Role of Left-Hand Cut Contributions on Pole Extractions from Lattice Data: Case Study for T_{cc}(3875)

We discuss recent lattice data for the T_{cc}(3875)^{+} state to stress, for the first time, a potentially strong impact of left-hand cuts from the one-pion exchange on the pole extraction for near-threshold exotic states. In particular, if the left-hand cut is located close to the two-particle threshold, which happens naturally in the DD^{*} system for the pion mass exceeding its physical value, the effective-range expansion is valid only in a very limited energy range up to the cut and as such is of little use to reliably extract the poles. Then, an accurate extraction of the pole locations requires the one-pion exchange to be implemented explicitly into the scattering amplitudes. Our findings are general and potentially relevant for a wide class of hadronic near-threshold states.

Eight-Channel Multispectral Image Database for Saliency Prediction.

Saliency prediction is a very important and challenging task within the computer vision community. Many models exist that try to predict the salient regions on a scene from its RGB image values. Several new models are developed, and spectral imaging techniques may potentially overcome the limitations found when using RGB images. However, the experimental study of such models based on spectral images is difficult because of the lack of available data to work with. This article presents the first eight-channel multispectral image database of outdoor urban scenes together with their gaze data recorded using an eyetracker over several observers performing different visualization tasks. Besides, the information from this database is used to study whether the complexity of the images has an impact on the saliency maps retrieved from the observers. Results show that more complex images do not correlate with higher differences in the saliency maps obtained.

A Semantic and Knowledge-Based Approach for Handover Management.

Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM.

Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range.

Images captured under bad weather conditions (e.g., fog, haze, mist, dust, etc.), suffer from poor contrast and visibility, and color distortions. The severity of this degradation depends on the distance, the density of the atmospheric particles and the wavelength. We analyzed eight single image dehazing algorithms representative of different strategies and originally developed for RGB images, over a database of hazy spectral images in the visible range. We carried out a brute force search to find the optimum three wavelengths according to a new combined image quality metric. The optimal triplet of monochromatic bands depends on the dehazing algorithm used and, in most cases, the different bands are quite close to each other. According to our proposed combined metric, the best method is the artificial multiple exposure image fusion (AMEF). If all wavelengths within the range 450-720 nm are used to build a sRGB renderization of the imagaes, the two best-performing methods are AMEF and the contrast limited adaptive histogram equalization (CLAHE), with very similar quality of the dehazed images. Our results show that the performance of the algorithms critically depends on the signal balance and the information present in the three channels of the input image. The capture time can be considerably shortened, and the capture device simplified by using a triplet of bands instead of the full wavelength range for dehazing purposes, although the selection of the bands must be performed specifically for a given algorithm.

Single Image Dehazing Algorithm Analysis with Hyperspectral Images in the Visible Range.

In foggy or hazy conditions, images are degraded due to the scattering and attenuation of atmospheric particles, reducing the contrast and visibility and changing the color. This degradation depends on the distance, the density of the atmospheric particles and the wavelength. We have tested and applied five single image dehazing algorithms, originally developed to work on RGB images and not requiring user interaction and/or prior knowledge about the images, on a spectral hazy image database in the visible range. We have made the evaluation using two strategies: the first is based on the analysis of eleven state-of-the-art metrics and the second is two psychophysical experiments with 126 subjects. Our results suggest that the higher the wavelength within the visible range is, the higher the quality of the dehazed images. The quality increases for low haze/fog levels. The choice of the best performing algorithm depends on the criterion prioritized by the metric design strategy. The psychophysical experiment results show that the level of agreement between observers and metrics depends on the criterion set for the observers' task.

Multifocus HDR VIS/NIR hyperspectral imaging and its application to works of art.

