cycle at two temperature tests (-20°C and 25°C). The calendar test was carried out on one single battery at -20 °C and mid-range of state of charge (50%). Their capacities were continuously measured every two or three days. An aging model is developed and added to a preliminary single-cell electrothermal model to establish, in future works, a thermal strategy capable of predicting how the cell ages. This aging model was then validated by comparing its predictions with the aging data obtained from a cycling test at 0 °C. © 1967-2012 IEEE
Sharing Ghost Variables in a Collection of Abstract Domains
International audienceWe propose a framework in which we share ghost variables across a collection of abstract domains allowing precise proofs of complex properties. In abstract interpretation, it is often necessary to be able to express complex properties while doing a precise analysis. A way to achieve that is to combine a collection of domains, each handling some kind of properties, using a reduced product. Separating domains allows an easier and more modular implementation, and eases soundness and termination proofs. This way, we can add a domain for any kind of property that is interesting. The reduced product, or an approximation of it, is in charge of refining abstract states, making the analysis precise. In program verification, ghost variables can be used to ease proofs of properties by storing intermediate values that do not appear directly in the execution. We propose a reduced product of abstract domains that allows domains to use ghost variables to ease the representation of their internal state. Domains must be totally agnostic with respect to other existing domains. In particular the handling of ghost variables must be entirely decentralized while still ensuring soundness and termination of the analysis
IKOS: A Framework for Static Analysis based on Abstract Interpretation (Tool Paper)
The RTCA standard (DO-178C) for developing avionic software and getting certification credits includes an extension (DO-333) that describes how developers can use static analysis in certification. In this paper, we give an overview of the IKOS static analysis framework that helps developing static analyses that are both precise and scalable. IKOS harnesses the power of Abstract Interpretation and makes it accessible to a larger class of static analysis developers by separating concerns such as code parsing, model development, abstract domain management, results management, and analysis strategy. The benefits of the approach is demonstrated by a buffer overflow analysis applied to flight control systems
Origin of discrepancy between electrical and mechanical anomalies in lead-free (K,Na)NbO3 -based ceramics
[EN] Ferroelectric polymorphic phase coexistence, associated with either the presence of a morphotropic phase boundary or a temperature-driven polymorphic phase transition, is currently acknowledged as the key to high piezoelectric activity and is searched when new perovskite materials are developed, like lead-free alternatives to state-of-the-art Pb(Zr,Ti)O3. This requires characterization tools that allow phase coexistence and transitions to be readily identified, among which measurements of the temperature dependences of Young's modulus and mechanical losses by dynamical mechanical analysis stand out as a powerful technique to complement standard electrical characterizations. We report here the application of this technique to (K1-xNax)NbO3-based materials, which are under extensive investigation as environmentally friendly high sensitivity piezoelectrics. The elastic anomalies associated with the different phase transitions are identified and are shown to be distinctively shifted in relation to the dielectric ones. The origin of this discrepancy is discussed with the help of temperature-dependent Raman spectroscopy and is proposed to be a characteristic of diffuse phase transitions.The authors would like to thank CAPES and the Sâo Paulo Research Foundation (FAPESP), Grants No. 2012/08457-7 and No. 2013/00134-7, for the financial support. M.A. also acknowledges funding from MINECO through the MAT2014-58816-R Project.Peer Reviewe
P16-37. HIV controllers with weak CD8+ T cell responses maintain a tight control of infection despite carrying infectious viruses
International audienc
PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions
The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity
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