High-frequency characterization of packaging network in to-can photodiode modules

A simple method for analyzing the effects of TO packaging network on the high-frequency response of photodiode modules is presented. This method is established based on the relations of the scattering parameters of the packaging network, photodiode chip, and module. It is shown that the results obtained by this method agree well with those obtained by the conventional comparison method. The proposed method is much more convenient since only the electrical domain measurements are required. (C) 2008 Wiley Periodicals, Inc.

Evaluation of the new ESR network software for the retrieval of direct sun products from cimel ce318 and prede pom01 sun-sky radiometers.

The European Skynet Radiometers network (EuroSkyRad or ESR) has been recently established as a research network of European PREDE sun-sky radiometers. Moreover, ESR is federated with SKYNET, an international network of PREDE sun-sky radiometers mostly present in East Asia. In contrast to SKYNET, the European network also integrates users of the CIMEL CE318 sky–sun photometer. Keeping instrumental duality in mind, a set of open source algorithms has been developed consisting of two modules for (1) the retrieval of direct sun products (aerosol optical depth, wavelength exponent and water vapor) from the sun extinction measurements; and (2) the inversion of the sky radiance to derive other aerosol optical properties such as size distribution, single scattering albedo or refractive index. In this study we evaluate the ESR direct sun products in comparison with the AERosol RObotic NETwork (AERONET) products. Specifically, we have applied the ESR algorithm to a CIMEL CE318 and PREDE POM simultaneously for a 4-yr database measured at the Burjassot site (Valencia, Spain), and compared the resultant products with the AERONET direct sun measurements obtained with the same CIMEL CE318 sky–sun photometer. The comparison shows that aerosol optical depth differences are mostly within the nominal uncertainty of 0.003 for a standard calibration instrument, and fall within the nominal AERONET uncertainty of 0.01–0.02 for a field instrument in the spectral range 340 to 1020 nm. In the cases of the Ångström exponent and the columnar water vapor, the differences are lower than 0.02 and 0.15 cm, respectively. Therefore, we present an open source code program that can be used with both CIMEL and PREDE sky radiometers and whose results are equivalent to AERONET and SKYNET retrievals.

The Interlaboratory Robustness Of Next-Generation Sequencing (IRON) Study Phase II: Deep-Sequencing Analyses Of Hematological Malignancies Performed In 8,867 Cases By An International Network Involving 27 Laboratories

Introduction: Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8).

Aims: In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany).

Results: We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies.

Conclusion: Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far.

Formal calibration methodology for CFD models of naturally ventilated indoor environments

Well planned natural ventilation strategies and systems in the built environments may provide healthy and comfortable indoor conditions, while contributing to a significant reduction in the energy consumed by buildings. Computational Fluid Dynamics (CFD) is particularly suited for modelling indoor conditions in naturally ventilated spaces, which are difficult to predict using other types of building simulation tools. Hence, accurate and reliable CFD models of naturally ventilated indoor spaces are necessary to support the effective design and operation of indoor environments in buildings. This paper presents a formal calibration methodology for the development of CFD models of naturally ventilated indoor environments. The methodology explains how to qualitatively and quantitatively verify and validate CFD models, including parametric analysis utilising the response surface technique to support a robust calibration process. The proposed methodology is demonstrated on a naturally ventilated study zone in the library building at the National University of Ireland in Galway. The calibration process is supported by the on-site measurements performed in a normally operating building. The measurement of outdoor weather data provided boundary conditions for the CFD model, while a network of wireless sensors supplied air speeds and air temperatures inside the room for the model calibration. The concepts and techniques developed here will enhance the process of achieving reliable CFD models that represent indoor spaces and provide new and valuable information for estimating the effect of the boundary conditions on the CFD model results in indoor environments. © 2012 Elsevier Ltd.

Comparative study of human erythrocytes by digital holographic microscopy, confocal microscopy, and impedance volume analyzer.

