Number Of Digits Research Articles

Drone-based imaging to assess the microbial water quality in an irrigation pond: A pilot study.

Microbial water quality datasets are essential in irrigated agricultural practices to detect and inform measures to prevent the contamination of produce. Escherichia coli (E. coli) concentrations are commonly used to evaluate microbial water quality. Remote sensing imagery has been successfully used to retrieve several water quality parameters that can be determinants of E. coli habitats in waterbodies. This pilot study was conducted to test the possibility of using imagery from a small unmanned aerial vehicle (sUAV or drone) to improve the estimation of microbial water quality in small irrigation ponds. In situ measurements of pH, turbidity, specific conductance, and concentrations of dissolved oxygen, chlorophyll-a, phycocyanin, and fluorescent dissolved organic matter were taken at depths of 0-15 cm in 23 locations across a pond in Central Maryland, USA. The pond surface was concurrently imaged using a drone with three modified GoPro cameras, and a multispectral MicaSense RedEdge camera with five spectral bands. The GoPro imagery was decomposed into red, blue, and green components. Mean digital numbers for 1-m radius areas in the images were combined with the water quality data to provide input for a regression tree-based analysis. The accuracy of the regression-tree data description with "only imagery" inputs was the same or better than that of trees constructed with "only water-quality parameters" as inputs. From multiple cross-validation runs with "only imagery" inputs for the regression trees, the average (±SD) determination coefficient and root-mean-squared error of the decimal logarithm of E. coli concentrations were 0.793 ± 0.035 and 0.131 ± 0.011, respectively. The results of this study demonstrate the opportunities for using sUAV imagery for obtaining a more accurate delineation of the spatial variation of E. coli concentrations in irrigation ponds.

Development of aboveground mangrove forests’ biomass dataset for Southeast Asia based on ALOS-PALSAR 25-m mosaic

Southeast Asia (SEA) has the largest mangrove forest area in the world, which plays an important role in the global carbon cycle and is helping to mitigate climate change. In order to manage the mangrove forests in SEA, their total biomass needs to be determined. However, development of a biomass dataset based on field survey is time consuming. An aboveground biomass (AGB) dataset of mangrove forests was developed for SEA based on ALOS PALSAR 25-m mosaic. Specifically, ALOS-PALSAR 25-m images were first retrieved for SEA from the Kyoto and Carbon Initiative projects and then converted from a digital number to a normalized radar cross-section format in decibels. Samples of mangrove forests in SEA were collected as regions of interest from ALOS PALSAR data based on visual interpretation using Landsat data and Google Earth imagery. A rule-based classification method based on mangrove backscattering characteristics was then used to classify mangroves and nonmangroves in the region. Subsequently, an empirical model was adopted to estimate the AGB of the mangrove forests and an AGB dataset was developed. The results indicate that the spatial distribution of mangrove forests over SEA is 5.1 million hectares, and the estimated average AGB is 140.5 ± 136.1 Mg / ha.

Deep Learning-Generated Nighttime Reflectance and Daytime Radiance of the Midwave Infrared Band of a Geostationary Satellite

Midwave infrared (MWIR) band of 3.75 μm is important in satellite remote sensing in many applications. This band observes daytime reflectance and nighttime radiance according to the Earth’s and the Sun’s effects. This study presents an algorithm to generate no-present nighttime reflectance and daytime radiance at MWIR band of satellite observation by adopting the conditional generative adversarial nets (CGAN) model. We used the daytime reflectance and nighttime radiance data in the MWIR band of the meteoritical imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), as well as in the longwave infrared (LWIR; 10.8 μm) band of the COMS/MI sensor, from 1 January to 31 December 2017. This model was trained in a size of 1024 × 1024 pixels in the digital number (DN) from 0 to 255 converted from reflectance and radiance with a dataset of 256 images, and validated with a dataset of 107 images. Our results show a high statistical accuracy (bias = 3.539, root-mean-square-error (RMSE) = 8.924, and correlation coefficient (CC) = 0.922 for daytime reflectance; bias = 0.006, RMSE = 5.842, and CC = 0.995 for nighttime radiance) between the COMS MWIR observation and artificial intelligence (AI)-generated MWIR outputs. Consequently, our findings from the real MWIR observations could be used for identification of fog/low cloud, fire/hot-spot, volcanic eruption/ash, snow and ice, low-level atmospheric vector winds, urban heat islands, and clouds.

