Optimal Acquisition Research Articles

The Status Quo and Belief Polarization of Inattentive Agents: Theory and Experiment

We show that rational but inattentive agents can become polarized, even in expectation. This is driven by agents’ choice of not only how much information to acquire, but also what type of information. We present how optimal information acquisition, and subsequent belief formation, depends crucially on the agent-specific status quo valuation. Beliefs can systematically update away from the realized truth and even agents with the same initial beliefs might become polarized. We design a laboratory experiment to test the model’s predictions; the results confirm our predictions about the mechanism (rational information acquisition) and its effect on beliefs (systematic polarization). Keywords: polarization, beliefs updating, rational inattention, status quo, experiment. JEL codes: C92, D72, D83, D84, D91

Optimal Color Composition Method for Generating High-Quality Daily Photographic Time Series From PhenoCam

Phenology camera (PhenoCam) data and the derived green chromatic coordinate (GCC) time series are commonly used to track seasonal changes in canopy greenness. However, the GCC time series is noisy because color distortion commonly exists in the captured photographs owing to the varying illumination conditions and nonlinear response of the consumer-grade camera to the incoming light. Hence, we proposed an optimal color composition (OCC) method to generate high-quality daily photographic time series by compositing multiple photographs captured in a single day. First, the optimal acquisition time with good illumination conditions and correct exposure settings is determined for each pixel throughout the day based on a comprehensive color index, combining the brightness and saturation. A virtual photograph consisting of the selected digital numbers acquired at the optimal time is then composited for each day. Finally, the daily GCC time series is calculated based on the virtual photographs. By testing the photographs of six forest sites, the proposed method was compared with the commonly used 90th percentile (Per90) filter. The results show that the daily photographs composited using the OCC method were more homogeneous with less shaded areas compared to those selected by the Per90 filter, and the corresponding GCC time series derived from the OCC method is more stable and less influenced by varying atmospheric conditions and solar angles than the Per90 filter. These results indicate that the OCC method can generate high-quality daily photographic time series with the potential to better indicate seasonal color changes in the forest canopy.

Selection of optimal cardiac phases for ECG-triggered coronary CT angiography in pediatrics.

The use of coronary computed tomography angiography (CCTA) in children remains limited by patient's irradiation, and motion artefacts impairing image quality. Triggering the acquisition at the appropriate moment, and acquiring only necessary components of the cardiac cycle could overcome these limitations. Yet, optimal cardiac intervals to perform CCTA as a function of heart rate (HR) have not yet been addressed in pediatrics. Fifty children with coronary artery anomalies underwent a CCTA on a wide-coverage single-beat CT scanner. Multiple phases from 25% to 85% of the R-R interval were acquired and reconstructed with 10% increments. Two radiologists independently assessed motion artifacts on each cardiac phase using a 4-point semi-quantitative scale. At patient level, the best phase for acquisition was found in diastole for patients with HR≤75bpm and in systole for patients with HR>85bpm. At coronary segments and structures level, median optimal phases were reported at 70%, 80%, 47%, 50%, and 54% of the R-R interval for patients with HR≤60, 61-75, 86-100, 101-130, and >130bpm respectively. For patients with HR between 76 and 85bpm, no clear trend could be observed. Optimal acquisition durations represented 10% (2 phases), 20% (3 phases), 50% (multiphase), 20% (3 phases), and 10% (2 phases) of the R-R interval for patients with HR≤60, 61-75, 76-100, 101-130, and >130bpm, respectively. Optimal positioning and duration of CCTA acquisition intervals were investigated as a function of children's HR, to reduce motion artifacts and patient's irradiation.

18F-NaF PET/CT of Obese Patients on a Lutetium-Yttrium Oxyorthosilicate PET/CT System: Patient Dosimetry, Optimization of Injected Activity, and Acquisition Time.

