Clermont Auvergne INP

Research about stigmatization in eating disorders (EDs) has highlighted stereotypes, prejudices, and discrimination against people with EDs, as well as their harmful effects on them, including self-stigma and a difficult recovery process. Whereas a recent review focused on the consequences of ED stigma, our work aimed to provide a broader synthesis of ED stigma, including its consequences, but also its content and distribution. More precisely, we focused on three EDs-namely, anorexia nervosa, bulimia nervosa, and binge eating disorder. Based on a systematic search of four major databases in psychology, the present scoping review includes 46 studies published between 2004 and 2021. We did not conduct any quality assessment of the studies included, because our aim was to provide a wide-ranging overview of these topics instead of an appraisal of evidence answering a precise research question. The review confirmed the existence of a common ED stigma: all individuals affected by EDs reviewed here were perceived as responsible for their situation, and elicited negative emotions and social distance. However, our review also depicted a specific stigma content associated with each ED. In addition, the demographic characteristics of the stigmatizing individuals had a notable influence on the extent of ED stigma: men, young adults, and low-income individuals appeared to be the most stigmatizing toward individuals with EDs. It is important to note that ED stigma had a negative effect on individuals' eating disorders, psychological wellbeing, and treatment-seeking behavior. There is an urgent need for further research on the adverse effects of ED stigma and its prevention.

Empirical studies have noticed the differing impact of product and process innovation on international competitiveness, the level of employment and the types of skills used, and on the profit rate of firms (Vernon, 1966; Rottmann and Ruschinski, 1997; Duguet and Greenan, 1997; Capon et al., 1992). These studies show that the type of innovative behaviour of firms is important. However, little is known from either a theoretical or an empirical point of view, about the determinants of these different types of innovation. Therefore, the purpose of this study is to identify the microeconomic determinants of the innovative behaviour of French manufacturing firms. Studying a sample of innovative firms, we try to understand why they develop product innovations rather than process innovations, or product and process innovations simultaneously.

Importance: Two recent meta-analyses reported a high prevalence of both anxiety and depression in patients with alopecia areata (AA), as well as a positive association of AA with anxiety and depression, without distinguishing between disorders and symptoms. Yet, depression and anxiety can manifest either as symptoms identified in questionnaires or as specific diagnoses defined by Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision criteria. Objective: To perform a large meta-analysis separating the prevalence of depressive and anxiety disorders from that of depressive and anxiety symptoms in patients with AA. Data Sources: PubMed, ScienceDirect, the Cochrane Library, Embase, and PsycINFO databases were searched from inception through August 1, 2020. Study Selection: Studies that contained data on the prevalence of depressive or anxiety disorders or symptoms were included. Data Extraction and Synthesis: The Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guidelines were used. Pooled prevalence was calculated with a random effects model meta-analysis that took into account between- and within-study variability. Meta-regressions were used to study the association between variations in prevalence and study characteristics. Main Outcomes and Measures: The prevalence of depressive and anxiety disorders and symptoms in patients with AA. Results: Thirty-seven articles (29 on depression and 26 on anxiety) that met the inclusion criteria were identified. By distinguishing between disorders and symptoms, the prevalence of both depressive disorders (9%) and unspecified anxiety disorders (13%) in patients with AA was shown to be greater than that in the general population. The prevalence and odds ratio (OR) of depressive disorders (prevalence, 9%; OR, 1.38) and anxiety disorders of which each category had been specifically studied (prevalence, 7%-17%; OR, 1.51-1.69) were markedly lower than that of depressive symptoms (prevalence, 37%; OR, 2.70) and anxiety symptoms (prevalence, 34%; OR, 3.07). Meta-regressions showed that variations in prevalence were mainly associated with methodological differences between studies. Conclusions and Relevance: In this systematic review and meta-analysis, the separate analyses showed that 7% to 17% of patients with AA had depressive or anxiety disorders that require psychiatric care, including specific medication. Additionally, more than one-third of patients had symptoms that are warning signs and that need monitoring because they can develop into disorders.