Detecting nutrient deficiency in spruce forests using multispectral satellite imagery

Nutrient deficiency in forest stands has a negative impact on timber production. Although there are numerous studies investigating nutrient deficiency in forests using remote sensing, research has usually focused on extracting nutrient/pigment concentrations using hyperspectral imagery. Results of studies using this method of assessment are uncertain at the canopy level. This study proposes using freely available multispectral imagery to identify nutrient deficiency in commercially managed forest plantations. A classification map of nutrient deficient, healthy, and a third class, other, for State spruce forests in the Republic of Ireland was constructed using multispectral Sentinel 2 images from Spring and a Random Forest model. The forest area of interest (AOI) was Sitka spruce or Norway spruce plantations greater than 12 years old. Results showed that the overall accuracy was 89% and the associated Kappa Index of agreement was 79%. An unbiased area estimator was vital for an accurate estimate of the scale of nutrient deficiency, which concluded that 23% of the AOI was nutrient deficient. Early detection of nutrient deficiency is crucial to mitigate negative impacts on productivity so a time series analysis of the spectral response of healthy and nutrient deficient classes using Google Earth Engine's Landsat 5, 7, and 8 archive was carried out. A control of known nutrient deficient sites, as identified through foliar analysis, was used for comparison with the nutrient deficient and healthy training data. The spectral response showed a decrease through time for all of the foliar analysis and training data using the green (520–600 nm), red (630–690 nm), and SWIR spectra (1550–1700 nm) during Spring. This decreasing trend is due to the growth of foliage, with the difference in spectral response between nutrient deficient and healthy stands being attributed to the presence of chlorosis in stands suffering from nutrient deficiency. Spectral thresholds using digital numbers for nutrient deficient stands were identified for an operational optimum age cohort of between 10–12 years old which will be used for early detection.

Assessment of Night-Time Lighting for Global Terrestrial Protected and Wilderness Areas

Protected areas (PAs) play an important role in biodiversity conservation and ecosystem integrity. However, human development has threatened and affected the function and effectiveness of PAs. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night-time stable light (NTL) data have proven to be an effective indicator of the intensity and change of human-induced urban development over a long time span and at a larger spatial scale. We used the NTL data from 1992 to 2013 to characterize the human-induced urban development and studied the spatial and temporal variation of the NTL of global terrestrial PAs. We selected seven types of PAs defined by the International Union for Conversation of Nature (IUCN), including strict nature reserve (Ia), wilderness area (Ib), national park (II), natural monument or feature (III), habitat/species management area (IV), protected landscape/seascape (V), and protected area with sustainable use of natural resources (VI). We evaluated the NTL digital number (DN) in PAs and their surrounding buffer zones, i.e., 0–1 km, 1–5 km, 5–10 km, 10–25 km, 25–50 km, and 50–100 km. The results revealed the level, growth rate, trend, and distribution pattern of NTL in PAs. Within PAs, areas of types V and Ib had the highest and lowest NTL levels, respectively. In the surrounding 1–100 km buffer zones, type V PAs also had the highest NTL level, but type VI PAs had the lowest NTL level. The NTL level in the areas surrounding PAs was higher than that within PAs. Types Ia and III PAs showed the highest and lowest NTL growth rate from 1992 to 2013, respectively, both inside and outside of PAs. The NTL distributions surrounding the Ib and VI PAs were different from other types. The areas close to Ib and VI boundaries, i.e., in the 0–25 km buffer zones, showed lower NTL levels, for which the highest NTL level was observed within the 25–100 km buffer zone. However, other types of PAs showed the opposite NTL patterns. The NTL level was lower in the distant buffer zones, and the lowest night light was within the 1–25 km buffer zones. Globally, 6.9% of PAs are being affected by NTL. Conditions of wilderness areas, e.g., high latitude regions, Tibetan Plateau, Amazon, and Caribbean, are the least affected by NTL. The PAs in Europe, Asia, and North America are more affected by NTL than South America, Africa, and Oceania.

