[Le port du masque affecte l'identification des expressions faciales émotionnelles, surtout chez les personnes âgées]. / Wearing face masks makes identifying emotional facial expressions harder, especially for older adults.

Younger adults have difficulties identifying emotional facial expressions from faces covered by face masks. It is important to evaluate how face mask wearing might specifically impact older people, because they have lower emotion identification performance than younger adults, even without face masks. We compared performance of 62 young and 38 older adults in an online task of emotional facial expression identification using masked or unmasked pictures of faces with fear, happiness, anger, surprise, and neutral expression, from different viewpoints. Face masks affected performance in both age groups, but more so in older adults, specifically for negative emotions (anger, fear), in favour of the saliency hypothesis as an explanation for the positive advantage. Additionally, face masks more affected emotion recognition on profile than on three-quarter or full-face views. Our results encourage using clearer and full-face expressions when dealing with older people while wearing face masks.

Evaluation of eyelid features' changes before and after COVID-19 pandemic amongst healthcare and home office workers.

PURPOSE: To evaluate the eyelid features' changes after N95 face mask (FM) usage in healthcare workers through the new type of Coronavirus Disease 2019 (COVID-19) pandemic and make a comparison with home-office workers as a control group with a computer vision algorithm. MATERIALS AND METHODS: Sixty healthcare workers and forty control participants with similar demographic features included. Standardized biometric photographs which were taken before and after the COVID-19 pandemic, analyzed by the ImageJ program (NIH, Bethesda, Md.) software. The distances between the central light reflex on the cornea and the upper (UE) and lower eyelid (LE) were recorded as the marginal reflex distances. (MRD1, MRD2 respectively) Parameters of pretarsal show (PTS) of UE and brow pupil diameter (BPD) were analyzed for both of the eyes. RESULTS: There were no significant differences among the groups' measurements before the COVID-19 pandemic. In healthcare workers' group after the pandemic, values of MRD1, PTS, BPD showed a significant decrease in their right eye (p = 0.001, p = 0.002, p = 0.001 respectively) and same values reduced in the left eyes as well when compared with pre-pandemic measurements. (p = 0.048, p = 0.001, p = 0.001 respectively) PTS and BPD values were decreased for both right and left eyes of the controls. (p = 0.044, p = 0.001 and p = 0.001, p = 0.001 respectively) MRD1 measurements after the pandemic showed no difference either in the right or left eyes of the control group after the pandemic. (p = 0.071 and p = 0.065 respectively). DISCUSSION: Results showed that both BPD and PTS values decreased independently from the previous FM usage in both of the groups. Even though MRD1 values remained within the normal values, a significant decrease was detected in the healthcare workers group which suggested the cause was newly developed upper eyelid (UE) dermatochalasis after long hours of FM usage. Although it is hard to make a truly objective evaluation both usage of standardized biometric photographs and a computer-based measurement system makes the results reliable.

MetaV: A Pioneer in feature Augmented Meta-Learning Based Vision Transformer for Medical Image Classification.

Image classification, a fundamental task in computer vision, faces challenges concerning limited data handling, interpretability, improved feature representation, efficiency across diverse image types, and processing noisy data. Conventional architectural approaches have made insufficient progress in addressing these challenges, necessitating architectures capable of fine-grained classification, enhanced accuracy, and superior generalization. Among these, the vision transformer emerges as a noteworthy computer vision architecture. However, its reliance on substantial data for training poses a drawback due to its complexity and high data requirements. To surmount these challenges, this paper proposes an innovative approach, MetaV, integrating meta-learning into a vision transformer for medical image classification. N-way K-shot learning is employed to train the model, drawing inspiration from human learning mechanisms utilizing past knowledge. Additionally, deformational convolution and patch merging techniques are incorporated into the vision transformer model to mitigate complexity and overfitting while enhancing feature representation. Augmentation methods such as perturbation and Grid Mask are introduced to address the scarcity and noise in medical images, particularly for rare diseases. The proposed model is evaluated using diverse datasets including Break His, ISIC 2019, SIPaKMed, and STARE. The achieved performance accuracies of 89.89%, 87.33%, 94.55%, and 80.22% for Break His, ISIC 2019, SIPaKMed, and STARE, respectively, present evidence validating the superior performance of the proposed model in comparison to conventional models, setting a new benchmark for meta-vision image classification models.

