3D Scatter Research Articles

Analyzing Histone Modifications Using Tiled Binned Clustering and 3D Scatter Plots

A major goal in epigenetics is understanding how cells differentiate into different cell types. Besides the increase of individual data sets, the amount of replicated experiments generating a tremendous amount of data is ever increasing. While biologists primarily analyze their data on the highest level using statistical correlations or on the lowest level analyzing nucleotide sequences, determining the fate of histone modifications during cell specification necessitates improved analysis capabilities on one or more intermediate levels. For this type of analysis, it proved to be very useful to use tiled binned scatter plot matrices showing binary relationships or to use tiled binned 3D scatter plots showing ternary relationships. Quarternary or general n-ary relationships are not easily analyzable using visualization techniques like scatter plots, only. Therefore, we augmented existing clustering methods with the tiling and binning idea enabling the analysis of n-ary relationships. Analyzing the changes of histone modifications comparing two cell lines using tiled binned clustering, we found new, unknown relations in the data.

Image-based quantitative analysis of tear film lipid layer thickness for meibomian gland evaluation

BackgroundDry eye syndrome is one of the most common ocular diseases, and meibomian gland dysfunction (MGD) is the leading cause of evaporative dry eye syndrome. When the tear film lipid layer becomes thin due to obstructive or hyposecretory meibomian gland dysfunction, the excessive evaporation of the aqueous layer can occur, and this causes evaporative dry eye syndrome. Thus, measuring the lipid layer thickness (LLT) is essential for accurate diagnosis and proper treatment of evaporative dry eye syndrome.MethodsWe used a white LED panel with a slit lamp microscope to obtain videos of the lipid layer interference patterns on the cornea. To quantitatively analyze the LLT from interference colors, we developed a novel algorithm that can automatically perform the following processes on an image frame: determining the radius of the iris, locating the center of the pupil, defining region of interest (ROI), tracking the ROI, compensating for the color of iris and illumination, and producing comprehensive analysis output. A group of dry eye syndrome patients with hyposecretory MGD, dry eye syndrome without MGD, hypersecretory MGD, and healthy volunteers were recruited. Their LLTs were analyzed and statistical information—mean and standard deviation, the relative frequency of LLT at each time point, and graphical LLT visualization—were produced.ResultsUsing our algorithm, we processed the lipid layer interference pattern and automatically analyzed the LLT distribution of images from patients. The LLT of hyposecretory MGD was thinner (45.2 ± 11.6 nm) than that of dry eye syndrome without MGD (69.0 ± 9.4 nm) and healthy volunteers (68.3 ± 13.7 nm) while the LLT of hypersecretory MGD was thicker (93.5 ± 12.6 nm) than that of dry eye syndrome without MGD. Patients’ LLTs were statistically analyzed over time, visualized with 3D surface plots, and displayed using 3D scatter plots of image pixel data for comprehensive assessment.ConclusionsWe developed an image-based algorithm for quantitative measurement as well as statistical analysis of the LLT despite fluctuation and eye movement. This pilot study demonstrates that the quantitative LLT analysis of patients is consistent with the functions of meibomian glands clinically evaluated by an ophthalmologist. This approach is a significant step forward in developing a fully automated instrument for evaluating dry eye syndrome and for providing proper guidance of treatment.

Gaia Data Release 1

Context: The first Gaia data release (DR1) delivered a catalogue of astrometry and photometry for over a billion astronomical sources. Within the panoply of methods used for data exploration, visualisation is often the starting point and even the guiding reference for scientific thought. However, this is a volume of data that cannot be efficiently explored using traditional tools, techniques, and habits. Aims: We aim to provide a global visual exploration service for the Gaia archive, something that is not possible out of the box for most people. The service has two main goals. The first is to provide a software platform for interactive visual exploration of the archive contents, using common personal computers and mobile devices available to most users. The second aim is to produce intelligible and appealing visual representations of the enormous information content of the archive. Methods: The interactive exploration service follows a client-server design. The server runs close to the data, at the archive, and is responsible for hiding as far as possible the complexity and volume of the Gaia data from the client. This is achieved by serving visual detail on demand. Levels of detail are pre-computed using data aggregation and subsampling techniques. For DR1, the client is a web application that provides an interactive multi-panel visualisation workspace as well as a graphical user interface. Results: The Gaia archive Visualisation Service offers a web-based multi-panel interactive visualisation desktop in a browser tab. It currently provides highly configurable 1D histograms and 2D scatter plots of Gaia DR1 and the Tycho-Gaia Astrometric Solution (TGAS) with linked views. An innovative feature is the creation of ADQL queries from visually defined regions in plots. [abridged]

