Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters

A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, acdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating acdom at the wavelength 412 nm (acdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, Rrs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite Rrs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate acdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m−1 from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived acdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of acdom (412) is provided for a coastal transect in the south of Vietnam.

Natural killer (NK) cells have shown promise in the treatment of malignancy. However, the widespread use of these cells may be limited by both the lack of resources and the expertise needed to manufacture them and the apparent need to use only fresh cells. The NHLBI-sponsored Production Assistance for Cellular Therapies group was established to provide the resources and expertise to carry out cell therapy research, including support of clinical trials. Here we describe the qualification of in transit activation of an NK-cell therapy product in preparation for a Phase I clinical trial at a distant medical center. Nonmobilized apheresis mononuclear cell collections were CD3+ cell depleted, placed into culture bags with interleukin (IL)-2, and shipped from Minneapolis/Saint Paul, Minnesota, to Columbus, Ohio, and back to Minneapolis/Saint Paul, under warm, monitored temperatures. Products underwent quality control (QC) testing including cell count, immunophenotyping, viability, endotoxin, sterility culture, and cytotoxicity assays. One product tested the relative importance of IL-2 and controlled incubation. The length of shipment ranged from 14 to 16 hours, and temperatures were well controlled. QC testing was acceptable based upon previous in-house experience. Controlled incubation was not necessary for successful activation of NK cells, but IL-2 appeared essential. The need for novel cell therapies to be infused as fresh products may be a limitation for various cell types. However, we have shown that NK cells can be successfully shipped in the fresh state (allowing 48 hr from apheresis to product infusion) for use at clinical centers. Although IL-2 is critical for NK-cell activation, a 37 °C, 5% CO2 incubator is not.

Improved X-Ray Safety, Quality Control, and Resource Management in Medical Imaging Using QATrack+

Lee, Y.-K.; Choi, J.-K., and Lee, H.-J., 2020. A study on seasonal dynamics of suspended particulate matter in Korea coastal waters using GOCI. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 232-245. Coconut Creek (Florida), ISSN 0749-0208.Analysis of suspended particulate matter (SPM) is a key to understanding the turbulent sediment flow in the Heuksan mud belt (HMB), located along the southwestern coast of the Korean Peninsula. The purpose of this study was to investigate intra-annual variability in remotely sensed SPM data derived from the Geostationary Ocean Color Imager (GOCI) around the HMB over a period of 1 year (2013). Monthly averaged SPM images obtained by the GOCI showed pronounced seasonal changes in turbid water. Dominant environmental factors for intra-annual and diurnal variability of SPM, including river discharge, winds, and tides, were assessed. Monsoon wind dominated seasonal variation in SPM dispersion; the extent of turbid water increased during the winter and decreased during the summer months. Diurnal variation observed from 1-day composite images showed clearly that tidal current was the dominant factor affecting the short-term dispersal pattern of SPM. The gate-controlled river discharge showed the reverse seasonal pattern compared with SPM concentration. However, a turbid plume from the Geum River observed in GOCI data could support the identification of this river as the major source of the HMB. In conclusion, this study demonstrated that the spatial and temporal dynamics of the HMB, including intra-annual and diurnal variability, can be successfully detected using the GOCI.

In this study, a comprehensive quality control (QC) system for in-situ precipitation data records was developed and applied to Canadian in situ precipitation datasets. The system includes a pair of screening procedures to screen for two types of random errors: one procedure is applied to the untransformed monthly total precipitation data series, which is good at finding erroneous data of unusually large values; another is applied to the log-transformed monthly precipitation data (in mm) series, log(P + 0.1), which is good at identifying erroneous zero or near-zero monthly total precipitation amounts. The system then applies three QC (threshold, kriging, and temporal) tests and a decision-making process to confirm whether the screened suspects are erroneous. There is generally good agreement between all the QC tests, while the decision-making process yields the most accurate results when compared to the manually reviewed results. The QC work on Canadian precipitation data sets revealed that it is necessary to apply a pair of screening procedures to identify both types of random errors. All the monthly values identified to be erroneous are set to missing, and so are the corresponding daily values, while keeping records of the original data.

Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters

Particulate metals and their settling velocities in the Humber Estuary, UK

The results of a long-term, comprehensive CT quality control (QC) program were analyzed to investigate differences in failure rates based on QC test, scanner utilization pattern, and number of channels, as well as explore issues regarding testing frequency. CT QC data were collected over a 4-yr period for 26 CT scanners representing two different vendors and using three different QC programs culminating in over 100 scanner-years of QC data. QC tests analyzed included water tests [mean CT number, standard deviation, and uniformity], linearity tests [air, water, and acrylic], and artifact analysis [water phantom and large phantom]. The data were organized based on scanner use, number of channels, scanner modality, and QC test. Logistic regression model analysis with generalized estimating equation method was used to estimate failure rates for each group. A significant difference between failure rates with respect to QC test was found (p-value = 0.02). Large phantom artifacts, standard deviation of water, and water phantom artifacts had the three highest failure rates. No significant difference was found between failure rates organized by scanner use, scanner modality, or number of channels. Standard deviation of water is the most important quantitative value to collect as part of a daily QC program. Uniformity and linearity tests have relatively low failure rates and, therefore, may not require daily verification. While its failure rates were moderate, daily artifact analysis is suggested due to its potentially high impact on clinical image quality. Weekly or monthly large phantom artifact analysis is encouraged for those sites possessing an appropriate phantom.

This research work was undertaken to assess the application of quality control concepts in the production of masonry blocks for building projects in Imo State, Nigeria.The study was embarked upon in order to examine the different types of masonry blocks produced in the state, and to assess the level of quality control concepts applied in their production processes, using selected block industries in Owerri Municipality.The study also was aimed at finding out the educational qualifications of the workers at those block industries.The research was an attempt to search for answers to the problem of building and infrastructural collapse that has become rampant in Nigeria recently.Data for the research was collected through the views of the staff and management of the case study block industries and data analysis which was carried out by the use of percentages and frequency tables and chi-square statistical tool, revealed that the problem of low quality masonry blocks used in building projects were due to several latent factors like "time lag" between mixing and placing of mix into mould; mould of placing mix into mould before compaction; type of cement; and inappropriate sand-cement-water mixture ratio.These things were found to have great and decisive effects on the ultimate strength and quality of the building blocks.The research also revealed that poor mixing of cement, sand and water, lack of quality control measures and low quality sand were responsible for low quality blocks in many block producing small and medium scale industries.This situation is contributing to building and infrastructural collapse.The study therefore recommends that quality control concepts should be applied in the production of masonry blocks.The use of acceptance sampling tests for all the raw materials used in masonry block production and application of control-chart for work-in-process should be adopted.The pre-process, inprocess, and post-process inspections and testings must be carried out for the production and standardization of high-quality building blocks before the products are made available to the customer.

Modelling the inherent optical properties and estimating the constituents׳ concentrations in turbid and eutrophic waters

The performance of different atmospheric correction algorithms for the Ocean and Land Colour Instrument (OLCI) on board of Sentinel-3 (S3) is evaluated for retrieval of water-leaving radiance reflectance, and derived parameters chlorophyll-a concentration and turbidity in turbid coastal waters in the Belgian Coastal Zone (BCZ). This is performed using in situ measurements from an autonomous pan-and-tilt hyperspectral radiometer system (PANTHYR). The PANTHYR provides validation data for any satellite band between 400 and 900 nm, with the deployment in the BCZ of particular interest due to the wide range of observed Near-InfraRed (NIR) reflectance. The Dark Spectrum Fitting (DSF) atmospheric correction algorithm is adapted for S3/OLCI processing in ACOLITE, and its performance and that of 5 other processing algorithms (L2-WFR, POLYMER, C2RCC, SeaDAS, and SeaDAS-ALT) is compared to the in situ measured reflectances. Water turbidities across the matchups in the Belgian Coastal Zone are about 20–100 FNU, and the overall performance is best for ACOLITE and L2-WFR, with the former providing lowest relative (Mean Absolute Relative Difference, MARD 7–27%) and absolute errors (Mean Average Difference, MAD -0.002, Root Mean Squared Difference, RMSD 0.01–0.016) in the bands between 442 and 681 nm. L2-WFR provides the lowest errors at longer NIR wavelengths (754–885 nm). The algorithms that assume a water reflectance model, i.e. POLYMER and C2RCC, are at present not very suitable for processing imagery over the turbid Belgian coastal waters, with especially the latter introducing problems in the 665 and 709 nm bands, and hence the chlorophyll-a and turbidity retrievals. This may be caused by their internal model and/or training dataset not being well adapted to the waters encountered in the BCZ. The 1020 nm band is used most frequently by ACOLITE/DSF for the estimation of the atmospheric path reflectance (67% of matchups), indicating its usefulness for turbid water atmospheric correction. Turbidity retrieval using a single band algorithm showed good performance for L2-WFR and ACOLITE compared to PANTHYR for e.g. the 709 nm band (MARD 15 and 17%), where their reflectances were also very close to the in situ observations (MARD 11%). For the retrieval of chlorophyll-a, all methods except C2RCC gave similar performance, due to the RedEdge band-ratio algorithm being robust to typical spectrally flat atmospheric correction errors. C2RCC does not retain the spectral relationship in the Red and RedEdge bands, and hence its chlorophyll-a concentration retrieval is not at all reliable in Belgian coastal waters. L2-WFR and ACOLITE show similar performance compared to in situ radiometry, but due to the assumption of spatially consistent aerosols, ACOLITE provides less noisy products. With the superior performance of ACOLITE in the 490–681 nm wavelength range, and smoother output products, it can be recommended for processing of S3/OLCI data in turbid waters similar to those encountered in the BCZ. The ACOLITE processor for OLCI and the in situ matchup dataset used here are made available under an open source license.