Environmental risks of mask wastes binding pollutants: Phytotoxicity, microbial community, nitrogen and carbon cycles.

The increasing contamination of mask wastes presents a significant global challenge to ecological health. However, there is a lack of comprehensive understanding regarding the environmental risks that mask wastes pose to soil. In this study, a total of 12 mask wastes were collected from landfills. Mask wastes exhibited negligible morphological changes, and bound eight metals and four types of organic pollutants. Masks combined with pollutants inhibited the growth of alfalfa and Elymus nutans, reducing underground biomass by 84.6 %. Mask wastes decreased the Chao1 index and the relative abundances (RAs) of functional bacteria (Micrococcales, Gemmatimonadales, and Sphingomonadales). Metagenomic analysis showed that mask wastes diminished the RAs of functional genes associated with nitrification (amoABC and HAO), denitrification (nirKS and nosZ), glycolysis (gap2), and TCA cycle (aclAB and mdh), thereby inhibiting the nitrogen transformation and ATP production. Furthermore, some pathogenic viruses (Herpesviridae and Tunggulvirus) were also found on the mask wastes. Structural equation models demonstrated that mask wastes restrained soil enzyme activities, ultimately affecting nitrogen and carbon cycles. Collectively, these evidences indicate that mask wastes contribute to soil health and metabolic function disturbances. This study offers a new perspective on the potential environmental risks associated with the improper disposal of masks.

A Dynamic Multi-Scale Convolution Model for Face Recognition Using Event-Related Potentials.

With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP components and the representation of familiar and unfamiliar faces. To address this, this paper proposes a model based on Dynamic Multi-Scale Convolution for group recognition of familiar and unfamiliar faces. This approach uses generated weight masks for cross-subject familiar/unfamiliar face recognition using a multi-scale model. The model employs a variable-length filter generator to dynamically determine the optimal filter length for time-series samples, thereby capturing features at different time scales. Comparative experiments are conducted to evaluate the model's performance against SOTA models. The results demonstrate that our model achieves impressive outcomes, with a balanced accuracy rate of 93.20% and an F1 score of 88.54%, outperforming the methods used for comparison. The ERP data extracted from different time regions in the model can also provide data-driven technical support for research based on the representation of different ERP components.

Detecting Internal Defects in FRP-Reinforced Concrete Structures through the Integration of Infrared Thermography and Deep Learning.

This study represents a significant advancement in structural health monitoring by integrating infrared thermography (IRT) with cutting-edge deep learning techniques, specifically through the use of the Mask R-CNN neural network. This approach targets the precise detection and segmentation of hidden defects within the interfacial layers of Fiber-Reinforced Polymer (FRP)-reinforced concrete structures. Employing a dual RGB and thermal camera setup, we captured and meticulously aligned image data, which were then annotated for semantic segmentation to train the deep learning model. The fusion of the RGB and thermal imaging significantly enhanced the model's capabilities, achieving an average accuracy of 96.28% across a 5-fold cross-validation. The model demonstrated robust performance, consistently identifying true negatives with an average specificity of 96.78% and maintaining high precision at 96.42% in accurately delineating damaged areas. It also showed a high recall rate of 96.91%, effectively recognizing almost all actual cases of damage, which is crucial for the maintenance of structural integrity. The balanced precision and recall culminated in an average F1-score of 96.78%, highlighting the model's effectiveness in comprehensive damage assessment. Overall, this synergistic approach of combining IRT and deep learning provides a powerful tool for the automated inspection and preservation of critical infrastructure components.

Antimicrobial Face Masks and Mask Covers with a Salt-Coated Stacked Spunbond Polypropylene Fabric: Effective Inactivation of Resilient Pathogens and Prevention of Contact Transmission.

