VISJET & VISFLOOD: Software for environment hydraulic modeling & visualization

We present two general interactive PC-based modeling and visualization software systems developed for the study of two types of environmental water flows: buoyant jet mixing and urban drainage problems. VISJET (http://www.aoe-water.hku.hk/visjet) is arguably the most robust software with advanced graphics for the prediction of mixing and transport of effluent discharges into a stratified crossflow. The prediction engine is a Lagrangian model for buoyant jets with three-dimensional trajectories, and is based on extensive basic experiments and turbulence model calculations. It can be used in outfall design and environmental impact assessment, and as an educational or training tool. VISFLOOD (http://www.aoe-water.hku.hk/visflood) is based on the numerical solution of the Saint-Venant equations, and caters for the simulation of unsteady flood propagation in urban drainage systems. Both software systems are fully interactive with data interrogation; the 3D visualization is fully integrated with the model engine, and enables the user to appreciate the context of the problem in a most effective way. Both models have been well-validated against laboratory and field data, and have been applied to many actual engineering projects. This software product is an outcome of a grant by the Hong Kong Innovation and Technology Fund (ITF).published_or_final_versio

FSL-BM: Fuzzy Supervised Learning with Binary Meta-Feature for Classification

This paper introduces a novel real-time Fuzzy Supervised Learning with Binary Meta-Feature (FSL-BM) for big data classification task. The study of real-time algorithms addresses several major concerns, which are namely: accuracy, memory consumption, and ability to stretch assumptions and time complexity. Attaining a fast computational model providing fuzzy logic and supervised learning is one of the main challenges in the machine learning. In this research paper, we present FSL-BM algorithm as an efficient solution of supervised learning with fuzzy logic processing using binary meta-feature representation using Hamming Distance and Hash function to relax assumptions. While many studies focused on reducing time complexity and increasing accuracy during the last decade, the novel contribution of this proposed solution comes through integration of Hamming Distance, Hash function, binary meta-features, binary classification to provide real time supervised method. Hash Tables (HT) component gives a fast access to existing indices; and therefore, the generation of new indices in a constant time complexity, which supersedes existing fuzzy supervised algorithms with better or comparable results. To summarize, the main contribution of this technique for real-time Fuzzy Supervised Learning is to represent hypothesis through binary input as meta-feature space and creating the Fuzzy Supervised Hash table to train and validate model.Comment: FICC201

Effects of heavy modes on vacuum stability in supersymmetric theories

We study the effects induced by heavy fields on the masses of light fields in supersymmetric theories, under the assumption that the heavy mass scale is much higher than the supersymmetry breaking scale. We show that the square-masses of light scalar fields can get two different types of significant corrections when a heavy multiplet is integrated out. The first is an indirect level-repulsion effect, which may arise from heavy chiral multiplets and is always negative. The second is a direct coupling contribution, which may arise from heavy vector multiplets and can have any sign. We then apply these results to the sGoldstino mass and study the implications for the vacuum metastability condition. We find that the correction from heavy chiral multiplets is always negative and tends to compromise vacuum metastability, whereas the contribution from heavy vector multiplets is always positive and tends on the contrary to reinforce it. These two effects are controlled respectively by Yukawa couplings and gauge charges, which mix one heavy and two light fields respectively in the superpotential and the Kahler potential. Finally we also comment on similar effects induced in soft scalar masses when the heavy multiplets couple both to the visible and the hidden sector.Comment: LaTex, 24 pages, no figures; v2 some comments and references adde

The singlet scalar as FIMP dark matter

The singlet scalar model is a minimal extension of the Standard Model that can explain the dark matter. We point out that in this model the dark matter constraint can be satisfied not only in the already considered WIMP regime but also, for much smaller couplings, in the Feebly Interacting Massive Particle (FIMP) regime. In it, dark matter particles are slowly produced in the early Universe but are never abundant enough to reach thermal equilibrium or annihilate among themselves. This alternative framework is as simple and predictive as the WIMP scenario but it gives rise to a completely different dark matter phenomenology. After reviewing the calculation of the dark matter relic density in the FIMP regime, we study in detail the evolution of the dark matter abundance in the early Universe and the predicted relic density as a function of the parameters of the model. A new dark matter compatible region of the singlet model is identified, featuring couplings of order 10^-11 to 10^-12 for singlet masses in the GeV to TeV range. As a consequence, no signals at direct or indirect detection experiments are expected. The relevance of this new viable region for the correct interpretation of recent experimental bounds is emphasized.Comment: 12 pages, 6 figure