Nanomaterials are present in a wide variety of health products, drugs and medical devices and their use is constantly increasing, varying in terms of diversity and quantity. The topic is vast because it covers nanodrugs, but also excipients (that includes varying proportions of NMs) and medical devices (with intended or not-intended (by-products of wear) nanoparticles). Although researchers in the field of nanomedicines in clinical research and industry push for clearer definitions and relevant regulations, the endeavor is challenging due to the enormous diversity of NMs in use and their specific properties. In addition, regulatory hurdles and discrepancies are often cited as obstacles to the clinical development of these innovative products. The scientific council of the Agence Nationale de Sécurité du Médicament et des produits de santé (ANSM) undertook a multidisciplinary analysis encompassing fundamental, environmental and societal dimensions with the aim of identifying topics of interest for regulatory assessment and surveillance. This analysis allowed for proposing some recommendations for approximation and harmonization of international regulatory practices for the assessment of the risk/benefit balance of these products, considering as well the public expectations as regards efficacy and safety of nanomaterials used in Health products, in terms of human and environmental health.

Shape servoing is the problem of controlling the shape of a deformable object via robotic manipulation, exploiting sensory feedback. In many shape servoing scenarios of practical interest, the object has a natural tendency to preserve local rigidity. Motivated by this observation, we propose to use the As-Rigid-As-Possible deformation model for shape servoing. Specifically, we propose a novel control scheme based on a deformation Jacobian computed from this model. The proposed scheme drives the object to a desired 3D shape using as feedback the object’s measured current 3D shape. The scheme is simple to implement, and it avoids some typical requirements in existing work: specifically, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(i)</i> we do not need to know the object’s mechanical deformation parameters, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(ii)</i> we do not use a Jacobian computed from data collected over a time window while the robots move. We test the proposed scheme in bi-arm shape servoing experiments with a variety of deformable objects of different material (paper, rubber, plastic). Tracking of the deformable object’s surface in 3D is performed in our experiments via an algorithm based on monocular vision. The experimental results validate the practicality of our scheme.

The aging of our population is accompanied by an increased prevalence of chronic diseases. Among those, liver, joint and adipose tissue-related pathologies have a major socio-economic impact. They share common origins as they result from a dysregulation of the inflammatory and metabolic status. Plant-derived nutrients and especially polyphenols, exert a large range of beneficial effects in the prevention of chronic diseases but require clinically validated approaches for optimized care management. In this study, we designed an innovative clinical approach considering the metabolites produced by the digestive tract following the ingestion of an artichoke leaf extract. Human serum, enriched with metabolites deriving from the extract, was collected and incubated with human hepatocytes, human primary chondrocytes and adipocytes to determine the biological activity of the extract. Changes in cellular behavior demonstrated that the artichoke leaf extract protects hepatocytes from lipotoxic stress, prevents adipocytes differentiation and hyperplasia, and exerts chondroprotective properties in an inflammatory context. These data validate the beneficial health properties of an artichoke leaf extract at the clinical level and provide both insights and further evidence that plant-derived nutrients and especially polyphenols from artichoke may represent a relevant alternative for nutritional strategies addressing chronic disease issues.

