Assessing The Hydrologic Restoration Of An Urbanized Area Via Integrated Distributed Hydrological Model

published_or_final_versio

Optimizing bio-retention system locations for stormwater management using genetic algorithm

As part of stormwater best management practices, bio-retention systems have been applied in a number of developed countries to minimize the change of hydrological regime due to urbanization. Optimization techniques have also been applied to determine the locations that give the most hydrological benefits. However, optimization tools are commonly built in together with specific hydrological models, usually restricting the choices and components of hydrological models. Furthermore, it is redundant to build another hydrological model that has a built-in optimization tool if a hydrological model, and possibly more comprehensive one, has already been developed for the study area. The objective of this study is to develop a genetic algorithm (GA) that is independent from and can therefore be coupled with any existing integrated distributed hydrological model to optimize the locations of bio-retention systems. The GA is written in Visual Basic considering factors such as topography, distance from a river and groundwater table depth. The alternative combinations of bio-retention locations suggested by the GA are used as inputs of an integrated distributed hydrological model. The combination that gives the lowest outlet discharge is then regarded as the best solution. We demonstrate the approach by taking Marina catchment in Singapore as a case study and feeding the GA with results from MIKESHE. Overall, the GA developed is not only transferable to other study area but also can also be coupled with any hydrological model that is the most suitable for that particular case study.postprin

Managing stormwater with low impact development in highly urbanized areas

2014 is the 25th Anniverssary of the Drainage Services Department (DSD) of the HKSAR GovernmentPaper A2-2Low impact development (LID) implements small-scale hydrologic controls throughout a catchment to replicate the pre-development hydrologic regimes or in other terms control stormwater as close to the source as possible. Examples of such controls include green roofs, bioretention swales, rain gardens, porous pavements. This project evaluates the effectiveness of large-scale LID implementation in Singapore and Hong Kong. We examine the hydrologic impacts, namely peak discharge mitigation and baseflow restoration, under different land uses, rainfall conditions and LID strategies. For further comparison, we adopt an integrated distributed hydrological model for Singapore and a lumped hydraulic model for Hong Kong. Studies of both Singapore and Hong Kong suggest that LID is effective if there is substantial level of infrastructures (e.g., covering 5 to 10% of catchment area). LID is more efficient in reducing/delaying peak discharge and restoring baseflow on an average long term basis. However, its performance, particularly in peak discharge mitigation, diminishes during design storms (e.g., ARI of 5 years). In terms of modeling techniques, integrated distributed hydrologic models require extensive parameterization but can accurately simulate some important processes (e.g., increase of infiltration and restoration of baseflow) that are simplified in lumped hydraulic models. Overall, large-scale LID potentially provides more sustainable stormwater management but its success depends on factors such as design objectives, existing land uses and drainage networks. We should therefore further research to increase the feasibility of large-scale LID in highly urbanized areas such as Singapore and Hong Kong.postprin

Super-Resolved Enhancement of a Single Image and Its Application in Cardiac MRI

Super-resolved image enhancement is of great importance in medical imaging. Conventional methods often require multiple low resolution (LR) images from different views of the same object or learning from large amount of training datasets to achieve success. However, in real clinical environments, these prerequisites are rarely fulfilled. In this paper, we present a self-learning based method to perform superresolution (SR) from a single LR input. The mappings between the given LR image and its downsampled versions are modeled using support vector regression on features extracted from sparse coded dictionaries, coupled with dual-tree complex wavelet transform based denoising. We demonstrate the efficacy of our method in application of cardiac MRI enhancement. Both quantitative and qualitative results show that our SR method is able to preserve fine textural details that can be corrupted by noise, and therefore can maintain crucial diagnostic information

Zicam-Induced Damage to Mouse and Human Nasal Tissue

Intranasal medications are used to treat various nasal disorders. However, their effects on olfaction remain unknown. Zicam (zinc gluconate; Matrixx Initiatives, Inc), a homeopathic substance marketed to alleviate cold symptoms, has been implicated in olfactory dysfunction. Here, we investigated Zicam and several common intranasal agents for their effects on olfactory function. Zicam was the only substance that showed significant cytotoxicity in both mouse and human nasal tissue. Specifically, Zicam-treated mice had disrupted sensitivity of olfactory sensory neurons to odorant stimulation and were unable to detect novel odorants in behavioral testing. These findings were long-term as no recovery of function was observed after two months. Finally, human nasal explants treated with Zicam displayed significantly elevated extracellular lactate dehydrogenase levels compared to saline-treated controls, suggesting severe necrosis that was confirmed on histology. Our results demonstrate that Zicam use could irreversibly damage mouse and human nasal tissue and may lead to significant smell dysfunction

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

The LRRK2 signalling system

The LRRK2 gene is a major contributor to genetic risk for Parkinson's disease and understanding the biology of the leucine-rich repeat kinase 2 (LRRK2, the protein product of this gene) is an important goal in Parkinson's research. LRRK2 is a multi-domain, multi-activity enzyme and has been implicated in a wide range of signalling events within the cell. Because of the complexities of the signal transduction pathways in which LRRK2 is involved, it has been challenging to generate a clear idea as to how mutations and disease associated variants in this gene are altered in disease. Understanding the events in which LRRK2 is involved at a systems level is therefore critical to fully understand the biology and pathobiology of this protein and is the subject of this review