Production de verre à boire et phénomènes de mode en région parisienne à l'époque moderne

A partir du XVIe siècle et surtout tout au long du XVIIe siècle, la production de verres à boire d'influence italienne s'intensifient marquant les débuts d'une massification de la consommation, en réaction et en lien avec une production ostentatoire des "Venise" et "façons de Venise". Ces productions sont le fruit d'une main d'œuvre qualifiée d'abord italienne et plus particulièrement altaraise qui semble s'adapter à la demande locale. L'absence de sources concernant les productions en provenance des ateliers de fabrication et de toute marque ou signature sur les produits nous a conduit à aborder le complexe technique de production et ses liens avec le marché soumis aux phénomènes de mode par le biais d'une documentation périphérique. Le vaisselier provenant de contextes archéologiques et de collections muséales, l'iconographie relative à ces productions nous ont fourni des informations morphologiques, stylistiques et techniques marqueurs d'évolutions au sein de gammes de production mais également temporelles ou géographiques. L'enregistrement informatique de ces données corrélées à l'étude du réseau technique par le biais d'approches traditionnellement historiques notamment à partir des sources notariales (contrats de ventes, inventaires après décès, livres de compte) montre son potentiel méthodologique pour l'étude de la verrerie à l'époque moderne.During the 16th and more importantly the 17th century, the production of Italian-style drinking glass grows, both following the ostentatious "Venise" and "Façon de Venise" productions and in reaction to them, in the context of the birth of mass consumption. Those glasses are first produced by craftsmen qualified as "Italian", and more specifically Altarists, who adapt to the local demand. The lack of direct documentation about the workshops' production and the absence of any maker's mark or signature on the products themselves led us to consider peripheral sources to study the glassware production technical complex and its links with the evolutions of the market and the related fashion changes. The glassware from archaeological contexts and museum collections and the iconographic record depicting those objects provided us with morphological, stylistic and technical data which allowed us to distinguish different product ranges, as well as to study the variations of those ranges with regard to time and space. The computational processing of those data, linked to classic historical approaches such as notarial sources (sales contracts, post-mortem inventories, account books, etc.), shows its methodological potential for the study of modern glass

The Association between Type and Intensity of Sport and Tobacco or Nicotine Use-A Cross-Sectional Study among Young Swiss Men.

The objective of this study was to assess the association between tobacco/nicotine use and type and intensity of sport. Data were drawn from the second follow-up of the Cohort Study on Substance Use Risk Factors. Young Swiss men completed a questionnaire about tobacco/nicotine use (cigarette, vaping, snus, snuff), type and intensity of sport and other demographic and medical variables. Among the 5414 included participants (mean age 25.5), 3434 (63.4%) reported regularly practicing a sport. They had a lower rate of cigarette smoking (32.3%) compared with participants not practicing a sport (44.6%) but a higher rate of snus use (15.0% vs. 10.0%). In adjusted models, individual-sport participants were less likely to use snus and snuff (OR = 0.63, 95% CI = 0.51-0.77 and OR = 0.73, 95% CI = 0.61-0.88), compared with team-sport participants. The association was inversed for vaping users (OR = 1.54, 95% CI = 1.03-2.30). Furthermore, participants who practiced high-intensity sports had a lower likelihood to smoke cigarettes (OR = 0.63, 95% CI = 0.52-0.78) compared with low-intensity sports. Our findings suggest that type and intensity of sport are associated with tobacco/nicotine use. Youth who practice an individual sport are less likely to use snus or snuff and more likely to vape compared with a team sport. This could help better target smoking prevention in young people

The Determinants of the Preferred Walking Speed in Individuals with Obesity.

The preferred walking speed (PWS), also known as the "spontaneous" or "self-selected" walking speed, is the speed normally used during daily living activities and may represent an appropriate exercise intensity for weight reduction programs aiming to enhance a more negative energy balance. The aim of this study was to examine, simultaneously, the energetics, mechanics, and perceived exertion determinants of PWS in individuals with obesity. Twenty-three adults with obesity (age 32.7 ± 6.8 years, body mass index 33.6 ± 2.6 kg/m2) were recruited. The participants performed 10 min of treadmill familiarization, and PWS was determined. Each subject performed six 5-min walking trials (PWS 0.56, 0.83, 1.11, 1.39, and 1.67 m/s). Gas exchanges were collected and analyzed to obtain the gross energy cost of walking (GCw), rated perceived exertion (RPE) was measured using a 6-20 Borg scale, and the external mechanical work (Wext) and the fraction of mechanical energy recovered by the pendular mechanism (Recovery) were computed using an instrumented treadmill. Second-order least-squares regression was used to calculate the optimal walking speed (OWS) of each variable. No significant difference was found between PWS (1.28 ± 0.13 m/s) and OWS for GCw (1.28 ± 0.10 m/s), RPE cost of walking (1.38 ± 0.14 m/s), and Recovery (1.48 ± 0.27 m/s; p > 0.06 for all), but the PWS was significantly faster than the OWS for Wext (0.98 ± 0.56 m/s; p < 0.02). Multiple regression (r = 0.72; p = 0.003) showed that ∼52% of the variance in PWS was explained by Recovery, Wext, and height. The main finding of this study was that obese adults may select their PWS in function of several competing demands, since this speed simultaneously minimizes pendular energy transduction, energy cost, and perceived exertion during walking. Moreover, recovery of mechanical work, external work, and height seem to be the major determinants of PWS in these individuals