Red blood cell (RBC) parameters such as morphology, volume, refractive index, and hemoglobin content are of great importance for diagnostic purposes. Existing approaches require complicated calibration procedures and robust cell perturbation. As a result, reference values for normal RBC differ depending on the method used. We present a way for measuring parameters of intact individual RBCs by using digital holographic microscopy (DHM), a new interferometric and label-free technique with nanometric axial sensitivity. The results are compared with values achieved by conventional techniques for RBC of the same donor and previously published figures. A DHM equipped with a laser diode (lambda = 663 nm) was used to record holograms in an off-axis geometry. Measurements of both RBC refractive indices and volumes were achieved via monitoring the quantitative phase map of RBC by means of a sequential perfusion of two isotonic solutions with different refractive indices obtained by the use of Nycodenz (decoupling procedure). Volume of RBCs labeled by membrane dye Dil was analyzed by confocal microscopy. The mean cell volume (MCV), red blood cell distribution width (RDW), and mean cell hemoglobin concentration (MCHC) were also measured with an impedance volume analyzer. DHM yielded RBC refractive index n = 1.418 +/- 0.012, volume 83 +/- 14 fl, MCH = 29.9 pg, and MCHC 362 +/- 40 g/l. Erythrocyte MCV, MCH, and MCHC achieved by an impedance volume analyzer were 82 fl, 28.6 pg, and 349 g/l, respectively. Confocal microscopy yielded 91 +/- 17 fl for RBC volume. In conclusion, DHM in combination with a decoupling procedure allows measuring noninvasively volume, refractive index, and hemoglobin content of single-living RBCs with a high accuracy.

Calibration de systèmes de caméras et projecteurs dans des applications de création multimédia

Ce mémoire s'intéresse à la vision par ordinateur appliquée à des projets d'art technologique. Le sujet traité est la calibration de systèmes de caméras et de projecteurs dans des applications de suivi et de reconstruction 3D en arts visuels et en art performatif. Le mémoire s'articule autour de deux collaborations avec les artistes québécois Daniel Danis et Nicolas Reeves. La géométrie projective et les méthodes de calibration classiques telles que la calibration planaire et la calibration par géométrie épipolaire sont présentées pour introduire les techniques utilisées dans ces deux projets. La collaboration avec Nicolas Reeves consiste à calibrer un système caméra-projecteur sur tête robotisée pour projeter des vidéos en temps réel sur des écrans cubiques mobiles. En plus d'appliquer des méthodes de calibration classiques, nous proposons une nouvelle technique de calibration de la pose d'une caméra sur tête robotisée. Cette technique utilise des plans elliptiques générés par l'observation d'un seul point dans le monde pour déterminer la pose de la caméra par rapport au centre de rotation de la tête robotisée. Le projet avec le metteur en scène Daniel Danis aborde les techniques de calibration de systèmes multi-caméras. Pour son projet de théâtre, nous avons développé un algorithme de calibration d'un réseau de caméras wiimotes. Cette technique basée sur la géométrie épipolaire permet de faire de la reconstruction 3D d'une trajectoire dans un grand volume à un coût minime. Les résultats des techniques de calibration développées sont présentés, de même que leur utilisation dans des contextes réels de performance devant public.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Automatic internal calibration in liquid chromatography/Fourier transform ion cyclotron resonance mass spectrometry of protein digests

Accurately measured peptide masses can be used for large-scale protein identification from bacterial whole-cell digests as an alternative to tandem mass spectrometry (MS/MS) provided mass measurement errors of a few parts-per-million (ppm) are obtained. Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) routinely achieves such mass accuracy either with internal calibration or by regulating the charge in the analyzer cell. We have developed a novel and automated method for internal calibration of liquid chromatography (LC)/FTICR data from whole-cell digests using peptides in the sample identified by concurrent MS/MS together with ambient polydimethyl-cyclosiloxanes as internal calibrants in the mass spectra. The method reduced mass measurement error from 4.3 +/- 3.7 ppm to 0.3 +/- 2.3 ppm in an E. coli LC/FTICR dataset of 1000 MS and MS/MS spectra and is applicable to all analyses of complex protein digests by FTICRMS. Copyright (c) 2006 John Wiley & Sons, Ltd.

Observing wind, aerosol particles, clouds and precipitation: Finland's new ground-based remote-sensing network

The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

Network modelling for Townsville distribution system

Drinking water quality guidelines are becoming increasingly stringent. To comply with these guidelines and to manage water quality in a distribution system, improved understanding of the movement and fate of drinking water constituents within the system is required. This study illustrates the construction and calibration of an electronic model of the Townsville drinking water distribution system. Being in the tropics, the temperature of the water in the distribution system changes little throughout the year (usually between 20 and 25°C); also, water is supplied to the system from two sources, the location of the blending of these waters is varies with demand.