Mutational Type and Configuration of an Individual Gene May Differentially Impact the Clinical and Phenotypic Features

Myelodysplastic syndromes (MDS) arise in older adults through the stepwise acquisition of multiple somatic mutations. The genetic heterogeneity that results includes mutations of diverse genes and their combinations, clonal hierarchy, genetic configuration (e.g., bi-allelic or compound heterozygous, hemizygous lesions), specific positions within a gene including canonical hotspots vs. other positions, and types of mutation (truncations vs. missense), all of which could differentially affect pathogenesis. Given the binary status (e.g. mutated vs. wild-type) used in many clinical analyses, the true impact of specific types of mutations may be obscured and their specific roles underestimated. Deep targeted NGS was carried out for a panel of the 36 most frequently mutated genes in 1,809 MDS patients (low-risk MDS (n=839) vs. high-risk MDS (n=607), MDS/MPN (n=212), and sAML n=151). Copy number alterations (CNA) were also evaluated by combining karyotyping, microarray, and digital copy number analysis. With a mean coverage of 862x, after removing SNPs and errors, 3,971 somatic mutations were identified, the most common (>10% of cases) being TET2, SF3B1, ASXL1, del(5q), SRSF2, complex karyotype, and del(7q). For the purpose of this proof of concept analysis we focused on illustrative genes (TP53, RUNX1, TET2, and EZH2) affected by 2 recurrent hits. Bi-allelic TET2 or TP53 mutations were found in 15% (271/1,809) and 4% (72/1,809) of patients, respectively. TET2 and RUNX1 were most likely biallelic, whereas TP53 and EZH2 were most often affected by mutations and somatic deletion. Comparing the distribution of canonical vs. other types of mutations in genes, DNMT3A mutations affected the canonical site (R882) in 17% (35/203) of patients, were truncating in 39% (79/203) and missense in 44% (89/203) have also been found; deletions affecting the DNMT3A locus are rare. Within U2AF1, U2AF1Q157 are more frequent than U2AF1S34 (54% vs. 35%). Next, we checked correlation between these different types of mutations of one gene. 78 significant combinations were found. For instance, U2AF1Q157 mutations more commonly accompanied ASXL1 mutations and del(7q) and less frequently DNMT3A and BCOR mutations, trisomy8 and del(20) when compared to U2AF1S34 mutations [ASXL1 mutations 53% (42/80) in U2AF1Q157 vs. 16% (8/49) in U2AF1S34, P < .0001]. TET2 Bi-allelic mutations were more commonly associated with ZRSR2 and SRSF2 mutations, and less frequently del(5q) when compared to TET2 mono-allelic mutations [SRSF2 mutations 29% (80/276) in TET2-bi vs. 15% (34/227) in TET2-mono, P = .003]. In addition, patients with SRSF2 missense mutations were more likely to have RUNX1 bi-allelic mutations than those with SRSF2 in-frame mutations. We evaluated the impact of different types of mutations and combinations of them on disease phenotypes and survival. We then evaluated the impact of different types of mutations and their combinations on clinical phenotypes including dichotomous morphological (MDS vs. MDS/MPN) features, progressive (low- vs. high risk) subtypes. EZH2 bi-allelic alterations were more commonly associated with myleoproliferative features` compared to EZH2 mono-allelic alteration (q=.016). TET2 bi-allelic alterations and truncating mutations were found more frequently in higher-risk subtypes than TET2 mono-allelic and missense mutations (q<.001). In survival analyses, patients with DNMT3AR882 mutations had a poorer prognosis than those with truncating and the other missense mutations [P = .033, HR 1.86 (1.05-3.3)]. Next, using the PyClone bioanalytic pipeline, we recapitulated for each patient the clonal hierarchy and defined "dominant" vs. "secondary" mutations. DNMT3AR882 mutations were likely to be dominant/founder lesions compared to truncating or the other missense mutations: 77% (27/35) for R882 vs. 51% (40/79) for truncating vs. 45% (47/98) for the other missense, p=.0046. Specific dominant and secondary mutational pairs also differentially affected survival compared to the reverse configuration (q<.1) including EZH2 and RUNX1 or BCOR and U2AF1 or RUNX1 and BCOR. In conclusion, we report a comprehensive analysis of various types and configurations of lesions of individual commonly affected genes. Our results indicate that establishment of clinical or phenotypic correlations requires consideration of the type, rank and configuration of somatic mutations. Disclosures Mukherjee: McGraw Hill Hematology Oncology Board Review: Other: Editor; Bristol-Myers Squibb: Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Projects in Knowledge: Honoraria; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Partnership for Health Analytic Research, LLC (PHAR, LLC): Consultancy. Nazha:Incyte: Speakers Bureau; Daiichi Sankyo: Consultancy; Jazz Pharmacutical: Research Funding; Tolero, Karyopharma: Honoraria; Abbvie: Consultancy; MEI: Other: Data monitoring Committee; Novartis: Speakers Bureau. Sekeres:Millenium: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Ogawa:Asahi Genomics: Equity Ownership; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; Qiagen Corporation: Patents & Royalties; RegCell Corporation: Equity Ownership; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Kan Research Laboratory, Inc.: Consultancy. Maciejewski:Novartis: Consultancy; Alexion: Consultancy.