18F-NaF PET/CT has a rapid single-pass extraction and fast clearance from soft tissues, resulting in a good target-to-background ratio. This study aimed to establish the optimum acquisition time and dosimetry for 18F-NaF PET/CT to evaluate bone metastases in obese patients. A secondary objective was to evaluate the impact of acquisition time on image quality, lesion detection rate, noise level, and radiation burden in this patient group. Methods: In total, 60 patients were included in the study (20 patients with a body mass index (BMI) of 30.0-34.9 kg/m2, 20 with a BMI of 35-39.9 kg/m2, and 20 with a BMI of >40 kg/m2). Images were acquired after intravenous injection of a 2.2 MBq/kg (0.06 mCi/kg) dose of 18F-NaF. Data were acquired in list mode using ordered-subset expectation maximization reconstruction. The raw data were rebinned to simulate scans with acquisition times of 2, 2.5, and 3 min per bed position. The scans were visually analyzed by 2 observers and scored by rank against a panel of parameters (overall image quality, noise level, background soft tissue, and lesion detectability), and the contrast-to-noise ratio (CNR) was calculated. Results: The mean CNR was 20.19 ± 8.39 for a 2-min acquisition, 21.03 ± 8.35 for 2.5 min, and 22.16 ± 8.37 for 3 min. There were no statistically significant differences in CNR among the 3 different acquisition durations (P > 0.05). Lesion delineation was excellent and independent of the acquisition time. All relevant lesions could be identified with all 3 acquisition times. A mean activity of 215.4 ± 31.3 MBq was injected, with estimated mean effective absorbed doses of 4.09 ± 0.59 mSv for 18F-NaF PET and 7.88 ± 1.66 mSv for CT alone. Conclusion: 18F-NaF PET/CT can be beneficial in obese patients because of its good pharmacokinetics. Optimal osseous staging can be achieved with relatively low doses and radiation burden. Lesion delineation was excellent regardless of acquisition time. However, it is recommended that an acquisition of 3 min per bed position be used in patients with a BMI of more than 40.

Mapping the fractional coverage of the invasive shrub Ulex europaeus with multi-temporal Sentinel-2 imagery utilizing UAV orthoimages and a new spatial optimization approach

Mapping the occurrence patterns of invasive plant species and understanding their invasion dynamics is a crucial requirement for preventing further spread to so far unaffected regions. An established approach to map invasive species across large areas is based on the combination of satellite or aerial remote sensing data with ground truth data from fieldwork. Unmanned aerial vehicles (UAV, also referred to as unmanned aerial systems (UAS)) may represent an interesting and low-cost alternative to labor-intensive fieldwork. Despite the increasing use of UAVs in the field of remote sensing in the last years, operational methods to combine UAV and satellite data are still sparse. Here, we present a new methodological framework to estimate the fractional coverage (FC%) of the invasive shrub species Ulex europaeus (common gorse) on Chiloé Island (south-central Chile), based on ultra-high-resolution UAV images and a medium resolution intra-annual time-series of Sentinel-2. Our framework is based on three steps: 1) Land cover classification of the UAV orthoimages, 2) reduce the spatial shift between UAV-based land cover classification maps and Sentinel-2 imagery and 3) identify optimal satellite acquisition dates for estimating the actual distribution of Ulex europaeus.In Step 2 we translate the challenging co-registration task between two datasets with very different spatial resolutions into an (machine learning) optimization problem where the UAV-based land cover classification maps obtained in Step 1 are systematically shifted against the satellite images. Based on several Random Forest (RF) models, an optimal fit between varying land cover fractions and the spectral information of Sentinel-2 is identified to correct the spatial offset between both datasets.Considering the spatial shifts of the UAV orthoimages and using optimally timed Sentinel-2 acquisitions led to a significant improvement for the estimation of the current distribution of Ulex europaeus. Furthermore, we found that the Sentinel-2 acquisition from November (flowering time of Ulex europaeus) was particularly important in distinguishing Ulex europaeus from other plant species. Our mapping results could support local efforts in controlling Ulex europaeus. Furthermore, the proposed workflow should be transferable to other use cases where individual target species that are visually detectable in UAV imagery are considered. These findings confirm and underline the great potential of UAV-based groundtruth data for detecting invasive species.

Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

BackgroundDiffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. MethodsA multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. ResultsThe SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. ConclusionThe single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.

A motor-imagery channel-selection method based on SVM-CCA-CS

In electroencephalography, multi-channel electroencephalogram (EEG) signals are usually utilized to improve classification accuracy. However, a large set of EEG channels increases the computational complexity, reduces the real-time performance and causes wearability difficulties. Channel selection methods have been widely investigated to reduce the number of channels with an acceptable loss of accuracy for EEG-based motor-imagery recognition. In this paper, we present a novel algorithm, called Support Vector Machine-Canonical Correlation Analysis-Channel Selection (SVM-CCA-CS). First, the energy features of the wavelet packet subnodes of the motor-imagery EEG signals are extracted. Then the weights of feature groups are calculated as initial channel weights, based on the CCA algorithm. The initial channel weights are further adjusted, according to the contribution of each channel to the classification accuracy via SVM, and the top channels with larger weights are eventually selected. The results show that the average accuracy of all subjects can reach 80.03% by using the first 30 channels with the largest weights from among the total of 118 channels. For the right hand and foot motor-imagery tasks, the generally applicable optimal channels are mostly located in the left hemisphere. Our generally applicable channel observation of the whole brain cortex suggests contralateral control correspondence: for unilateral motor imagery, the optimal channels are concentrated in the contralateral hemisphere. This is consistent with the contralateral control of the body by the human brain: the majority of the human motor and sensory fibers tend to control the contralateral limbs and pass through the midline of the body. Our proposed method provides optimal acquisition and analysis of the positions of EEG signals in specific motor-imagery tasks.

Fast versus conventional HAADF-STEM tomography of nanoparticles: advantages and challenges

HAADF-STEM tomography is a widely used experimental technique for analyzing nanometer-scale structures of a large variety of materials in three dimensions. It is especially useful for studying crystalline nanoparticles, where conventional TEM tomography suffers from diffraction-related artefacts. Unfortunately, the acquisition of a HAADF-STEM tilt series can easily take up one hour or more, depending on the complexity of the experiment. It is therefore challenging to investigate samples that do not withstand long electron beam illumination or to acquire a large number of tilt series during a single TEM experiment. The latter would facilitate obtaining more statistically representative 3D data, and enable performing dynamic in situ 3D characterizations with a finer time resolution. Various HAADF-STEM acquisition strategies have been proposed to accelerate the tomographic acquisition and reduce the required electron dose. These methods include tilting the holder continuously while acquiring a projection “movie” and a hybrid, incremental, methodology which combines the benefits of the conventional and continuous technique. However, until now an experimental evaluation of these techniques has been lacking. In this paper, the different acquisition strategies will be experimentally compared in terms of speed, resolution and electron dose. This evaluation will be performed based on experimental tilt series, acquired for various metallic nanoparticles with different shapes and sizes. We discuss the necessary data processing and provide a general guideline that can be used to determine the most optimal acquisition strategy for specific electron tomography experiments.

Information Acquisition in Matching Markets: The Role of Price Discovery

We explore the acquisition and flow of information in matching markets through a model of college admissions with endogenous costly information acquisition. We extend the notion of stability to this partial information setting, and introduce regret-free stability as a refinement that additionally requires optimal student information acquisition. We show regret-free stable outcomes exist, and finding them is equivalent to finding appropriately-defined market-clearing cutoffs. To understand information flows, we recast matching mechanisms as price-discovery processes. No mechanism guarantees a regret-free stable outcome, because information deadlocks imply some students must acquire information sub optimally. Our analysis suggests approaches for facilitating efficient price discovery, leveraging historical information or market sub-samples to estimate cutoffs. We show that mechanisms that use such methods to advise applicants on their admission chances yield approximately regret-free stable outcomes. A survey of university admission systems highlights the practical importance of providing applicants with information about their admission chances.

