Properties of extragalactic dust inferred from linear polarimetry of Type Ia Supernovae

Aims
The aim of this paper is twofold: 1) to investigate the properties of extragalactic dust and compare them to what is seen in the Galaxy; 2) to address in an independent way the problem of the anomalous extinction curves reported for reddened Type Ia Supernovae (SN) in connection to the environments in which they explode. 

Methods
The properties of the dust are derived from the wavelength dependence of the continuum polarization observed in four reddened Type Ia SN: 1986G, 2006X, 2008fp, and 2014J. The method is based on the observed fact that Type Ia SN have a negligible intrinsic continuum polarization. This and their large luminosity makes them ideal tools to probe the dust properties in extragalactic environments.

Results
All four objects are characterized by exceptionally low total-to-selective absorption ratios (R<inf>V</inf>) and display an anomalous interstellar polarization law, characterized by very blue polarization peaks. In all cases the polarization position angle is well aligned with the local spiral structure. While SN 1986G is compatible with the most extreme cases of interstellar polarization known in the Galaxy, SN 2006X, 2008fp, and 2014J show unprecedented behaviours. The observed deviations do not appear to be connected to selection effects related to the relatively large amounts of reddening characterizing the objects in the sample.

Conclusions
The dust responsible for the polarization of these four SN is most likely of interstellar nature. The polarization properties can be interpreted in terms of a significantly enhanced abundance of small grains. The anomalous behaviour is apparently associated with the properties of the galactic environment in which the SN explode, rather than with the progenitor system from which they originate. For the extreme case of SN 2014J, we cannot exclude the contribution of light scattered by local material; however, the observed polarization properties require an ad hoc geometrical dust distribution.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

The TARANIS laser : A multi-terawatt system for laser plasma physics

The Terawatt Apparatus for Relativistic And Non-linear Interdisciplinary Science (TARANIS), installed in the Centre for Plasma Physics at the Queen's University Belfast, supports a wide ranging science program, including laser-driven particle acceleration, X-ray lasers and high energy density physics experiments. We present (1) an overview of the laser facility, (2) results of preliminary investigations on proton acceleration, laser action at 13.9 nm and Kα sources and (3) speculation on future experiments using these extreme sources.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Parametric study to extract bridge frequencies from the dynamic response of passing vehicles

A conventional way to identify bridge frequencies is utilizing vibration data measured directly from the bridge. A drawback with this approach is that the deployment and maintenance of the vibration sensors are generally costly and time-consuming. One way to cope with the drawback is an indirect approach utilizing vehicle vibrations while the vehicle passes over the bridge. In the indirect approach, however, the vehicle vibration includes the effect of road surface roughness, which makes it difficult to extract the bridge modal properties. One solution may be subtracting signals of two trailers towed by a vehicle to reduce the effect of road surface roughness. A simplified vehicle-bridge interaction model is used in the numerical simulation; the vehicle - trailer and bridge system are modeled as a coupled model. In addition, a laboratory experiment is carried out to verify results of the simulation and examine feasibility of the damage detection by the indirect method.

Novel system for distant assessment of cataract surgical quality in rural China

BACKGROUND: This study aims to assess the quality of various steps of manual small incision cataract surgery and predictors of quality, using video recordings.
DESIGN: This paper applies a retrospective study.
PARTICIPANTS: Fifty-two trainees participated in a hands-on small incision cataract surgery training programme at rural Chinese hospitals.
METHODS: Trainees provided one video each recorded by a tripod-mounted digital recorder after completing a one-week theoretical course and hands-on training monitored by expert trainers. Videos were graded by two different experts, using a 4-point scale developed by the International Council of Ophthalmology for each of 12 surgical steps and six global factors. Grades ranged from 2 (worst) to 5 (best), with a score of 0 if the step was performed by trainers.
MAIN OUTCOME MEASURES: Mean score for the performance of each cataract surgical step rated by trainers.
RESULTS: Videos and data were available for 49/52 trainees (94.2%, median age 38 years, 16.3% women and 77.5% completing > 50 training cases). The majority (53.1%, 26/49) had performed ≤ 50 cataract surgeries prior to training. Kappa was 0.57∼0.98 for the steps (mean 0.85). Poorest-rated steps were draping the surgical field (mean ± standard deviation = 3.27 ± 0.78), hydro-dissection (3.88 ± 1.22) and wound closure (3.92 ± 1.03), and top-rated steps were insertion of viscoelastic (4.96 ± 0.20) and anterior chamber entry (4.69 ± 0.74). In linear regression models, higher total score was associated with younger age (P = 0.015) and having performed >50 independent manual small incision cases (P = 0.039).
CONCLUSIONS: More training should be given to preoperative draping, which is poorly performed and crucial in preventing infection. Surgical experience improves ratings.© 2015 Royal Australian and New Zealand College of Ophthalmologists.

