140 research outputs found

    Gaussian inference for data-driven state-feedback design of nonlinear systems

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    Data-driven control of nonlinear systems with rigorous guarantees is a challenging problem as it usually calls for nonconvex optimization and requires often knowledge of the true basis functions of the system dynamics. To tackle these drawbacks, this work is based on a data-driven polynomial representation of general nonlinear systems exploiting Taylor polynomials. Thereby, we design state-feedback laws that render a known equilibrium point globally asymptotically stable while operating with respect to a desired quadratic performance criterion. The calculation of the polynomial state feedback boils down to a single sum-ofsquares optimization problem, and hence to computationally tractable linear matrix inequalities. Moreover, we examine state-input data in presence of Gaussian noise by Bayesian inference to overcome the conservatism of deterministic noise characterizations from recent data-driven control approaches for Gaussian noise.Comment: Final version, accepted for presentation at the 22nd IFAC World Congress, 202

    Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch

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    Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.Comment: 14 pages, 4 figure

    Applied Interventions in the Prevention and Treatment of Obesity Through the Research of Professor Jane Wardle

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    Purpose of Review Obesity presents a challenge for practitioners, policy makers, researchers and for those with obesity themselves. This review focuses on psychological approaches to its management and prevention in children and adults. Recent Findings Through exploring the work of the late Professor Jane Wardle, we look at the earliest behavioural treatment approaches and how psychological theory has been used to develop more contemporary approaches, for example incorporating genetic feedback and habit formation theory into interventions. We also explore how Jane has challenged thinking about the causal pathways of obesity in relation to eating behaviour. Beyond academic work, Jane was an advocate of developing interventions which had real-world applications. Summary Therefore, we discuss how she not only developed new interventions but also made these widely available and the charity that she established

    Mechanism of PP2A-mediated IKKβ dephosphorylation: a systems biological approach

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    BACKGROUND: Biological effects of nuclear factor-kappaB (NF kappaB) can differ tremendously depending on the cellular context. For example, NF kappaB induced by interleukin-1 (IL-1) is converted from an inhibitor of death receptor induced apoptosis into a promoter of ultraviolet-B radiation (UVB)-induced apoptosis. This conversion requires prolonged NF kappaB activation and is facilitated by IL-1 + UVB-induced abrogation of the negative feedback loop for NF kappaB, involving a lack of inhibitor of kappaB (I kappaB alpha) protein reappearance. Permanent activation of the upstream kinase IKK beta results from UVB-induced inhibition of the catalytic subunit of Ser-Thr phosphatase PP2A (PP2Ac), leading to immediate phosphorylation and degradation of newly synthesized I kappaB alpha. RESULTS: To investigate the mechanism underlying the general PP2A-mediated tuning of IKK beta phosphorylation upon IL-1 stimulation, we have developed a strictly reduced mathematical model based on ordinary differential equations which includes the essential processes concerning the IL-1 receptor, IKK beta and PP2A. Combining experimental and modelling approaches we demonstrate that constitutively active, but not post-stimulation activated PP2A, tunes out IKK beta phosphorylation thus allowing for I kappaB alpha resynthesis in response to IL-1. Identifiability analysis and determination of confidence intervals reveal that the model allows reliable predictions regarding the dynamics of PP2A deactivation and IKK beta phosphorylation. Additionally, scenario analysis is used to scrutinize several hypotheses regarding the mode of UVB-induced PP2Ac inhibition. The model suggests that down regulation of PP2Ac activity, which results in prevention of I kappaB alpha reappearance, is not a direct UVB action but requires instrumentality. CONCLUSION: The model developed here can be used as a reliable building block of larger NF kappa B models and offers comprehensive simplification potential for future modeling of NF kappa B signaling. It gives more insight into the newly discovered mechanisms for IKK deactivation and allows for substantiated predictions and investigation of different hypotheses. The evidence of constitutive activity of PP2Ac at the IKK complex provides new insights into the feedback regulation of NF kappa B, which is crucial for the development of new anti-cancer strategies

    Smoking and mental illness: results from population surveys in Australia and the United States

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    <p>Abstract</p> <p>Background</p> <p>Smoking has been associated with a range of mental disorders including schizophrenia, anxiety disorders and depression. People with mental illness have high rates of morbidity and mortality from smoking related illnesses such as cardiovascular disease, respiratory diseases and cancer. As many people who meet diagnostic criteria for mental disorders do not seek treatment for these conditions, we sought to investigate the relationship between mental illness and smoking in recent population-wide surveys.</p> <p>Methods</p> <p>Survey data from the US National Comorbidity Survey-Replication conducted in 2001–2003, the 2007 Australian Survey of Mental Health and Wellbeing, and the 2007 US National Health Interview Survey were used to investigate the relationship between current smoking, ICD-10 mental disorders and non-specific psychological distress. Population weighted estimates of smoking rates by disorder, and mental disorder rates by smoking status were calculated.</p> <p>Results</p> <p>In both the US and Australia, adults who met ICD-10 criteria for mental disorders in the 12 months prior to the survey smoked at almost twice the rate of adults without mental disorders. While approximately 20% of the adult population had 12-month mental disorders, among adult smokers approximately one-third had a 12-month mental disorder – 31.7% in the US (95% CI: 29.5%–33.8%) and 32.4% in Australia (95% CI: 29.5%–35.3%). Female smokers had higher rates of mental disorders than male smokers, and younger smokers had considerably higher rates than older smokers. The majority of mentally ill smokers were not in contact with mental health services, but their rate of smoking was not different from that of mentally ill smokers who had accessed services for their mental health problem. Smokers with high levels of psychological distress smoked a higher average number of cigarettes per day.</p> <p>Conclusion</p> <p>Mental illness is associated with both higher rates of smoking and higher levels of smoking among smokers. Further, a significant proportion of smokers have mental illness. Strategies that address smoking in mental illness, and mental illness among smokers would seem to be important directions for tobacco control. As the majority of smokers with mental illness are not in contact with mental health services for their condition, strategies to address mental illness should be included as part of population health-based mental health and tobacco control efforts.</p

    Forest canopy gap fraction from terrestrial laser scanning

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    A terrestrial laser scanner (TLS) was used to measure canopy directional gap fraction distribution in forest stands in the Swiss National Park, eastern Switzerland. A scanner model was derived to determine the expected number of laser shots in all directions, and these data were compared with the measured number of laser hits to determine directional gap fraction at eight sampling points. Directional gap fraction distributions were determined from digital hemispherical photographs recorded at the same sampling locations in the forest, and these data were compared with distributions computed from the laser scanner data. The results showed that the measured directional gap fraction distributions were similar for both hemispherical photography and TLS data with a high degree of precision in the area of overlap of orthogonal laser scans. Analysis of hemispherical photography to determine canopy gap fraction normally requires some manual data processing; laser scanners offer semiautomatic measurement of directional gap fraction distribution plus additional threedimensional information about tree height, gap size, and foliage distributions

    Area under the curve-derived measures for the characterization of longitudinal patient responses

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