In response to the ongoing threat posed by respiratory diseases, ensuring effective transmission protection is crucial for public health. To address the drawbacks of single-use face masks/respirators, which can be a potential source of contact-based transmission, we have designed an antimicrobial face mask and mask covering utilizing a stack of salt-coated spunbond (SB) fabric. This fabric acts as an outer layer for the face mask and as a covering over a conventional mask, respectively. We evaluated the universal antimicrobial performance of the salt-coated three-stacked SB fabric against enveloped/nonenveloped viruses and spore-forming/nonspore-forming bacteria. The distinctive pathogen inactivation efficiency was confirmed, including resistant pathogens such as human rhinovirus and Clostridium difficile. In addition, we tested other filter attributes, such as filtration efficiency and breathability, to determine the optimal layer for salt coating and its effects on performance. Our findings revealed that the outer layer of a conventional face mask plays a crucial role in contact transmission through contaminated face masks and respirators. Through contact transmission experiments using droplets involving three types of contaminants (fluorescent dyes, bacteria, and viruses), the salt-coated stacked SB fabric demonstrated a superior effect in preventing contact transmission compared to SB or meltblown polypropylene fabrics─an issue challenging to existing masks. Our results demonstrate that the use of salt-coated stacked SB fabrics as (i) the outer layer of a mask and (ii) a mask cover over a mask enhances overall filter performance against infectious droplets, achieving high pathogen inactivation and low contact-based transmission while maintaining breathability.

Efficiency of Combining Heated Eye Mask with Intense Pulsed Light Therapy as a Treatment Option for Evaporative Dry Eye Disease.

Background and objectives: The study aimed to establish the efficiency of combining the Posiforlid heated eye mask with intense pulsed light therapy (IPL), as a treatment strategy for evaporative dry eye disease. Materials and methods: This study included 110 patients, respectively 220 eyes, diagnosed with evaporative dry eye disease, patients between 18 and 86 years old, divided into two study groups. The first one, the control group, consisted of 73 patients treated with IPL therapy, and the second of 37 patients, who underwent IPL therapy associated with Posiforlid heated eye mask. Subjective evolution was assessed using an eye fitness test (EFT) regarding symptomatology. Objective assessment of the ocular surface was performed by tear film stability evaluation (TFSE), non-invasive first break-up time (NIFBUT), non-invasive average breakup time (NIABUT), ocular surface inflammatory evaluation (OSIE), measuring of the central tear meniscus height (CTMH) and thinnest tear meniscus height (TTMH). The assessment was performed at the beginning of the IPL treatment, during the IPL sessions, at the end of the IPL treatment, and afterward, at 3, 6, and 12 months. Results: Tear film stability has increased in both study cases, but no statistically significant difference was observed between the two groups studied. For the control group, tear film stability evaluation (TFSE) started from 310.56 ± 389.54 at baseline (time 1 presentation) to 114.40 ± 122.90 after 12 months, and for the heated mask group, from 391.11 ± 456.45 (time 1 presentation) to 97.38 ± 105.98 after 12 months. NIABUT increased from 10.72 ± 4.90 seconds to 14.79 ± 3.72 seconds in the control group, and from 11.11 ± 5.08 seconds to 15.84 ± 2.26 seconds in the second group. OSIE decreased, as expected, from 7.18 ± 7.93 percent in the control group to 2.24 ± 2.38 percent after 12 months and from 7.42 ± 7.77 percent to 2.47 ± 2.50 percent in the Posiforlid group. Although significantly lower, there was no significant difference between the two studied groups. No statistically significant changes were registered in the studied quantitative parameters. Using the EFT test, great improvements were registered regarding symptomatology, with a score increasing from 29.99 ± 8.60 to 39.10 ± 5.08 in the control group and from 27.35 ± 9.24 to 38.35 ± 4.62 in the other group. Again, the same statistical result was registered on this variable. Conclusions: The improvement of tear film stability, ocular surface inflammatory condition, and subjective symptoms during IPL therapy sessions and the first year of observation after the completion of the treatment was not necessarily increased by the additional use of a heated eye mask. Abbreviations: IPL = intense pulsed light therapy, EFT = eye fitness test, NIFBUT = non-invasive first break-up time, NIABUT = non-invasive average break-up time, OSIE = ocular surface inflammatory evaluation, TFSE = tear film stability evaluation, CTMH = central tear meniscus height, TTMH = thinnest tear meniscus height, DED = dry eye disease, MGD = meibomian gland dysfunction, SD = standard deviation.

Fabric structure and polymer composition as key contributors to micro(nano)plastic contamination in face masks.