This paper presents a complete framework for capturing and processing hyperspectral reflectance images of artworks in situ, using a hyperspectral line scanner. These capturing systems are commonly used in laboratory conditions synchronized with scanning stages specifically designed for planar surfaces. However, when the intended application domain does not allow for image capture in these controlled conditions, achieving useful spectral reflectance image data can be a very challenging task (due to uncontrolled illumination, high-dynamic range (HDR) conditions in the scene, and the influence of chromatic aberration on the image quality, among other factors). We show, for the first time, all the necessary steps in the image capturing and post-processing in order to obtain high-quality HDR-based reflectance in the visible and near infrared, directly from the data captured by using a hyperspectral line scanner coupled to a rotating tripod. Our results show that the proposed method outperforms the normal capturing process in terms of dynamic range, color and spectral accuracy. To demonstrate the potential interest of this processing strategy for on-site analysis of artworks, we applied it to the study of a vintage copy of the famous painting "Transfiguration" by Raphael, as well as a facsimile of "The Golden Haggadah" from the British Library of London. The second piece has been studied for the identification of highly reflective gold-foil covered areas.

How daylight influences high-order chromatic descriptors in natural images.

Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and the reduction of the number of discernible colors when salient regions are considered.

Colorimetric analysis of outdoor illumination across varieties of atmospheric conditions.

Solar illumination at ground level is subject to a good deal of change in spectral and colorimetric properties. With an aim of understanding the influence of atmospheric components and phases of daylight on colorimetric specifications of downward radiation, more than 5,600,000 spectral irradiance functions of daylight, sunlight, and skylight were simulated by the radiative transfer code, SBDART [Bull. Am. Meteorol. Soc.79, 2101 (1998)], under the atmospheric conditions of clear sky without aerosol particles, clear sky with aerosol particles, and overcast sky. The interquartile range of the correlated color temperatures (CCT) for daylight indicated values from 5712 to 7757 K among the three atmospheric conditions. A minimum CCT of ∼3600 K was found for daylight when aerosol particles are present in the atmosphere. Our analysis indicated that hemispheric daylight with CCT less than 3600 K may be observed in rare conditions in which the level of aerosol is high in the atmosphere. In an atmosphere with aerosol particles, we also found that the chromaticity of daylight may shift along the green-purple direction of the Planckian locus, with a magnitude depending on the spectral extinction by aerosol particles and the amount of water vapor in the atmosphere. The data analysis showed that an extremely high value of CCT, in an atmosphere without aerosol particles, for daylight and skylight at low sun, is mainly due to the effect of Chappuis absorption band of ozone at ∼600 nm. In this paper, we compare our data with well-known observations from previous research, including the ones used by the CIE to define natural daylight illuminants.

Generation of a novel monoclonal antibody that recognizes the alpha (α)-amidated isoform of a valine residue.

BACKGROUND: Alpha (α)-amidation of peptides is a mechanism required for the conversion of prohormones into functional peptide sequences that display biological activities, receptor recognition and signal transduction on target cells. Alpha (α)-amidation occurs in almost all species and amino acids identified in nature. C-terminal valine amide neuropeptides constitute the smallest group of functional peptide compounds identified in neurosecretory structures in vertebrate and invertebrate species. METHODS: The α-amidated isoform of valine residue (Val-CONH2) was conjugated to KLH-protein carrier and used to immunize mice. Hyperimmune animals displaying high titers of valine amide antisera were used to generate stable hybridoma-secreting mAbs. Three productive hybridoma (P15A4, P17C11, and P18C5) were tested against peptides antigens containing both the C-terminal α-amidated (-CONH2) and free α-carboxylic acid (-COO(-)) isovariant of the valine residue. RESULTS: P18C5 mAb displayed the highest specificity and selectivity against C-terminal valine amidated peptide antigens in different immunoassays. P18C5 mAb-immunoreactivity exhibited a wide distribution along the neuroaxis of the rat brain, particularly in brain areas that did not cross-match with the neuronal distribution of known valine amide neuropeptides (α-MSH, adrenorphin, secretin, UCN1-2). These brain regions varied in the relative amount of putative novel valine amide peptide immunoreactive material (nmol/µg protein) estimated through a fmol-sensitive solid-phase radioimmunoassay (RIA) raised for P18C5 mAb. CONCLUSIONS: Our results demonstrate the versatility of a single mAb able to differentiate between two structural subdomains of a single amino acid. This mAb offers a wide spectrum of potential applications in research and medicine, whose uses may extend from a biological reagent (used to detect valine amidated peptide substances in fluids and tissues) to a detoxifying reagent (used to neutralize exogenous toxic amide peptide compounds) or as a specific immunoreagent in immunotherapy settings (used to reduce tumor growth and tumorigenesis) among many others.

