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Carbon monoxide (CO) detection in human breath is the focus of much research because of CO's possible use as a marker molecule for different diseases. Detecting CO in human breath remains a tough challenge because of the low concentrations of CO (ppm range) that must be detected. Another problem is that many other molecules, which can be found in human breath, can interfere in these measurements. Additionally, a time resolution of less than 1 s is needed to resolve the CO curve of an exhalation. In this study (13)CO instead of (12)CO concentration is measured. The measurements are performed with a cavity leak-out spectroscopy system. The system's properties match the above-mentioned specifications for measurements, even of the rare isotopologue with high specificity, a time resolution of less than 1 s and a detection limit of 7 ppb Hz(-1/2). Two investigations are presented here. The first is a measurement showing intraday changes between 9.5% and 23.3% of the exhaled CO level due to vigorous exercise. The second shows a long-term observation of the CO base level revealing natural variations in the recorded CO concentration. The covered time period is 25 weeks during which the differences between the minimum and maximum CO levels for each test case reached 84%.

It is our great honor today to present our program on the on-line analysis of RR interval variability.

The use of dielectrophoresis for the construction of artificial skin tissue with skin cells in follicle-like 3D cell aggregates in well-defined patterns is demonstrated. To analyse the patterns produced and to study their development after their formation a Virtual Instrument (VI) system was developed using the LabVIEW IMAQ Vision Development Module. A series of programming functions (algorithms) was used to isolate the features on the image (in our case; the patterned aggregates) and separate them from all other unwanted regions on the image. The image was subsequently converted into a binary version, covering only the desired microarray regions which could then be analysed by computer for automatic object measurements. The analysis utilized the simple and easy-to-use User-Specified Multi-Regions Masking (MRM) technique, which allows one to concentrate the analysis on the desired regions specified in the mask. This simplified the algorithms for the analysis of images of cell arrays having similar geometrical properties. By having a collection of scripts containing masks of different patterns, it was possible to quickly and efficiently develop sets of custom virtual instruments for the offline or online analysis of images of cell arrays in the database.

Giovanni, the Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization and Analysis Infrastructure, has provided researchers with advanced capabilities to perform data exploration and analysis with observational data from NASA Earth observation satellites. In the past 5-10 years, examining geophysical events and processes with remote-sensing data required a multistep process of data discovery, data acquisition, data management, and ultimately data analysis. Giovanni accelerates this process by enabling basic visualization and analysis directly on the World Wide Web. In the last two years, Giovanni has added new data acquisition functions and expanded analysis options to increase its usefulness to the Earth science research community.

The fast-growing demand of computational fluid dynamics (CFD) application for computing resources stimulates the development of high performance computing (HPC) and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis. In response to large-scale and long-time running for the application of CFD, online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency. As a result, this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system. The infrastructure is part of the parallel application performance monitor and analysis system (PAPMAS) and is composed of two modules which are scalable data transmission module and data storage module. The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation. Furthermore, some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.

Application investigations of rapid biochemical oxygen demand (BOD) online analyzer for surface water in Wuxi, China were carried out since 2013. The analyzer adopted a novel working principle, that is, the oxygen concentration of the sample to be tested was regarded as a reference, and the oxygen consumption by the biofilm reactor (BFR) was calculated according to the difference between the reference and sample effluent from BFR. The BFR was fabricated via a cultivation process using naturally occurring microbial seeds from in site surface water. This analytical principle was first presented and clearly clarified, and the impact of microbial endogenous respiration to the measured values was also proposed and analyzed. The improved analyzers were equipped in three application sites with significant differences in BOD concentration, for the purpose of evaluating the feasibility and applicability of the proposed method. This study revealed that the online analyzer could continually operate over 30 days without human intervention and additional chemical reagent consumption. The obtained rapid BOD trend line showed that this analyzer could track the fluctuation of the biodegradable organic compound level timely and accurately. The innovative analytical method, as well as the outstanding adaptation and well accuracy rating, provided the highlights for wide applications in the future. Keywords: Biofilm reactor, Biochemical oxygen demand (BOD), Application demonstration, Online analysis

