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Climatological changes occur globally but have local impacts. Increased storminess, sea level rise and more powerful waves are expected to batter the coastal zone more often and more intense. To understand climate change impacts, regional bathymetry information is paramount. A major issue is that the bathymetries are often non-existent or if they do exist, outdated. This sparsity can be overcome by space-borne satellite techniques to derive bathymetry. Sentinel-2 optical imagery is collected continuously and has a revisit-time around a few days depending on the orbital-position around the world. In this work, Sentinel-2 imagery derived wave patterns are extracted using a localized radon transform. A discrete fast-Fourier (DFT) procedure per direction in Radon space (sinogram) is then applied to derive wave spectra. Sentinel-2 time-lag between detector bands is employed to compute the spectral wave-phase shift and depth using the gravity wave linear dispersion. With this novel technique, regional bathymetries are derived at the test-site of Capbreton, France with an root mean squared (RMS)-error of 2.58 m and a correlation coefficient of 0.82 when compared to the survey for depths u

Lines of therapy (LOT) derived from real-world healthcare data not only depict real-world cancer treatment sequences, but also help define patient phenotypes along the course of disease progression and therapeutic interventions. The sequence of prescribed anticancer therapies can be defined as temporal phenotyping resulting from changes in morphological (tumor staging), biochemical (biomarker testing), physiological (disease progression), and behavioral (physician prescribing and patient adherence) parameters. We introduce a novel methodology that is a two-part approach: 1) create an algorithm to derive patient-level LOT and 2) aggregate LOT information via clustering to derive temporal phenotypes, in conjunction with visualization techniques, within a large insurance claims dataset. We demonstrated the methodology using two examples: metastatic non-small cell lung cancer and metastatic melanoma. First, we generated a longitudinal patient cohort for each cancer type and applied a set of rules to derive patient-level LOT. Then the LOT algorithm outputs for each cancer type were visualized using Sankey plots and K-means clusters based on durations of LOT and of gaps in therapy betwee

Abstract Fragility functions are the key components of damage analysis for the next generation performance-based earthquake engineering (PBEE-2) framework. Despite being widely discussed and researched topic in almost all seismically active regions, fragility functions for Nepali buildings are not widely researched to date. This paper derives empirical fragility functions for residential buildings using more than a million damage data from the 1934 Bihar-Nepal earthquake (MW ∼8.4), 1980 Chainpur earthquake (MW 6.5), 1988 Eastern Nepal earthquake (MW 6.8), 2011 Eastern Nepal earthquake (MW 6.9), and 2015 Gorkha seismic sequence (MW 7.8). A new damage classification system is proposed in this study and fragility functions for reinforced concrete, brick masonry, and stone masonry building classes are derived. As seismic site effects is one of the leading factor contributing damage in the case of Himalayan earthquakes, fragility functions considering seismic site effects are also derived for all three building classes. Finally, fragility functions derived in this study are compared with existing fragility functions and discussion regarding the discrepancies is presented. Together with

There is increasing interest in the use of quantitative transcriptomic data to determine benchmark dose (BMD) and estimate a point of departure (POD) for human health risk assessment. Although studies have shown that transcriptional PODs correlate with those derived from apical endpoint changes, there is no consensus on the process used to derive a transcriptional POD. Specifically, the subsets of informative genes that produce BMDs that best approximate the doses at which adverse apical effects occur have not been defined. To determine the best way to select predictive groups of genes, we used published microarray data from dose–response studies on six chemicals in rats exposed orally for 5, 14, 28, and 90 days. We evaluated eight approaches for selecting genes for POD derivation and three previously proposed approaches (the lowest pathway BMD, and the mean and median BMD of all genes). The relationship between transcriptional BMDs derived using these 11 approaches and PODs derived from apical data that might be used in chemical risk assessment was examined. Transcriptional BMD values for all 11 approaches were remarkably aligned with corresponding apical PODs, with the vast major