The surge in face mask use due to COVID-19 has raised concerns about micro(nano)plastics (MNPs) from masks. Herein, focusing on fabric structure and polymer composition, we investigated MNP generation characteristics, mechanisms, and potential risks of surgical polypropylene (PP) and fashionable polyurethane (PU) masks during their wearing and photoaging based on stereomicroscope, µ-Fourier transform infrared spectroscopy (µ-FTIR), and scanning electron microscope (SEM) techniques. Compared with new PP and PU masks (66 ± 16 MPs/PP-mask, 163 ± 83 MPs/PU-mask), single- and multiple-used masks exhibited remarkably increased MP type and abundance (600-1867 MPs/PP-mask, 607-2167 MPs/PU-mask). Disinfection exacerbated endogenous MP generation in masks, with washing (416 MPs/PP-mask, 30,708 MPs/PU-mask) being the most prominent compared to autoclaving (219 MPs/PP-mask, 553 MPs/PU-mask) and alcohol spray (162 MPs/PP-mask, 18,333 MPs/PU-mask). Photoaging led to massive generation of MPs (8.8 × 104-3.7 × 105 MPs/PP-layer, 1.0 × 105 MPs/PU-layer) and NPs (5.2 × 109-3.6 × 1013 NPs/PP-layer, 3.5 × 1012 NPs/PU-layer) from masks, presenting highly fabric structure-dependent aging modes as "fragmentation" for fine fiber-structure PP mask and "erosion" for 3D mesh-structure PU mask. The MNPs derived from PP/PU mask caused significant deformities of Zebrafish (Danio rerio) larvae. These findings underscore the potential adverse effects of masks on humans and aquatic organisms, advocating to enhance proper use and rational disposal for masks.

Effects of Mask Usage During the COVID-19 Pandemic on Sign and Symptoms of Temporomandibular Joint Disorder: A Survey Study.

Objective: To evaluate possible temporomandibular disorders (TMD) symptoms that may occur due to mask use in dentists during the coronavirus disease-2019 pandemic period and identify potentially effective factors. Methods: An online questionnaire consisting of three parts was sent to dentists and clinical dental students. The first part included questions regarding sociodemographic information. In the second part, questions were asked to evaluate stress levels, TMD symptoms, and treatment of TMD, if any, before (T0) and during the pandemic (T1). In the last part, professional mask choice, mask-related parafunctional movements, and breathing patterns while wearing a mask were evaluated. Results: TMD symptoms and stress levels were significantly higher at T1. An increase in mouth breathing and mask-related parafunctional movements was reported during the use of N95 masks compared with daily life in dentists whose professional mask selection was an N95 respirator. The change in temporomandibular joints pain and muscle pain at rest between T0 and T1 was higher in those whose professional mask choice was N95 respirators than in those who chose to wear one surgical mask. Conclusion: The increase in mouth breathing and mask-related parafunctional movements during the use of N95 respirators may increase TMD.

Variation in the fitted filtration efficiency of disposable face masks by sex.

BACKGROUND & OBJECTIVE: Disposable face masks are a primary protective measure against the adverse health effects of exposure to infectious and toxic aerosols such as airborne viruses and particulate air pollutants. While the fit of high efficiency respirators is regulated in occupational settings, relatively little is known about the fitted filtration efficiencies of ear loop style face masks worn by the public. METHODS: We measured the variation in fitted filtration efficiency (FFE) of four commonly worn disposable face masks, in a cohort of healthy adult participants (N = 100, 50% female, 50% male, average age = 32.3 ± 9.2 years, average BMI = 25.5 ± 3.4) using the U.S. Occupational Safety and Health Administration Quantitative Fit Test, for an N95 (respirator), KN95, surgical, and KF94 masks. The latter three ear loop style masks were additionally tested in a clip-modified condition, tightened using a plastic clip to centrally fasten loops in the back of the head. RESULTS: The findings show that sex is a major determinant of the FFE of KN95, surgical, and KF94 masks. On average, males had an 11% higher FFE relative to females, at baseline testing. We show that a simple modification using an ear loop clip, results in improvements in the average FFE for females but provides comparatively minor changes for males. On average, females had a 20% increased FFE when a clip was worn behind the head, relative to a 6% increase for males. IMPACT: The efficacy of a disposable face mask as protection against air contaminants depends on the efficiency of the mask materials and how well it fits the wearer. We report that the sex of the wearer is a major determinant of the baseline fitted filtration efficiency (FFE) of commonly available ear loop style face masks. In addition, we show that a simple fit modifier, an ear loop clip fastened behind the head, substantially improves baseline FFE for females but produces only minor changes for males. These findings have significant public health implications for the use of face masks as a protective intervention against inhalational exposure to airborne contaminants.

