Stabilization of wave systems with input delay in the boundary control

2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Decentralized learning with budgeted network load using Gaussian copulas and classifier ensembles

We examine a network of learners which address the same classification task but must learn from different data sets. The learners cannot share data but instead share their models. Models are shared only one time so as to preserve the network load. We introduce DELCO (standing for Decentralized Ensemble Learning with COpulas), a new approach allowing to aggregate the predictions of the classifiers trained by each learner. The proposed method aggregates the base classifiers using a probabilistic model relying on Gaussian copulas. Experiments on logistic regressor ensembles demonstrate competing accuracy and increased robustness in case of dependent classifiers. A companion python implementation can be downloaded at https://github.com/john-klein/DELC

Activation of Ventral Tegmental Area 5-HT2C Receptors Reduces Incentive Motivation

FUNDING AND DISCLOSURE The research was funded by Wellcome Trust (WT098012) to LKH; and National Institute of Health (DK056731) and the Marilyn H. Vincent Foundation to MGM. The University of Michigan Transgenic Core facility is partially supported by the NIH-funded University of Michigan Center for Gastrointestinal Research (DK034933). The remaining authors declare no conflict of interest. ACKNOWLEDGMENTS We thank Dr Celine Cansell, Ms Raffaella Chianese and the staff of the Medical Research Facility for technical assistance. We thank Dr Vladimir Orduña for the scientific advice and technical assistance.Peer reviewedPublisher PD

Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding

This work addresses the problem of semantic scene understanding under dense fog. Although considerable progress has been made in semantic scene understanding, it is mainly related to clear-weather scenes. Extending recognition methods to adverse weather conditions such as fog is crucial for outdoor applications. In this paper, we propose a novel method, named Curriculum Model Adaptation (CMAda), which gradually adapts a semantic segmentation model from light synthetic fog to dense real fog in multiple steps, using both synthetic and real foggy data. In addition, we present three other main stand-alone contributions: 1) a novel method to add synthetic fog to real, clear-weather scenes using semantic input; 2) a new fog density estimator; 3) the Foggy Zurich dataset comprising $3808$ real foggy images, with pixel-level semantic annotations for $16$ images with dense fog. Our experiments show that 1) our fog simulation slightly outperforms a state-of-the-art competing simulation with respect to the task of semantic foggy scene understanding (SFSU); 2) CMAda improves the performance of state-of-the-art models for SFSU significantly by leveraging unlabeled real foggy data. The datasets and code are publicly available.Comment: final version, ECCV 201

Correction: An intrinsically stretchable humidity sensor based on anti-drying, self-healing and transparent organohydrogels

Correction for ‘An intrinsically stretchable humidity sensor based on anti-drying, self-healing and transparent organohydrogels’ by Jin Wu et al., Mater. Horiz., 2019, 6, 595–603, DOI: 10.1039/C8MH01160E

Host-star and exoplanet compositions: A pilot study using a wide binary with a polluted white dwarf

Planets and stars ultimately form out of the collapse of the same cloud of gas. Whilst planets, and planetary bodies, readily loose volatiles, a common hypothesis is that they retain the same refractory composition as their host star. This is true within the Solar System. The refractory composition of chondritic meteorites, Earth and other rocky planetary bodies are consistent with solar, within the observational errors. This work aims to investigate whether this hypothesis holds for exoplanetary systems. If true, the internal structure of observed rocky exoplanets can be better constrained using their host star abundances. In this paper, we analyse the abundances of the K-dwarf, G200-40, and compare them to its polluted white dwarf companion, WD 1425+540. The white dwarf has accreted planetary material, most probably a Kuiper belt-like object, from an outer planetary system surviving the star's evolution to the white dwarf phase. Given that binary pairs are chemically homogeneous, we use the binary companion, G200-40, as a proxy for the composition of the progenitor to WD 1425+540. We show that the elemental abundances of the companion star and the planetary material accreted by WD 1425+540 are consistent with the hypothesis that planet and host-stars have the same true abundances, taking into account the observational errors

TSC1/2 mutations define a molecular subset of HCC with aggressive behaviour and treatment implication