Shape recognition of acoustic scatterers using the singularity expansion method

Acoustic target recognition for two-dimensional (2D) acoustic scatterers is investigated using the singularity expansion method (SEM). Based on the Watson transformation series of the scattering field, the SEM poles can be calculated and their physical interpretation given, along with the exact normal mode for any acoustic scattering problem. Typical oscillatory phenomena appear as a series of damped sinusoidal signals in the time domain and as a standing-wave distribution in the space. These external oscillation modes are associated with the SEM poles. We note that the positions of these poles in the complex frequency plane are uniquely determined by the shape and flexible characteristics of the target regardless of the waveforms and positions of the incident signals. We then infer that SEM poles can be used as the characteristic parameters for target shape recognition. The relationship between the positions of SEM poles and the geometrical characters of 2D scatterers has been established not only for cylinders but also for other general 2D scatterers. The new method and the related calculation results provide an effective way to perform shape recognition using an acoustic scattering field, with potential applications in non-destructive testing and acoustic imaging.

The 5th International Conference on Science & Engineering in Mathematics, Chemistry and Physics 2017 (ScieTech 2017), The Ramada Bintang Hotel, Kuta, Bali, Indonesia 21 - 22 January 2017

The 5th International Conference on Science & Engineering in Mathematics, Chemistry and Physics 2017 (ScieTech 2017), The Ramada Bintang Hotel, Kuta, Bali, Indonesia 21 - 22 January 2017

Detection of diluted contaminants on chicken carcasses using a two-dimensional scatter plot based on a two-dimensional hyperspectral correlation spectrum

A two-dimensional (2D) scatter plot method based on the 2D hyperspectral correlation spectrum is proposed to detect diluted blood, bile, and feces from the cecum and duodenum on chicken carcasses. First, from the collected hyperspectral data, a set of uncontaminated regions of interest (ROIs) and four sets of contaminated ROIs were selected, whose average spectra were treated as the original spectrum and influenced spectra, respectively. Then, the difference spectra were obtained and used to conduct correlation analysis, from which the 2D hyperspectral correlation spectrum was constructed using the analogy method of 2D IR correlation spectroscopy. Two maximum auto-peaks and a pair of cross peaks appeared at 656 and 474 nm. Therefore, 656 and 474 nm were selected as the characteristic bands because they were most sensitive to the spectral change induced by the contaminants. The 2D scatter plots of the contaminants, clean skin, and background in the 474- and 656-nm space were used to distinguish the contaminants from the clean skin and background. The threshold values of the 474- and 656-nm bands were determined by receiver operating characteristic (ROC) analysis. According to the ROC results, a pixel whose relative reflectance at 656 nm was greater than 0.5 and relative reflectance at 474 nm was lower than 0.3 was judged as a contaminated pixel. A region with more than 50 pixels identified was marked in the detection graph. This detection method achieved a recognition rate of up to 95.03% at the region level and 31.84% at the pixel level. The false-positive rate was only 0.82% at the pixel level. The results of this study confirm that the 2D scatter plot method based on the 2D hyperspectral correlation spectrum is an effective method for detecting diluted contaminants on chicken carcasses.

