Color Distribution Research Articles

The WISE-2MASS Survey: Red Quasars Into the Radio Quiet Regime

We present a highly complete sample of broad-line (Type 1) QSOs out to z ∼ 3 selected by their mid-infrared colors, a method that is minimally affected by dust reddening. We remove host-galaxy emission from the spectra and fit for excess reddening in the residual QSOs, resulting in a Gaussian distribution of colors for unreddened (blue) QSOs, with a tail extending toward heavily reddened (red) QSOs, defined as having E(B − V) > 0.25. This radio-independent selection method enables us to compare red and blue QSO radio properties in both the FIRST (1.4 GHz) and VLASS (2–4 GHz) surveys. Consistent with recent results from optically selected QSOs from SDSS, we find that red QSOs have a significantly higher detection fraction and a higher fraction of compact radio morphologies at both frequencies. We employ radio stacking to investigate the median radio properties of the QSOs including those that are undetected in FIRST and VLASS, finding that red QSOs have significantly brighter radio emission and steeper radio spectral slopes compared with blue QSOs. Finally, we find that the incidence of red QSOs is strongly luminosity dependent, where red QSOs make up >40% of all QSOs at the highest luminosities. Overall, red QSOs comprise ∼40% of higher luminosity QSOs, dropping to only a few percent at lower luminosities. Furthermore, red QSOs make up a larger percentage of the radio-detected QSO population. We argue that dusty AGN-driven winds are responsible for both the obscuration as well as excess radio emission seen in red QSOs.

The Effect of Pretreatments on the Physical Properties and Starch Structure of Potato Chips Dried by Microwaves under Vacuum.

Native potato starch has a semi-crystalline structure associated with a low glycemic index. Microwave vacuum drying (MWVD) produces crispy snacks under mild temperatures, reducing starch structural changes. However, blanching pretreatment gelatinizes starch, reducing crystallinity. A promising alternative is drying raw or blanched-then-cooled potatoes by MWVD. Cooling the blanched potato before MWVD aims to promote the partial return of the crystalline structure. Thus, this study evaluated how different pretreatments affect potato chips’ starch structure and physical properties. Three samples were dried by MWVD: (i) raw (MWVD-RW), (ii) blanched (MWVD-BL), and (iii) blanched followed by cooling (4 °C for 48 h) (MWVD-BLC) potatoes. MWVD-RW samples presented a higher starch crystallinity (16.9%), which disappeared in MWVD-BL samples and partially returned in MWVD-BLC (8.7%). MWVD-BL and MWVD-BLC samples presented lower bulk (<0.338 g cm−3) density and higher porosity (>74%) and crispness. On the other hand, MWVD-BLC samples presented intermediate characteristics for color, true density, and porous distribution compared to others. All samples showed high porosity (>69%) and crispy texture. Therefore, based on the quality assessment, the MWVD-RW and MWVD-BLC produced healthy and crispy oil-free chips with a potentially lower glycemic index.

Comparison of high hydrostatic pressure and thermal processing on microorganisms and quality of anthocyanin-rich fruit puree

High hydrostatic pressure (HHP, 400 MPa/10 min and 500 MPa/8 min) and thermal processing (TP, 90°C/2 min) were comparatively evaluated by examining their impacts on microorganisms, physicochemical characteristics (TSS, pH, color, ascorbic acid, total phenols, total anthocyanins, and particle size distribution), antioxidant activity, endogenous enzyme activity, and sensory quality of the anthocyanin-rich fruit puree during 20 days of storage at 4°C. The count of total aerobic bacteria (TAB) in HHP treated samples was less than 2.02 log10CFU/mL, and yeasts and molds (Y&amp;amp;M) were not detected during storage. Compared with TP treated samples, the total anthocyanins, total phenols, ascorbic acid, antioxidant capacity, and color of HHP treated ones were better maintained. Principal component analysis (PCA) also proved that the original quality of puree could be better preserved by HHP after treatment and during storage. However, the activity of polyphenol oxidase (PPO) and pectin meth esterase (PME) in HHP treated samples were not inactivated totally. In sum, better quality parameters were observed in HHP treated samples, so HHP was a potential way to be applied to fruit puree.

