Hand-held voltammetric analyser for real-time monitoring of heavy metals in situ

This paper presents a novel hand-held instrument capable of real-time in situ detection and identification of heavy metals. The proposed system provides the facilities found in a traditional lab-based instrument in a hand held a design. In contrast to existing commercial systems, it can stand alone without the need of an associated computer. The electrochemical instrument uses anodic stripping voltammetry which is a precise and sensitive analytical method with excellent limits of detection. The sensors comprise disposable screen-printed (solid working) electrodes rather than the more common hanging mercury drop electrodes. The system is reliable, easy to use, safe, avoids expensive and time-consuming procedures and may be used in a variety of situations to help in the fields of environmental assessment and control.

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

Pegada hídrica de um olival super-intensivo sob clima mediterrânico, utilizando medições de campo e deteção remota

A pegada hídrica de uma cultura representa o volume de água necessário para produzir, relacionando as necessidades hídricas da cultura com a produção. As suas componentes, pegadas hídricas azul, verde e cinzenta, referem-se respectivamente aos volumes de água superficial e subterrânea, precipitação e de água necessária para assimilar a poluição utilizados pela cultura. A determinação das pegadas hídricas azul e verde é normalmente conseguida através da estimativa da evapotranspiração cultural, aplicando coeficientes culturais a uma evapotranspiração de referência, calculada a partir de dados meteorológicos. No presente estudo foram utilizadas medições da evapotranspiração para estimar a pegada hídrica de um olival super-intensivo na região de Évora. As necessidades hídricas foram medidas utilizando um método de fluxo de seiva para determinar a transpiração e o método micrometeorológico das flutuações instantâneas para medir directamente a evapotranspiração. Esta técnica foi utilizada durante um período de tempo limitado, enquanto as medições do fluxo de seiva, que foram efectuadas para períodos alargados, permitiram a extensão dos registos. A evapotranspiração medida directamente apresentou valores de cerca de 3 mm d-1 e o quociente entre evapotranspiração real e evapotranspiração de referência é próximo de 0,6 para o mesmo período. Comparou-se a estimativa da pegada hídrica obtida com o procedimento habitual com a resultante de medições in-situ e utilizando técnicas de deteção remota. A pegada hídrica do olival sob estudo foi inferior às simulações encontradas na literatura, o que pode ser explicado por diferenças na densidade de plantação, produção e gestão da rega. O olival em estudo obteve uma produção elevada, com um azeite que preencheu as características essenciais à classificação de azeite extra virgem, o mais valorizado, o que contraria o efeito do elevado consumo de água, resultando numa pegada hídrica inferior à de olivais não regados ou com menor densidade de plantação.

A Single-Frame Super-Resolution Innovative Approach

Super-resolution refers to the process of obtaining a high resolution image from one or more low resolution images. In this work, we present a novel method for the super-resolution problem for the limited case, where only one image of low resolution is given as an input. The proposed method is based on statistical learning for inferring the high frequencies regions which helps to distinguish a high resolution image from a low resolution one. These inferences are obtained from the correlation between regions of low and high resolution that come exclusively from the image to be super-resolved, in term of small neighborhoods. The Markov random fields are used as a model to capture the local statistics of high and low resolution data when they are analyzed at different scales and resolutions. Experimental results show the viability of the method.

Real time manufacturing systems simulator

A área da simulação computacional teve um rápido crescimento desde o seu apareciment, sendo actualmente uma das ciências de gestão e de investigação operacional mais utilizadas. O seu princípio baseia-se na replicação da operação de processos ou sistemas ao longo de períodos de tempo, tornando-se assim uma metodologia indispensável para a resolução de variados problemas do mundo real, independentemente da sua complexidade. Das inúmeras áreas de aplicação, nos mais diversos campos, a que mais se destaca é a utilização em sistemas de produção, onde o leque de aplicações disponível é muito vasto. A sua aplicação tem vindo a ser utilizada para solucionar problemas em sistemas de produção, uma vez que permite às empresas ajustar e planear de uma maneira rápida, eficaz e ponderada as suas operações e os seus sistemas, permitindo assim uma rápida adaptação das mesmas às constantes mudanças das necessidades da economia global. As aplicações e packages de simulação têm seguindo as tendências tecnológicas pelo que é notório o recurso a tecnologias orientadas a objectos para o desenvolvimento das mesmas. Este estudo baseou-se, numa primeira fase, na recolha de informação de suporte aos conceitos de modelação e simulação, bem como a respectiva aplicação a sistemas de produção em tempo real. Posteriormente centralizou-se no desenvolvimento de um protótipo de uma aplicação de simulação de ambientes de fabrico em tempo real. O desenvolvimento desta ferramenta teve em vista eventuais fins pedagógicos e uma utilização a nível académico, sendo esta capaz de simular um modelo de um sistema de produção, estando também dotada de animação. Sem deixar de parte a possibilidade de integração de outros módulos ou, até mesmo, em outras plataformas, houve ainda a preocupação acrescida de que a sua implementação recorresse a metodologias de desenvolvimento orientadas a objectos.

A framework for fault tolerant real time systems based on reconfigurable FPGAs

To increase the amount of logic available to the users in SRAM-based FPGAs, manufacturers are using nanometric technologies to boost logic density and reduce costs, making its use more attractive. However, these technological improvements also make FPGAs particularly vulnerable to configuration memory bit-flips caused by power fluctuations, strong electromagnetic fields and radiation. This issue is particularly sensitive because of the increasing amount of configuration memory cells needed to define their functionality. A short survey of the most recent publications is presented to support the options assumed during the definition of a framework for implementing circuits immune to bit-flips induction mechanisms in memory cells, based on a customized redundant infrastructure and on a detection-and-fix controller.