Development of the chick wing and leg neuromuscular systems and their plasticity in response to changes in digit numbers

The tetrapod limb has long served as a paradigm to study vertebrate pattern formation. During limb morphogenesis, a number of distinct tissue types are patterned and subsequently must be integrated to form coherent functional units. For example, the musculoskeletal apparatus of the limb requires the coordinated development of the skeletal elements, connective tissues, muscles and nerves. Here, using light-sheet microscopy and 3D-reconstructions, we concomitantly follow the developmental emergence of nerve and muscle patterns in chicken wings and legs, two appendages with highly specialized locomotor outputs. Despite a comparable flexor/extensor-arrangement of their embryonic muscles, wings and legs show a rotated innervation pattern for their three main motor nerve branches. To test the functional implications of these distinct neuromuscular topologies, we challenge their ability to adapt and connect to an experimentally altered skeletal pattern in the distal limb, the autopod. Our results show that, unlike autopod muscle groups, motor nerves are unable to fully adjust to a changed peripheral organisation, potentially constrained by their original projection routes. As the autopod has undergone substantial morphological diversifications over the course of tetrapod evolution, our results have implications for the coordinated modification of the distal limb musculoskeletal apparatus, as well as for our understanding of the varying degrees of motor functionality associated with human hand and foot malformations.

Algorithm Research and Hardware Implementation of High Precision Floating Point Exponential Function

Exponential function is of great significance for high-precision calculation in computer technology. The study of exponential function plays a very important role in modern communication and signal processing. With the rapid increase of the number of digits in computer computing, the fixed-point representation range is small and limited in practical applications. The floating-point number indicates a wide range of teaching and has a wider range of applications. Therefore, the research direction of this article is the hardware algorithm research and implementation of high-precision floating-point exponential function. The goal is to implement the 64-bit high-precision exponential function hardware implementation in accordance with IEEE754 standard. In this paper, the vector mode in the CORDIC algorithm is used to improve the efficiency of the algorithm by improving the iterative method. The 64-bit floating-point exponential function operation is realized by FPGA, and the accuracy is achieved when compared with the PYTHON operation result.

A new method of relative radiometric calibration for hyperspectral imaging based on skylight monitor

A new method of relative radiometric calibration based on the skylight monitor is presented for airborne hyperspectral remote sensing to eliminate the negative effect on data resulting from the time-varying skylight during a long flight. In terms of large area operation of mapping or spectral imaging, a static radiation model hardly reveals actual cases as external environment keeps changing. Compared with common considerable factors, fluctuation of skylight is the primary one that may observably affect spectral imaging continuously leading to radiation changes upon flight lines. To get rid of the influence of skylight on spectral imagery and monitoring the variation during the flight, we assemble a set of skylight monitor fixed to the aircraft cabin for the sake of recording the semi-spherical skylight keeping synchronization with hyperspectral imaging system and the position and orientation system. The skylight monitor consists of a cosine corrector on the top receiving the skylight, a stable optical fiber and a visible and near-infrared linear array modular spectrometer. The corresponding matched data of skylight with each frame of images is used to correct related digital number after stripe non-uniformity correction, achieving mean relative standard deviation (coefficient of variation or CV) of under 6% for all 256 bands. The final result shows a satisfactory calibrated image of an appropriate evaluation criteria with contrast of the original image.

Effects of profile interpolation in cam mechanisms

Realization of cam profiles passes through a discretization, truncation and interpolation of ideal designed motion profiles. This process affects the kinematics and the dynamics of a cam mechanism. This work aims to study and quantify this process and suggest a correct choice of the number of points that describes the profile, the number of digits adopted to represent these points and the type of interpolation adopted in working machines to reconstruct the original motion profile. The case of a single dwell rotary cam with translating follower is presented through numerical and experimental tests. The obtained results demonstrate that the linear interpolation can be an effective solution, interpolating a number of points in an optimal range avoiding excesses. Furthermore, the study highlights that the number of adopted digits may show a non-negligible effect.