A review of species of the genus Mocyta (Coleoptera, Staphylinidae) in Ukraine

A review of the genus Mocyta Mulsant &amp; Rey, 1874, which is represented in Ukraine; a description of the main morphological features and diagnostic features is made, data on ecological features, seasonal activity of adults, the distribution of representatives of the genus in Ukraine and the world and the keys to identify the species are presented. The information on the distribution of species of the genus Mocyta in the territory of Ukraine has been clarified and significantly supplemented by new findings. The results can be used to address a number of theoretical issues of faunistics, zoogeography, and ecology, as well as in compiling the inventory of the fauna of the Ukrainian Carpathians, for comparative faunal research, in the analysis of species distribution, in biogeographic constructions, studies of faunogenesis, ecological monitoring and prediction of consequences of the influence of human activities on natural ecosystems of the region. The genus Mocyta is a widespread genus, which in terms of the combination of morphological and biological features belongs to the tribe Athetini Casey, 1910 of the subfamily Aleocharinae Fleming, 1821 of the family Staphylinidae Latreille, 1802. There are 26 known species in the fauna of Palearctic, 5 of which (Mocyta clientula, M. fungi fungi, M. fussi, M. orbata, M. orphana) are represented in the fauna of Ukraine. However, it is likely that there are two more species (M. amplicollis and M. negligens), identified for the surrounding areas, for which characteristics and comparative diagnoses have also been provided. This paper is a continuation of the initiated series of reviews of genera and species of the tribe Athetini of the fauna of Ukraine. Taking into account the wide geographical distribution and significant individual variability in size, colour and shape of the spermatheca of representatives of the genus, the identification of the latter presents some significant difficulties.

Thermal effects of plumage coloration

Plumage coloration can have substantial effects on a bird's energy budget. This is because different colours reflect and absorb light differently, affecting the heat loads acquired from solar radiation. We examine the thermal effects of feather coloration on solar heat gain and flight performance and discuss the potential role of plumage colour on a bird's energy budget. Early investigations of the effects of plumage colour on thermoregulation revealed complex interactions between environmental conditions and physical properties of the plumage that may have led to diverse behavioural and physiological adaptations of birds to their thermal environment. While darker feather surfaces absorb more light, and heat more, than light‐coloured surfaces under exposure to the sun, this relationship is not always straightforward when considering heat transfer to the skin. Heat transfer through plumage varies depending on multiple factors, such as feather density and transmission of light. For instance, higher transmissivity of light‐coloured plumage can increase heat loads reaching skin level, while conduction and convection transfer heat from the surface of dark feathers to the skin. Solar heating can affect the metabolic costs of maintaining a constant body temperature, and depending on environmental conditions, colours can have either a positive or negative effect on a bird's energy budget. More specifically, solar heating can be advantageous in the cold but may increase the energetic costs associated with thermoregulation when ambient temperature is high. More recent studies have further suggested that the thermal properties of feather coloration might reduce the energetic costs of flight. This is because surface heating can affect the ratio between lift and drag on a wing. As concluding remarks, we provide future directions for new lines of research that will aid in improving our understanding of the thermal effects of feather coloration on a bird's energy budget, which can potentially explain factors driving colour evolution and distribution patterns in birds.