Improved Algorithm of SCS-CN Model Parameters in Typical Inland River Basin in Central Asia

Rainfall-runoff relationship is the most important factor for hydrological structures, social and economic development on the background of global warmer, especially in arid regions. The aim of this paper is find the suitable method to simulate the runoff in arid area. The Soil Conservation Service Curve Number (SCS-CN) is the most popular and widely applied model for direct runoff estimation. In this paper, we will focus on Wen-quan Basin in source regions of Boertala River. It is a typical valley of inland in Central Asia. First time to use the 16m resolution remote sensing image about high-definition earth observation satellite “Gaofen-1” to provide a high degree accuracy data for land use classification determine the curve number. Use surface temperature/vegetation index (TS/VI) construct 2D scatter plot combine with the soil moisture absorption balance principle calculate the moisture-holding capacity of soil. Using original and parameter algorithm improved SCS-CN model respectively to simulation the runoff. The simulation results show that the improved model is better than original model. Both of them in calibration and validation periods Nash-Sutcliffe efficiency were 0.79, 0.71 and 0.66,038. And relative error were3%, 12% and 17%, 27%. It shows that the simulation accuracy should be further improved and using remote sensing information technology to improve the basic geographic data for the hydrological model has the following advantages: 1) Remote sensing data having a planar characteristic, comprehensive and representative. 2) To get around the bottleneck about lack of data, provide reference to simulation the runoff in similar basin conditions and data-lacking regions.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy**Dedicated to Professor Kankan Bhattacharyya.

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels.

Use of promoter-anchored rapd analysis for divergence assessment in soybean as against conventionally used ISSR assay

The present study was aimed to compare the genetic diversity among 24 soybean genotypes as revealed by Promoter-anchored amplified polymorphism based on RAPD (PAAP-RAPD) primer-combinations analysis and Inter Simple Sequence Repeat (ISSR) analysis. All the 16 PAAP-RAPD primer-combinations, derived from 4 Promoter-based primers (TA1/G1/CA1/GC1) and 4 RAPD primers (OPE 1/5/7/9) showed amplification, of which 8 were polymorphic. They produced 63 loci, of which 52 were polymorphic. All 20 ISSR primers used were polymorphic generating 115 alleles of which 95 were polymorphic. The similarity coefficient based on ISSR and PAAP-RAPD analysis ranged from 0.67 to 0.93 and 0.41 to 1.00, respectively. The PAAP-RAPD consensus tree revealed 17 clusters; while ISSR revealed all genotypes as separate clusters. In 2D scatter plot, these were broadly classified into 5 major groups. Group-Ia had lowest divergence (MAUS71, KDS 344, KDS387, NRC94, KDS722, Bragg and KDS743) while Group-Ib had low divergence (Birsa Soya1, KDS749, KDS726, KDS739 and JS335). Moderate divergence was observed in Group II (JS9305 and RKS 18) and Group III (Himso 1684, Dsb22 and MACS450). Group IV (KDS741, VLS65, Rpp3 PI462312 variant, EC241778 and PI462312) had highest divergence. Only two genotypes (KDS753 and DS228) were placed separately in both the analyses. The study revealed that PAAP-RAPD has an advantage that it may specifically target regulatory regions of various candidate genes during molecular tagging for a specific trait.

Stray light in cone beam optical computed tomography: II. Reduction using a convergent light source

Optical cone beam computed tomography (CBCT) using a broad beam and CCD camera is a fast method for densitometry of 3D optical gel dosimeters. However, diffuse light sources introduce considerable stray light into the imaging system, leading to underestimation of attenuation coefficients and non-uniformities in CT images unless corrections are applied to each projection image. In this study, the light source of a commercial optical CT scanner is replaced with a convergent cone beam source consisting of almost exclusively image forming primary rays. The convergent source is achieved using a small isotropic source and a Fresnel lens. To characterize stray light effects, full-field cone beam CT imaging is compared to fan beam CT (FBCT) using a 1 cm high fan beam aperture centered on the optic axis of the system. Attenuating liquids are scanned within a large 96 mm diameter uniform phantom and in a small 13.5 mm diameter finger phantom. For the uniform phantom, cone and fan beam CT attenuation coefficients agree within a maximum deviation of (1 ± 2)% between mean values over a wide range from 0.036 to 0.43 cm−1. For the finger phantom, agreement is found with a maximum deviation of (4 ± 2)% between mean values over a range of 0.1–0.47 cm−1. With the convergent source, artifacts associated with refractive index mismatch and vessel optical features are more pronounced. Further optimization of the source size to achieve a balance between quantitative accuracy and artifact reduction should enable practical, accurate 3D dosimetry, avoiding time consuming 3D scatter measurements.