Portable X-ray Fluorescence (p-XRF) Uncertainty Estimation for Glazed Ceramic Analysis: Case of Iznik Tiles

The aim of this study is to estimate the uncertainty of a portable X-ray fluorescence (p-XRF) instrument for the (semi-quantitative) analyses of tiles with underglaze decoration. Before starting the campaign of on-site measurements, the optimum acquisition time and the most accurate calibration mode were selected. For this purpose, the elemental composition of two glass standards of NIST (SRM610 and SRM612) and a Corning A standard were measured with varied times (5–360 s) and in different calibration modes (Mining, Mining Light Elements, Soil, and Rare Earth Elements). Afterwards, a set of blue-and-white tiles that was unearthed at Iznik Tile Kilns Excavation between the dig seasons of 2015 and 2019 was examined with p-XRF by selecting ten points of measure from each layer (body, transparent glaze, and blue coloured areas). The elemental composition of different layers was evaluated by means of the intragroup and intergroup data. They were also compared to the previous studies and found that the corrosion-free, homogeneous, and non-porous surfaces decrease the relative standard deviation (RSD) by increasing the consistency of the compositional data. The major elements found in the matrix of each layer (Al and Si for the body, Pb and Sn for the glaze) have the lowest value of RSD, as expected. However, the comparison of the data with the analysis of the reference materials showed that the content of Mg and also Si, which belong to the low-Z elements group, is shifted relatively towards the higher compositional values. The impossibility of measuring the elemental composition of sodium does not hinder the classification of the samples. Although the transition metals have very low concentrations, p-XRF measurements appear rather consistent and the intrinsic scattering of the data observed for a single artefact is largely smaller than those observed for the tiles of different historical buildings. Thus, it allows the classification to be made related to the different techniques used.

Extrapolating canopy phenology information using Sentinel-2 data and the Google Earth Engine platform to identify the optimal dates for remotely sensed image acquisition of semiarid mangroves

Continuum monitoring of mangrove ecosystems is required to maintain and improve upon national mangrove conservation strategies. In particular, mangrove canopy assessments using remote sensing methods can be undertaken rapidly and, if freely available, optimize costs. Although such spaceborne data have been used for such purposes, their application to map mangroves at the species level has been limited by the capacity to provide continuous data. The objective of this study was to assess mangrove seasonal patterns using seven multispectral vegetation indices based on a Sentinel-2 (S2) time series (July 2018 to October 2019) to assess phenological trajectories of various semiarid mangrove classes in the Google Earth Engine platform using Fourier analysis for an area located in Western Mexico. The results indicate that the months from November through December and from May through July were critical in mangrove species discrimination using the EVI2, NDVI, and VARI series. The Random Forest classification accuracy for the S2 image was calculated at 79% during the optimal acquisition period (June 25, 2019), whereas only 55% accuracy was calculated for the non-optimal image acquired date (March 2, 2019). Although mangroves are considered evergreen forests, the phenological pattern of various mangrove canopies, based on these indices, were shown to be very similar to the surrounding land-based semiarid deciduous forest. Consequently, it is believed that the rainfall pattern is likely to be the key environmental factor driving mangrove phenology in this semiarid coastal system and thus the degree of success in mangrove remote sensing classification endeavors. Identifying the optimal dates when canopy spectral conditions are ideal in achieving mangrove species discrimination could be of utmost importance when purchasing more expensive very-high spatial resolution satellite images or collecting spatial data from UAVs.

Evaluation of commercial virtually imaged phase array and Fabry-Pérot based Brillouin spectrometers for applications to biology.

Measuring the complex mechanical properties of biological objects has become a necessity to answer key questions in mechanobiology and to propose innovative clinical and therapeutic strategies. In this context, Brillouin light scattering (BLS) has recently come into vogue, offering quantitative imaging of the mechanical properties without labels and with a micrometer resolution. In biological samples, the magnitude of the spectral changes are typically of a few tens of MHz, and the ability of modern spectrometers to monitor such subtle changes needs to be evaluated. Moreover, the multiplicity of variations in optical arrangements, specific to each lab, requires to set a standard for the assessment of the characteristics of BLS systems. In this paper we propose a protocol to evaluate the precision and accuracy of two commercial spectrometers that is reproducible across labs. For a meaningful comparison, we coupled the spectrometers to the same microscope and to the same laser. We first evaluated the optimum acquisition time and laser power. We evaluated the precision using pure water samples. We determined the accuracy by probing water solutions with increasing concentration of salt and comparing it with theory. Following these quantifications, we applied the VIPA-based spectrometer to tumor spheroids engineered from different cell lines that possess different metastatic potentials and resistance to therapies. On these models, we detected significant changes in the linewidth suggesting that BLS measurements of the viscosity could be used as a read-out to distinguish different levels of drug resistance.