Time on screens (screen time) on multiple digital devices (computers, mobile phones, tablets, television screens, etc.) due to varied motivations (work, leisure, entertainment, gaming, etc.) has become an integral part of population behaviour. However, a significant evidence gap exists in screen time accumulated over ubiquitous mobile devices such as smartphones. This study aimed to develop an accurate, reliable and replicable methodology to derive objective screen time (i.e., screen-state) from all types of citizen-owned smartphones. A convenience sample of 538 adults (≥18 years) from two largest urban centres in Saskatchewan, Canada (Regina and Saskatoon) was recruited in 2017 and 2018. Participants used a custom-built smartphone application to provide objective and subjective data. A novel methodology was developed to derive objective screen-state, and these data were compared with subjective measures. The findings showed that objective screen-state from smartphones can be derived and assessed across a range of cut-points that take into consideration varied measurement errors. When objective measures were compared with subjective reporting, the results indicated that participant

Abstract For decades, although the inverse kinematics (IK) problem of six degrees of freedom (DOF) manipulator with general geometry has been solved, there is still needed an efficient and unified method to derive the IK formulas for the six-DOF manipulator with simple geometry. In this paper, we propose an improved method of disconnection and re-connection to achieve this purpose. Firstly, we determined the position selection of the two cutting points and the attitude setting at the first cutting point. Next, we gave the new conditions for the re-connection of the two sub-chains and the corresponding equations. Then, we summarized five methods of cutting the manipulator into two three-DOF sub-chains and corresponding equation deformations, as well as the selection principles of equation deformations. Finally, we used three examples to demonstrate the effectiveness of the method. The results show that the expressions of six joint variables can be derived from only six equations. The solutions of the wrist joint variables are not affected by the singularity.

Abstract The stable carbon isotopic composition (δ13C) measured in tree rings is a standard proxy for paleoclimate reconstructions and is increasingly being used as a paleophysiological proxy. To fully exploit the potential of tree ring δ13C proxy, atmospheric CO2 concentration and δ13C (δ13CO2) data are required to correct tree ring δ13C from the declining trend of δ13CO2 due to fossil fuel burning since 1850 CE, and to derive physiological parameters using biochemical models that link photosynthesis to δ13C. These atmospheric data are available from direct measurements or can be inferred from indirect proxies such as ice cores covering the Common Era (CE) at variable temporal resolutions. For almost two decades, tree-ring researchers have relied on a dataset derived from fitted linear regressions of ice core measurements available through the seminal McCarroll and Loader (2004) article for the 1850−2003 CE period. However, new calibrations and compilations of ice core data and direct measurements are now available as part of Earth System Modelling efforts which remain overlooked by the tree ring research community.Here, we present an overview of the new and freely available datas

A statistical method to establish an intensity-duration curve (I-D curve) for debris flows is highly dependent on a large amount of debris flows and rainfall events and is impossible for a gully lacking observation data. To overcome this limitation, a physics-based model to derive the I-D curve is presented. In this new model, the density of the debris flow is chosen as the key parameter, based on which, the rainfall intensity and duration necessary for fitting I-D curve are obtained. The physical model is validated in Jiangjia Gully, a typical debris flow valley with several debris flows each year. A series of I-D curves under the conditions of different antecedent rainfalls were fitted. These derived curves are similar to the shape of the curve from the statistical method, but having upper and lower boundary lines related to the necessary conditions for the occurrence of debris flows. The precision of the new model is identified as about 80.5% using 63 collected rainfalls in Jiangjia Gully in Yunan province, China. This value is 27.7% higher than the curve fitted through the statistical method. This new physical model is capable of improving the deficiency of the statistical meth

We present ^{3{D}}BAROLO,† a new code that derives rotation curves of galaxies from emission-line observations. This software fits 3D tilted-ring models to spectroscopic data cubes and can be used with a variety of observations: from H I and molecular lines to optical/IR recombination lines. We describe the structure of the main algorithm and show that it performs much better than the standard 2D approach on velocity fields. A number of successful applications, from high to very low spatial resolution data are presented and discussed. ^{3D}BAROLO can recover the true rotation curve and estimate the intrinsic velocity dispersion even in barely resolved galaxies (˜2 resolution elements) provided that the signal to noise of the data is larger than 2-3. It can also be run automatically thanks to its source-detection and first-estimate modules, which make it suitable for the analysis of large 3D data sets. These features make ^{3D}BAROLO a uniquely useful tool to derive reliable kinematics for both local and high-redshift galaxies from a variety of different instruments including the new generation Integral Field Units, ALMA and the SKA pathfinders.