Recovering of weather degraded images based on RGB response ratio constancy.

Images captured under bad weather conditions suffer from poor contrast and visibility. These effects are noticeable for haze, mist, fog, or dust storms. We have proposed a recovering method for images captured for several adverse weather conditions based on the RGB response ratio constancy under illuminant changes. This algorithm improves the visibility, contrast, and color in degraded images with low computational times. We obtain results similar to those from previously published deweathering methods but with no prior information about the image content or atmospheric parameters needed.

Nonrigid registration with free-form deformation model of multilevel uniform cubic B-splines: application to image registration and distortion correction of spectral image cubes.

In spectral imaging, spatial and spectral information of an image scene are combined. There exist several technologies that allow the acquisition of this kind of data. Depending on the optical components used in the spectral imaging systems, misalignment between image channels can occur. Further, the projection of some systems deviates from that of a perfect optical lens system enough that a distortion of scene content in the images becomes apparent to the observer. Correcting distortion and misalignment can be complicated for spectral image data if they are different at each image channel. In this work, we propose an image registration and distortion correction scheme for spectral image cubes that is based on a free-form deformation model of uniform cubic B-splines with multilevel grid refinement. This scheme is adaptive with respect to image size, degree of misalignment, and degree of distortion, and in that sense is superior to previous approaches. We support our proposed scheme with empirical data from a Bragg-grating-based hyperspectral imager, for which a registration accuracy of approximately one pixel was achieved.

Understanding the effect of correlated colour temperatures on spatio-chromatic properties of natural images.

Despite the natural occurrence of global and local daylight changes in natural scenes, the human visual system typically adapts well to these changes and develops stable colour perception. In a previous study, the influence of daylight characterized by its Correlated Colour Temperatures (CCT) on different chromatic descriptors was analysed (Ojeda et al., 2017). The results showed that chromatic information is almost constant for CCT values above 14,000 K, with local extremes occurring in the range of low CCTs. The aim of this work is to extend the analysis of the CCT dependence of the illuminant to those that consider the spatio-chromatic structure, including second order descriptors (gradients, spectral slope, spectral signature, and PCA) and higher order descriptors (kurtosis, skewness, and number of relevant colours). Our results show that most of the descriptors exhibit horizontal asymptotic behaviour for CCTs above 15,000 K and local extremes in the range of 3,900 K-9,600 K. For those descriptors that could be analysed in CIELAB space, sufficient statistical evidence was obtained to consider skewness, kurtosis, and the independent spectral slopes of the L* channel as equal in the range of CCTs used. However, the slight variations in spectral signatures and the directions of the principal components when applying PCA to image patches are not statistically significant and cannot be considered equal under different illuminants. The number of relevant colours (NRC) exhibits sensitivity to temperature variations and behaves similarly to the other descriptors, due to its small number.

Efficient quantization of painting images by relevant colors.

Realistic images often contain complex variations in color, which can make economical descriptions difficult. Yet human observers can readily reduce the number of colors in paintings to a small proportion they judge as relevant. These relevant colors provide a way to simplify images by effectively quantizing them. The aim here was to estimate the information captured by this process and to compare it with algorithmic estimates of the maximum information possible by colorimetric and general optimization methods. The images tested were of 20 conventionally representational paintings. Information was quantified by Shannon's mutual information. It was found that the estimated mutual information in observers' choices reached about 90% of the algorithmic maxima. For comparison, JPEG compression delivered somewhat less. Observers seem to be efficient at effectively quantizing colored images, an ability that may have applications in the real world.

Understanding the 0++ and 2++ charmonium(-like) states near 3.9 GeV.