Estimation of cardiac output from test-bolus during coronary computed tomography angiography: a personalized mathematical model

Abstract Background Contrast enhancement is measured in the aorta at set intervals of time during the test-bolus series of a coronary computed tomography angiography [CCTA]. Its primary purpose is to ascertain the timing delay of the main scan after contrast administration to ensure optimal image acquisition. The change in contrast enhancement over time correlates directly with contrast medium concentration in the vessel. If the complete time density curve [TDC] is known and corrected for contrast enhancement due to recirculation it can be used to estimate the cardiac output [CO], by e.g. a modified Stewart-Hamilton equation, as shown by Mahnken et al. Purpose The current study aims to explore ways to improve the mathematical estimation of CO. In practical applications only part of the TDC is known. By integrating patient factors, contrast factors and scanning factors with a mathematical compartment model, the CO can be estimated. Estimated CO is subsequently used to simulate the distribution of contrast medium in the body, enabling prospective adjustment of contrast medium administration protocol that could be tailored to each individual, utilizing the lowest possible dose of contrast to achieve diagnostically acceptable CCTA images. Methods Test-bolus images were acquired sequentially at two second intervals over the aorta from 40 patients with a clinical indication for CCTA. According to clinical routines, premedication with beta-blockers was performed in 35 patients and sublingual nitroglycerine in 39 patients. Attenuation in the aorta was measured by a centrally placed region of interest with a width of half the aortic diameter. Each participant underwent cardiac magnetic resonance imaging [MRI] immediately after CCTA, from which actual CO was measured as a method of validation. A mathematical compartment model for distribution of contrast, outlined by Bae et al. was improved and used to estimate the CO from the TDC in the aorta during the test-bolus. The estimated CO [COEst] was compared with CO calculated from MRI [COMR], and estimated attenuation in the aorta [HUEst] was compared with measured attenuation in the aorta during test-bolus in CCTA [HUCT]. Results One patient was excluded due to unacceptable cardiac MRI. Our model showed a strong correlation between COEst and COMR for all patients (r=0.62, p&amp;lt;0.001) and a higher correlation for women than men when separated by gender (men r=0.58, p=0.006; women r=0.63, p=0.005). Women had an average COEst 1.92 L/min significantly lower than men (p&amp;lt;0.001), despite no statistical difference in COMR between men and women. Conclusion An improved mathematical model for estimation of CO can be a valuable tool to improve individualized contrast administration protocols and increase the diagnostic information extracted from a CCTA. In addition to known physical factors it is clear that gender and weight, including their derivatives, must play a more significant role in estimation. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Stavanger University Hospital

On the optimization of bone SPECT/CT in terms of image quality and radiation dose.

IntroductionThe purpose of this study was to present the optimization process of CT parameters to reduce patient exposure during bone SPECT/CT without affecting the quality of SPECT images with attenuation correction (AC).Material and methodsA fillable phantom reflecting realistic bone scintigraphy conditions was developed and acquired on an AnyScan SC. SPECT/CT scans were carried out with different x‐ray tube current values (10, 20, 30, 40, 50, 60, 70, 90, 110, 130, 150, and 200 mA) at three different high‐voltage values (80, 100, and 120 kV). The contrast (C) and coefficients of variation (CV) in the SPECT images as well as the signal‐to‐noise ratio (SNR) and noise (SDCT) in the CT images with CTDIvol were measured. An optimal acquisition protocol that obtained SPECT/CT images with no artifacts on both CT and SPECT images, acceptable C, SNR, CV, and SDCT values, and the largest reduction in patient exposure compared to the reference acquisition procedure was sought.ResultsThe optimal set of parameters for bone SPECT/CT was determined based on a phantom study. It has been implemented in clinical practice. Two groups of patients were examined according to the baseline and optimized protocols, respectively. The new SPECT/CT protocol substantially reduced patients’ radiation exposure compared to the old protocol while maintaining the required diagnostic quality of SPECT and CT images.ConclusionsIn the study, we present a methodology that finds a compromise between diagnostic information and patient exposure during bone SPECT/CT procedures.