Lunar textural analysis based on WAC-derived kilometer-scale roughness and entropy maps

In general, textures are thought to be some complicated repeated patterns formed by elements, or primitives which are sorted in certain rules. Lunar surfaces record the interactions between its outside environment and itself, thus, based on high-resolution DEM model or image data, there are some topographic features which have different roughness and entropy values or signatures on lunar surfaces. Textures of lunar surfaces can help us to concentrate on typical topographic and photometric variations and reveal the relationships between obvious features (craters, impact basins, sinuous rilles (SRs) and ridges) with resurfacing processes on the Moon. In this paper, the term surface roughness is an expression of the variability of a topographic or photometric surface at kilometer scale, and the term entropy can characterize the variability inherent in a geological and topographic unit and evaluate the uncertainty of predictions made by a given geological process. We use the statistical moments of gray-level histograms in different-sized neighborhoods (e.g., 3, 5, 10, 20, 40 and 80 pixels) to compute the kilometer-scale roughness and entropy values, using the mosaic image from 70°N to 70°S obtained by Lunar Reconnaissance Orbiter (LRO) Wide Angle Camera (WAC). Large roughness and entropy signatures were only found in the larger scale maps, while the smallest 3-pixel scale map had more disorderly and unsystematic textures. According to the entropy values in 10-pixel scale entropy map, we made a frequency curve and categorized lunar surfaces into three types, shadow effects, maria and highlands. A 2D scatter plot of entropy versus roughness values was produced and we found that there were two point clusters corresponding to the highlands and maria, respectively. In the last, we compared the topographic and photometric signatures derived from Lunar Orbiter Laser Altimeter (LOLA) data and WAC mosaic image. On the lunar surfaces, the ridges have obvious multilevel topographic textures which are sensitive to the topographic changes, while the ejecta deposits of fresh craters appear obvious photometric textures which are sensitive to the brightness variations.

Impact of New Scatter Correction Strategies on High-Resolution Research Tomograph Brain PET Studies.

PurposeThe aim of this study is to evaluate the impact of different scatter correction strategies on quantification of high-resolution research tomograph (HRRT) data for three tracers covering a wide range in kinetic profiles.ProceduresHealthy subjects received dynamic HRRT scans using either (R)-[11C]verapamil (n = 5), [11C]raclopride (n = 5) or [11C]flumazenil (n = 5). To reduce the effects of patient motion on scatter scaling factors, a margin in the attenuation correction factor (ACF) sinogram was applied prior to 2D or 3D single scatter simulation (SSS).ResultsSome (R)-[11C]verapamil studies showed prominent artefacts that disappeared with an ACF-margin of 10 mm or more. Use of 3D SSS for (R)-[11C]verapamil showed a statistically significant increase in volume of distribution compared with 2D SSS (p < 0.05), but not for [11C]raclopride and [11C]flumazenil studies (p > 0.05).ConclusionsWhen there is a patient motion-induced mismatch between transmission and emission scans, applying an ACF-margin resulted in more reliable scatter scaling factors but did not change (and/or deteriorate) quantification.