Patch Similarity Convolutional Neural Network for Urban Flood Extent Mapping Using Bi-Temporal Satellite Multispectral Imagery

Urban flooding is a major natural disaster that poses a serious threat to the urban environment. It is highly demanded that the flood extent can be mapped in near real-time for disaster rescue and relief missions, reconstruction efforts, and financial loss evaluation. Many efforts have been taken to identify the flooding zones with remote sensing data and image processing techniques. Unfortunately, the near real-time production of accurate flood maps over impacted urban areas has not been well investigated due to three major issues. (1) Satellite imagery with high spatial resolution over urban areas usually has nonhomogeneous background due to different types of objects such as buildings, moving vehicles, and road networks. As such, classical machine learning approaches hardly can model the spatial relationship between sample pixels in the flooding area. (2) Handcrafted features associated with the data are usually required as input for conventional flood mapping models, which may not be able to fully utilize the underlying patterns of a large number of available data. (3) High-resolution optical imagery often has varied pixel digital numbers (DNs) for the same ground objects as a result of highly inconsistent illumination conditions during a flood. Accordingly, traditional methods of flood mapping have major limitations in generalization based on testing data. To address the aforementioned issues in urban flood mapping, we developed a patch similarity convolutional neural network (PSNet) using satellite multispectral surface reflectance imagery before and after flooding with a spatial resolution of 3 meters. We used spectral reflectance instead of raw pixel DNs so that the influence of inconsistent illumination caused by varied weather conditions at the time of data collection can be greatly reduced. Such consistent spectral reflectance data also enhance the generalization capability of the proposed model. Experiments on the high resolution imagery before and after the urban flooding events (i.e., the 2017 Hurricane Harvey and the 2018 Hurricane Florence) showed that the developed PSNet can produce urban flood maps with consistently high precision, recall, F1 score, and overall accuracy compared with baseline classification models including support vector machine, decision tree, random forest, and AdaBoost, which were often poor in either precision or recall. The study paves the way to fuse bi-temporal remote sensing images for near real-time precision damage mapping associated with other types of natural hazards (e.g., wildfires and earthquakes).

A new topological and hierarchical river coding method based on the hydrology structure

River network coding is important for hydrological model on the aspects of water cycles simulation, water resources evaluation and extreme hydrological events forecast. However, the existing river network coding methods had several disadvantages, such as, the river network coding structure is too complex to understand, the river network topology is difficult to identify, the river network coding capacity is limited. To overcome the above-mentioned shortcomings, this paper proposed a new topological and hierarchical river coding method based on the river network created by the DEM (Digital Elevation Method) data and ArcGIS software. This method systematically defines the river levels based on the hydrology structure from outlet to source. The river directly flows into the watershed outlet is river L1, the branch of river L1 with a certain catchment area is river L2, the branch of L2 with a certain catchment area is river L3, and so on. Secondly, we proposed a flexible coding scheme that encode the river segments with pure digital numbers hierarchically. Taking the two-digits scheme for example, the L1 river segments are coded with a sequence number, such as [01], [02], [03], […]. The L2 river segments inherit the river code from the L1 stem river segment, add a serial of self-order numbers (01, 02, 03, ……) from the junction to the river source, and become [0101], [0102], [0103], […]. The process of coding the river segments at subsequent level is similar. Finally, this new coding method was programmed in Matlab software, and successfully examined in the Amazon River basin, the world's largest watershed, as a case study. The results show that the new method is competent for easily controlling the river level and river segment density, flexibly adjusting the code digital numbers to fit different basins with abundant or little rivers, easily plotting the topological relationship, automatically encoding by computer program and easily understood. In a word, this study is a useful attempt to create new river network coding method, and it also has positive significance to promote the hydrological simulation research.

Ryū revisited: printf floating point conversion

Ryū Printf is a new algorithm to convert floating-point numbers to decimal strings according to the printf %f, %e, and %g formats: %f generates ‘full’ output (integer part of the input, dot, configurable number of digits), %e generates scientific output (one leading digit, dot, configurable number of digits, exponent), and %g generates the shorter of the two. Ryū Printf is based on the Ryū algorithm, which converts binary floating-point numbers to the shortest equivalent decimal floating-point representation. We provide quantitative evidence that Ryū Printf is between 3.8 and 55 times faster than existing printf implementations. Furthermore, we show that both Ryū and Ryū Printf generalize to arbitrary number bases. This finding implies the existence of a fast algorithm to convert from base-10 to base-2, as long as the maximum precision of the input is known a priori.