Mixed Mediation of Supersymmetry Breaking with Anomalous U(1) Gauge Symmetry

Models with anomalous U(1) gauge symmetry contain various superfields which can have nonzero supersymmetry breaking auxiliary components providing the origin of soft terms in the visible sector, e.g. the U(1) vector superfield, the modulus or dilaton superfield implementing the Green-Schwarz anomaly cancellation mechanism, U(1)-charged but standard model singlet matter superfield required to cancel the Fayet-Iliopoulos term, and finally the supergravity multiplet. We examine the relative strength between these supersymmetry breaking components in a simple class of models, and find that various different mixed mediations of supersymmetry breaking, involving the modulus, gauge, anomaly and D-term mediations, can be realized depending upon the characteristics of D-flat directions and how those D-flat directions are stabilized with a vanishing cosmological constant. We identify two parameters which represent such properties and thus characterize how the various mediations are mixed. We also discuss the moduli stabilization and soft terms in a variant of KKLT scenario, in which the visible sector K\"ahler modulus is stabilized by the D-term potential of anomalous U(1) gauge symmetry.Comment: 30 pages, 5 figure

The mu problem and sneutrino inflation

We consider sneutrino inflation and post-inflation cosmology in the singlet extension of the MSSM with approximate Peccei-Quinn(PQ) symmetry, assuming that supersymmetry breaking is mediated by gauge interaction. The PQ symmetry is broken by the intermediate-scale VEVs of two flaton fields, which are determined by the interplay between radiative flaton soft masses and higher order terms. Then, from the flaton VEVs, we obtain the correct mu term and the right-handed(RH) neutrino masses for see-saw mechanism. We show that the RH sneutrino with non-minimal gravity coupling drives inflation, thanks to the same flaton coupling giving rise to the RH neutrino mass. After inflation, extra vector-like states, that are responsible for the radiative breaking of the PQ symmetry, results in thermal inflation with the flaton field, solving the gravitino problem caused by high reheating temperature. Our model predicts the spectral index to be n_s\simeq 0.96 due to the additional efoldings from thermal inflation. We show that a right dark matter abundance comes from the gravitino of 100 keV mass and a successful baryogenesis is possible via Affleck-Dine leptogenesis.Comment: 27 pages, no figures, To appear in JHE

Does the `Higgs' have Spin Zero?

The Higgs boson is predicted to have spin zero. The ATLAS and CMS experiments have recently reported of an excess of events with mass ~ 125 GeV that has some of the characteristics expected for a Higgs boson. We address the questions whether there is already any evidence that this excess has spin zero, and how this possibility could be confirmed in the near future. The excess observed in the gamma gamma final state could not have spin one, leaving zero and two as open possibilities. We calculate the angular distribution of gamma gamma pairs from the decays of a spin-two boson produced in gluon-gluon collisions, showing that is unique and distinct from the spin-zero case. We also calculate the distributions for lepton pairs that would be produced in the W W* decays of a spin-two boson, which are very different from those in Higgs decays, and note that the kinematics of the event selection used to produce the excess observed in the W W* final state have reduced efficiency for spin two.Comment: 22 pages, 22 figures, Version accepted for publication in JHEP, includes additional plots of dilepton mass distribution

Oral immunization of haemaggulutinin H5 expressed in plant endoplasmic reticulum with adjuvant saponin protects mice against highly pathogenic avian influenza A virus infection

Pandemics in poultry caused by the highly pathogenic avian influenza (HPAI) A virus occur too frequently globally, and there is growing concern about the HPAI A virus due to the possibility of a pandemic among humans. Thus, it is important to develop a vaccine against HPAI suitable for both humans and animals. Various approaches are underway to develop such vaccines. In particular, an edible vaccine would be a convenient way to vaccinate poultry because of the behaviour of the animals. However, an edible vaccine is still not available. In this study, we developed a strategy of effective vaccination of mice by the oral administration of transgenic Arabidopsis plants (HA-TG) expressing haemagglutinin (HA) in the endoplasmic reticulum (ER). Expression of HA in the ER resulted in its high-level accumulation, N-glycosylation, protection from proteolytic degradation and long-term stability. Oral administration of HA-TG with saponin elicited high levels of HA-specific systemic IgG and mucosal IgA responses in mice, which resulted in protection against a lethal influenza virus infection with attenuated inflammatory symptoms. Based on these results, we propose that oral administration of freeze-dried leaf powders from transgenic plants expressing HA in the ER together with saponin is an attractive strategy for vaccination against influenza A virus.X111411Ysciescopu