We propose that the X(3915) observed in the J/ψω channel is the same state as the χc2(3930), and the X(3960), observed in the Ds+Ds- channel, is an S-wave Ds+Ds- hadronic molecule. In addition, the JPC=0++ component in the B+→D+D-K+ assigned to the X(3915) in the current Review of Particle Physics has the same origin as the X(3960), which has a mass around 3.94 GeV. To check the proposal, the available data in the DD¯ and Ds+Ds- channels from both B decays and γγ fusion reaction are analyzed considering both the DD¯-DsD¯s-D*D¯*-Ds*D¯s* coupled channels with 0++ and a 2++ state introduced additionally. It is found that all the data in different processes can be simultaneously well reproduced, and the coupled-channel dynamics produce four hidden-charm scalar molecular states with masses around 3.73, 3.94, 3.99 and 4.23 GeV, respectively. The results may deepen our understanding of the spectrum of charmonia as well as of the interactions between charmed hadrons.

Contrast edge colors under different natural illuminations.

Essential to sensory processing in the human visual system is natural illumination, which can vary considerably not only across space but also along the day depending on the atmospheric conditions and the sun's position in the sky. In this work, edges derived from the three postreceptoral Luminance, Red-Green, and Blue-Yellow signals were computed from hyperspectral images of natural scenes rendered with daylights of Correlated Color Temperatures (CCTs) from 2735 to 25,889 K; for low CCT, the same analysis was performed using Planckian illuminants up to 800 K. It was found that average luminance and chromatic edge contrasts were maximal for low correlated color temperatures and almost constants above 10,000 K. The magnitude of these contrast changes was, however, only about 2% across the tested daylights. Results suggest that the postreceptoral opponent and nonopponent color vision mechanisms produce almost constant responses for color edge detection under natural illumination.

Spectral recovery of outdoor illumination by an extension of the Bayesian inverse approach to the Gaussian mixture model.

The Bayesian inference approach to the inverse problem of spectral signal recovery has been extended to mixtures of Gaussian probability distributions of a training dataset in order to increase the efficiency of estimating the spectral signal from the response of a transformation system. Bayesian (BIC) and Akaike (AIC) information criteria were assessed in order to provide the Gaussian mixture model (GMM) with the optimum number of clusters within the spectral space. The spectra of 2600 solar illuminations measured in Granada (Spain) were recovered over the range of 360-830 nm from their corresponding tristimulus values using a linear model of basis functions, the Wiener inverse (WI) method, and the Bayesian inverse approach extended to the GMM (BGMM). A model of Gaussian mixtures for solar irradiance was deemed to be more appropriate than a single Gaussian distribution for representing the probability distribution of the solar spectral data. The results showed that the estimation performance of the BGMM method was better than either the linear model or the WI method for the spectral approximation of daylight from the three-dimensional tristimulus values.

Color changes in objects in natural scenes as a function of observation distance and weather conditions.

We have analyzed the changes in the color of objects in natural scenes due to atmospheric scattering according to changes in the distance of observation. Hook-shaped curves were found in the chromaticity diagram when the object moved from zero distance to long distances, where the object chromaticity coordinates approached the color coordinates of the horizon. This trend is the result of the combined effect of attenuation in the direct light arriving to the observer from the object and the airlight added during its trajectory. Atmospheric scattering leads to a fall in the object's visibility, which is measurable as a difference in color between the object and the background (taken here to be the horizon). Focusing on color difference instead of luminance difference could produce different visibility values depending on the color tolerance used. We assessed the cone-excitation ratio constancy for several objects at different distances. Affine relationships were obtained when an object's cone excitations were represented both at zero distance and increasing distances. These results could help to explain color constancy in natural scenes for objects at different distances, a phenomenon that has been pointed out by different authors.

Psychophysical Determination of the Relevant Colours That Describe the Colour Palette of Paintings.