True Sensor Captured Radiance and Surface Reflectance from Landsat-8 Multispectral Image sets

Proper validation of multispectral image sets that are produced by Satellite Sensors, in this era of big-data computing, is an important aspect in signal processing of natural semantic scenes. In this research article we explore fundamental issues that are cropped up in radiance correction and surface reflectance measurements. We calibrate the raw Landsat-8 imagery digital numbers by using standard functional oriented modular programs in R software, for true sensor radiance and reflectance values. This important preprocessing step is essential for activities that use multispectral images for natural resources monitoring and change-detection studies. It is noted that the procedures for preprocessing can be applied in machine learning algorithms for scientific studies.

Assessment of sedimentation process in flood water spreading system using IRS (P5) and supervised classification algorithms (case study: Dahandar plain, Minab city, south of Iran)

Many parts of Iran are dry plains that seem suitable places for building flood spreading systems and diverting flash floods to infiltration areas in order to recharge ground water resources. After passing a period of time, sediment deposition decreases the artificial recharge capacity of flood spreading system infiltration basins. Panchromatic images of IRS(P5) satellite are appropriate tools for studying sediment distribution, texture and thickness on the surface of these systems. For monitoring sediment distribution, the panchromatic images used that were taken in 2007,2010 and 2016. For evaluating sediment texture and thickness, 40 samples were collected from surface soil of different places all over Dahandar flood spreading system, in Minab city. By using Hydrometer method and soil texture triangle, different percentages of sand, silt, clay, soil texture types and sediment thickness were determined. Then by using simple linear regression the relationship between different percentages of sand, silt, clay and sediment thickness with the digital numbers of 2016 Panchromatic image were evaluated. The values of R2 for sand, silt, clay and sediment thickness were 0.428, 0.343, 0.227 and 0.429 respectively. Different algorithms of supervised classification (maximum likelihood, minimum distance, parallelepiped) were used for creating maps with different classes of sand, silt, clay, soil texture types and sediment thickness. For sand particles, maximum likelihood algorithm with over all accuracy of 64%, for silt particles minimum distance-raw algorithm with over all accuracy of 51%, for clay particles minimum distance-normalized with over all accuracy of 46% showed the greatest values. For sediment thickness, different algorithms had the same function. The mentioned methods could reasonably explain the distribution of sand, silt and clay particles, soil texture and sediment thickness all over the flood spreading system.

Terminal digit preference: a source of measurement error in breast cancer diameter reporting

Objectives: Women diagnosed with breast cancer are offered treatment and therapy based on tumor characteristics, including tumor diameter. There is scarce knowledge whether tumor diameter is accurately reported, or whether it is unconsciously rounded to the nearest half-centimeter (terminal digit preference). This study aimed to assess the precision (number of digits) of breast cancer tumor diameters and whether they are affected by terminal digit preference. Furthermore, we aimed to assess the agreement between mammographic and histopathologic tumor diameter measurements.Material and Methods: This national registry study included reported mammographic and registered histopathologic tumor diameter information from the Cancer Registry of Norway for invasive breast cancers diagnosed during 2012–2016. Terminal digit preference was assessed using histograms. Agreement between mammographic and histopathologic measurements was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots.Results: Mammographic, histopathologic, or both tumor measurements were available for 7792, 13,541 and 6865 cases, respectively. All mammographic and 97.2% of histopathologic tumor diameters were recorded using whole mm. Terminal digits of zero or five were observed among 38.7% and 34.8% of mammographic and histopathologic measurements, respectively. There was moderate agreement between the two measurement methods (ICC = 0.52, 95% CI: 0.50–0.53). On average, mammographic measurements were 1.26 mm larger (95% limits of agreement: −22.29–24.73) than histopathologic measurements. This difference increased with increasing tumor size.Conclusion: Terminal digit preference was evident among breast cancer tumor diameters in this nationwide study. Further studies are needed to investigate the potential extent of under-staging and under-treatment resulting from this measurement error.