Concomitant CIS on TURBT does not impact oncological outcomes in patients treated with neoadjuvant or induction chemotherapy followed by radical cystectomy

© Springer-Verlag GmbH Germany, part of Springer Nature 2018Background: Cisplatin-based neoadjuvant chemotherapy (NAC) for muscle invasive bladder cancer improves all-cause and cancer specific survival. We aimed to evaluate whether the detection of carcinoma in situ (CIS) at the time of initial transurethral resection of bladder tumor (TURBT) has an oncological impact on the response to NAC prior to radical cystectomy. Patients and methods: Patients were identified retrospectively from 19 centers who received at least three cycles of NAC or induction chemotherapy for cT2-T4aN0-3M0 urothelial carcinoma of the bladder followed by radical cystectomy between 2000 and 2013. The primary and secondary outcomes were pathological response and overall survival, respectively. Multivariable analysis was performed to determine the independent predictive value of CIS on these outcomes. Results: Of 1213 patients included in the analysis, 21.8% had concomitant CIS. Baseline clinical and pathologic characteristics of the ‘CIS’ versus ‘no-CIS’ groups were similar. The pathological response did not differ between the two arms when response was defined as pT0N0 (17.9% with CIS vs 21.9% without CIS; p = 0.16) which may indicate that patients with CIS may be less sensitive to NAC or ≤ pT1N0 (42.8% with CIS vs 37.8% without CIS; p = 0.15). On Cox regression model for overall survival for the cN0 cohort, the presence of CIS was not associated with survival (HR 0.86 (95% CI 0.63–1.18; p = 0.35). The presence of LVI (HR 1.41, 95% CI 1.01–1.96; p = 0.04), hydronephrosis (HR 1.63, 95% CI 1.23–2.16; p = 0.001) and use of chemotherapy other than ddMVAC (HR 0.57, 95% CI 0.34–0.94; p = 0.03) were associated with shorter overall survival. For the whole cohort, the presence of CIS was also not associated with survival (HR 1.05 (95% CI 0.82–1.35; p = 0.70). Conclusion: In this multicenter, real-world cohort, CIS status at TURBT did not affect pathologic response to neoadjuvant or induction chemotherapy. This study is limited by its retrospective nature as well as variability in chemotherapy regimens and surveillance regimens.Peer reviewedFinal Accepted Versio

A statistical downscaling framework for environmental mapping

In recent years, knowledge extraction from data has become increasingly popular, with many numerical forecasting models, mainly falling into two major categories—chemical transport models (CTMs) and conventional statistical methods. However, due to data and model variability, data-driven knowledge extraction from high-dimensional, multifaceted data in such applications require generalisations of global to regional or local conditions. Typically, generalisation is achieved via mapping global conditions to local ecosystems and human habitats which amounts to tracking and monitoring environmental dynamics in various geographical areas and their regional and global implications on human livelihood. Statistical downscaling techniques have been widely used to extract high-resolution information from regional-scale variables produced by CTMs in climate model. Conventional applications of these methods are predominantly dimensional reduction in nature, designed to reduce spatial dimension of gridded model outputs without loss of essential spatial information. Their downside is twofold—complete dependence on unlabelled design matrix and reliance on underlying distributional assumptions. We propose a novel statistical downscaling framework for dealing with data and model variability. Its power derives from training and testing multiple models on multiple samples, narrowing down global environmental phenomena to regional discordance through dimensional reduction and visualisation. Hourly ground-level ozone observations were obtained from various environmental stations maintained by the US Environmental Protection Agency, covering the summer period (June–August 2005). Regional patterns of ozone are related to local observations via repeated runs and performance assessment of multiple versions of empirical orthogonal functions or principal components and principal fitted components via an algorithm with fully adaptable parameters. We demonstrate how the algorithm can be extended to weather-dependent and other applications with inherent data randomness and model variability via its built-in interdisciplinary computational power that connects data sources with end-users