A comparison of vegetable leaves and replicated biomimetic surfaces on the binding of Escherichia coli and Listeria monocytogenes

Biofouling in the food industry is a huge issue, and one possible way to reduce surface fouling is to understand how naturally cleaning surfaces based on biomimetic designs influence bacterial binding. Four self-cleaning leaves (Tenderheart cabbage, Cauliflower, White cabbage and Leek) were analysed for their surface properties and artificial re-plicates were produced. The leaves and surfaces were subjected to attachment, adhesion and retention assays using Escherichia coli and Listeria monocytogenes. For the attachment assays, the lowest cell numbers occurred on the least hydrophobic and smooth surfaces but were higher than the flat control surface, regardless of the strain. Following the ad-hesion assays, using L. monocytogenes, the Tenderheart and Cauliflower biomimetic re-plicated leaves resulted in significantly lowered cell adhesion. Following the retention assays, White cabbage demonstrated lower cell retention for both types of bacteria on the biomimetic replicated surface compared to the flat control surface. The biomimetic sur-faces were also more efficient at avoiding bacterial retention than natural leaves, with reductions of about 1 and 2 Log in L. monocytogenes and E. coli retention, respectively, on most of the produced surfaces. Although the surfaces were promising in reducing bac-terial binding, the results suggested that different experimental assays exerted different influences on the conclusions. This work demonstrated that consideration needs to be given to the environmental factors where the surface is to be used and that bacterial species influence the propensity of biofouling on a surface. (c) 2022 The Author(s). Published by Elsevier Ltd on behalf of Institution of Chemical Engineers. This is an open access article under the CC BY license (http://creative-commons.org/licenses/by/4.0/)

Person identification using deep neural networks on physiological biomarkers during exercise

Much progress has been made in wearable sensors that provide real-time continuous physiological data from non- invasive measurements including heart rate and biofluids such as sweat. This information can potentially be used to identify the health condition of a person by applying machine learning algorithms on the physiological measurements. We present a person identification task that uses machine learning algorithms on a set of biomarkers collected from 30 subjects carrying out a cycling experiment. We compared an SVM and a gated recurrent neural network (RNN) for real-time accuracy using different window sizes of the measured data. Results show that using all biomarkers gave the best results from any of the models. With all biomarkers, the gated RNN model achieved ∼90% accuracy even in a 30 s time window; and ∼92.3% accuracy in a 150 s time window. Excluding any of the biomarkers leads to at least 7.4% absolute accuracy drop for the RNN model. The RNN implementation on the Jetson Nano incurs a low latency of ∼45 ms per inference

Predicting Hydration Status Using Machine Learning Models From Physiological and Sweat Biomarkers During Endurance Exercise: A Single Case Study

Improper hydration routines can reduce athletic performance. Recent studies show that data from noninvasive biomarker recordings can help to evaluate the hydration status of subjects during endurance exercise. These studies are usually carried out on multiple subjects. In this work, we present the first study on predicting hydration status using machine learning models from single-subject experiments, which involve 32 exercise sessions of constant moderate intensity performed with and without fluid intake. During exercise, we measured four noninvasive physiological and sweat biomarkers including heart rate, core temperature, sweat sodium concentration, and whole-body sweat rate. Sweat sodium concentration was measured from six body regions using absorbent patches. We used three machine learning models to determine the percentage of body weight loss as an indicator of dehydration with these biomarkers and compared the prediction accuracy. The results on this single subject show that these models gave similar mean absolute errors, while in general the nonlinear models slightly outperformed the linear model in most of the experiments. The prediction accuracy of using the whole-body sweat rate or heart rate was higher than using core temperature or sweat sodium concentration. In addition, the model trained on the sweat sodium concentration collected from the arms gave slightly better accuracy than from the other five body regions. This exploratory work paves the way for the use of these machine learning models to develop personalized health monitoring together with emerging, noninvasive wearable sensor devices

Drawing inspiration from nature to develop anti-fouling coatings: the development of biomimetic polymer surfaces and their effect on bacterial fouling

The development of self-cleaning biomimetic surfaces has the potential to be of great benefit to human health, in addition to reducing the economic burden on industries worldwide. Consequently, this study developed a biomimetic wax surface using a moulding technique which emulated the topography of the self-cleaning Gladiolus hybridus (Gladioli) leaf. A comparison of topographies was performed for unmodified wax surfaces (control), biomimetic wax surfaces, and Gladioli leaves using optical profilometry and scanning electron microscopy. The results demonstrated that the biomimetic wax surface and Gladioli leaf had extremely similar surface roughness parameters, but the water contact angle of the Gladioli leaf was significantly higher than the replicated biomimetic surface. The self-cleaning properties of the biomimetic and control surfaces were compared by measuring their propensity to repel Escherichia coli and Listeria monocytogenes attachment, adhesion, and retention in mono-and co-culture conditions. When the bacterial assays were carried out in monoculture, the biomimetic surfaces retained fewer bacteria than the control surfaces. However, when using co-cultures of the bacterial species, only following the retention assays were the bacterial numbers reduced on the biomimetic surfaces. The results demonstrate that such surfaces may be effective in reducing biofouling if used in the appropriate medical, marine, and industrial scenarios. This study provides valuable insight into the anti-fouling physical and chemical control mechanisms found in plants, which are particularly appealing for engineering purposes

Analyse de la variabilité de la fréquence cardiaque : méthodes, limites et exemples cliniques [Heart rate variability: methods, limitations and clinical examples]

Heart rate variability (HRV) is an analysis of milliseconds variations in intervals between heartbeats and has become an increasingly used tool for clinical investigation of fatigue, especially in athletes. Eliciting an indirect index of the autonomic nervous system regulation on the heart rate, HRV correlates with different fatigue states and appears to be a powerful biomarker in their monitoring. This article presents the tools to familiarize with this method while detailing good practices for use and interpretation. A method allowing characterization of different fatigue states is also presented for a clinical use with a systemic approach

PCR screening of an African fermented pearl-millet porridge metagenome to investigate the nutritional potential of its microbiota

Cereals are staple foods in most African countries, and many African cereal-based foods are spontaneously fermented. The nutritional quality of cereal products can be enhanced through fermentation, and traditional cereal-based fermented foods (CBFFs) are possible sources of lactic acid bacteria (LAB) with useful nutritional properties. The nutritional properties of LAB vary depending on the species and even on the strain, and the microbial composition of traditional CBFFs varies from one traditional production unit (TPU) to another. The nutritional quality of traditional CBFFs may thus vary depending on their microbial composition. As the isolation of potentially useful LAB from traditional CBFFs can be very time consuming, the aim of this study was to use PCR to assess the nutritional potential of LAB directly on the metagenomes of pearl-millet based fermented porridges (ben-saalga) from Burkina Faso. Genes encoding enzymes involved in different nutritional activities were screened in 50 metagenomes extracted from samples collected in 10 TPUs in Ouagadougou. The variability of the genetic potential was recorded. Certain genes were never detected in the metagenomes (genes involved in carotenoid synthesis) while others were frequently detected (genes involved in folate and riboflavin production, starch hydrolysis, polyphenol degradation). Highly variable microbial composition - assessed by real-time PCR - was observed among samples collected in different TPUs, but also among samples from the same TPU. The high frequency of the presence of genes did not necessarily correlate with in situ measurements of the expected products. Indeed, no significant correlation was found between the microbial variability and the variability of the genetic potential. In spite of the high rate of detection (80%) of both genes folP and folK, encoding enzymes involved in folate synthesis, the folate content in ben-saalga was rather low (median: 0.5 μg/100 g fresh weight basis). This work highlighted the limit of evaluating the nutritional potential of the microbiota of traditional fermented foods by the only screening of genes in metagenomes, and suggests that such a screening should be completed by a functional analysis

Comparison of detection methods used to determine Escherichia coli and meat exudate removal from stainless steel surfaces following different physical cleaning methods.

Food products can be contaminated by residual organic materials and food-borne pathogenic microorganisms through contact with biofouling present on surfaces. Efficient cleaning is needed to maintain hygienic requirements and for quality assurance of food contact surfaces. To evaluate the efficacy of cleaning procedures, it is essential to use reliable detection and quantification methods that can detect both organic material and microorganisms retained on surfaces. Repeated fouling with both organic material (meat exudate) and microorganisms (Escherichia coli) on 304 2B finish stainless steel surfaces was carried out. The surfaces were then cleaned using either a soak, spray or wipe method (in water) in order compare various biofouling detection methods. Following enumeration of the microorganisms by plate counting, the results demonstrated that the soak and spray washes were the best cleaning methods, whereas the wipe clean produced the least hygienic surface. ATP bioluminescence further demonstrated that the spray cleaned surface was the most hygienic followed by the soaked cleaned surfaces. However, percentage coverage counts demonstrated that the number of retained cells on following the soak wash was the greatest (77.38 % after 30 washes) and the amount of organic material retained was greater than 50% on all the surfaces, and was not significantly different between the different types of cleans or number of washes. Visualisation of the surfaces using epifluorescence microscopy and scanning electron microscopy demonstrated that the soak clean was the least hygienic in terms of bacterial retention. This suggests that the biofouling on the surface was difficult to remove following the soak cleaning method. UV detection demonstrated that it was difficult to detect organic material, regardless of the cleaning method used. However, when using more intense UV at selected wavelengths, the 330 nm - 360 nm illuminated the retained biofouling on the surfaces with the greatest intensity. The use of the different cleaning assays resulted in differences in cell and organic material distribution across the surfaces. The recorded level of contamination varied depending on the detection method used in this study. Our results highlighted that, in addition to the quantification method, visual images and quantification may help to better understand the fouling process on surfaces since certain cleaning methods may result in organic material being difficult to remove and detect