Objective We investigated the mutational landscape of mammalian target of rapamycin (mTOR) signalling cascade in hepatocellular carcinomas (HCCs) with chronic HBV background, aiming to evaluate and delineate mutation-dependent mechanism of mTOR hyperactivation in hepatocarcinogenesis. Design We performed next-generation sequencing on human HCC samples and cell line panel. Systematic mutational screening of mTOR pathway-related genes was undertaken and mutant genes were evaluated based on their recurrence. Protein expressions of tuberous sclerosis complex (TSC)1, TSC2 and pRPS6 were assessed by immunohistochemistry in human HCC samples. Rapamycin sensitivity was estimated by colony-formation assay in HCC cell lines and the treatment was further tested using our patient-derived tumour xenograft (PDTX) models. Results We identified and confirmed multiple mTOR components as recurrently mutated in HBV-associated HCCs. Of significance, we detected frequent (16.2%, n=18/111) mutations of TSC1 and TSC2 genes in the HCC samples. The spectrum of TSC1/2 mutations likely disrupts the endogenous gene functions in suppressing the downstream mTOR activity through different mechanisms and leads to more aggressive tumour behaviour. Mutational disruption of TSC1 and TSC2 was also observed in HCC cell lines and our PDTX models. TSC-mutant cells exhibited reduced colony-forming ability on rapamycin treatment. With the use of biologically relevant TSC2-mutant PDTXs, we demonstrated the therapeutic benefits of the hypersensitivity towards rapamycin treatment. Conclusions Taken together, our findings suggest the significance of previously undocumented mutation-dependent mTOR hyperactivation and frequent TSC1/2 mutations in HBV-associated HCCs. They define a molecular subset of HCC having genetic aberrations in mTOR signalling, with potential significance of effective specific drug therapy.published_or_final_versio

Homework self-regulation strategies: a gender and educational-level invariance analysis

This study investigates the measurement invariance as a function of gender and educational level of the Homework Behavior Questionnaire (Ktpc), an instrument developed to assess students' homework self-regulation strategies. A sample of 1400 elementary and middle school students was used. Results of confirmatory factor analysis indicated a good fit of the theoretical model composed of three dimensions: planning, execution and evaluation of the homework completion. The results also provided evidence for the existence of metric invariance and partial scalar measurement invariance across boys and girls and across the elementary school and the middle school students. The reliability of the scores in the three dimensions was high. Girls obtained higher scores than boys in planning, execution and evaluation. Middle school students had lower scores in planning compared to the elementary school students. These findings are discussed, and their implications for practice are highlighted.This study was partially conducted at the Psychology Research Centre (UID/PSI/01662/2013), University of Minho, and supported by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by FEDER, through COMPETE2020, under the PT2020 Partnership Agreement (POCI-01-0145-FEDER-007653). The first author is also supported by grant SFRH/BPD/102549/2014 from the Portuguese Foundation for Science and Technology.info:eu-repo/semantics/publishedVersio

Molecular identification of adenoviruses associated with respiratory infection in Egypt from 2003 to 2010.

BACKGROUND: Human adenoviruses of species B, C, and E (HAdV-B, -C, -E) are frequent causative agents of acute respiratory infections worldwide. As part of a surveillance program aimed at identifying the etiology of influenza-like illness (ILI) in Egypt, we characterized 105 adenovirus isolates from clinical samples collected between 2003 and 2010. METHODS: Identification of the isolates as HAdV was accomplished by an immunofluorescence assay (IFA) and confirmed by a set of species and type specific polymerase chain reactions (PCR). RESULTS: Of the 105 isolates, 42% were identified as belonging to HAdV-B, 60% as HAdV-C, and 1% as HAdV-E. We identified a total of six co-infections by PCR, of which five were HAdV-B/HAdV-C co-infections, and one was a co-infection of two HAdV-C types: HAdV-5/HAdV-6. Molecular typing by PCR enabled the identification of eight genotypes of human adenoviruses; HAdV-3 (n = 22), HAdV-7 (n = 14), HAdV-11 (n = 8), HAdV-1 (n = 22), HAdV-2 (20), HAdV-5 (n = 15), HAdV-6 (n = 3) and HAdV-4 (n = 1). The most abundant species in the characterized collection of isolates was HAdV-C, which is concordant with existing data for worldwide epidemiology of HAdV respiratory infections. CONCLUSIONS: We identified three species, HAdV-B, -C and -E, among patients with ILI over the course of 7 years in Egypt, with at least eight diverse types circulating