Expert Consensus on Optimal Acquisition and Development of the International Bowel Ultrasound Segmental Activity Score [IBUS-SAS]: A Reliability and Inter-rater Variability Study on Intestinal Ultrasonography in Crohn's Disease.

Background and AimsIntestinal ultrasound [IUS] is an accurate, patient-centreed monitoring tool that objectively evaluates Crohn’s disease [CD] activity. However no current, widely accepted, reproducible activity index exists to facilitate consistent IUS identification of inflammatory activity. The aim of this study is to identify key parameters of CD inflammation on IUS, evaluate their reliability, and develop an IUS index reflecting segmental activity.MethodsThere were three phases: [1] expert consensus Delphi method to derive measures of IUS activity; [2] an initial, multi-expert case acquisition and expert interpretation of 20 blinded cases, to measure inter-rater reliability for individual measures; [3] refinement of case acquisition and interpretation by 12 international experts, with 30 blinded case reads with reliability assessment and development of a segmental activity score.ResultsDelphi consensus: 11 experts representing seven countries identified four key parameters including: [1] bowel wall thickness [BWT]; [2] bowel wall stratification; [3] hyperaemia of the wall [colour Doppler imaging]; and [4] inflammatory mesenteric fat. Blind read: each variable exhibited moderate to substantial reliability. Optimal, standardised image and cineloop acquisition were established. Second blind read and score development: intra-class correlation coefficient [ICC] for BWT was almost perfect at 0.96 [0.94–0.98]. All four parameters correlated with the global disease activity assessment and were included in the final International Bowel Ultrasound Segmental Activity Score with almost perfect ICC (0.97 [0.95–0.99, p <0.001]).ConclusionsUsing expert consensus and standardised approaches, identification of key activity measurements on IUS has been achieved and a segmental activity score has been proposed, demonstrating excellent reliability.

Raman scattering detection of high explosives on human hair

High explosives (HE) represent a high risk to the safety and health of the general population. Therefore, there is an ongoing demand for methods of analysis with limits of detection at trace levels for these hazardous chemicals. Since human hair is one of the main physical attributes of our bodies, the interaction of hair surfaces with HE can be of critical importance in forensic and security applications. Noninvasive in situ approaches such as spectroscopic methods are preferred for elucidating these interactions. Among the spectroscopy-based methodologies, those based on Raman scattering are often favored because the sharpness of the vibrational signals facilitates the precise location of the peak maxima and enables more precise determination of the band shifts due to intermolecular interactions. This preliminary study is based on the detection of the HEs 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), and pentaerythritol tetranitrate (PETN) on human hair strands by RS. Raman spectral libraries obtained with a 660-nm laser excitation line were generated for black, bleached, and natural gray hair using direct deposition of PETN, TNT, and RDX. Results obtained were confirmed using portable systems operating at 785 and 1064 nm. Spectral data were preprocessed to correct a high fluorescence background exhibited by the samples due to the indole groups and melanin present in hair. Despite the high fluorescence levels that characterized all the samples, the vibrational signatures that identify the presence of the HEs studied could be detected once the optimum acquisition parameters were established. Among the three hair types studied, gray hair was the best substrate to observe the vibrations of HE crystals on hair. A method limit of detection of 2 ± 1 ng was estimated from image analysis of the HE crystals observed and confirmed as ∼3 ± 1 ng using spectroscopic analysis.