Image quality in B-mode ultrasound is important as it reflects the diagnostic accuracy and diagnostic information provided during clinical scanning. Quality assurance programs for B-mode ultrasound systems/components are comprised of initial quality acceptance testing and subsequent regularly scheduled quality control testing. The importance of quality assurance programs for B-mode ultrasound image quality using ultrasound phantoms is well documented in the human medical and medical physics literature. The purpose of this prospective, cross-sectional, survey study was to determine the prevalence and methodology of quality acceptance testing and quality control testing of image quality for ultrasound system/components among veterinary sonographers. An online electronic survey was sent to 1497 members of veterinary imaging organizations: the American College of Veterinary Radiology, the Veterinary Ultrasound Society, and the European Association of Veterinary Diagnostic Imaging, and a total of 167 responses were received. The results showed that the percentages of veterinary sonographers performing quality acceptance testing and quality control testing are 42% (64/151; 95% confidence interval 34-52%) and 26% (40/156: 95% confidence interval 19-33%) respectively. Of the respondents who claimed to have quality acceptance testing or quality control testing of image quality in place for their ultrasound system/components, 0% have performed quality acceptance testing or quality control testing correctly (quality acceptance testing 95% confidence interval: 0-6%, quality control testing 95% confidence interval: 0-11%). Further education and guidelines are recommended for veterinary sonographers in the area of quality acceptance testing and quality control testing for B-mode ultrasound equipment/components.

Roads are essential necessity of every nation and it is possible that even with proper designs, the roads might not be constructed to the design standard due to poor quality assurance and control resulting in poor pavement quality. This study presents experimental results carried out on various hot - mix asphalt (HMA) samples obtained across different Asphalt plants in South West Nigeria. This was done to determine the extent to which the HMA used in the construction and rehabilitation of Nigerian roads affect their service life. Six samples of the asphalt binder (bitumen) were obtained from each plant over a period of six months and tested. The tested properties were assessed based on the level of conformance with the specifications and requirements from the FMWH General Specification (Roads and Bridges). The results revealed that HMA from plant B had a specific gravity of 1.01, penetration of 65.00 mm, softening point of 53 oC, flash point of 237.00 oC, peak Marshall Stability of 18.25 kN, flow of 3.87 mm and voids in total mixture peak value of 5.08 %. HMA from plant E had a specific gravity of 1.03, penetration of 65.00 mm, softening point of 51 oC, flash point of 239.00 oC, peak marshall stability of 18.26 kN, flow of 3.67 mm and voids in total mixture peak value of 4.99 % and these were adjudged the best in conformance with the FMWH specifications. Adequate monitoring of HMA quality for either binder or wearing courses by carrying out quality control and assurance tests is thereby recommended as it affects pavement durability and performance. Keywords: Hot-mix asphalt, quality assurance, quality control, marshall stability, flow test

This study aimed to develop a machine-learning approach for early failure detection in custom low-voltage power supply (LVPS) electronic boards within a quality control process. Neural Networks (NNs) were applied as an anomaly-detection model to classify data between two distinct Quality Control (QC) tests, focusing on the performance metrics of the boards. The QC tests occur before and after the boards are subjected to a burn-in test and are referred to as initial and final testing, respectively. The experimental setup includes configuring both test stations, along with a burn-in station, to capture relevant measurement data. The proposed method effectively used measured parameter features to predict potential failures, by distinguishing the patterns in the test bench datasets, improving the reliability of the LVPS boards. The accuracy of the NNs demonstrates preliminary results on the quality control procedure, indicating its potential within quality control.