Real Time Skin Color Detection Based on Adaptive HSV Thresholding

The detection of human skin color has been studied extensively during the past two decades. It is an essential task for various computer vision applications such as biometric authentication, face/hands tracking and gesture analysis. New machine learning methods are effective for skin color detection. However, they are not suitable for real time applications since they are computationally heavy. A lightweight approach for skin color detection consists of using segmentation rules extracted by an investigation on skin color distribution. The kin appearance varies with diversity of image types, acquisition parameters and scene illumination. There are no general segmentation rules that provide effective skin segmentation for different scene conditions. In this paper we present a real-time skin color detector which adapts itself according to tracked human parts. First, initial thresholds are calculated using two popular skin datasets. Those thresholds can also be calculated quickly using small training sets. The proposed skin color detector showed comparable skin segmentation to DeepLabV3++ application and an improvement in term of F1 measure when compared to methods that relies on static rules.

The role of infographic elements in the perception of the recipient -an analytical study on the infographic page in Al-Naba newspaper

Infographic elements (numbers, colors, shapes, and symbols) play a major role in infographic design, because of their impact on the recipient’s perception of the messages to be delivered, so the communicator cannot achieve his goals without them, as numbers and statistics are important elements in the infographic. A large amount of information and data inside the body of the figure is a process that cannot be achieved without numbers, and that its presentation in an interesting and attractive way is not done without the use of colors, and the process of highlighting the important part of the message to be communicated requires a variation in the distribution of colors within the design body. And if we want the message to be stuck in the mind of the recipient, the symbols are enough to achieve this because of their ability to consolidate the message in the mind of the recipient, which helps to remember it when exposed to it a second time. code instead. In order to display them in a smooth and understandable way for the recipient, we must use shapes, whether they are geometric shapes such as square, rectangle, circle and other regular or irregular shapes.

Why bananas look yellow: The dominant hue of object colours

In this study, we propose a new approach to the perceptual representation of object colours. Three-dimensional objects have a polychromatic colour distribution. Yet, human observers abstract from the variation along the three perceptual colour dimensions when describing objects, such as when we say, “a banana is yellow”. We propose that the perceived object colour is determined by the dominant hue. The dominant hue corresponds to the first principal component of an object’s chromaticities. Across three experiments, we show for a sample of objects that the chromatic variation away from the dominant hue is almost completely neglected by human observers under non-laboratory viewing conditions. This is partly due to the low visibility of this variation, and partly to attentional change blindness. These findings reveal the potential role of dominant hue in the perception of object colours. Dominant hue may enable us to determine the most representative colours of objects because perceived object colours tend to be maximally bright and saturated. The present findings also imply that we can simplify the colour distributions of objects by projecting them onto their dominant hue. This may be useful for computational applications.

Autofluorescent Biomolecules in Diptera: From Structure to Metabolism and Behavior.

Light-based phenomena in insects have long attracted researchers’ attention. Surface color distribution patterns are commonly used for taxonomical purposes, while optically-active structures from Coleoptera cuticle or Lepidoptera wings have inspired technological applications, such as biosensors and energy accumulation devices. In Diptera, besides optically-based phenomena, biomolecules able to fluoresce can act as markers of bio-metabolic, structural and behavioral features. Resilin or chitinous compounds, with their respective blue or green-to-red autofluorescence (AF), are commonly related to biomechanical and structural properties, helpful to clarify the mechanisms underlying substrate adhesion of ectoparasites’ leg appendages, or the antennal abilities in tuning sound detection. Metarhodopsin, a red fluorescing photoproduct of rhodopsin, allows to investigate visual mechanisms, whereas NAD(P)H and flavins, commonly relatable to energy metabolism, favor the investigation of sperm vitality. Lipofuscins are AF biomarkers of aging, as well as pteridines, which, similarly to kynurenines, are also exploited in metabolic investigations. Beside the knowledge available in Drosophila melanogaster, a widely used model to study also human disorder and disease mechanisms, here we review optically-based studies in other dipteran species, including mosquitoes and fruit flies, discussing future perspectives for targeted studies with various practical applications, including pest and vector control.

Intrinsic tension in the supernova sector of the local Hubble constant measurement and its implications

ABSTRACT We reanalyse observations of Type Ia supernovae (SNe) and Cepheids used in the local determination of the Hubble constant and find strong evidence that SN standardization in the calibration sample (galaxies with observed Cepheids) requires a steeper slope of the colour correction than in the cosmological sample (galaxies in the Hubble flow). The colour correction in the calibration sample is consistent with being entirely due to an extinction correction due to dust with properties similar to those of the Milky Way (RB ≈ 4.6 ± 0.4) and there is no evidence for intrinsic scatter in the SN peak magnitudes. An immediate consequence of this finding is that the local measurement of the Hubble constant becomes dependent on the choice of SN reference colour, i.e. the colour of an unreddened SN. Specifically, the Hubble constant inferred from the same observations decreases gradually with the reference colour assumed in the SN standardization. We recover the Hubble constant measured by SH0ES for the standard choice of reference colour (SALT2 colour parameter c = 0), while for a reference colour that coincides with the blue end of the observed SN colour distribution (c ≈ −0.13), the Hubble constant from Planck observations of the cosmic microwave background (CMB) [assuming a flat Lambda cold dark matter (ΛCDM) cosmological model] is recovered. These results are intriguing in that they may provide an avenue for resolving the Hubble tension. However, since there is no obvious physical basis for the differences in colour corrections in the two SN samples, the origin of these requires further investigation.

Identifying the influence of surface texture waveforms on colors of polished surfaces using an explainable AI approach

An explainable artificial intelligence approach based on consolidating the Local Interpretable and Model-agnostic Explanation (LIME) model outputs was devised to discern the influence of the surface morphology on the colors exhibited by stainless-steel 304 parts polished with a Magnetic Abrasive Finishing (MAF) process. The MAF polishing process was used to create two regions, each appearing either blue or red to the naked eye. The color distribution was microscopically heterogeneous, i.e., some red microscale patches were dispersed in blue regions, and vice versa. The surface morphology was represented in the frequency domain (using a 2D Fourier transform) to capture the harmonic surface patterns, such as the feed and lay marks from the polishing process. A Convolutional Neural Network (CNN) was employed to identify the color of the region from the frequency characteristics of the surface morphology. The CNN was able to predict the observed colors with test accuracies exceeding 99%, suggesting that the frequency characteristics of the surface morphology of the red regions are distinctly different from those of the blue regions. A LIME model was constructed around each small segment within each region of the surface to identify the frequency features that are influential for differentiating between the colors. To deal with the effect of heterogeneity, an algorithm based on the query by experts was used to reconcile the local influences and gather the global explanations of the frequency characteristics that inform the blue versus red regions. We found that the dominant morphological features in the red regions are those that capture the polishing lay patterns underlying surface structure, whereas those in the blue regions capture the non-uniform and high-frequency waveform patterns, such as those result when oxide films form due to the intense polishing conditions.

A Comparative Study on the Loss Functions for Image Enhancement Networks

Image enhancement and image retouching processes are often dominated by global (shift-invariant) change of colour and tones. Most &#x201C;deep learning&#x201D; based methods proposed for image enhancement are trained to enforce similarity in pixel values and/or in the high-level feature space. We hypothesise that for tasks, such as image enhancement and retouching, which involve a significant shift in colour statistics, training the model to restore the overall colour distribution can be of vital importance. To address this, we study the effect of a Histogram Matching loss function on a state-of-the art colour enhancement network &#x2014; HDRNet. The loss enforces similarity of the RGB histograms of the predicted and the target images. By providing detailed qualitative and quantitative comparison of different loss functions on varied datasets, we conclude that enforcing similarity in the colour distribution achieves substantial improvement in performance and can play a significant role while choosing loss functions for image enhancement networks.

Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography

Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases. This research deals with the three major renal diseases categories: kidney stones, cysts, and tumors, and gathered and annotated a total of 12,446 CT whole abdomen and urogram images in order to construct an AI-based kidney diseases diagnostic system and contribute to the AI community’s research scope e.g., modeling digital-twin of renal functions. The collected images were exposed to exploratory data analysis, which revealed that the images from all of the classes had the same type of mean color distribution. Furthermore, six machine learning models were built, three of which are based on the state-of-the-art variants of the Vision transformers EANet, CCT, and Swin transformers, while the other three are based on well-known deep learning models Resnet, VGG16, and Inception v3, which were adjusted in the last layers. While the VGG16 and CCT models performed admirably, the swin transformer outperformed all of them in terms of accuracy, with an accuracy of 99.30 percent. The F1 score and precision and recall comparison reveal that the Swin transformer outperforms all other models and that it is the quickest to train. The study also revealed the blackbox of the VGG16, Resnet50, and Inception models, demonstrating that VGG16 is superior than Resnet50 and Inceptionv3 in terms of monitoring the necessary anatomy abnormalities. We believe that the superior accuracy of our Swin transformer-based model and the VGG16-based model can both be useful in diagnosing kidney tumors, cysts, and stones.

Evaluating the feasibility of interpretable machine learning for globular cluster detection

Extragalactic globular clusters (GCs) are important tracers of galaxy formation and evolution because their properties, luminosity functions, and radial distributions hold valuable information about the assembly history of their host galaxies. Obtaining GC catalogues from photometric data involves several steps which will likely become too time-consuming to perform on the large data volumes that are expected from upcoming wide-field imaging projects such as Euclid. In this work, we explore the feasibility of various machine learning methods to aid the search for GCs in extensive databases. We use archivalHubbleSpace Telescope data in theF475WandF850LPbands of 141 early-type galaxies in the Fornax and Virgo galaxy clusters. Using existing GC catalogues to label the data, we obtained an extensive data set of 84929 sources containing 18556 GCs and we trained several machine learning methods both on image and tabular data containing physically relevant features extracted from the images. We find that our evaluated machine learning models are capable of producing catalogues of a similar quality as the existing ones which were constructed from mixture modelling and structural fitting. The best performing methods, ensemble-based models such as random forests, and convolutional neural networks recover ∼90−94% of GCs while producing an acceptable amount of false detections (∼6−8%), with some falsely detected sources being identifiable as GCs which have not been labelled as such in the used catalogues. In the magnitude range 22 &lt; m4_g ≤ 24.5 mag, 98−99% of GCs are recovered. We even find such high performance levels when training on Virgo and evaluating on Fornax data (and vice versa), illustrating that the models are transferable to environments with different conditions, such as different distances than in the used training data. Apart from performance metrics, we demonstrate how interpretable methods can be utilised to better understand model predictions, recovering that magnitudes, colours, and sizes are important properties for identifying GCs. Moreover, comparing colour distributions from our detected sources to the reference distributions from input catalogues finds great agreement and the mean colour is recovered even for systems with fewer than 20 GCs. These are encouraging results, indicating that similar methods trained on an informative sub-sample can be applied for creating GC catalogues for a large number of galaxies, with tools being available for increasing the transparency and reliability of said methods.

Analysis of the physiological load on lumbar vertebrae in patients with osteoporosis: a finite-element study

This study aims to investigate the difference in physiological loading on the spine in three different motions (flexion–extension, lateral bending, and axial rotation) between osteoporotic and normal spines, using finite element modelling. A three-dimensional finite element (FE) model centered on the lumbar spine was constructed. We applied two different material properties of osteoporotic and normal spines. For the FE analysis, three loading conditions (flexion–extension, lateral bending, and axial rotation) were applied. The von Mises stress was higher on the nucleus pulposus at all vertebral levels in all movements, in the osteoporosis group than in the normal group. On the annulus fibrosus, the von Mises stress increased at the level of L3–L4, L4–L5, and L5–S in the flexion–extension group and at L4–L5 and L5–S levels in the lateral bending group. The values of two motions, flexion–extension and lateral bending, increased in the L4 and L5 cortical bones. In axial rotation, the von Mises stress increased at the level of L5 of cortical bone. Additionally, the von Mises stress increased in the lower endplate of L5–S and L4–L5 in all movements, especially lateral bending. Even in the group with no increase, there was a part that received increased von Mises stress locally for each element in the three-dimensional reconstructed view of the pressure distribution in color. The von Mises stress on the lumbar region in the three loading conditions, was greater in most components of osteoporotic vertebrae than in normal vertebrae and the value was highest in the nucleus pulposus. Considering the increase in the measured von Mises stress and the local increase in the pressure distribution, we believe that these results can contribute to explaining discogenic pain and degeneration.

Intelligent Detection of Rice Leaf Diseases Based on Histogram Color and Closing Morphological

Harvest drop in rice because of leaf blast is a vital issue in the country’s food stock and social life where rice is the primary source of food. Epidemics can cause leaf blasts due to weather conditions or environmental transformation. Therefore, early detection of leaf blast is needed to take precautions action to save the harvest. This research presents a new approach for rice leaf blast detection. It seizes colour distribution and shapes to determine the damaging leaf. Two main features: colour and shape, are key points to measure the similarity of an image by comparing the image query and database. The image extraction uses histogram colour throughout the pre-processing phase. The approach will take the dominant colour of leaf. Since this green colour dominated the leaf, the green will be converted from RGB to the HSV domain with 256 range. The shape feature extraction based on morphology closing will calculate the images’ area, diameter, and perimeter. The process is continued by resizing the image and convert into a grayscale mode to apply canny edge detection. The experiment uses 267 images dataset and 74 testing data consisting of 2 categories: blast disease leaf and healthy leaf. The trial results achieve an 85.71% accuracy rate to detect blast disease by colour feature, 71.42% by shape feature, and 85.71% by combined colourshape features

Shell colors and microstructures of four pearl oyster species in the South China Sea

Wild marine pearl oyster shells have rich colors, and the color and gloss of pearls cultivated by pearl oysters are closely related to the pearl layer color of the mantle. Therefore, in this study, four important wild marine pearl oyster species (Pinctada maxima, Pteria penguin, Pinctada margaritifera, and Pinctada fucata) were collected from the South China Sea, and a colorimeter was used to measure the color of their inner and outer shells. We analyzed the color range of their shells and the correlation between the color parameters; additionally, we observed the microstructure of their shells using a scanning electron microscope. The results showed that the color distribution and brightness of the inner shells of the four species were wider than that of the outer shells. In addition, the color distribution range of the outer and inner shells of the four pearl oyster species were P. fucata > P. margaritifera > P. maxima > Pt. penguin and Pt. penguin > P. fucata > P. margaritifera > P. maxima, respectively. Concerning the microstructures of the four pearl oysters, the shell structures of P. maxima, P. margaritifera and P. fucata had a honeycomb arrangement, whereas Pt. penguin had an irregular polygon structure. The P. maxima and P. margaritifera with a strong nacre secretion ability that area and thickness of the single crystal particles were larger than those of Pt. penguin and P. fucata.

Effect of storage time on the microbial, physicochemical and sensory characteristics of ovine whey‐based fruit beverages

SummaryThe aim of this study was to establish the physicochemical, sensory and microbiological quality of ovine whey‐based fruit beverages produced from pasteurised ovine whey (mango flavoured–sugar sweetened [M‐Su], pineapple flavoured–extra sugar sweetened [P‐ESu], and tropical fruit flavoured–stevia sweetened [T‐St]), and the changes in quality of these beverage types during the 15‐day storage. The beverages were evaluated for their pH, colour, sediment and particle size distribution, microbiological count and sensory quality. No significant differences in the pH and the microbial counts among the beverages were noted during the storage period; however, the particle size distribution reflected the sediment formation that significantly decreased during the same period in all beverage types. The beverages were getting lighter during storage, which was evident by increasing L* and decreasing a* values for colour. All three beverage types had very high scores for taste and odour after 9 days, and colour and sediment after 5 days of storage. Beverage‐type T‐St was most preferred by consumers, with the highest scores for taste, odour and sensory appearance. These results can assist in the better determination of the deteriorative changes in a variety of ovine whey‐based beverages, necessary changes in product composition that might result in improved product quality, and yet reducing losses incurred during ovine milk processing. In this sense, this research's findings contribute to the utilisation of whey beverages by the dairy industry to the development of functional products.

ADDGALS: Simulated Sky Catalogs for Wide Field Galaxy Surveys

We present a method for creating simulated galaxy catalogs with realistic galaxy luminosities, broadband colors, and projected clustering over large cosmic volumes. The technique, denoted Addgals (Adding Density Dependent GAlaxies to Lightcone Simulations), uses an empirical approach to place galaxies within lightcone outputs of cosmological simulations. It can be applied to significantly lower-resolution simulations than those required for commonly used methods such as halo occupation distributions, subhalo abundance matching, and semi-analytic models, while still accurately reproducing projected galaxy clustering statistics down to scales of r ∼ 100 h −1kpc . We show that Addgals catalogs reproduce several statistical properties of the galaxy distribution as measured by the Sloan Digital Sky Survey (SDSS) main galaxy sample, including galaxy number densities, observed magnitude and color distributions, as well as luminosity- and color-dependent clustering. We also compare to cluster–galaxy cross correlations, where we find significant discrepancies with measurements from SDSS that are likely linked to artificial subhalo disruption in the simulations. Applications of this model to simulations of deep wide-area photometric surveys, including modeling weak-lensing statistics, photometric redshifts, and galaxy cluster finding, are presented in DeRose et al., and an application to a full cosmology analysis of Dark Energy Survey (DES) Year 3 like data is presented in DeRose et al. We plan to publicly release a 10,313 square degree catalog constructed using Addgals with magnitudes appropriate for several existing and planned surveys, including SDSS, DES, VISTA, Wide-field Infrared Survey Explorer, and Rubin Observatory’s Legacy Survey of Space and Time.

The dark matter halo masses of elliptical galaxies as a function of observationally robust quantities

Context. The assembly history of the stellar component of a massive elliptical galaxy is closely related to that of its dark matter halo. Measuring how the properties of galaxies correlate with their halo mass can therefore help to understand their evolution. Aims. We investigate how the dark matter halo mass of elliptical galaxies varies as a function of their properties, using weak gravitational lensing observations. To minimise the chances of biases, we focus on the following galaxy properties that can be determined robustly: the surface brightness profile and the colour. Methods. We selected 2409 central massive elliptical galaxies (log M*/M⊙ ≳ 11.4) from the Sloan Digital Sky Survey spectroscopic sample. We first measured their surface brightness profile and colours by fitting Sérsic models to photometric data from the Kilo-Degree Survey (KiDS). We fitted their halo mass distribution as a function of redshift, rest-frame r-band luminosity, half-light radius, and rest-frame u − g colour, using KiDS weak lensing measurements and a Bayesian hierarchical approach. For the sake of robustness with respect to assumptions on the large-radii behaviour of the surface brightness, we repeated the analysis replacing the total luminosity and half-light radius with the luminosity within a 10 kpc aperture, Lr, 10, and the light-weighted surface brightness slope, Γ10. Results. We did not detect any correlation between the halo mass and either the half-light radius or colour at fixed redshift and luminosity. Using the robust surface brightness parameterisation, we found that the halo mass correlates weakly with Lr, 10 and anti-correlates with Γ10. At fixed redshift, Lr, 10 and Γ10, the difference in the average halo mass between galaxies at the 84th percentile and 16th percentile of the colour distribution is 0.00 ± 0.11 dex. Conclusion. Our results indicate that the average star formation efficiency of massive elliptical galaxies has little dependence on their final size or colour. This suggests that the origin of the diversity in the size and colour distribution of these objects lies with properties other than the halo mass.