Parametric scans of HB and LS-RPA regimes employing Petawatt laser

By contrast to the Target Normal Sheath acceleration (TNSA) mechanism [1], Radiation Pressure Acceleration (RPA) is currently attracting a substantial amount of experimental [2,3] and theoretical [4-6] attention worldwide due to its superior scaling in terms of ion energy and laser-ion conversion efficiency. Employing Vulcan Petawatt lasers of the Rutherford Appleton Laboratory, UK, both the Hole-boring (HB) and the Light-Sail (LS) regimes of the RPA have been extensively explored. When the target thickness is of the order of hole-boring velocity times the laser pulse duration, highly collimated plasma jets of near solid density are ejected from the foil, lasting up to ns after the laser interaction. By changing the linear polarisation of the laser to circular, improved homogeneity in the jet's spatial density profile is achieved which suggests more uniform and sustained radiation pressure drive on target ions. By decreasing the target areal density or increasing irradiance on the target, the LS regime of the RPA is accessed where relatively high flux (~ 1012 particles/MeV/Sr) of ions are accelerated to ~ 10 MeV/nucleon energies in a narrow energy bandwidth. The ion energy scaling obtained from the parametric scans agrees well with theoretical estimation based on RPA mechanism and the narrow bandwidth feature in the ion spectra is studied by 2D particle-in-simulations.

Behavioral modeling optimization and enhancement for high-speed analog mixed-signal I/O interfaces

A integridade do sinal em sistemas digitais interligados de alta velocidade, e avaliada através da simulação de modelos físicos (de nível de transístor) é custosa de ponto vista computacional (por exemplo, em tempo de execução de CPU e armazenamento de memória), e exige a disponibilização de detalhes físicos da estrutura interna do dispositivo. Esse cenário aumenta o interesse pela alternativa de modelação comportamental que descreve as características de operação do equipamento a partir da observação dos sinais eléctrico de entrada/saída (E/S). Os interfaces de E/S em chips de memória, que mais contribuem em carga computacional, desempenham funções complexas e incluem, por isso, um elevado número de pinos. Particularmente, os buffers de saída são obrigados a distorcer os sinais devido à sua dinâmica e não linearidade. Portanto, constituem o ponto crítico nos de circuitos integrados (CI) para a garantia da transmissão confiável em comunicações digitais de alta velocidade. Neste trabalho de doutoramento, os efeitos dinâmicos não-lineares anteriormente negligenciados do buffer de saída são estudados e modulados de forma eficiente para reduzir a complexidade da modelação do tipo caixa-negra paramétrica, melhorando assim o modelo standard IBIS. Isto é conseguido seguindo a abordagem semi-física que combina as características de formulação do modelo caixa-negra, a análise dos sinais eléctricos observados na E/S e propriedades na estrutura física do buffer em condições de operação práticas. Esta abordagem leva a um processo de construção do modelo comportamental fisicamente inspirado que supera os problemas das abordagens anteriores, optimizando os recursos utilizados em diferentes etapas de geração do modelo (ou seja, caracterização, formulação, extracção e implementação) para simular o comportamento dinâmico não-linear do buffer. Em consequência, contributo mais significativo desta tese é o desenvolvimento de um novo modelo comportamental analógico de duas portas adequado à simulação em overclocking que reveste de um particular interesse nas mais recentes usos de interfaces de E/S para memória de elevadas taxas de transmissão. A eficácia e a precisão dos modelos comportamentais desenvolvidos e implementados são qualitativa e quantitativamente avaliados comparando os resultados numéricos de extracção das suas funções e de simulação transitória com o correspondente modelo de referência do estado-da-arte, IBIS.

Validation of the needle targeting accuracy of a MRI/TRUS- image-guided system for transperineal prostate cancer biopsy

Multi-parametric magnetic resonance imaging (mp-MRI) has become an increasingly important method for detecting and treating prostate cancer. Transrectal ultrasound (TRUS) is the most commonly used method for guiding prostate needle biopsy and remains the gold standard for diagnosis of prostate cancer. MRI-to-TRUS image reg- istration is an important technology for enabling computer-assisted targeting of the majority of prostate lesions that are visible in MRI but not independently distinguishable in TRUS images. The aim of this study was to estimate the needle placement accuracy of an image guidance system (SmartTargetÒ), developed by our research group, using a surgical training phantom.

An heuristic approach for optimal location of gas supply units in transportation system

The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Fractional dynamics of a system with particles subjected to impacts

This paper studies the dynamics of a system composed of a collection of particles that exhibit collisions between them. Several entropy measures and different impact conditions of the particles are tested. The results reveal a Power Law evolution both of the system energy and the entropy measures, typical in systems having fractional dynamics.

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.