In this manuscript, we elaborate on a procedure to derive ϵ-factorised differential equations for multi-scale, multi-loop classes of Feynman integrals that evaluate to special functions beyond multiple polylogarithms. We demonstrate the applicability of our approach to diverse classes of problems, by working out ϵ-factorised differential equations for single- and multi-scale problems of increasing complexity. To start we are reconsidering the well-studied equal-mass two-loop sunrise case, and move then to study other elliptic two-, three- and four-point problems depending on multiple different scales. Finally, we showcase how the same approach allows us to obtain ϵ-factorised differential equations also for Feynman integrals that involve geometries beyond a single elliptic curve.

Aircraft type recognition remains challenging, due to their tiny sizes and geometric distortions in large-scale panchromatic satellite images. This paper proposes a framework for aircraft type recognition by focusing on shape preservation, spatial transformations, and geospatial attributes derivation. First, we construct an aircraft segmentation model to obtain masks representing the shape of aircrafts by employing a learnable shape-preserved and deformable network in the mask RCNN architecture. Then, the orientation of the segmented aircrafts is determined by estimating the symmetrical axes using their gradient information. Besides template matching, we derive the length and width of aircrafts using the geotagged information of images to further categorize the types of aircrafts. Also, we present an effective inferencing mechanism to overcome the issue of partial detection or missing aircrafts in large-scale images. The efficacy of the proposed framework is demonstrated on large-scale panchromatic images with ground sampling distances of 0.65m (C2S).

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then aggregated to Plant Functional Types (PFTs). Next, the spatial abundance of PFTs at MODIS resolution (500 m) is calculated using Landsat data (30 m). Based on these PFT abundances, representative trait values are calculated for MODIS pixels with nearby trait data. Finally, different regression algorithms are applied to globally predict trait estimates from these MODIS pixels using remote sensing and climate data. The methods were compared in terms of precision, robustness and efficiency. The best

The origin and physiological significance of lipid droplets (LDs) in the nucleus is not clear. Here we show that nuclear LDs in hepatocytes are derived from apolipoprotein B (ApoB)-free lumenal LDs, a precursor to very low-density lipoproprotein (VLDL) generated in the ER lumen by microsomal triglyceride transfer protein. ApoB-free lumenal LDs accumulate under ER stress, grow within the lumen of the type I nucleoplasmic reticulum, and turn into nucleoplasmic LDs by disintegration of the surrounding inner nuclear membrane. Oleic acid with or without tunicamycin significantly increases the formation of nucleoplasmic LDs, to which CTP:phosphocholine cytidylyltransferase α (CCTα) is recruited, resulting in activation of phosphatidylcholine (PC) synthesis. Perilipin-3 competes with CCTα in binding to nucleoplasmic LDs, and thus, knockdown and overexpression of perilipin-3 increases and decreases PC synthesis, respectively. The results indicate that nucleoplasmic LDs in hepatocytes constitute a feedback mechanism to regulate PC synthesis in accordance with ER stress. The origin and physiological significance of lipid droplets (LDs) in the nucleus is not clear. Here authors show that nucl

Abstract Z-number, combined with constraint and reliability of the information, is an effective frame to simulate the thinking of humans. How to derive knowledge of Z-numbers, especially from the objective data may become a fascinating and open issue. In this paper, a method of deriving knowledge of Z-numbers from the perspective of Dempster–Shafer theory is proposed. The proposed method considers the Z-number generating from objective and subjective data using Dempster–Shafer theory. Some numerical examples and experimental simulations are used to illustrate the effectiveness of the proposed methodology.

Undisputedly, derivation of theoretical systematic uncertainties is an inseparable ingredient of any robust analysis dealing with experimental data. However, it is not uncommon, even for those analyses that use state of the art methods and tools to suffer from insufficient statistics when it comes to the simulated datasets used to estimate systematic uncertainties. This practically limits the power, and sometimes the robustness of the analysis. In this paper, we present SysCalc, a code which is able to derive weights for various important theoretical systematic uncertainties, including those related to the choice of the Parton Distribution Function sets and the various scale choices. SysCalc utilizes the central sample generated events to estimate the related systematic uncertainties, thus, omitting the need for generating dedicated systematics datasets, and with only a minimal added cost in terms of computing resources. In this paper we discuss the working principles of the code accompanied by various validation plots. We also discuss the structure of the code followed by a practical guide for how to use the tool.

