Breath detection using short-time Fourier transform analysis in electrical impedance tomography

Spectral analysis based on short-time Fourier transform (STFT) using Kaiser window is proposed to examine the frequency components of neonates EIT data. In this way, a simultaneous spatial-time-frequency analysis is achieved

Investigating Microbiome Differences Between Red Romaine Lettuce Grown from Sanitized and Unsanitized Seeds

The International Space Station (ISS) as an integral component for the discovery and development of advanced robotics, materials, communications, medicine, agriculture, and environmental science due to it currently being the world's only microgravity laboratory of its kind. Because the ISS is a contained system with confined quarters, much research has been undertaken to assess and diminish the number of microbiological risks associated with astronauts inhabiting the station for extended periods of time. Notable microbiological risk factors include drinking water, air, and food. As an avenue for both mental/emotional respite and a source of fresh produce for astronauts, a vegetable production system has been employed on the ISS. In order to understand the microbial risks involved with a "pick and eat" vegetable system on the International Space Station (ISS), this study aims to compare microbial differences between sanitized and unsanitized seeds by tracking and identifying seedborne microbes throughout the development of red romaine lettuce (Lactuca sativa)-a plant species that has already been grown on the ISS

Compressive sensing in electrical impedance tomography for breathing monitoring

Continuous functional thorax monitoring using EIT has been extensively researched. A limiting factor in high temporal resolution, three dimensional, and fast EIT is the handling of the volume of raw impedance data produced for transmission and storage. Owing to the periodicity of breathing that may be reflected in EIT boundary measurements, data dimensionality may be reduced efficiently at the time of sampling using compressed sensing techniques. Measurements using a 32-electrode 48-frame-per-second EIT system from 30 neonates were post-processed to simulate random demodulation acquisition method on 2000 frames for compression ratios (CRs) ranging from 2-100. Sparse reconstruction was performed by solving the basis pursuit problem using SPGL1 package. The global impedance data was used in the subsequent studies. The signal to noise ratio (SNR) for the entire frequency band (0 Hz - 24 Hz) and three local frequency bands were analysed. A breath detection algorithm was applied to traces and the subsequent error-rates were calculated while considering the outcome of the algorithm applied to a down-sampled and linearly interpolated version of the traces as the baseline. SNR degradation was proportional with CR. The mean degradation for 0 Hz - 8 Hz was below ~15 dB for all CRs. The error-rates in the outcome of the breath detection algorithm in the case of decompressed traces were lower than those of the associated down-sampled traces for CR≥25, corresponding to sub-Nyquist rate for breathing. For instance, the mean error-rate associated with CR = 50 was ~60% lower than that of the corresponding down-sampled traces. To the best of our knowledge, no other study has evaluated compressive sensing on boundary impedance data in EIT. While further research should be directed at optimising the acquisition and decompression techniques for this application, this contribution serves as the baseline for future efforts. [Abstract copyright: Creative Commons Attribution license.

Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange

Estimation of thorax shape for forward modelling in lungs EIT

The thorax models for pre-term babies are developed based on the CT scans from new-borns and their effect on image reconstruction is evaluated in comparison with other available models

A parametric model for the changes in the complex valued conductivity of a lung during tidal breathing

Classical homogenization theory based on the Hashin-Shtrikman coated ellipsoids is used to model the changes in the complex valued conductivity (or admittivity) of a lung during tidal breathing. Here, the lung is modeled as a two-phase composite material where the alveolar air-filling corresponds to the inclusion phase. The theory predicts a linear relationship between the real and the imaginary parts of the change in the complex valued conductivity of a lung during tidal breathing, and where the loss cotangent of the change is approximately the same as of the effective background conductivity and hence easy to estimate. The theory is illustrated with numerical examples, as well as by using reconstructed Electrical Impedance Tomography (EIT) images based on clinical data from an ongoing study within the EU-funded CRADL project. The theory may be potentially useful for improving the imaging algorithms and clinical evaluations in connection with lung EIT for respiratory management and monitoring in neonatal intensive care units

The first report of familial adult T-cell leukemia/lymphoma in Iran

We describe two siblings, 26-year-old man and 19-year-old woman, from northeast of Iran, who presented with similar clinical manifestations and within one year, diagnosed as Adult T-Cell Leukemia/Lymphoma (ATLL)

Optimized breath detection algorithm in electrical impedance tomography

This paper defines a method for optimizing the breath delineation algorithms used in Electrical Impedance Tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern. Our approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project. Three different algorithms are proposed that are improving the breath detector performance by adding conditions on 1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, 2) minimum tidal impedance amplitude and 3) minimum tidal breath rate obtained from Time-Frequency (TF) analysis. As a baseline the zero crossing algorithm has been used with some default parameters based on the Swisstom EIT device. Based on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the Receiver Operating Characterics (ROC). This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors. [Abstract copyright: © 2018 Institute of Physics and Engineering in Medicine.

Microbial Monitoring from the Frontlines to Space: Department of Defense Small Business Innovation Research Technology Aboard the International Space Station

The RAZOR (trademark) EX, a quantitative Polymerase Chain Reaction (qPCR) instrument, is a portable, ruggedized unit that was designed for the Department of Defense (DoD) with its reagent chemistries traceable to a Small Business Innovation Research (SBIR) contract beginning in 2002. The PCR instrument's primary function post 9/11 was to enable frontline soldiers and first responders to detect biological threat agents and bioterrorism activities in remote locations to include field environments. With its success for DoD, the instrument has also been employed by other governmental agencies including Department of Homeland Security (DHS). The RAZOR (Trademark) EX underwent stringent testing by the vendor, as well as through the DoD, and was certified in 2005. In addition, the RAZOR (trademark) EX passed DHS security sponsored Stakeholder Panel on Agent Detection Assays (SPADA) rigorous evaluation in 2011. The identification and quantitation of microbial pathogens is necessary both on the ground as well as during spaceflight to maintain the health of astronauts and to prevent biofouling of equipment. Currently, culture-based monitoring technology has been adequate for short-term spaceflight missions but may not be robust enough to meet the requirements for long-duration missions. During a NASA-sponsored workshop in 2011, it was determined that the more traditional culture-based method should be replaced or supplemented with more robust technologies. NASA scientists began investigating innovative molecular technologies for future space exploration and as a result, PCR was recommended. Shortly after, NASA sponsored market research in 2012 to identify and review current, commercial, cutting edge PCR technologies for potential applicability to spaceflight operations. Scientists identified and extensively evaluated three candidate technologies with the potential to function in microgravity. After a thorough voice-of-the-customer trade study and extensive functional and safety evaluations, the RAZOR (trademark) EX PCR instrument(Bio-Fire Defense, Salt Lake City, UT) was selected as the most promising current technology for spaceflight monitoring applications

Comparison of Sample and Detection Quantification Methods for Salmonella Enterica from Produce

The purpose of this study was to identify and optimize fast and reliable sampling and detection methods for the identification of pathogens that may be present on produce grown in small vegetable production units on the International Space Station (ISS), thus a field setting. Microbiological testing is necessary before astronauts are allowed to consume produce grown on ISS where currently there are two vegetable production units deployed, Lada and Veggie