Development and Deployment of Wireless Sensor Network in Paddy Fields of Kuttanad

The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

Assessing the uncertainty associated with intermittent rainfall fields

[1] In many practical situations where spatial rainfall estimates are needed, rainfall occurs as a spatially intermittent phenomenon. An efficient geostatistical method for rainfall estimation in the case of intermittency has previously been published and comprises the estimation of two independent components: a binary random function for modeling the intermittency and a continuous random function that models the rainfall inside the rainy areas. The final rainfall estimates are obtained as the product of the estimates of these two random functions. However the published approach does not contain a method for estimation of uncertainties. The contribution of this paper is the presentation of the indicator maximum likelihood estimator from which the local conditional distribution of the rainfall value at any location may be derived using an ensemble approach. From the conditional distribution, representations of uncertainty such as the estimation variance and confidence intervals can be obtained. An approximation to the variance can be calculated more simply by assuming rainfall intensity is independent of location within the rainy area. The methodology has been validated using simulated and real rainfall data sets. The results of these case studies show good agreement between predicted uncertainties and measured errors obtained from the validation data.

Quantifying mesoscale variability in ocean transient tracer fields

A powerful way to test the realism of ocean general circulation models is to systematically compare observations of passive tracer concentration with model predictions. The general circulation models used in this way cannot resolve a full range of vigorous mesoscale activity (on length scales between 10–100 km). In the real ocean, however, this activity causes important variability in tracer fields. Thus, in order to rationally compare tracer observations with model predictions these unresolved fluctuations (the model variability error) must be estimated. We have analyzed this variability using an eddy‐resolving reduced‐gravity model in a simple midlatitude double‐gyre configuration. We find that the wave number spectrum of tracer variance is only weakly sensitive to the distribution of (large scale slowly varying) tracer sources and sinks. This suggests that a universal passive tracer spectrum may exist in the ocean. We estimate the spectral shape using high‐resolution measurements of potential temperature on an isopycnal in the upper northeast Atlantic Ocean, finding a slope near k −1.7 between 10 and 500 km. The typical magnitude of the variance is estimated by comparing tracer simulations using different resolutions. For CFC‐ and tritium‐type transient tracers the peak magnitude of the model variability saturation error may reach 0.20 for scales shorter than 100 km. This is of the same order as the time mean saturation itself and well over an order of magnitude greater than the instrumental uncertainty.

An analysis of real time implementation of Fourier transform-based frequency recognition algorithms

Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

Quantifying volcanic ash dispersal and impact of the Campanian Ignimbrite super-eruption

1] We apply a novel computational approach to assess, for the first time, volcanic ash dispersal during the Campanian Ignimbrite (Italy) super-eruption providing insights into eruption dynamics and the impact of this gigantic event. The method uses a 3D time-dependent computational ash dispersion model, a set of wind fields, and more than 100 thickness measurements of the CI tephra deposit. Results reveal that the CI eruption dispersed 250–300 km3 of ash over ∼3.7 million km2. The injection of such a large quantity of ash (and volatiles) into the atmosphere would have caused a volcanic winter during the Heinrich Event 4, the coldest and driest climatic episode of the Last Glacial period. Fluorine-bearing leachate from the volcanic ash and acid rain would have further affected food sources and severely impacted Late Middle-Early Upper Paleolithic groups in Southern and Eastern Europe

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

C(k)-solvability near the characteristic set for a class of planar complex vector fields of infinite type

This paper deals with semi-global C(k)-solvability of complex vector fields of the form L = partial derivative/partial derivative t + x(r) (a(x) + ib(x))partial derivative/partial derivative x, r >= 1, defined on Omega(epsilon) = (-epsilon, epsilon) x S(1), epsilon > 0, where a and b are C(infinity) real-valued functions in (-epsilon, epsilon). It is shown that the interplay between the order of vanishing of the functions a and b at x = 0 influences the C(k)-solvability at Sigma = {0} x S(1). When r = 1, it is permitted that the functions a and b of L depend on the x and t variables, that is, L = partial derivative/partial derivative t + x(a(x, t) + ib(x, t))partial derivative/partial derivative x, where (x, t) is an element of Omega(epsilon).

Generalized pseudo-likelihood estimates for markov random fields on lattice

In this paper we generalize Besag's pseudo-likelihood function for spatial statistical models on a region of a lattice. The correspondingly defined maximum generalized pseudo-likelihood estimates (MGPLEs) are natural extensions of Besag's maximum pseudo-likelihood estimate (MPLE). The MGPLEs connect the MPLE and the maximum likelihood estimate. We carry out experimental calculations of the MGPLEs for spatial processes on the lattice. These simulation results clearly show better performances of the MGPLEs than the MPLE, and the performances of differently defined MGPLEs are compared. These are also illustrated by the application to two real data sets.

Tree-based iterated local search for Markov random fields with applications in image analysis

The maximum a posteriori assignment for general structure Markov random fields is computationally intractable. In this paper, we exploit tree-based methods to efficiently address this problem. Our novel method, named Tree-based Iterated Local Search (T-ILS), takes advantage of the tractability of tree-structures embedded within MRFs to derive strong local search in an ILS framework. The method efficiently explores exponentially large neighborhoods using a limited memory without any requirement on the cost functions. We evaluate the T-ILS on a simulated Ising model and two real-world vision problems: stereo matching and image denoising. Experimental results demonstrate that our methods are competitive against state-of-the-art rivals with significant computational gain.