FOLK is an online analysis and retrieval system developed for the 1801 census of Norway, which is machine readable in a full-text and a coded version, each with approximately 1,000,000 records on individuals. The main advantage of the system is speed. FOLK consists of several parts:- A fast program for statistical analysis of the simple kind. Cross tabulations can be done in 1/16 of the time used by SPSS.- An interface to statistical and graphical packages for more complicated analysis.- A retrieval system for finding subsets of the data base. The subset can be anything from a single person to a region. Information from the coded and the full text version can be used for subtracting individuals.- A recoding system for recoding the coded version using a simple semantic analysis of the full-text version.- A fully computerized record linkage system. Information from other sources can be automatically added to the records on the individuals in the census.

Expert systems provide a new way of dealing with the computer-aided management of nuclear plants by combining several knowledge bases and reasoning modes together with a set of numerical models for real-time analysis of transients. New development tools are required together with metaknowledge bases handling temporal hypothetical reasoning and planning. They have to be efficient and robust because during a transient, neither measurements nor models, nor scenarios are hold as absolute references. SEXTANT is a general purpose physical analyzer intended to provide a pattern and avoid duplication of general tools and knowledge bases for similar applications. It combines several knowledge bases concerning measurements, models and qualitative behavior of PWR with a mechanism of conjecture-refutation and a set of simplified models matching the current physical state. A prototype is under assessment by dealing with integral test facility transients. For its development, SEXTANT requires a powerful shell. SPIRAL is such a toolkit, oriented towards online analysis of complex processes and already used in several applications.

There is currently a lot of activity in R\&D for future collider experiments. Multiple detector prototypes are being tested, each one with slightly different requirements regarding the format of the data to be analysed. This has generated a variety of ad-hoc solutions for data acquisition and online data monitoring. We present a generic C++11 online monitoring framework called DQM4HEP, which is designed for use as a generic online monitor for particle physics experiments, ranging from small tabletop experiments to large multi-detector testbeams, such as those currently ongoing/planned at the DESY II or CERN SPS beamlines. We present results obtained using DQM4HEP at several testbeams where the CALICE AHCAL, SDHCAL and SiWECAL detector prototypes have been tested. During these testbeams, online analysis using DQM4HEP�� framework has been developed and used. We also present the currently ongoing work to integrate DQM4HEP within the EUDAQ tool. EUDAQ is a tool for common and generic data acquisition within the AIDA-2020 collaboration. This will allow these two frameworks to work together as a generic and complete DAQ and monitoring system for any type of detector prototype tested on beam tests, which is one of the goals of the AIDA-2020 project., IEEE NSS/MIC 2017 Conference Record

A mobile sampling and measurement system for the analysis of gaseous and liquid samples in the field was developed. An inductively coupled plasma optical emission spectrometer (ICP-OES), which is built into a van, was used as detector. The analytical system was calibrated with liquid and/or gaseous standards. It was shown that identical mass flows of either gaseous or liquid standards resulted in identical ICP-OES signal intensities. In a field measurement campaign trace and minor elements in the raw flue gas of a waste wood combustor were monitored. Sampling was performed with a highly transport efficient liquid quench system, which allowed to observe temporal variations in the elemental process gas composition. After a change in feedstock an immediate change of the element concentrations in the flue gas was detected. A comparison of the average element concentrations during the combustion of the two feedstocks showed a high reproducibility for matrix elements that are expected to be present in similar concentrations. On the other hand elements that showed strong differences in their concentration in the feedstock were also represented by a higher concentration in the flue gas. Following the temporal variations of different elements revealed strong correlations between a number of elements, such as chlorine with sodium, potassium and zinc, as well as arsenic with lead, and calcium with strontium. (c) 2012 Elsevier Ltd. All rights reserved.