Integrated approach of using ASTER-derived emissivity and pixel temperature for delineating different granitoids – a case study in parts of Dharwar Craton, India

We have delineated different granitoids based on variation in emissivity and relative surface temperature recorded in thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor of EO-1 satellite. In this regard, we have used emissivity normalization algorithm to derive broadband emissivity from thermal bands of ASTER sensor to delineate different lithounits of the granitoid family. We have compared emissivity and radiance image composites in terms of delineation of different granitoids. We have also used false colour composite (FCC) image derived using two emissivity bands and temperature (derived using emissivity normalisation method) bands to delineate different granitoids. We could differentiate different granitoids in the three-dimensional (3D) data space of ASTER-derived emissivity bands (second and third bands) and temperature bands. Based on the analysis of 3D scatter plot, we also proposed a ternary diagram of emissivity and temperature, which can be used to delineate different granitoids.

&lt;i&gt;In Situ&lt;/i&gt; Testing and Heterogeneity of UFG Cu at Elevated Temperatures

Experiments were conducted to investigate deformation-induced processes during in-situ tensile test at elevated temperature. Consequently the microstructure after creep loading was examined by 3D Electron Back Scatter Diffraction (EBSD) technique. The billets of coarse-grained copper were processed by equal-channel angular pressing (ECAP) at room temperature using a die that had an internal angle of 90° between the two parts of the channel and an outer arc of curvature of ~ 20°, where these two parts intersect. The pressing speed was 10 mm/min. To obtain an ultrafine-grained (UFG) material, the billets were subsequently pressed by route Bc by 8 ECAP passes to give the mean grain size ~ 0.7 μm. The constant strain-rate test in tension was performed at 473 K using testing GATAN stage Microtest 2000EW with EH 2000 heated grips which is configured for in-situ electron back scatter diffraction (EBSD) observations. Microstructure was examined by FEG-SEM TESCAN MIRA 3 XM equipped by EBSD detector HKL NordlysMax from OXFORD INSTRUMENT. The tensile test was interrupted by fast stress reductions after different deformation step and observation of microstructure changes was performed. Despite of a considerable interest in ECAP processing method, there are not many works documenting microstructure evolution and changes during creep testing and determining creep mechanisms of ultrafine-grained materials processed by ECAP. It was found that creep resistance of UFG pure Al and Cu is considerably improved after one ECAP pass in comparison with coarse grained material, however, further repetitive pressing leads to a noticeable deterioration in creep properties of ECAP material. Recently it was observed the coarsening of the grains in microstructure of ECAP copper during creep at elevated temperature. It was suggested that creep behaviour is controlled by storage and dynamic recovery of dislocations at high-angle boundaries. In the present work was found that ultrafine-grained microstructure is instable and significant grain growth has already occurred during heating to the testing temperature. Static recrystallization during heating led to the formation of high fraction of special boundaries Σ3 and Σ9. The tensile deformation at 473 K led to the additional grain growth and formation of new grains. Microstructure was investigated also by 3D EBSD.

Efficient evaluation of object-centric exploration queries for visualization

The most effective way to explore data is through visualizing the results of exploration queries. For example, an exploration query could be an aggregate of some measures over time intervals, and a pattern or abnormality can be discovered through a time series plot of the query results. In this paper, we examine a special kind of exploration query, namely object-centric exploration query. Common examples include claims made about athletes in sports databases, such as "it is newsworthy that LeBron James has scored 35 or more points in nine consecutive games." We focus on one common type of visualization, i.e., 2d scatter plot with heatmap. Namely, we consider exploration queries whose results can be plotted on a two-dimensional space, possibly with colors indicating object densities in regions. While we model results as pairs of numbers, the types of the queries are limited only by the users' imagination. In the LeBron James example above, the two dimensions are minimum points scored per game and number of consecutive games, respectively. It is easy to find other equally interesting dimensions, such as minimum rebounds per game or number of playoff games. We formalize this problem and propose an efficient, interactive-speed algorithm that takes a user-provided exploration query (which can be a blackbox function) and produces an approximate visualization that preserves the two most important visual properties: the outliers and the overall distribution of all result points.

