Continuous analysis of nitrogen dioxide in gas streams of plants

Analyzer and sampling system continuously monitors nitrogen dioxide concentrations in the feed and tail gas streams of a facility recovering nitric acid. The system, using a direct calorimetric approach, makes use of readily available equipment and is flexible and reliable in operation

IUPUI mechanical engineering technology senior assessment

This paper discusses the methods and analysis of 6-semesters of senior assessment examination data identifying the courses and subject material students found the most difficult to solve in the MET program Senior Assessment Examination. The analysis results indicate that MET 111 (Applied Statics), MET 213 (Dynamics), and MET 348 (Engineering Materials) are courses in need of potential improvement. Furthermore, subject areas such as the calculation of entropy change, the calculation of pressure drop flow through a pipe, and Hooke's Law are subject material that poses greatest problems for senior students. For the past 12 years, the Mechanical Engineering Technology (MET) Program faculty at IUPUI require all seniors to take a MET Senior Assessment Examination that is similar in content to the Fundamentals of Engineering (FE) examination. This paper discusses the methods used to provide insightful and actionable inputs for the IUPUI MET program process improvements plan. The raw data consists of test scores from 123 senior students who took the examination from 2014 through 2016. The Accreditation Board for Engineering & Technology (ABET) is an organization that ensures universities and institutions like IUPUI meet certain accreditation requirements and requires that each program develops a continuous improvement plan. The improvement plan typically consists of a compilation of student materials, employer surveys, and course evaluations used to ensure continuous improvement within a program. In 2004 IUPUI, MET program faculty decided that a standardized senior examination would be part of the program process improvement process, [1]

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Local and Global Distinguishability in Quantum Interferometry

A statistical distinguishability based on relative entropy characterises the fitness of quantum states for phase estimation. This criterion is employed in the context of a Mach-Zehnder interferometer and used to interpolate between two regimes, of local and global phase distinguishability. The scaling of distinguishability in these regimes with photon number is explored for various quantum states. It emerges that local distinguishability is dependent on a discrepancy between quantum and classical rotational energy. Our analysis demonstrates that the Heisenberg limit is the true upper limit for local phase sensitivity. Only the `NOON' states share this bound, but other states exhibit a better trade-off when comparing local and global phase regimes.Comment: 4 pages, in submission, minor revision

Effectiveness of tobacco control television advertisements with different types of emotional content on tobacco use in England, 2004–2010

Aim: To examine the effects of tobacco control television advertisements with positive and negative emotional content on adult smoking prevalence and cigarette consumption. Design: Analysis of monthly cross-sectional surveys using generalised additive models. Setting: England. Participants: 60 000 adults aged 18 years or over living in England and interviewed in the Opinions and Lifestyle Survey from 2004 to 2010. Measurements: Current smoking status, daily cigarette consumption, tobacco control gross rating points (GRPs—a measure of per capita advertising exposure), cigarette costliness, concurrent tobacco control policies, sociodemographic variables. Results: After adjusting for cigarette costliness, other tobacco control policies and individual characteristics, we found that a 400-point increase in positive emotive GRPs was associated with 7% lower odds of smoking (odds ratio (OR) 0.93, 95% CI 0.87 to 0.98) 1 month later and a similar increase in negative emotive GRPs was significantly associated with 4% lower odds of smoking (OR 0.96, 95% CI 0.92 to 0.999) 2 months later. An increase in negative emotive GRPs from 0 to 400 was also associated with a significant 3.3% (95% CI 1.1 to 5.6) decrease in average cigarette consumption. There was no evidence that the association between positive emotive GRPs and the outcomes differed depending on the intensity of negative emotive GRPs (and vice versa). Conclusions: This is the first study to explore the effects of campaigns with different types of emotive content on adult smoking prevalence and consumption. It suggests that both types of campaign (positive and negative) are effective in reducing smoking prevalence, whereas consumption among smokers was only affected by campaigns evoking negative emotions