The beneficial effect of transparent surgical masks on the communication of adults with hearing loss within clinical settings.

Purpose: The study examined the benefits of transparent versus non-transparent surgical masks on the speech intelligibility in quiet of adult cochlear implant (CI) users, in conjunction with patient preferences and the acoustic effects of the different masks on the speech signal.Methods: Speech tracking test (STT) scores and acoustical characteristics were measured in quiet for live speech in three different conditions, without mask, with a non-transparent surgical mask and with a transparent surgical mask. Patients were asked about their experience with the face masks. The study sample consists of 30 patients using a cochlear implant.Results: We found a significant difference in speech perception among all conditions, with the speech tracking scores revealing a significant advantage when switching from the non-transparent surgical mask to the transparent one. The transparent surgical mask, although it does not transmit high frequencies effectively, seems to have minimal effect on speech comprehension in practice when lip movements are visible. This substantial benefit is further emphasized in the questionnaire, where 82% of the patients express a preference for the transparent surgical mask.Conclusion: The study highlights significant benefits for patients in speech intelligibility in quiet with the use of medically safe transparent facemasks. Transitioning from standard surgical masks to transparent masks demonstrates highly significant effectiveness and patient satisfaction for patients with hearing loss. This research strongly advocates for the implementation of transparent masks in broader hospital and perioperative settings.

In scenarios mandating mask usage, it's advisable for caregivers to opt for transparent surgical masks. Specifically within perioperative settings, where patients might not be able to utilise their hearing aids or cochlear implants, it becomes imperative for all caregivers to consistently wear transparent surgical masks to prevent communication impediments.When utilising a transparent surgical mask, caregivers must recognise that sound may be altered and maintaining a clear view of the face and lips is crucial for effective communication.

Airflow detailed analysis through a face mask using the schlieren technique.

This work presents an exhaustive visualization of the airflow expulsed by a person while breathing, talking, exhaling, and blowing inside a closed room wearing a disposable face mask like those used in hospitals for patient protection and those who care for them. An optical schlieren experimental arrangement was used to obtain some of the relevant physical characteristics of the airflow, such as its refractive index gradient, the distribution of temperature, and the associated velocity field for all the tests developed. We tested three face masks, one of the surgical types and the others of the N95 series with denominations KN95 and 3MN95 (Aura TC-84A-8590). The results show appreciable differences between the masks evaluated; the surgical mask was the one that allowed the most abrupt output airflow through it in the field of view of the experimental setup. However, were also found some differences in the performance of the KN95 and 3MN95 masks. The KN95 face mask had the best performance since it expulsed to its surroundings the lowest airflow with different physical properties to the input airflow. The results obtained are relevant since it was possible to estimate the expulsed airflow velocity as a function of the distance for every face mask tested, which allows for understanding its filtering capacity by restricting the flow of potential pathogens from the mouth or nose of one person to another. Undoubtedly, the airflow behavior determination around a face mask can help to reduce the risk of spreading infectious airborne particles.

On-mask detection of SARS-CoV-2 related substances by surface enhanced Raman scattering.

We have developed a convenient surface-enhanced Raman scattering (SERS) platform based on vertical standing gold nanowires (v-AuNWs) which enabled the on-mask detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) related substances such as the Spike-1 protein and the corresponding pseudo-virus. The Spike-1 protein was clearly distinguished from BSA protein with an accuracy above 99 %, and the detection limit could be achieved down to 0.01 µg/mL. Notably, a similar accuracy was achieved for the pseudo-SARS-CoV-2 (pSARS-2) virus as compared to the pseudo-influenza H7N9 (pH7N9) virus. The sensing strategy and setups could be easily adapted to the real SARS-CoV-2 virus and other highly contagious viruses. It provided a promising way to screen the virus carriers by a fast evaluation of their wearing v-AuNWs integrated face-mask which was mandatory during the pandemic.

Masked distress: The mediated effects of face masks on physical and emotional suffocation.