In an early study, the so-called "relevant colour" in a painting was heuristically introduced as a term to describe the number of colours that would stand out for an observer when just glancing at a painting. The purpose of this study is to analyse how observers determine the relevant colours by describing observers' subjective impressions of the most representative colours in paintings and to provide a psychophysical backing for a related computational model we proposed in a previous work. This subjective impression is elicited by an efficient and optimal processing of the most representative colour instances in painting images. Our results suggest an average number of 21 subjective colours. This number is in close agreement with the computational number of relevant colours previously obtained and allows a reliable segmentation of colour images using a small number of colours without introducing any colour categorization. In addition, our results are in good agreement with the directions of colour preferences derived from an independent component analysis. We show that independent component analysis of the painting images yields directions of colour preference aligned with the relevant colours of these images. Following on from this analysis, the results suggest that hue colour components are efficiently distributed throughout a discrete number of directions and could be relevant instances to a priori describe the most representative colours that make up the colour palette of paintings.

Impact of transplantation on neutrophil extracellular trap formation in patients with end-stage renal disease: A single-center, prospective cohort study.

ABSTRACT: Increased neutrophil extracellular trap (NET) formation associates with high cardiovascular risk and mortality in patients with end-stage renal disease (ESRD). However, the effect of transplantation on NETs and its associated markers remains unclear. This study aimed to characterize circulating citrullinated Histone H3 (H3cit) and Peptidyl Arginase Deiminase 4 (PAD4) in ESRD patients undergoing transplantation and evaluate the ability of their neutrophils to release NETs.This prospective cohort study included 80 healthy donors and 105 ESRD patients, out of which 95 received a transplant. H3cit and PAD4 circulating concentration was determined by enzyme-linked immunosorbent assay in healthy donors and ESRD patients at the time of enrollment. An additional measurement was carried out within the first 6 months after transplant surgery. In vitro NET formation assays were performed in neutrophils isolated from healthy donors, ESRD patients, and transplant recipients.H3cit and PAD4 levels were significantly higher in ESRD patients (H3cit, 14.38 ng/mL [5.78-27.13]; PAD4, 3.22 ng/mL [1.21-6.82]) than healthy donors (H3cit, 6.45 ng/mL [3.30-11.65], P < .0001; PAD4, 2.0 ng/mL [0.90-3.18], P = .0076). H3cit, but not PAD4, increased after transplantation, with 44.2% of post-transplant patients exhibiting high levels (≥ 27.1 ng/mL). In contrast, NET release triggered by phorbol 12-myristate 13-acetate was higher in neutrophils from ESRD patients (70.0% [52.7-94.6]) than healthy donors (32.2% [24.9-54.9], P < .001) and transplant recipients (19.5% [3.5-65.7], P < .05).The restoration of renal function due to transplantation could not reduce circulating levels of H3cit and PAD4 in ESRD patients. Furthermore, circulating H3cit levels were significantly increased after transplantation. Neutrophils from transplant recipients exhibit a reduced ability to form NETs.

Trichromatic red-green-blue camera used for the recovery of albedo and reflectance of rough-textured surfaces under different illumination conditions.

Photometric-stereo techniques are based on the fact that image intensity depends upon the orientation of the surface with regard to the source of the illumination and its spectral reflectance. They are of special interest when dealing with rough surfaces because they usually present shadowed regions where sudden illumination changes might be found. In the present work we introduce an extension of the four-source photometric-stereo algorithm to color images that is able to recover the surface spectral reflectance of objects captured with a red-green-blue (RGB) camera. This method allows image rendering, even for rough-textured surfaces, under different directions of the impinging illumination. In addition, the introduction of spectral recovery techniques applied to the albedo and spectral reflectance from rough surfaces offers the possibility of image rendering for scenes captured under sources of illumination differing in spectral distribution. Using albedo instead of RGB information helps to avoid any shadows or highlights that might falsify results. One of the advantages of this spectral-based photometric-stereo method is that it can recover not only the albedo values, but also the spectral reflectance spectrum of an object's surface on a pixel-by-pixel basis, as can be done with more complex hyperspectral imaging devices involving a camera coupled to an extensive set of narrowband filters.