Understanding the Users Personal Attributes Similarity Across Online Social Networks

In this modern era of technology, everyone accessing the Internet is obsessed with social media. A User accesses different social media services to fulfill his diverse needs. For instance, Instagram is mainly used for sharing personal visual content while Twitter is known for finding latest news and trends, similarly Facebook for personal posts. Such services lead to the distribution of personal information of an Internet user on these platforms. In this paper, we build a framework to discover the relationship among the attributes of a user across the social media.We use different fuzzy string matching algorithms to find the similarities between the attributes. We extract the ‘name’ and ‘username’ from a publicly shared dataset and apply two character based and token based algorithms on these features. The results are indicative of the fact that only a limited number of users share the same name and username across the sites. On further analysis, it is found that although name and username of most of the users do not exactly match, they tend to be similar with the infinitesimal difference like; underscore, period, one digit numbers, etc. This study provides an analysis of the typical variations in names and usernames, which can further be studied for the extension to other social networks This profile will help in behavior analysis of a user, which will further help us to improve recommendations and analyze for criminal behavior and similar applications.

Evaluation of lossless and lossy algorithms for the compression of scientific datasets in netCDF-4 or HDF5 files

Abstract. The increasing volume of scientific datasets requires the use of compression to reduce data storage and transmission costs, especially for the oceanographic or meteorological datasets generated by Earth observation mission ground segments. These data are mostly produced in netCDF files. Indeed, the netCDF-4/HDF5 file formats are widely used throughout the global scientific community because of the useful features they offer. HDF5 in particular offers a dynamically loaded filter plugin so that users can write compression/decompression filters, for example, and process the data before reading or writing them to disk. This study evaluates lossy and lossless compression/decompression methods through netCDF-4 and HDF5 tools on analytical and real scientific floating-point datasets. We also introduce the Digit Rounding algorithm, a new relative error-bounded data reduction method inspired by the Bit Grooming algorithm. The Digit Rounding algorithm offers a high compression ratio while keeping a given number of significant digits in the dataset. It achieves a higher compression ratio than the Bit Grooming algorithm with slightly lower compression speed.

On-Orbit Radiance Calibration of Nighttime Sensor of LuoJia1-01 Satellite Based on Lunar Observations

The high-resolution nighttime light (NTL) data of the LuoJia1-01 NTL remote sensing satellite has enriched the available data of NTL remote sensing applications. The radiance calibration used as a reference to convert the digital number (DN) recorded by the nighttime sensor into the radiance of the corresponding ground object is the basic premise to the effective application of the NTL data. Owing to the lack of on-board calibration equipment and the absence of an absolute radiometric calibration light source at night, it is difficult for LuoJia1-01 to carry out on-orbit radiance calibration. The moon, as an exoatmospheric stable radiation source, is widely used for the radiometric calibration of remote sensing satellite sensors and to monitor the stability of the visible and near-infrared sensors. This study, based on lunar observation of the LuoJia1-01 NTL sensor, focused on on-orbit radiometric calibration and included monitoring changes in the nighttime sensor radiometric response for nearly a year by using the Robotic Lunar Observatory (ROLO) lunar irradiance model (Version 311 g). The results showed that: (1) the consistency of the radiometric calibration results based on the ROLO model and the laboratory calibration results of LuoJia1-01 exceeded 90%; (2) the nighttime sensor of LuoJia1-01 radiometric response underwent approximately 6% degradation during the observation period of nearly one year (353 days).

Radiometric calibration of the SIMBIO-SYS STereo imaging Channel

The STereo imaging Channel (STC) is a double wide-angle camera developed to be one of the channels of the SIMBIO-SYS instrument onboard of the ESA BepiColombo mission to Mercury. STC main goal is to map in 3D the whole Mercury surface. The geometric and radiometric responses of the STC Proto Flight model have been characterized on-ground during the calibration campaign. The derived responses will be used to calibrate the STC images that will be acquired in flight. The aim is to determine the functions linking the detected signal in digital number to the radiance of the target surface in physical units. The result of the radiometric calibration consists in the determination of well-defined quantities: (1) the dark current as a function of the integration time and of the detector temperature, settled and controlled to be stable at 268 K; (2) the read out noise, which is associated with the noise signal of the read-out electronic; and (3) the fixed pattern noise, which is generated by the different response of each pixel. Once these quantities are known, the photon response and the photo-response non-uniformity, which represents the variation of the photon responsivity of a pixel in an array, can be derived. The final result of the radiometric calibration is the relation between the radiance of an accurately known and uniform source, and the digital numbers measured by the detector.