Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants

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Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors

Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.Peer reviewe

New particle formation in the fresh flue-gas plume from a coal-fired power plant: effect of flue-gas cleaning

Atmospheric emissions, including particle number and size distribution, from a 726 MWth coal-fired power plant were studied experimentally from a power plant stack and flue-gas plume dispersing in the atmosphere. Experiments were conducted under two different flue-gas cleaning conditions. The results were utilized in a plume dispersion and dilution model taking into account particle formation precursor (H2SO4 resulted from the oxidation of emitted SO2) and assessment related to nucleation rates. The experiments showed that the primary emissions of particles and SO2 were effectively reduced by flue-gas desulfurization and fabric filters, especially the emissions of particles smaller than 200 nm in diameter. Primary pollutant concentrations reached background levels in 200–300 s. However, the atmospheric measurements indicated that new particles larger than 2.5 nm are formed in the flue-gas plume, even in the very early phases of atmospheric ageing. The effective number emission of nucleated particles were several orders of magnitude higher than the primary particle emission. Modelling studies indicate that regardless of continuing dilution of the flue gas, nucleation precursor (H2SO4 from SO2 oxidation) concentrations remain relatively constant. In addition, results indicate that flue-gas nucleation is more efficient than predicted by atmospheric aerosol modelling. In particular, the observation of the new particle formation with rather low flue-gas SO2 concentrations changes the current understanding of the air quality effects of coal combustion. The results can be used to evaluate optimal ways to achieve better air quality, particularly in polluted areas like India and China

Indirect monitoring of flue gas NOx emissions in natural gas and oil fired heating plants

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Indirect NOx emission monitoring in natural gas fired boilers

New emission regulations will increase the need for inexpensive NOx emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NOx emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of 1 applications in practise. However, each boiler model should be identified individually.acceptedVersionPeer reviewe

Physical and chemical characteristics of flue-gas particles in a large pulverized fuel-fired power plant boiler during co-combustion of coal and wood pellets

Fossil fuel combustion should be decreased in future years in order to lower the CO2 emissions of energy production. The reduction can be achieved by increasing the amount of CO2-neutral fuels in energy production. Here 6–13% of coal was substituted with industrial or roasted pellets in a pulverized fuel-fired power plant without making any changes to fuel grinding or low-NOx burners. The effect of pellet addition for the flue gas particles was studied with direct sampling from the boiler super heater area. Based on primary dilution ratio tests, transmission electron microscope images, and the natural electric charge of the particles, it was observed that particles in the flue gas are spherical and have been formed in the boiler at high temperatures. The pellet addition lowered the total particle number concentrations with all of the studied pellet–coal mixtures in comparison to the coal combustion. The 10.5% industrial pellet addition caused a second mode in the particle number size distribution. In addition, based on the chemical analysis of the collected size-fractioned particle samples, results indicated that the pellet addition did not increase the corrosion risk of the boiler. However, the changes in the particle number size distribution and total particle number concentration can affect the operation of electrostatic precipitators and flue gas cleaning.publishedVersionPeer reviewe

Characteristics of particle emissions and their atmospheric dilution during co-combustion of coal and wood pellets in a large combined heat and power plant

Coal combustion is one of the most significant anthropogenic CO2 and air pollution sources globally. This paper studies the atmospheric emissions of a power plant fuelled with a mixture of industrial pellets (10.5%) and coal (89.5%). Based on the stack measurements, the solid particle number emission, which was dominated by sub-200 nm particles, was 3.4×1011 MJ-1 for the fuel mixture when electrostatic precipitator (ESP) was cleaning the flue gas. The emission factor was 50 mg MJ-1 for particulate mass and 11 740 ng MJ-1 for the black carbon with the ESP. In the normal operation situation of the power plant, i.e., including the flue-gas desulphurisation and fabric filters (FGD and FF), the particle number emission factor was 1.7×108 MJ-1, particulate mass emission factor 2 mg MJ-1 and black carbon emission factor 14 ng MJ-1. Transmission electron microscopy (TEM) analysis supported the particle number size distribution measurement in terms of particle size and the black carbon concentration. The TEM images of the particles showed variability of the particle sizes, morphologies and chemical compositions. The atmospheric measurements, conducted in the flue-gas plume, showed that the flue-gas dilutes closed to background concentrations in 200 sec. However, an increase in particle number concentration was observed when the flue gas aged. This increase in particle number concentration was interpret as formation of new particles in the atmosphere. In general, the study highlights the importance of detailed particle measurements when utilizing new fuels in existing power plants. Implications: CO2 emissions of energy production decrease when substituting coal with biofuels. The effects of fuels changes on particle emission characteristics have not been studied comprehensively. In this study conducted for a real-scale power plant, co-combustion of wood pellets and coal caused elevated black carbon emissions. However, it was beneficial from the total particle number and particulate mass emission point of view. Flue-gas cleaning can significantly decrease the pollutant concentrations but also changes the characteristics of emitted particles. Atmospheric measurements implicated that the new particle formation in the atmospheric flue-gas plume should be taken into account when evaluating all effects of fuel changes.” Are implication statements part of the manuscript?.acceptedVersionPeer reviewe