This study explores the effects of bodily states on emotions based on embodied cognition theories of conceptual metaphor and feelings-as-information theory. Specifically, it investigates how physical suffocation induced by mask-wearing affects perceptions of emotional suffocation related to one's romantic relationship and financial situation. In this quantitative online experiment, we employed a convenience sampling method through a crowdsourcing platform. Adult participants (N = 180, 25 years or older and involved in a romantic relationship) were randomly assigned to three conditions: wearing COVID-19 masks properly, wearing masks on their chins, or not wearing masks. After completing a puzzle meant to prolong mask-wear, participants filled out digital questionnaires assessing their experiences of physical and psychological distress. The results supported our proposed mechanisms, revealing that increased feeling of physical suffocation while wearing masks properly, compared to the other conditions, was linked to heightened feelings of financial and romantic distress, supporting the conceptual metaphor account. This link was partially mediated by elevated state anxiety, aligning with the feelings-as-information theory. This study demonstrates how bodily experiences can impact emotional states, and highlights the complex interplay between everyday behaviours like mask-wearing and emotions.

The Impact of Mask-Wearing on Allergic Rhinitis Symptoms During the COVID-19 Pandemic Among the Saudi Population: A Cross-Sectional Study.

BACKGROUND: Allergic rhinitis (AR) is an inflammatory disease of the nasal mucosa caused by certain allergens that may be found indoors or outdoors, and it greatly impacts the patient's quality of life. The COVID-19 epidemic offers an excellent chance to examine how using a face mask affects allergy. AIM: The present study aimed to evaluate the impact of face mask wearing on AR symptoms among subjects living in the northern, southern, eastern, western, and central regions of Saudi Arabia. SUBJECTS AND METHODS: This cross-sectional, survey-based study was undertaken in all Saudi Arabia regions in 2022. We included female and male adults living in Saudi Arabia who have AR and completed the Arabic version of an electronic self-administered questionnaire. RESULTS: The overall received responses were 2252. According to the study eligibility criteria, we assessed the data of 470 participants who self-reported to have been diagnosed with AR. There was no significant change in the proportions of nasal symptoms severity before and after wearing face masks during the pandemic (p = 0.867), while a significant negative change was observed in the rates of moderate and severe ophthalmic symptoms (p < 0.001). The need for AR drugs was significantly increased during the pandemic (no need for drugs was reported by 45.3% before the pandemic and by 37.9% during the pandemic, p < 0.001). However, the use of AR drugs was significantly associated with the improvement of AR symptoms (p < 0.001); complete and partial eliminations of AR symptoms were higher with the use of masks during the pandemic (11.3% and 36.8%) than before the pandemic period (10.6% and 34.5%). CONCLUSIONS: Face mask usage was not associated with improved symptoms or severity of AR. Wearing the masks was associated with increased severity of ophthalmic symptoms. The use of face masks was associated with a significant increase in the partial and complete elimination of AR symptoms with the use of AR drugs, particularly with the constant use of masks.

A two-center randomized controlled trial of a repairing mask as an adjunctive treatment for mild to moderate rosacea.

OBJECTIVE: To investigate the efficacy and safety of a repairing mask as an adjunctive treatment for skin barrier maintenance of mild to moderate rosacea. METHODS: Patients with rosacea were recruited in this dual center randomized controlled trial from November 2019 to December 2021. A total of 64 patients were included and randomized into two groups at a ratio of 3:1 into a mask group (n = 47) and a control group (n = 17). Patients in the mask group received treatment with Dr. Yu Centella asiatica repairing facial mask three times weekly for a duration of 6 weeks. All participants were instructed to continue their regimen of 50 mg oral minocycline twice daily and to apply Dr. Yu Intensive Hydrating Soft Cream twice daily. The primary endpoint of this study was the Investigator Global Assessment (IGA) score. RESULTS: A total of 54 patients completed this trial, with 41 in the mask group and 13 in the control group. After using this facial mask for 3 and 6 weeks, the IGA, facial skin dryness, facial flushing, and severity of skin lesion in the mask group showed significantly improvement (p < 0.05). Moreover, the change in the delta degree of skin flushing was significantly higher than that in the control group (p = 0.037). Throughout the study, no adverse events were reported in either group of participants. CONCLUSION: The Dr. Yu Centella asiatica repairing facial mask, as an adjunctive treatment of rosacea, appears to effectively repair and protect the skin barrier, alleviate cutaneous symptoms of rosacea, and is both efficacious and safe for patient use.

Unsupervised stain augmentation enhanced glomerular instance segmentation on pathology images.