A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria

Classical decision and value of information theories have been applied in the oil and gas industry from the 1960s with partial success. In this research, we identify that the classical theory of value of information has weaknesses related with optimal data acquisition selection, data fuzziness and fuzzy decision criteria and we propose a modification in the theory to fill the gaps found. The research presented in this paper integrates theories and techniques from statistical analysis and artificial intelligence to develop a more coherent, robust and complete methodology for assessing the value of acquiring new information in the context of the oil and gas industry. The proposed methodology is applied to a case study describing a value of information assessment in an oil field where two alternatives for data acquisition are discussed. It is shown that: i) the technique of design of experiments provides a full identification of the input parameters affecting the value of the project and allows a proper selection of the data acquisition actions, ii) when the fuzziness of the data is included in the assessment, the value of the data decreases compared with the case where data are assumed to be crisp; this result means that the decision concerning the value of acquiring new data depends on whether the fuzzy nature of the data is included in the assessment and on the difference between the project value with and without data acquisition, iii) the fuzzy inference system developed for this case study successfully follows the logic of the decision-maker and results in a straightforward system to aggregate decision criteria.

247TF The EndoVaginal Ultrasound Module

Ultrasound has become a ubiquitous technology in the emergency department. One specific subset of bedside ultrasound skills that can be difficult to develop, however, is endocavitary ultrasound. This is typically due to unfamiliarity with the probe itself and the invasive nature of the procedure. Oftentimes, this discomfort results in the ordering of radiology-performed scans which can lead to delays in diagnoses and increased costs incurred by the patient. This instructional module was developed to improve emergency medicine resident comfort with image acquisition and interpretation using the endocavitary probe while on their ultrasound rotation. The purpose of this instructional module is to improve emergency medicine residents’ understanding and knowledge of pelvic anatomy as well as technical skill with using the endocavitary ultrasound probe. It is also to apply knowledge of pelvic anatomy and bedside ultrasound skills to the common situation of appropriately evaluating a woman with first trimester vaginal bleeding. The instructional module will begin with a short pre-test including 5 separate clinical scenarios followed by ultrasound images. After this, there is a presentation meant to be reviewed by the learner(s) prior to arrival for the in-person session. Subsequently, the resident will be led through a directly proctored session reviewing handling of the endocavitary probe and how to navigate optimal image acquisition. Finally, there will be a post-test involving both a manikin with abnormal pelvic anatomy and then 10 more clinical scenarios. After completion of this module, emergency medicine residents will be able successfully obtain images using the endocavitary ultrasound probe. They will also be able to apply the information obtained with these images to patient management when treating a 1st trimester vaginal bleed.

Classification of the botanical and geographical origins of Chinese honey based on 1H NMR profile with chemometrics

In this paper, we report a newly developed non-target 1H NMR detection associated with chemometrics method to classify the botanical and geographical origins of the monofloral Chinese honey. 1H NMR tests of 218 monofloral honey samples of 8 classes (Acacia, Jujube, Linden, Longan, Orange, Rape, Sunflower, Vitex) collected in 2017–2019 across China were conducted under the optimal sample preparation conditions and NMR acquisition parameters. The whole profiles of NMR spectra instead of individual or partial signals from specific components were processed and extracted, then fed to SIMCA-P to classify the botanical and geographical origins through non-target statistical analysis. For the botanical origins, most of them could be classified clearly according to Principal Component Analysis (PCA) with both R2 and Q2 close to 1. Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model could classify the honey floral types successfully with R2Y and Q2 greater than 0.85. It is found that the integral bin for data extraction has no obvious influence on the classification. For the geographical origins, the classification at different geographical levels (providence and town) could be successfully distinguished by OPLS-DA model. The promising preliminary results with the geographical classification at 40 km level unambiguously demonstrate the application of this NMR-based multi-species non-targeted method for the honey authenticity. Successful result is obtained on a pilot prediction of the geographical classification. Comparing with the methods based on other techniques, the advantages of this reported one are less sample amount needed, simple preparation, short test time, and non-targeted multi-species detection.