Photonic crystal chips for optical interconnects and quantum information processing

We have recently demonstrated a number of functional photonic crystals devices and circuits, including an ultrafast, room temperature, low threshold, nanocavity laser with the direct modulation speed approaching 1 THz, an all-optical switch controlled with 60 fJ pulses and with the speed exceeding 200Hz, and a local, reversible tuning of individual quantum dots on a photonic crystal chip by up to 1.8nm, which was then used to tune single quantum dots into strong coupling with a photonic crystal cavity and to achieve a giant optical nonlinearity

An impact assessment methodology for urban surface runoff quality following best practice treatment

The paper develops an easy to apply desk-based semi-quantitative approach for the assessment of residual receiving water quality risks associated with urban surface runoff following its conveyance through best practice sustainable drainage systems (SUDS). The innovative procedure utilises an integrated geographical information system (GIS)-based pollution index approach based on surface area impermeability, runoff concentrations/loadings and individual SUDS treatment performance potential to evaluate the level of risk mitigation achievable by SUDS drainage infrastructure. The residual impact is assessed through comparison of the determined pollution index with regulatory receiving water quality standards and objectives. The methodology provides an original theoretically based procedure which complements the current acute risk assessment approaches being widely applied within pluvial flood risk management

Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

Effects of invisible particle emission on global inclusive variables at hadron colliders

We examine the effects of invisible particle emission in conjunction with QCD initial state radiation (ISR) on quantities designed to probe the mass scale of new physics at hadron colliders, which involve longitudinal as well as transverse final-state momenta. This is an extension of our previous treatment, arXiv:0903.2013, of the effects of ISR on global inclusive variables. We present resummed results on the visible invariant mass distribution and compare them to parton-level Monte Carlo results for top quark and gluino pair-production at the LHC. There is good agreement as long as the visible pseudorapidity interval is large enough (eta ~ 3). The effect of invisible particle emission is small in the case of top pair production but substantial for gluino pair production. This is due mainly to the larger mass of the intermediate particles in gluino decay (squarks rather than W-bosons). We also show Monte Carlo modelling of the effects of hadronization and the underlying event. The effect of the underlying event is large but may be approximately universal.Comment: 22 pages, expanded sections and other minor modifications. Version published in JHE

CNN Architectures for Large-Scale Audio Classification

Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNNs), AlexNet [1], VGG [2], Inception [3], and ResNet [4]. We investigate varying the size of both training set and label vocabulary, finding that analogs of the CNNs used in image classification do well on our audio classification task, and larger training and label sets help up to a point. A model using embeddings from these classifiers does much better than raw features on the Audio Set [5] Acoustic Event Detection (AED) classification task.Comment: Accepted for publication at ICASSP 2017 Changes: Added definitions of mAP, AUC, and d-prime. Updated mAP/AUC/d-prime numbers for Audio Set based on changes of latest Audio Set revision. Changed wording to fit 4 page limit with new addition

Assessing the impact of Swales on receiving water quality

Swales are one type of sustainable drainage system (SuDS) which contribute to the management of water quality in receiving waterbodies. Using a semi-quantitative approach, an impact assessment procedure is applied to the residual water quality that is carried forward to surface waters and groundwaters following treatment within a swale. Both volumetric and pollutant distributions are considered as stormwater passes through the swale system. The pollutant pathways followed by TSS, nitrate, chloride, metals (Cd, Cu, Pb, Zn) and polyaromatic hydrocarbons (PAHs) are determined for a swale receiving highway runoff. For TSS, metals and PAHs between 20% and 29% of the total mean influent pollutant load is predicted to be directed to infiltration through the underlying soils compared to between 4% and 16% of chloride and nitrate. Although surface water impacts are deemed possible, the discharges of swales to groundwaters are assessed to represent a negligible impact for effectively maintained systems

Flight Deck-Based Delegated Separation: Evaluation of an On-Board Interval Management System with Synthetic and Enhanced Vision Technology

An emerging Next Generation Air Transportation System concept - Equivalent Visual Operations (EVO) - can be achieved using an electronic means to provide sufficient visibility of the external world and other required flight references on flight deck displays that enable the safety, operational tempos, and visual flight rules (VFR)-like procedures for all weather conditions. Synthetic and enhanced flight vision system technologies are critical enabling technologies to EVO. Current research evaluated concepts for flight deck-based interval management (FIM) operations, integrated with Synthetic Vision and Enhanced Vision flight-deck displays and technologies. One concept involves delegated flight deck-based separation, in which the flight crews were paired with another aircraft and responsible for spacing and maintaining separation from the paired aircraft, termed, "equivalent visual separation." The operation required the flight crews to acquire and maintain an "equivalent visual contact" as well as to conduct manual landings in low-visibility conditions. The paper describes results that evaluated the concept of EVO delegated separation, including an off-nominal scenario in which the lead aircraft was not able to conform to the assigned spacing resulting in a loss of separation

UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python

The land surface, hydrological, and groundwater modelling communities all have expertise in simulating the hydrological processes at play in the terrestrial component of the Earth system. However, these communities, and the wider Earth system modelling community, have largely remained distinct with limited collaboration between disciplines, hindering progress in the representation of hydrological processes in the land component of Earth system models (ESMs). In order to address key societal questions regarding the future availability of water resources and the intensity of extreme events such as floods and droughts in a changing climate, these communities must come together and build on the strengths of one another to produce next-generation land system models that are able to adequately simulate the terrestrial water cycle under change. The development of a common modelling infrastructure can contribute to stimulating cross-fertilisation by structuring and standardising the interactions. This paper presents such an infrastructure, a land system framework, which targets an intermediate level of complexity and constrains interfaces between components (and communities) and, in doing so, aims to facilitate an easier pipeline between the development of (sub-)community models and their integration, both for standalone use and for use in ESMs. This paper first outlines the conceptual design and technical capabilities of the framework; thereafter, its usage and useful characteristics are demonstrated through case studies. The main innovations presented here are (1) the interfacing constraints themselves; (2) the implementation in Python (the Unified Framework for Hydrology, unifhy); and (3) the demonstration of standalone use cases using the framework. The existing framework does not yet meet all our goals, in particular, of directly supporting integration into larger ESMs, so we conclude with the remaining limitations of the current framework and necessary future developments.</p

Fair scans of the seesaw. Consequences for predictions on LFV processes

Usual analyses based on scans of the seesaw parameter-space can be biassed since they do not cover in a fair way the complete parameter-space. More precisely, we show that in the common "R-parametrization", many acceptable R-matrices, compatible with the perturbativity of Yukawa couplings, are normally disregarded from the beginning, which produces biasses in the results. We give a straightforward procedure to scan the space of complex R-matrices in a complete way, giving a very simple rule to incorporate the perturbativity requirement as a condition for the entries of the R-matrix, something not considered before. As a relevant application of this, we show that the extended believe that BR(mu --> e, gamma) in supersymmetric seesaw models depends strongly on the value of theta_13 is an "optical effect" produced by such biassed scans, and does not hold after a careful analytical and numerical study. When the complete scan is done, BR(mu --> e, gamma) gets very insensitive to theta_13. Moreover, the values of the branching ratio are typically larger than those quoted in the literature, due to the large number of acceptable points in the parameter-space which were not considered before. Including (unflavoured) leptogenesis does not introduce any further dependence on theta_13, although decreases the typical value of BR(mu --> e, gamma).Comment: 22 pages, 5 figure

Effect of state-mandated insurance coverage on accrual to community cancer clinical trials

Thirty-five U.S. states and territories have implemented policies requiring insurers to cover patient care costs in the context of cancer clinical trials; however, evidence of the effectiveness of these policies is limited. This study assesses the impact of state insurance mandates on clinical trial accrual among community-based practices participating in the NCI Community Clinical Oncology Program (CCOP), which enrolls approximately one-third of all NCI cancer trial participants. We analyzed CCOP clinical trial enrollment over 17 years in 37 states, 14 of which implemented coverage policies, using fixed effects least squares regression to estimate the effect of state policies on trial accrual among community providers, controlling for state and CCOP differences in capacity to recruit. Of 91 CCOPs active during this time, 28 were directly affected by coverage mandates. Average recruitment per CCOP between 1991 and 2007 was 95.1 participants per year (SD = 55.8). CCOPs in states with a mandate recruited similar numbers of participants compared to states without a mandate. In multivariable analysis, treatment trial accrual among CCOPs in states that had implemented a coverage mandate, was not statistically different than accrual among CCOPs in states that did not implement a coverage mandate (β = 2.95, p = 0.681). State mandates did not appear to confer a benefit in terms of CCOP clinical trial accrual. State policies vary in strength, which may have diluted their effect on accrual. Nonetheless, policy mandates alone may not have a meaningful impact on participation in clinical trials in these states