178 research outputs found

    Advancing Urban Flood Resilience With Smart Water Infrastructure

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    Advances in wireless communications and low-power electronics are enabling a new generation of smart water systems that will employ real-time sensing and control to solve our most pressing water challenges. In a future characterized by these systems, networks of sensors will detect and communicate flood events at the neighborhood scale to improve disaster response. Meanwhile, wirelessly-controlled valves and pumps will coordinate reservoir releases to halt combined sewer overflows and restore water quality in urban streams. While these technologies promise to transform the field of water resources engineering, considerable knowledge gaps remain with regards to how smart water systems should be designed and operated. This dissertation presents foundational work towards building the smart water systems of the future, with a particular focus on applications to urban flooding. First, I introduce a first-of-its-kind embedded platform for real-time sensing and control of stormwater systems that will enable emergency managers to detect and respond to urban flood events in real-time. Next, I introduce new methods for hydrologic data assimilation that will enable real-time geolocation of floods and water quality hazards. Finally, I present theoretical contributions to the problem of controller placement in hydraulic networks that will help guide the design of future decentralized flood control systems. Taken together, these contributions pave the way for adaptive stormwater infrastructure that will mitigate the impacts of urban flooding through real-time response.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163144/1/mdbartos_1.pd

    PIK3CA mutation enrichment and quantitation from blood and tissue

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    PIK3CA is one of the two most frequently mutated genes in breast cancers, occurring in 30-40% of cases. Four frequent 'hotspot' PIK3CA mutations (E542K, E545K, H1047R and H1047L) account for 80-90% of all PIK3CA mutations in human malignancies and represent predictive biomarkers. Here we describe a PIK3CA mutation specific nuclease-based enrichment assay, which combined with a low-cost real-time qPCR detection method, enhances assay detection sensitivity from 5% for E542K and 10% for E545K to 0.6%, and from 5% for H1047R to 0.3%. Moreover, we present a novel flexible prediction method to calculate initial mutant allele frequency in tissue biopsy and blood samples with low mutant fraction. These advancements demonstrated a quick, accurate and simple detection and quantitation of PIK3CA mutations in two breast cancer cohorts (first cohort n = 22, second cohort n = 25). Hence this simple, versatile and informative workflow could be applicable for routine diagnostic testing where quantitative results are essential, e.g. disease monitoring subject to validation in a substantial future study

    First Demonstration of Electrostatic Damping of Parametric Instability at Advanced LIGO

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    Interferometric gravitational wave detectors operate with high optical power in their arms in order to achieve high shot-noise limited strain sensitivity. A significant limitation to increasing the optical power is the phenomenon of three-mode parametric instabilities, in which the laser field in the arm cavities is scattered into higher-order optical modes by acoustic modes of the cavity mirrors. The optical modes can further drive the acoustic modes via radiation pressure, potentially producing an exponential buildup. One proposed technique to stabilize parametric instability is active damping of acoustic modes. We report here the first demonstration of damping a parametrically unstable mode using active feedback forces on the cavity mirror. A 15 538 Hz mode that grew exponentially with a time constant of 182 sec was damped using electrostatic actuation, with a resulting decay time constant of 23 sec. An average control force of 0.03 nN was required to maintain the acoustic mode at its minimum amplitude

    De novo variants predicting haploinsufficiency for DIP2C are associated with expressive speech delay.

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    The disconnected (disco)-interacting protein 2 (DIP2) gene was first identified in D. melanogaster and contains a DNA methyltransferase-associated protein 1 (DMAP1) binding domain, Acyl-CoA synthetase domain and AMP-binding sites. DIP2 regulates axonal bifurcation of the mushroom body neurons in D. melanogaster and is required for axonal regeneration in the neurons of C. elegans. The DIP2 homologues in vertebrates, Disco-interacting protein 2 homolog A (DIP2A), Disco-interacting protein 2 homolog B (DIP2B), and Disco-interacting protein 2 homolog C (DIP2C), are highly conserved and expressed widely in the central nervous system. Although there is evidence that DIP2C plays a role in cognition, reports of pathogenic variants in these genes are rare and their significance is uncertain. We present 23 individuals with heterozygous DIP2C variants, all manifesting developmental delays that primarily affect expressive language and speech articulation. Eight patients had de novo variants predicting loss-of-function in the DIP2C gene, two patients had de novo missense variants, three had paternally inherited loss of function variants and six had maternally inherited loss-of-function variants, while inheritance was unknown for four variants. Four patients had cardiac defects (hypertrophic cardiomyopathy, atrial septal defects, and bicuspid aortic valve). Minor facial anomalies were inconsistent but included a high anterior hairline with a long forehead, broad nasal tip, and ear anomalies. Brainspan analysis showed elevated DIP2C expression in the human neocortex at 10-24 weeks after conception. With the cases presented herein, we provide phenotypic and genotypic data supporting the association between loss-of-function variants in DIP2C with a neurocognitive phenotype
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