PURPOSE: In pathology images, different stains highlight different glomerular structures, so a supervised deep learning-based glomerular instance segmentation model trained on individual stains performs poorly on other stains. However, it is difficult to obtain a training set with multiple stains because the labeling of pathology images is very time-consuming and tedious. Therefore, in this paper, we proposed an unsupervised stain augmentation-based method for segmentation of glomerular instances. METHODS: In this study, we successfully realized the conversion between different staining methods such as PAS, MT and PASM by contrastive unpaired translation (CUT), thus improving the staining diversity of the training set. Moreover, we replaced the backbone of mask R-CNN with swin transformer to further improve the efficiency of feature extraction and thus achieve better performance in instance segmentation task. RESULTS: To validate the method presented in this paper, we constructed a dataset from 216 WSIs of the three stains in this study. After conducting in-depth experiments, we verified that the instance segmentation method based on stain augmentation outperforms existing methods across all metrics for PAS, PASM, and MT stains. Furthermore, ablation experiments are performed in this paper to further demonstrate the effectiveness of the proposed module. CONCLUSION: This study successfully demonstrated the potential of unsupervised stain augmentation to improve glomerular segmentation in pathology analysis. Future research could extend this approach to other complex segmentation tasks in the pathology image domain to further explore the potential of applying stain augmentation techniques in different domains of pathology image analysis.

The role of the environment: how mask wearing varies across different activities.

BACKGROUND: People's decisions to engage in protective health behaviors, such as mask wearing during the COVID-19 pandemic, are influenced by environmental and social contexts. Previous research on mask wearing used a single question about general mask usage in public, which may not reflect actual behavior in every setting. The likelihood of wearing a mask during one activity is also related to the likelihood of wearing a mask in another or avoiding an activity entirely. This analysis compared responses between a general question and activity-specific questions and identified patterns of mask-wearing behavior across activities. METHODS: Online, opt-in, cross-sectional surveys were conducted every 2 months from November 2020 to May 2021 (n = 2508), with quota sampling and weighting to achieve a representative sample of the U.S. POPULATION: Respondents were asked how frequently they wore a mask in public and during 12 specific activities including: on public transportation, while shopping, and attending social gatherings indoors and outdoors. Spearman's rank order correlation was used to compare the frequency of mask wearing reported using a general question versus an activity specific question. Additionally, a latent class analysis was conducted to identify patterns of mask wearing behavior across activities. RESULTS: There was little to no correlation (r = .16-0.33) between respondents' general attitudes towards mask wearing and their reported frequency of mask wearing in different activities. Latent class analysis identified six distinct groups based on their mask wearing behaviors and avoidance of certain activities. The largest group (29%) avoided ten of the twelve activities and always wore a mask during activities that could not be avoided. Additional groups included those who avoided most activities but made exceptions when around friends or family (20%), part time mask wearers (18%), and never mask wearers (6%). CONCLUSIONS: The findings suggest that activity-specific questions provide more accurate and useful information than a single general question. Specific, context based, questions allow for analyses that consider the nuances of people's decision-making regarding engaging in protective health behaviors, such as mask wearing, thus enabling public health professionals to create targeted guidelines and messages.

An Enhanced Mask R-CNN Approach for Pulmonary Embolism Detection and Segmentation.

Pulmonary embolism (PE) refers to the occlusion of pulmonary arteries by blood clots, posing a mortality risk of approximately 30%. The detection of pulmonary embolism within segmental arteries presents greater challenges compared with larger arteries and is frequently overlooked. In this study, we developed a computational method to automatically identify pulmonary embolism within segmental arteries using computed tomography (CT) images. The system architecture incorporates an enhanced Mask R-CNN deep neural network trained on PE-containing images. This network accurately localizes pulmonary embolisms in CT images and effectively delineates their boundaries. This study involved creating a local data set and evaluating the model predictions against pulmonary embolisms manually identified by expert radiologists. The sensitivity, specificity, accuracy, Dice coefficient, and Jaccard index values were obtained as 96.2%, 93.4%, 96.%, 0.95, and 0.89, respectively. The enhanced Mask R-CNN model outperformed the traditional Mask R-CNN and U-Net models. This study underscores the influence of Mask R-CNN's loss function on model performance, providing a basis for the potential improvement of Mask R-CNN models for object detection and segmentation tasks in CT images.