Prediction interval-based neural network modelling of polystyrene polymerization reactor - a new perspective of data-based modelling

In this paper, prediction interval (PI)-based modelling techniques are introduced and applied to capture the nonlinear dynamics of a polystyrene batch reactor system. Traditional NN models are developed using experimental datasets with and without disturbances. Simulation results indicate that traditional NNs cannot properly handle disturbances in reactor data and demonstrate a poor forecasting performance, with an average MAPE of 22% in the presence of disturbances. The lower upper bound estimation (LUBE) method is applied for the construction of PIs to quantify uncertainties associated with forecasts. The simulated annealing optimization technique is employed to adjust NN parameters for minimization of an innovative PI-based cost function. The simulation results reveal that the LUBE method generates quality PIs without requiring prohibitive computations. As both calibration and sharpness of PIs are practically and theoretically satisfactory, the constructed PIs can be used as part of the decision-making and control process of polymerization reactors. © 2014 The Institution of Chemical Engineers.

Uncertainty handling using neural network-based prediction intervals for electrical load forecasting

The complexity and level of uncertainty present in operation of power systems have significantly grown due to penetration of renewable resources. These complexities warrant the need for advanced methods for load forecasting and quantifying uncertainties associated with forecasts. The objective of this study is to develop a framework for probabilistic forecasting of electricity load demands. The proposed probabilistic framework allows the analyst to construct PIs (prediction intervals) for uncertainty quantification. A newly introduced method, called LUBE (lower upper bound estimation), is applied and extended to develop PIs using NN (neural network) models. The primary problem for construction of intervals is firstly formulated as a constrained single-objective problem. The sharpness of PIs is treated as the key objective and their calibration is considered as the constraint. PSO (particle swarm optimization) enhanced by the mutation operator is then used to optimally tune NN parameters subject to constraints set on the quality of PIs. Historical load datasets from Singapore, Ottawa (Canada) and Texas (USA) are used to examine performance of the proposed PSO-based LUBE method. According to obtained results, the proposed probabilistic forecasting method generates well-calibrated and informative PIs. Furthermore, comparative results demonstrate that the proposed PI construction method greatly outperforms three widely used benchmark methods. © 2014 Elsevier Ltd.

A methodology for simulating hydrogen sulphide generation in sewer network using EPA SWMM

Predicting hydrogen sulphide concentration in sewer network through modelling tools will be beneficial for many stakeholders to design appropriate mitigation strategies. However, the hydrogen sulphide modelling in a sewer network is crucially dependent on the hydraulic modelling of the sewer. The establishment of precise hydrogen sulphide and hydraulic modelling however requires detailed and accurate information about the sewer network structure and the model parameters. This paper outlines a novel approach for the development of hydraulic and hydrogen sulphide modelling to predict the concentration of hydrogen sulphide in sewer network. The approach combines the calculation of wastewater generation and implementation of flow routing on the EPA SWMM 5.0 platform to allow hydrodynamic simulations. Dynamic wave routing is used for hydraulic simulations. It is considered to be the best approach to route existing/old sewer flow. The build-up of hydrogen sulphide model includes the empirical models of hydrogen sulphide generation and emission. Trial of the model was conducted to simulate a sewer network in Seoul, South Korea with some hypothetical data. Further analysis on the use of chemical dosing on the sewer pipe was also performed by the model. Promising results have been obtained through the model, however calibration and validation of the model is required. The presented methodology provides a possibility of the free platform SWMM to be used as a prediction tool of hydrogen sulphide generation. © 2014 © 2014 Balaban Desalination Publications. All rights reserved.

Biomedical sensing analyzer (BSA) for mobile-health (mHealth)-LTE

The rapid expansion of mobile-based systems, the capabilities of smartphone devices, as well as the radio access and cellular network technologies are the wind beneath the wing of mobile health (mHealth). In this paper, the concept of biomedical sensing analyzer (BSA) is presented, which is a novel framework, devised for sensor-based mHealth applications. The BSA is capable of formulating the Quality of Service (QoS) measurements in an end-to-end sense, covering the entire communication path (wearable sensors, link-technology, smartphone, cell-towers, mobile-cloud, and the end-users). The characterization and formulation of BSA depend on a number of factors, including the deployment of application-specific biomedical sensors, generic link-technologies, collection, aggregation, and prioritization of mHealth data, cellular network based on the Long-Term Evolution (LTE) access technology, and extensive multidimensional delay analyses. The results are studied and analyzed in a LabView 8.5 programming environment.

Comparison Of Demand Pattern Calibration In Water Distribution Networks With Geographic And Non-Geographic Parameterization

Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.