Background/objectivesRenewed dietary recommendations for carbohydrates have recently been published by various international health authorities. The present work (1) reviews the methods and processes (systematic approach/review, inclusion of public consultation) used to identify, select and grade the evidence underpinning the recommendations, particularly for total carbohydrate (CHO), fibre and sugar consumption, and (2) examines the extent to which variation in the methods and processes applied relates to any differences in the final recommendations.Subjects/methodsA search of WHO, US, Canada, Australia and European sources identified 19 documents from 13 authorities with the desired detailed information. Processes and methods applied to derive recommendations were compiled and compared.Results(1) A relatively high total CHO and fibre intake and limited intake of (added or free) sugars are generally recommended. (2) Even where recommendations are similar, the specific justifications for quantitative/qualitative recommendations differ across authorities. (3) Differences in recommendations mainly arise from differences in the underlying definitions of CHO exposure and classification

Rare earth elements (REE) used to be taken as tracers of geological origin for fluvial transport. Nowadays their increased applications in innovative environmental-friendly technology (e.g. in catalysts, superconductors, lasers, batteries) and medical applications (e.g. MRI contrast agent) lead to man-made, elevated levels in the environment. So far, no regulatory thresholds for REE concentrations and emissions to the environment have been set because information on risks from REE is scarce. However, evidence gathers that REE have to be acknowledged as new, emerging contaminants with manifold ways of entry into the environment, e.g. through waste water from hospitals or through industrial effluents. This paper reviews existing information on bioaccumulation and ecotoxicity of lanthanum in the aquatic environment. Lanthanum is of specific interest as one of the major lanthanides in industrial effluents. This review focuses on the freshwater and the marine environment, and tackles the water column and sediments. From these data, methods to derive quality criteria for sediment and water are discussed and preliminary suggestions are made.

A major goal of regenerative medicine is to instruct formation of multipotent, tissue-specific stem cells from induced pluripotent stem cells (iPSCs) for cell replacement therapies. Generation of haematopoietic stem cells (HSCs) from iPSCs or embryonic stem cells (ESCs) is not currently possible, however, necessitating a better understanding of how HSCs normally arise during embryonic development. We previously showed that haematopoiesis occurs through four distinct waves during zebrafish development, with HSCs arising in the final wave in close association with the dorsal aorta. Recent reports have suggested that murine HSCs derive from haemogenic endothelial cells (ECs) lining the aortic floor. Additional in vitro studies have similarly indicated that the haematopoietic progeny of ESCs arise through intermediates with endothelial potential. Here we have used the unique strengths of the zebrafish embryo to image directly the generation of HSCs from the ventral wall of the dorsal aorta. Using combinations of fluorescent reporter transgenes, confocal time-lapse microscopy and flow cytometry, we have identified and isolated the stepwise intermediates as aortic haemogenic endothelium

When using microwave remote sensing for land use/land cover (LULC) classifications, there are a wide variety of imaging parameters to choose from, such as wavelength, imaging mode, incidence angle, spatial resolution, and coverage. There is still a need for further study of the combination, comparison, and quantification of the potential of multiple diverse radar images for LULC classifications. Our study site, the Qixing farm in Heilongjiang province, China, is especially suitable to demonstrate this. As in most rice growing regions, there is a high cloud cover during the growing season, making LULC from optical images unreliable. From the study year 2009, we obtained nine TerraSAR-X, two Radarsat-2, one Envisat-ASAR, and an optical FORMOSAT-2 image, which is mainly used for comparison, but also for a combination. To evaluate the potential of the input images and derive LULC with the highest possible precision, two classifiers were used: the well-established Maximum Likelihood classifier, which was optimized to find those input bands, yielding the highest precision, and the random forest classifier. The resulting highly accurate LULC-maps for the whole farm with a spatial resoluti

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