Actuator fault tolerant control of variable cycle engine using sliding mode control scheme

This paper presents a fault tolerant control (FTC) design for the actuator faults in a variable cycle engine (VCE). Ensured by the multiple variable geometries structure of VCE, the design is realized by distributing the control effort among the unfaulty actuators with the “functional redundancy” idea. The FTC design consists of two parts: the fault reconstruction part and the fault tolerant control part, which use a sliding mode observer (SMO) and a sliding mode control (SMC) scheme respectively. Considering the inaccuracy of the fault reconstruction result, the proposed design requires only inaccurate fault information. The stability of the closed-loop control system is proved and the existence condition for the proposed control law is analyzed. This work also reveals its relation to the sliding mode control allocation design and the adaptive SMC design. An application case is then studied for tolerating the loss of effectiveness fault of the nozzle area actuator. Results show that the FTC design is able to tolerate the fault and achieves the same control goal as in the fault-free situation. Finally, a hardware-in-the-loop test is carried out to verify the design in a real-time distributed control system, which demonstrates its use from the engineering perspective

Structural and dynamic disorder, not ionic trapping, controls charge transport in highly doped conducting polymers

Doped organic semiconductors are critical to emerging device applications, including thermoelectrics, bioelectronics, and neuromorphic computing devices. It is commonly assumed that low conductivities in these materials result primarily from charge trapping by the Coulomb potentials of the dopant counter-ions. Here, we present a combined experimental and theoretical study rebutting this belief. Using a newly developed doping technique, we find the conductivity of several classes of high-mobility conjugated polymers to be strongly correlated with paracrystalline disorder but poorly correlated with ionic size, suggesting that Coulomb traps do not limit transport. A general model for interacting electrons in highly doped polymers is proposed and carefully parameterized against atomistic calculations, enabling the calculation of electrical conductivity within the framework of transient localisation theory. Theoretical calculations are in excellent agreement with experimental data, providing insights into the disordered-limited nature of charge transport and suggesting new strategies to further improve conductivities

Structural and dynamic disorder, not ionic trapping, controls charge transport in highly doped conducting polymers

Doped organic semiconductors are critical to emerging device applications, including thermoelectrics, bioelectronics, and neuromorphic computing devices. It is commonly assumed that low conductivities in these materials result primarily from charge trapping by the Coulomb potentials of the dopant counter-ions. Here, we present a combined experimental and theoretical study rebutting this belief. Using a newly developed doping technique, we find the conductivity of several classes of high-mobility conjugated polymers to be strongly correlated with paracrystalline disorder but poorly correlated with ionic size, suggesting that Coulomb traps do not limit transport. A general model for interacting electrons in highly doped polymers is proposed and carefully parameterized against atomistic calculations, enabling the calculation of electrical conductivity within the framework of transient localisation theory. Theoretical calculations are in excellent agreement with experimental data, providing insights into the disordered-limited nature of charge transport and suggesting new strategies to further improve conductivities

Early Induction of Oxidative Stress in Mouse Model of Alzheimer Disease with Reduced Mitochondrial Superoxide Dismutase Activity

While oxidative stress has been linked to Alzheimer's disease, the underlying pathophysiological relationship is unclear. To examine this relationship, we induced oxidative stress through the genetic ablation of one copy of mitochondrial antioxidant superoxide dismutase 2 (Sod2) allele in mutant human amyloid precursor protein (hAPP) transgenic mice. The brains of young (5–7 months of age) and old (25–30 months of age) mice with the four genotypes, wild-type (Sod2+/+), hemizygous Sod2 (Sod2+/−), hAPP/wild-type (Sod2+/+), and hAPP/hemizygous (Sod2+/−) were examined to assess levels of oxidative stress markers 4-hydroxy-2-nonenal and heme oxygenase-1. Sod2 reduction in young hAPP mice resulted in significantly increased oxidative stress in the pyramidal neurons of the hippocampus. Interestingly, while differences resulting from hAPP expression or Sod2 reduction were not apparent in the neurons in old mice, oxidative stress was increased in astrocytes in old, but not young hAPP mice with either Sod2+/+ or Sod2+/−. Our study shows the specific changes in oxidative stress and the causal relationship with the pathological progression of these mice. These results suggest that the early neuronal susceptibility to oxidative stress in the hAPP/Sod2+/− mice may contribute to the pathological and behavioral changes seen in this animal model

High‐Efficiency Ion‐Exchange Doping of Conducting Polymers

Abstract: Molecular doping—the use of redox‐active small molecules as dopants for organic semiconductors—has seen a surge in research interest driven by emerging applications in sensing, bioelectronics, and thermoelectrics. However, molecular doping carries with it several intrinsic problems stemming directly from the redox‐active character of these materials. A recent breakthrough was a doping technique based on ion‐exchange, which separates the redox and charge compensation steps of the doping process. Here, the equilibrium and kinetics of ion exchange doping in a model system, poly(2,5‐bis(3‐alkylthiophen‐2‐yl)thieno(3,2‐b)thiophene) (PBTTT) doped with FeCl3 and an ionic liquid, is studied, reaching conductivities in excess of 1000 S cm−1 and ion exchange efficiencies above 99%. Several factors that enable such high performance, including the choice of acetonitrile as the doping solvent, which largely eliminates electrolyte association effects and dramatically increases the doping strength of FeCl3, are demonstrated. In this high ion exchange efficiency regime, a simple connection between electrochemical doping and ion exchange is illustrated, and it is shown that the performance and stability of highly doped PBTTT is ultimately limited by intrinsically poor stability at high redox potential

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO