Visible Component Research Articles

Urine Sediment Detection Algorithm Based on Channel Enhancement and Deformable Convolution.

Urine sediment detection is a vital method in clinical urine analysis for evaluating an individual's kidney and urinary system health, as well as identifying potential diseases. Nevertheless, urine sediment images exhibit the characteristic of diverse shapes for the same category of targets. These characteristics pose a considerable challenge to the accurate identification of the visible components within the images. We approach urine sediment detection as an object detection task and have introduced the specialized YOLOv7-CSD algorithm for this purpose. In particular, we have integrated channel enhancement feature pyramid network (CE-FPN) and selective kernel (SK) into the YOLOv7 model to address the issue of model confusion in classifying and identifying tasks caused by the feature aliasing effects of feature pyramid network (FPN). Furthermore, we enhance the efficient layer aggregation networks (ELAN) network by adding a second channel, enabling the model to acquire a more extensive set of feature information. On top of this, we introduce the deformable convolutional v3 (DCNv3) operator, allowing the model to dynamically adjust its receptive field, addressing the issue of variable shapes. Tested on the USE dataset and a dataset for urine crystals, YOLOv7-CSD achieves accuracies of 92.8 and 89.6 , respectively.

Development of a mobile application for rapid detection of meat freshness using deep learning

The freshness or spoilage of meat is critical in terms of meat color and quality criteria. Detecting the condition of the meat is important not only for consumers but also for the processing of the meat itself. Meat quality is influenced by various pre-slaughter factors including housing conditions, diet, age, genetic background, environmental temperature, and stress factors. Additionally, spoilage can occur due to the slaughtering process, though post-slaughter spoilage is more frequent and has a stronger correlation with postslaughter factors. The primary indicator of meat quality is the pH value, which can be high or low. Variations in pH values can lead to adverse effects in the final product such as color defects, microbial issues, short shelf life, reduced quality, and consumer complaints. Many of these characteristics are visible components of quality. This study aimed to develop a mobile application using deep learning-based image processing techniques for the rapid detection of freshness. The attributes of the source and the targeted predictions were found satisfactory, indicating that further advancements could be made in developing future versions of the application.

The glow of axion quark nugget dark matter. Part I. Large scale structures

Axion quark nuggets (AQN) are hypothetical, macroscopically large objects with a mass greater than a few grams and sub-micrometer size, formed during the quark-hadrontransition. Originating from the axion field, they offer a possible resolution of the similarity between visible and dark components of the Universe, i.e. ΩDM ∼ Ωvisible and observed matter-antimatter asymmetry. These composite objects behave as cold dark matter, interacting with ordinary matter and resulting in pervasive electromagnetic radiation throughout the Universe. This work aims to predict the electromagnetic signature in large-scale structures from this AQN-baryon interaction, accounting for thermal and non-thermal radiations.We use Magneticum hydrodynamical simulations to describe the realistic distribution and dynamics of gas and dark matter at cosmological scales. We construct a light cone encompassing a 1.4 square degree area on the sky, extending up to redshift z = 5.4, and we calculate the electromagnetic signature across a wide range of frequencies from radio, starting at ν ∼ 1 GHz, up to a few keV X-ray energies. We find that the AQNs electromagnetic signature is characterized by global (monopole) and fluctuation signals. The amplitude of both signals strongly depends on the average nugget mass and the ionization level of the baryonic environment, allowing us to identify a most optimistic scenario and a minimal configuration. The signal of our most optimistic scenario is often near the sensitivity limit of existing instruments, such as FIRAS in the ν = [100-500] GHz range and the South Pole Telescope for high-resolution ℓ > 4000 at ν = 95 GHz. Fluctuations in the Extra-galactic Background Light caused by the axion quark nuggets in the most optimistic scenario can also be tested with space-based imagers Euclid and James Webb Space Telescope. In general, our minimal configuration is still out of reach of existing instruments, but future experiments might be able to pose some constraints.We conclude that the axion quark nuggets model represents a viable model for dark matter, which does not violate the canons of cosmology nor existing observations. A reanalysis of existing data sets could provide some evidence of axion quark nuggets if our most optimistic configuration is correct. The best chances for testing the model reside in 1) ultra-deep infrared and optical surveys, 2) future experiments to probe the frequency spectrum of the cosmic microwave background, and 3) low-frequency (1 GHz < ν < 100 GHz) and high-resolution (ℓ ≳ 104) observations.

Gender discrimination lawsuits: How board gender diversity impacts gender litigation likelihood and outcomes

Gender discrimination in firms is an ongoing problem, yet we know little about whether board gender diversity affects gender discrimination litigation. Boards are an important and visible component of an organization’s leadership and are positioned to influence firm policies and attitudes. Using social identity theory, we consider how board gender diversity impacts firms that face gender discrimination lawsuits. Furthermore, we explore how greater board gender diversity provides reputational capital which acts as insurance against litigation outcomes. Using a dataset of gender discrimination lawsuits and experiments simulating jury decision making, we hypothesize that more gender diversity on the board will protect firms from gender discrimination litigation and its outcomes. We find that firms with greater board gender diversity are at a higher likelihood of incurring gender discrimination litigation yet receive more favorable decisions by judges and juries including a greater likelihood of receiving favorable verdicts and of paying lower damages.

The impact of visible light component bands on polyphenols from red grape seed extract powder encapsulated in alginate–whey protein matrix

Beads made of sodium alginate, whey protein concentrate, and red grape seed extract powder were exposed to white light and its red-orange, yellow-green-cyan, and cyan-blue-violet bands. The chemical analysis showed that encapsulation in the alginate–whey protein matrix protected polyphenols, flavonoids and cyanidin-3-O-glucoside when exposed to red-orange light. The reflectance spectra acquired from grape seed extract powder and grape seed extract beads were deconvoluted and anthocyanins-based moieties which contribute to the expression of bathochromic or hypsochromic effects were identified. The evolution of the peak areas assigned to the colored compounds confirms that the most intense polyphenol degradation occurred in grape seed extract powder and grape seed extract beads exposed to cyan-blue-violet light, as shown by the chemical analysis. The results of the study are important in choosing the light band from the visible spectrum which can be used to process food enriched with grape seed extract with minimal polyphenol degradation.

Preparing Prospective English Language Teachers for ICT Integration

This paper reports on a case study of six prospective English language teachers’ ICT training experiences and the connections between these experiences and their beliefs about how well their language teacher education program prepared them for effective technology integration in language classrooms. This study aimed at arguing the importance of the situational factors in the university coursework and fieldwork components of teacher education on future teachers’ technology-related beliefs and technology use. Data were gathered through surveys and semi-structured face-to-face interviews. The results provided some implications for curriculum updates in teacher education programs and necessary improvements in relevant policies to prepare their graduates to teach with technology-integrated classrooms. The development of a practical and integrated knowledge base of ICT use should be a visible component in teacher education programs.

Investigation of Criteria for Comparing of Natural and LED Radiation Spectral Distribution

The difference in the spectral composition of artificial and natural lighting can negatively affect health, as well as lead to a distorted perception of the color of surrounding objects. At the same time, a certain correction of the spectral composition of visible radiation in medical institutions and workplaces has a positive effect on human health, while can be carried lighting control out taking into account the data of personal sensor devices that determine the human condition. The purpose of the research was to select criteria for comparing natural and LED optical and visible radiation by spectral composition and by the visibility of color differences in natural and LED lighting. The effectiveness of the application of known and developed criteria for assessing the difference in the spectral composition of optical and visible radiation from natural and LED sources was investigated, as well as for the visibility of color differences in natural and LED lighting. To minimize the values of criteria are proposed additive and subtractive methods for calculating LED parameters. Their comparison allowed us to conclude that a more complex calculation algorithm, but higher performance for an additive technique than for a subtractive one with the same minimization results.It was found that to simulate the spectral composition of natural radiation using LEDs, it is most effective to use the criteria "standard deviations of the relative differences between the optical and visible spectral components of natural and LED radiation". A comparison of the criteria for the visibility of color differences in natural and LED lighting showed approximately the same effectiveness of using the criteria "small color differences" and "standard deviation by photoreceptors" at the present stage and the prospects for applying the second criterion, provided that its acceptable values are established.

A New Possible Way to Detect Axion Antiquark Nuggets

The axion anti-quark nugget (AQ¯N) model was developed to explain in a natural way the asymmetry between matter and antimatter in Universe. In this hypothesis, a similitude between the dark and the visible components exists. The lack of observability of any type of dark matter up to now, in particular AQ¯Ns, requires finding new ways of detecting these particles, if they exist. In spite of strong interaction with visible matter, for such objects a very small ratio of cross section to mass is expected and thus huge detector systems are necessary. This paper presents a new idea for the direct detection of the AQ¯Ns using minerals as natural rock deposits acting as paleo-detectors, where the latent signals of luminescence produced by interactions of AQ¯Ns are registered and can be identified as an increased and symmetrical deposited dose. The estimates were made for minerals widely distributed on Earth, for which the thermoluminescence (TL) signal is intense and if the thermal conditions are constant and with low temperatures, the lifetime of the latent signals is kept for geological time scales.

Winter Storm Severity Index in Alaska: Understanding the Usefulness for Impact-Based Winter Weather Severity Forecast Information

Abstract There is growing interest in impact-based decision support services to address complex decision-making, especially for winter storm forecasting. Understanding users’ needs for winter storm forecast information is necessary to make such impact-based winter forecasts relevant and useful to the diverse regions affected. A mixed-method social science research study investigated extending the winter storm severity index (WSSI) [operational for the contiguous United States (CONUS)] to Alaska, with consideration of the distinct needs of Alaskan stakeholders and the Alaskan climate. Data availability differences suggest the need for an Alaska-specific WSSI, calling for user feedback to inform the direction of product modifications. Focus groups and surveys in six regions of Alaska provided information on how the WSSI components, definitions, and categorization of impacts could align with stakeholder expectations and led to recommendations for the Weather Prediction Center to consider in developing the WSSI Alaska product. Overall, wind (strength and direction) and precipitation are key components to include. Air travel is a critical concern requiring wind and visibility information, while road travel is less emphasized (contrasting with CONUS needs). Special Weather Statements and Winter Storm Warnings are highly valued, and storm trajectory and transition (between precipitation types) information are the important contexts for decision-makers. Alaska is accustomed to and prepared for winter impacts but being able to understand how components (wind, snow, and ice) contribute to overall impact enhances the ability to respond and mitigate damage effectively. The WSSI adapted for Alaska can help address regional forecast needs, particularly valuable as the climate changes and typical winter conditions become more variable. Significance Statement Impact-based support services can assist decision-makers in prioritizing preparedness and mitigation actions related to winter storm events. The winter storm severity index adapted for specific considerations in Alaska (such as including wind and visibility components) can extend winter weather impact-based forecasting’s utility. Additionally, lessons learned from the process of adapting a national product to specific regional needs may inform best practices for gathering stakeholder input and feedback.

J0526+5934: A peculiar ultra-short-period double white dwarf

Context.Ultra-short-period compact binaries are important sources of gravitational waves. The class of short-period compact binaries includes, for example, the progenitors of type Ia supernovae and the progenitors of merger episodes that may lead to massive and magnetic single white dwarfs. J0526+5934 is one such example: it is an unresolved compact binary star with an orbital period of 20.5 min.Aims.The visible component of J0526+5934 was recently claimed to be a hot sub-dwarf star with a CO white dwarf companion. Our aim is to provide strong observational and theoretical evidence that the primary star is instead an extremely low-mass white dwarf, although the hot sub-dwarf nature cannot be completely ruled out.Methods.We analysed optical spectra together with time-series photometry of the visible component of J0526+5934 to constrain its orbital and stellar parameters. We also employed evolutionary sequences for low-mass white dwarfs to derive independent values of the primary mass.Results.From the analysis of our observational data, we find a stellar mass for the primary star in J0526+5934 of 0.26 ± 0.05M⊙, which perfectly matches the 0.237 ± 0.035M⊙independent measurement we derive from the theoretical evolutionary models. This value is considerably lower than the theoretically expected and generally observed mass range for hot sub-dwarf stars, but falls well within the mass limit values of extremely low-mass white dwarfs.Conclusions.We conclude J0526+5934 is the sixth ultra-short-period detached double white dwarf currently known.

Secondary scintillation yield from GEM electron avalanches in - and --isobutane for CYGNO — Directional Dark Matter search with an optical TPC

CYGNO is an international collaboration with the aim of operating a ▪ optical time projection chamber (TPC) for directional Dark Matter (DM) searches and solar neutrino spectroscopy, to be deployed at the Laboratori Nazionali del Gran Sasso (LNGS). A ▪/▪ (60/40) mixture is used, along with a triple Gas Electron Multiplier (GEM) cascade to amplify the ionisation signal. The scintillation produced in the electron avalanches is read out using a scientific complementary metal–oxide–semiconductor (sCMOS) camera. This solution has proven to provide very high sensitivity to interactions in the few ▪ energy range. The inclusion of a hydrogen-based gas will offer an even lighter target, resulting in a more efficient energy transfer in a DM particle collision, and consequently, a lower detection threshold. Additionally, longer track lengths of light nuclear recoils are easier to detect with a clearer direction. However, the addition of such gas will contribute to quenching the scintillation, jeopardizing the TPC performance. In this work, we demonstrate the feasibility of adding 1% to 5% isobutane to the ▪/▪ (60/40) mixture by measuring the respective absolute scintillation yield output. The overall scintillation produced in the charge avalanches is not drastically suppressed by quenching due to the isobutane addition. The presence of Penning transfer from excited He atoms to isobutane molecules increases the number of electrons in the avalanches, partially compensating for the loss of scintillation due to quenching. For the highest applied GEM voltage, the total number of photons produced in the avalanche per ▪ deposited in the absorption region presents a decrease of only a factor of about three, from 2.30(20)×104 to 8.2(4)×103▪, as the isobutane content increases from 0 to 5%. The quantification of the visible component of the scintillation shows that isobutane quenches both visible and ultraviolet (UV) photons emitted by ▪/▪.

Discovery of a dormant 33 solar-mass black hole in pre-release Gaia astrometry

Context. Gravitational waves from black-hole (BH) merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models – and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Aims. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. Methods. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. Results. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 ± 0.82 M⊙ BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. Conclusions. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way.

Silicon nitride stoichiometry tuning for visible photonic integrated components

In integrated photonics, silicon nitride-based devices operating in the visible range of light may experience auto-fluorescence, an undesired effect that can interfere with the propagating signal. In this article, a reduction in auto-fluorescence has been obtained by studying stoichiometric and silicon-rich silicon nitride, subjected to different post-thermal annealings in different atmospheres. Stoichiometric silicon nitride treated with rapid thermal annealing at 1100 °C in an argon atmosphere reduces the photoluminescence intensity of the material by 95%. Silicon-rich nitride shows a more stable photoluminescence response to different annealings and atmospheres than the stoichiometric. Compared to the stoichiometric material, the emission peaks experienced by the silicon-rich silicon nitride are red shifted between 140 and 190 nm, and the refractive index value is increased by 7% at 633 nm. Also, the interface effects have been studied, showing a remarkable contribution when the annealing is performed in an argon atmosphere, while no contribution from these effects is observed in a nitrogen atmosphere. Finally, taking advantage of the refractive index variation between nitrides, a vertical directional coupler using two asymmetric waveguides, one of each type of silicon nitride, has been designed and simulated, obtaining a coupling length of 9.8 μm with a coupling power of 95.8%, demonstrating the 3D integration capabilities of combining silicon nitride layers of variable composition.

Pain mechanisms in the transgender individual: a review.

Provide an overview of the literature addressing major areas pertinent to pain in transgender persons and to identify areas of primary relevance for future research. A team of scholars that have previously published on different areas of related research met periodically though zoom conferencing between April 2021 and February 2023 to discuss relevant literature with the goal of providing an overview on the incidence, phenotype, and mechanisms of pain in transgender patients. Review sections were written after gathering information from systematic literature searches of published or publicly available electronic literature to be compiled for publication as part of a topical series on gender and pain in the Frontiers in Pain Research. While transgender individuals represent a significant and increasingly visible component of the population, many researchers and clinicians are not well informed about the diversity in gender identity, physiology, hormonal status, and gender-affirming medical procedures utilized by transgender and other gender diverse patients. Transgender and cisgender people present with many of the same medical concerns, but research and treatment of these medical needs must reflect an appreciation of how differences in sex, gender, gender-affirming medical procedures, and minoritized status impact pain. While significant advances have occurred in our appreciation of pain, the review indicates the need to support more targeted research on treatment and prevention of pain in transgender individuals. This is particularly relevant both for gender-affirming medical interventions and related medical care. Of particular importance is the need for large long-term follow-up studies to ascertain best practices for such procedures. A multi-disciplinary approach with personalized interventions is of particular importance to move forward.

Predictors of street tree survival in Philadelphia: Tree traits, biophysical environment, and socioeconomic context

Street trees are highly visible components of the urban forest, providing ecosystem services to city residents, but tree mortality can result in a loss of these essential benefits. Here, we focus on how street tree survival in Philadelphia, Pennsylvania (US) has been influenced by 1) tree traits and attributes, 2) the local biophysical environment, and 3) socioeconomic context. We used a longitudinal monitoring approach with a 6-year time interval and 103 randomly-located, fixed-length permanent plots, containing a range of tree size classes, to assess street tree survival rates, predictors of survival, and the balance of tree losses and gains. Street trees surveyed in this study experienced an annual mortality rate of 3.68% and followed a Type III mortality curve, with the highest annual mortality rates in the smallest size class. On the surveyed plots, there was a net decrease of live trees over the study period (2657 to 2542; 4.33% decline). Multivariate logistic regression revealed significant associations between street tree survival and tree crown vigor, species traits (expected mature stature and drought tolerance), site type, land use type, % impervious surface in a 15 m buffer, parcel-level demolition events, % of residents in poverty, % unoccupied households, and % renter-occupied households. Additionally, the final model included a multiplicative interaction term between crown vigor and tree size with separation in pattern of small (DBH < 7.6 cm) from larger (DBH ≥ 7.6 cm) trees. Our findings suggest that targeted management interventions may enhance overall street tree survival, such as focusing on small trees, as well as trees in sidewalk cut-outs, commercial or industrial areas, or near demolition activity. Longitudinal monitoring studies such as ours provide valuable information about how urban forest systems change over time, with assessments that are valuable for management by municipal foresters and other street tree stewards.

Multimass modelling of milky way globular clusters – II. Present-day black hole populations

ABSTRACT Populations of stellar-mass black holes (BHs) in globular clusters (GCs) influence their dynamical evolution and have important implications on one of the main formation channels for gravitational wave sources. Inferring the size of these populations remains difficult, however. In this work, multimass models of 34 Milky Way GCs, first presented in Dickson et al., are used to explore the present-day BH populations. Direct constraints on both the total and visible mass components provided by several observables allow these models to accurately determine the distribution of the dark mass (including BHs) within clusters, as we demonstrate in a proof-of-concept fitting of the models to mock observations extracted from Monte Carlo cluster models. New constraints on the BH population retained to the present-day in each cluster are inferred from our models. We find that BH mass fractions ranging from 0 to 1 per cent of the total mass are typically required to explain the observations, except for ω Cen, for which we infer a mass fraction above 5 per cent, in agreement with previous works. Relationships between the dark remnant populations and other cluster parameters are examined, demonstrating a clear anticorrelation between the amount of BHs and mass segregation between visible stars, as well as a correlation between remnant mass fractions and the dynamical age of clusters. Our inferred BH populations are in good agreement overall with other recent studies using different methodologies, but with notable discrepancies for individual clusters.

Long-slit spectral study of the unusual post-interacting galaxy Arp 263

ABSTRACT Arp 263 is a single irregularly shaped galaxy with intense star formation. Its short tidal features of low brightness visible in both optics and the H i line, as well as the strong non-circular motion of atomic gas in the outskirts, give pieces of evidence of a recent merging with some intruder, non-observed directly. We carried out spectral observations of this galaxy at the 6 m telescope of the Special Astrophysical Observatory. The spectra for three positions of the spectral slit were obtained: two of them cross the central region of the galaxy and the third one runs along the nearly straight narrow chain of clumps of emission gas with a length of 4–5 kpc. We derived the profiles of velocity, fluxes, and oxygen abundances (O/H) along the slits. We confirm that within the radius of several kpc the galaxy rotates regularly. The maximal value of the rotational velocity allows us to conclude that the dark mass of the galaxy prevails over the mass of its visible components. The observed velocity profile along the peripheral star-forming chain gives pieces of evidence that it is located outside of the plane of the disc, and the gas that formed the chain is probably falling back on to the disc after being ejected from the galaxy. We discuss that the observed chain of clumps is the result of gravitational instability of the gaseous filament.

PERAN KEY OPINION LEADER TERHADAP KEPUTUSAN PEMBELIAN

In general, consumers will decide to purchase goods and services due to low pricing and in conjunction with their earnings level. However at the moment, consumers rely their decision to purchase a piece of apparel on the branded product and the personality who represents the brand. The intention of this study is to use case studies that involve actual consumers to evaluate how customers' decisions to make purchases under the Clarin The Label brand are influenced by key opinion leaders. Similar studies regarding Key Opinion Leaders on Consumer Purchase Decisions have not been found by researchers regarding their partial and simultaneous correlations. So with this it can be novelty in research so that it becomes new knowledge for consumers. This research used a descriptive qualitative methodology. In this study, three respondents were selected using the purposive sample method. The Visibility, Credibility, Attraction, and Power components have been appropriately applied in Rini Florencia's illustration based on the VisCAP model. With this, the Claryn The Label Key Opinion Leader encourages consumers' decision-making over their purchases.

Influence of the thermal expansion on the surface quality of coated and non-coated natural-fiber-reinforced composites

Natural fiber reinforced plastics (NFRP) are increasingly used as a sustainable material alternative to glass or carbon fiber reinforced plastics in lightweight solutions. Visible and/or decorative coated components must meet high surface qualities and defects such as fiber print-through due to different expansion behavior of fiber and matrix are not permitted. Various studies investigate the expansion behavior of NFRP under the influence of temperature and humidity on mechanical properties. In contrast, there are no studies that relate these properties to decoratively coated NFRP and the importance for surface quality. The present study aims to fill this gap using a flax fiber reinforced bio-based epoxy resin (FFRP) manufactured by resin transfer molding process (RTM). The surface roughness and the coefficient of thermal expansion (CTE) were determined as a function of the fiber mass fraction. Further, FFRP and carbon fiber reinforced plastics (CFRP) were decoratively coated and subjected to an alternating climate test. The results showed that reducing the fiber mass fraction of an FFRP to 40 % and using a glass-fiber non-woven on the surface, in combination with 50 % fiber mass fraction, were the most promising methods for reducing roughness in the uncoated state. In addition, the FFRP exhibited an increased CTE longitudinally of 11 ppmK−1 and transversely of 105 ppmK−1 to the fiber direction compared to the CFRP (5 and 79 ppmK−1), along with increased roughness of Ra 0.8 compared to 0.6. The effect of fiber print-through was shown for all variants by the stress in the alternating climate test.

Joint Segmentation and Identification Feature Learning for Occlusion Face Recognition.

The existing occlusion face recognition algorithms almost tend to pay more attention to the visible facial components. However, these models are limited because they heavily rely on existing face segmentation approaches to locate occlusions, which is extremely sensitive to the performance of mask learning. To tackle this issue, we propose a joint segmentation and identification feature learning framework for end-to-end occlusion face recognition. More particularly, unlike employing an external face segmentation model to locate the occlusion, we design an occlusion prediction module supervised by known mask labels to be aware of the mask. It shares underlying convolutional feature maps with the identification network and can be collaboratively optimized with each other. Furthermore, we propose a novel channel refinement network to cast the predicted single-channel occlusion mask into a multi-channel mask matrix with each channel owing a distinct mask map. Occlusion-free feature maps are then generated by projecting multi-channel mask probability maps onto original feature maps. Thus, it can suppress the representation of occlusion elements in both the spatial and channel dimensions under the guidance of the mask matrix. Moreover, in order to avoid misleading aggressively predicted mask maps and meanwhile actively exploit usable occlusion-robust features, we aggregate the original and occlusion-free feature maps to distill the final candidate embeddings by our proposed feature purification module. Lastly, to alleviate the scarcity of real-world occlusion face recognition datasets, we build large-scale synthetic occlusion face datasets, totaling up to 980193 face images of 10574 subjects for the training dataset and 36721 face images of 6817 subjects for the testing dataset, respectively. Extensive experimental results on the synthetic and real-world occlusion face datasets show that our approach significantly outperforms the state-of-the-art in both 1:1 face verification and 1:N face identification.