Controlling and managing the degree of phenotypic diversification of microbial populations is a challenging task. This task not only requires detailed knowledge regarding diversification mechanisms but also advanced technical set-ups for the real-time analyses and control of population behaviour on single-cell level. In this work, set-up, design and operation of the so called segregostat are described which, in contrast to a traditional chemostat, allows the control of phenotypic diversification of microbial populations over time. Two exemplary case studies will be discussed, i.e. phenotypic diversification dynamics of Eschericia coli and Pseudomonas putida based on outer membrane permeabilization, emphasizing the applicability and versatility of the proposed approach. Upon nutrient limitation, cell population tends to diversify into several subpopulations exhibiting distinct phenotypic features (non-permeabilized and permeabilized cells). Online analysis leads to the determination of the ratio between cells in these two states, which in turn triggers the addition of glucose pulses in order to maintain a predefined diversification ratio. These results prove that phenotypic diversification can be controlled by means of defined pulse-frequency modulation within continuously running bioreactor set-ups. This lays the foundation for systematic studies, not only of phenotypic diversification but also for all processes where dynamics single-cell approaches are required, such as synthetic co-culture processes.

There exists a continuous need to promote better Science Technology Engineering and Mathematics (STEM) education at the younger students. To satisfy this need hands-on laboratory assignments and inquiry learning projects are widely accepted as appropriate approaches. One key issue for both approaches is the effective and adaptive data logging. This article describes the development of educational datalogger devices, using open source software and hardware which can be used to collect, present and save data for both offline and online analysis. The novelty of the proposed devices lies on the fact the presented implementations are not dedicated devices bind to specific features but they can be seen as educational datalogger platforms which are expandable and adaptive to students’ needs in a minimum cost since they are based in open source solutions.

INTRODUCTION: Smart phones are becoming ubiquitous and their computing capabilities are ever increasing. Consequently, more attention is geared towards their potential use in research and medical settings. For instance, their built-in hardware can provide quantitative data for different movements. Therefore, the goal of the current study was to evaluate the capabilities of a standalone smart phone platform to characterize tremor. RESULTS: Algorithms for tremor recording and online analysis can be implemented within a smart phone. The smart phone provides reliable time- and frequency-domain tremor characteristics. The smart phone can also provide medically-relevant tremor assessments. DISCUSSION: Smart phones have the potential to provide researchers and clinicians with quantitative short- and long-term tremor assessments that are currently not easily available. METHODS: A smart phone application for tremor quantification and online analysis was developed. Then, smart phone results were compared to those obtained simultaneously with a laboratory accelerometer. Finally, results from the smart phone were compared to clinical tremor assessments.

A robust medical monitoring device should be able to provide intelligent diagnosis based on accurate analysis of physiological parameters in real-time. At the same time, such device must be able to adapt to the characteristics of a specific patient and desired diagnostic needs, and continue to operate even in presence of unexpected artifacts and accidental errors. A reconfigurable architecture is proposed for real-time assessment of individual's health status based on development of a patient-specific health index and online analysis and fusion of multi-parameter physiological signals. This is achieved by static configuration of processing elements and communication blocks in the architecture based on the patient's diagnostic needs. The proposed architecture is prototyped as a single integrated device on an FPGA platform and is evaluated using multi-parameter data from intensive care units (ICUs). Three representative test cases of concurrently analyzing Blood Pressure, Heart Rate, and Electrocardiogram (ECG) data from MIMIC database are presented. The results show the effectiveness of the proposed technique in eliminating false alarms caused by patient movements, monitor noise, or imperfections in the detection schemes.

The use of biogas in the energy sector requires efficient removal of harmful trace levels of impurities. Reliable and robust online analytical equipment to measure these impurities is necessary and must be validated using offline techniques. In this work, total silicon and siloxanes were measured at an industrial solid oxide fuel cell fed by biogas. SOFC anodes are sensitive to silicon-based contaminants even at parts-per-billion levels. Online measurements of total silicon were carried out using a nondispersive infrared sensor (NDIR). Different sampling methods, including chemical adsorption, liquid quenching, and solid-phase adsorption were used at six biogas sampling points. Organic silicon compounds in the samples were determined by offline methods including GC-FID and GC-ICP-MS. The online analyzer's performance was satisfactory in both untreated biogas, where it agreed within the error margin of the most reliable offline technique used, and in clean biogas, where