Virtual fit and design improvements of a filtering half-mask for sub-adult wearers.

The recent pandemic has shown that protecting the general population from hazardous substances or pathogens can be a challenging and urgent task. The key element to adequate protection is appropriately sized, well-fitted and sufficiently distributed personal protective equipment (PPE). While these conditions are followed for adult PPE wearers, they are less considered when it comes to protecting subadults. In this study, the assessment of the fit and design improvements of a 3D-printed facial half mask for subadult wearers (4-18 years) is designed. The target population was represented by 1137 subadults, aged 4.06-18.94 years, for whom 3D face models were acquired. The half mask tested, which was originally provided in one subadult size, did not fit appropriately the target population. This finding prompted the creation of four size categories using the age-dependent distribution of the centroid size calculated from 7 facial landmarks. For each size category, a modified half-mask virtual design was created, including resizing and reshaping, and fit was evaluated visually and numerically using averaged and random 3D face representatives.Practitioner summary: The reason for this study was to describe procedures which led to design improvement of an existing half-mask and provide respiratory protection for subadults. To address this, fit was assessed using an innovative metric approach. Four sizes were then created based on centroid size, resulting in improved fit and design.Abbreviations: CH: cheilion landmark; CS: centroid size; EX: exocanthion landmark; GN: gnathion landmark; N: nasion landmark; PPE: personal protective equipment; PR: pronasale landmark; RPE: respiratory protective equipment.

3D human face dataset was used for modifying and validating protective equipment for subadultsTo ensure optimal protection for subadults, four size categories were proposed based on 3D face landmarks and centroid sizeModified half-mask design fit was validated virtually using a visual and numerical approach.

Studying factors influencing facial developmental instability.

BACKGROUND: Developmental instability is a component of non-genetic variation that results from random variation in developmental processes. It is considered a sensitive indicator of the physiological state of individuals. It is reflected in various ways, but in this study we focussed on its reflection in fluctuating asymmetry (FA) and morphological integration. AIM: To assess how, if at all, variations of facial morphology mirror developmental instability across childhood with respect to sex, growth rate and socioeconomic/environmental factors. SUBJECTS AND METHODS: A set of 210 three-dimensional facial models (of children aged between 6.3 and 14.3 years) originating from the FIDENTIS 3D Face Database was subjected to landmark-based methods of geometric morphometrics to quantify the degree of facial asymmetry and facial morphological integration. In addition, the association with age, sex, and socioeconomic factors was assessed. RESULTS: Our results showed a nonlinear increase of FA with age up to the age of 14 years. The pattern of sex-related variants in facial FA differed in relation to age, as girls exhibited higher values of FA than boys up to the age of 9 years. We found that a signal of modularity based on functional demands and organisation of the face is of particular importance. Here, girls exhibited higher morphological covariation among modules. During more rapid adolescence-related growth, however, covariation among modules at the asymmetrical level decreased in both sexes. CONCLUSION: We can conclude that facial morphology was shown to be strongly integrated, particularly until adolescence. This covariation can facilitate an increase of FA. In addition, the results of this study indicate there is a weak association between socioeconomic stress and facial asymmetries. In contrast, sex and growth rate are reflected in developmental instability.

Impact of Antibiotics Associated with the Development of Toxic Epidermal Necrolysis on Early and Late-Onset Infectious Complications.

Toxic epidermal necrolysis (TEN) is a rare disease, which predominantly manifests as damage to the skin and mucosa. Antibiotics count among the most common triggers of this hypersensitive reaction. Patients with TEN are highly susceptible to infectious complications due to the loss of protective barriers and immunosuppressant therapy. The aim of this study was to investigate the potential relationship between antibiotics used before the development of TEN and early and late-onset infectious complications in TEN patients. In this European multicentric retrospective study (Central European Lyell syndrome: therapeutic evaluation (CELESTE)), records showed that 18 patients with TEN used antibiotics (mostly aminopenicillins) before the disease development (group 1), while in 21 patients, TEN was triggered by another factor (group 2). The incidence of late-onset infectious complications (5 or more days after the transfer to the hospital) caused by Gram-positive bacteria (especially by Enterococcus faecalis/faecium) was significantly higher in group 1 than in group 2 (82.4% vs. 35.0%, p = 0.007/p corr = 0.014) while no statistically significant difference was observed between groups of patients with infection caused by Gram-negative bacteria, yeasts, and filamentous fungi (p > 0.05). Patients with post-antibiotic development of TEN are critically predisposed to late-onset infectious complications caused by Gram-positive bacteria, which may result from the dissemination of these bacteria from the primary focus.

Age verification using random forests on facial 3D landmarks.

Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces - The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests: I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4%-91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.