Texture descriptions of lunar surface derived from LOLA data: Kilometer-scale roughness and entropy maps

The lunar global texture maps of roughness and entropy are derived at kilometer scales from Digital Elevation Models (DEMs) data obtained by Lunar Orbiter Laser Altimeter (LOLA) aboard on Lunar Reconnaissance Orbiter (LRO) spacecraft. We use statistical moments of a gray-level histogram of elevations in a neighborhood to compute the roughness and entropy value. Our texture descriptors measurements are shown in global maps at multi-sized square neighborhoods, whose length of side is 3, 5, 10, 20, 40 and 80 pixels, respectively. We found that large-scale topographical changes can only be displayed in maps with longer side of neighborhood, but the small scale global texture maps are more disorderly and unsystematic because of more complicated textures' details. Then, the frequency curves of texture maps are made out, whose shapes and distributions are changing as the spatial scales increases. Entropy frequency curve with minimum 3-pixel scale has large fluctuations and six peaks. According to this entropy curve we can classify lunar surface into maria, highlands, different parts of craters preliminarily. The most obvious textures in the middle-scale roughness and entropy maps are the two typical morphological units, smooth maria and rough highlands. For the impact crater, its roughness and entropy value are characterized by a multiple-ring structure obviously, and its different parts have different texture results. In the last, we made a 2D scatter plot between the two texture results of typical lunar maria and highlands. There are two clusters with largest dot density which are corresponded to the lunar highlands and maria separately. In the lunar mare regions (cluster A), there is a high correlation between roughness and entropy, but in the highlands (Cluster B), the entropy shows little change. This could be subjected to different geological processes of maria and highlands forming different landforms.

Three-dimensional positions of scattering centers reconstruction from multiple SAR images based on radargrammetry

A method and procedure is presented to reconstruct three-dimensional (3D) positions of scattering centers from multiple synthetic aperture radar (SAR) images. Firstly, two-dimensional (2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers’ location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.

Snow Growth and Transport Patterns in Orographic Storms as Estimated from Airborne Vertical-Plane Dual-Doppler Radar Data

Abstract Airborne vertical-plane dual-Doppler cloud radar data, collected on wind-parallel flight legs over a mountain in Wyoming during 16 winter storms, are used to analyze the growth, transport, and sedimentation of snow. In all storms the wind is rather strong, such that the flow is unblocked. The sampled clouds are mixed phase, shallow, and generally produce snowfall over the mountain only. The 2D scatterers’ mean motion in the vertical along-track plane below flight level is synthesized using one radar antenna pointing to nadir, and one 30° forward of nadir. This yields instantaneous cross-mountain hydrometeor streamlines. The dynamics of the orographic flow dominate the precipitation patterns across the mountain. Three patterns are distinguished: the first two contain small convective cells, either boundary layer (BL) convection or elevated convection, the latter likely due to the release of potential instability in orographically lifted air. In these patterns the cross-mountain flow is relatively undisturbed. Precipitation from BL convection falls mostly on the windward side but precipitation from elevated convection may fall mostly in the lee. The third pattern is marked by more stratified flow, often with vertically propagating mountain waves, and with strong, plunging flow in the lee, resulting in rapid clearing of the storm across the crest and occasionally a hydraulic jump. In this case, most snow tends to fall upwind of the crest, although a shallow, sublimating snow “foot” is often seen over the leeward slopes.

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor.

Compressive Sensing Imaging of Non-Sparse 2D Scatterers by a Total-Variation Approach Within the Born Approximation

The problem of imaging two-dimensional “non-sparse” scatterers with piecewise-constant contrast is solved through an innovative total-variation compressive sensing (TV-CS) technique. Under Born approximation (BA), the time-harmonic two-dimensional inverse scattering problem is reformulated into an equivalent Augmented Lagrangian one according to the TV-CS formulation. The resulting unconstrained functional is then minimized by means of a deterministic alternating direction algorithm. Selected results from a numerical assessment are discussed to give the interested reader some insights on the accuracy, the flexibility, the robustness, and the efficiency of the TV-CS inversion scheme also in comparison with available implementations of state-of-the-art inversion methods still formulated within the BA.