Sinking phytoplankton associated with carbon flux in the Atlantic Ocean

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Limnology and Oceanography 61 (2016): 1172–1187, doi:10.1002/lno.10253.The composition of sinking particles and the mechanisms leading to their transport ultimately control how much carbon is naturally sequestered in the deep ocean by the “biological pump.” While detrital particles often contain much of the sinking carbon, sinking of intact phytoplankton cells can also contribute to carbon export, which represents a direct flux of carbon from the atmosphere to the deep ocean by circumventing the surface ocean food web. Phytoplankton that contributed to carbon flux were identified in sinking material collected by short-term sediment trap deployments conducted along a transect off the eastern shore of South America. Particulate organic carbon flux at 125 m depth did not change significantly along the transect. Instead, changes occurred in the composition and association of phytoplankton with detrital particles. The fluxes of diatoms, coccolithophores, dinoflagellates, and nano-sized cells at 125 m were unrelated to the overlying surface population abundances, indicating that functional-group specific transport mechanisms were variable across locations. The dominant export mechanism of phytoplankton at each station was putatively identified by principal component analysis and fell into one of three categories; (1) transport and sinking of individual, viable diatom cells, (2) transport by aggregates and fecal pellets, or (3) enhanced export of coccolithophores through direct settling and/or aggregationFunding for the DeepDOM cruise was provided by the National Science Foundation (NSF) grant OCE-1154320 to E. B. Kujawinski and K. Longnecker, WHOI. Partial research support was provided by NSF through grants OCE-0925284, and OCE-1316036 to S.T. Dyhrman. C.A. Durkin was supported by a Woods Hole Oceanographic Institution Devonshire Postdoctoral Scholarship

Quantifying the optical properties and chromophore concentrations of turbid media by chemometric analysis of hyperspectral diffuse reflectance data collected using a fourier interferometric imaging system

A non-contact Fourier transform interferometric imaging system was used to collect hyperspectral images of the steady-state diffuse reflectance from a point source in turbid media for the spectral range of 550-850 nm. Steady-state diffuse reflectance profiles were generated from the hyperspectral images, and partial least-squares (PLS) regression was performed on the diffuse reflectance profiles to quantify absorption (mu (alpha)) and reduced scattering (mu (s)') properties of turbid media. The feasibility of using PLS regression to predict optical properties was examined for two different sets of spatially-resolved diffuse reflectance data. One set of data was collected from 40 turbid phantoms, while the second set was generated by convolving Monte Carlo simulations with the instrument response of the imaging system. Study results show that PLS prediction of mu (alpha) and mu (s)' was accurate to within +/-8% and +/-5%, respectively, when the model was trained on turbid phantom data. Moreover, PLS prediction of optical properties was considerably faster and more efficient than direct least-squares fitting of spatially-resolved profiles. When the PLS model was trained on Monte Carlo simulated data and subsequently used to predict mu (alpha) and mu (s)' from the diffuse reflectance of turbid phantom, the percent accuracies degraded to +/-12% and +/-5%, respectively. These accuracy values are applicable to homogenous, semi-infinite turbid phantoms with optical property ranges comparable to tissues

The Cathode Strip Chamber Data Acquisition System for CMS

The Cathode Strip Chamber (CSC) [1] Data Acquisition (DAQ) system for the CMS [2] experiment at the LHC [3] will be described. The CSC system is large, consisting of 218K cathode channels and 183K anode channels. This leads to a substantial data rate of ~1.5GByte/s at LHC design luminosity (1034cm-2s-1) and the CMS first level trigger (L1A) rate of 100KHz. The DAQ system consists of three parts. The first part is on-chamber Cathode Front End Boards (CFEB)[4], which amplify, shape, store, and digitise chamber cathode signals, and Anode Front End Boards (AFEB)[5], which amplify, shape and discriminate chamber anode signals. The second part is the Peripheral Crate Data Acquisition Motherboards (DAQMB), which control the onchamber electronics and the readout of the chamber. The third part is the off-detector DAQ interface boards, which perform real time error checking, electronics reset requests and data concentration. It passes the resulting data to a CSC local DAQ farm, as well as CMS main DAQ [6]. All electronics in the system employ FPGAs allowing programmability. In addition, several high-speed serial interface technologies are employed