Importance Although the COVID-19 pandemic has had a negative impact on mental health, there is no comprehensive longitudinal study of the entire population of a country without selection bias. Objective The objective of this study was to evaluate the prescription of psychotropic drugs during the COVID-19 pandemic, using data from the French national health data system (SNDS). Design, settings, and participants Prescriptions for psychotropic drugs (antidepressants, anxiolytics, hypnotics, and antipsychotics) from 1 January 2015 to 30 September 2021 were collected from administrative data provided by the SNDS. This database includes more than 99% of the French population, i.e., 67 million people. The data were analyzed using an interrupted time series analysis (ITSA) model. Main outcomes and measures Consumption of psychotropic drugs was aggregated in months and expressed in number of boxes per thousand inhabitants. Results During the study period, more than 1.3 billion boxes of psychotropic medications were dispensed. Comparison of psychotropic drug dispensing before and after the pandemic showed a relative increase of 0.76 (95 CI 0.57 to 0.95, p &amp;lt;0.001) boxes per month per thousand inhabitants, all classes of psychotropic drugs combined. Three classes saw their consumption increase in an almost similar proportion, respectively, by 0.23 (0.15 to 0.32, p &amp;lt;0.001) boxes for antidepressants, 0.27 (0.20 to 0.34, p &amp;lt;0.001) boxes for anxiolytics and 0.23 (0.17 to 0.30, p &amp;lt;0.001) boxes for hypnotics. The change in antipsychotic consumption was very small, with an increase of 0.04 boxes (0.02 to 0.06, p = 0.001) per month per thousand population. Conclusion and relevance The COVID-19 pandemic had led to an increase in the consumption of psychotropic drugs, confirming the significant impact of the pandemic on the mental health of the general population.

The accurate description of the dynamics of dry-joint masonry structures strongly relies on the characterisation of the interaction at the units’ interfaces. Several experimental techniques are available for estimating the mechanical properties of the interface (i.e. stiffness and damping), yet, their reliability remains questionable given the lack of comprehensive comparative studies. This work presents an extensive experimental campaign on the meso-scale mechanics of dry-joint interfaces and quantifies both the interface stiffness and interface damping. Importantly, this paper reveals, for the first time, remarkable agreement of the interface stiffness estimated by inherently different experimental methods, namely deformation-based and vibration-based. Thus, it paves the way for the formulation of reliable constitutive laws that govern structural response in numerical modelling of dry-joint masonry structures.

Google Scholar (GS) is a free tool that may be used by researchers to analyze citations; find appropriate literature; or evaluate the quality of an author or a contender for tenure, promotion, a faculty position, funding, or research grants. GS has become a major bibliographic and citation database. For assessing the literature, databases, such as PubMed, PsycINFO, Scopus, and Web of Science, can be used in place of GS because they are more reliable. The aim of this study was to examine the accuracy of citation data collected from GS and provide a comprehensive description of the errors and miscounts identified. For this purpose, 281 documents that cited 2 specific works were retrieved via Publish or Perish software (PoP) and were examined. This work studied the false-positive issue inherent in the analysis of neuroimaging data. The results revealed an unprecedented error rate, with 279 of 281 (99.3%) examined references containing at least one error. Nonacademic documents tended to contain more errors than academic publications (U=5117.0; P<.001). This viewpoint article, based on a case study examining GS data accuracy, shows that GS data not only fail to be accurate but also potentially expose researchers, who would use these data without verification, to substantial biases in their analyses and results. Further work must be conducted to assess the consequences of using GS data extracted by PoP.

Cross-laminated timber (CLT) is an innovative wood product that can be used to build midrise and tall wood construction as an alternative to concrete, masonry, and steel. As floor, roof, and wall made of CLT is subjected to out-of-plane bending, rolling shear (RS) failure of cross-layers can arise prior to bending failure of the outermost layers, which governs the load-carrying capacity of CLT. In fact, the global deflections of CLT depend on the rolling shear modulus of cross-layers, which is much lower than shear modulus parallel to grain. Therefore, it is necessary to determine and improve the rolling shear strength and modulus of cross-layers. In this paper, several test methods were firstly summarized, after which the main influence factors on rolling shear properties were reviewed. Finally, seven configurations of hybrid CLT with three layers were tested to assess the rolling shear properties of hybrid CLT, in which the outer layers are made of Spruce-Pine-Fir (SPF) and the cross-layer is made of different materials such as birch, compressed wood (CW), laminated veneer lumber (LVL), Parallel strand lumber (PSL), plywood, oriented strand board (OSB), and glued laminated bamboo (GLB). The CLT made of SPF was also tested, whose rolling shear properties were regarded as reference. The rolling shear properties of GLB are about twice as high as those of SPF. Other materials do not exhibit superior rolling shear properties to SPF. The compressed wood shows a significant ductility in rolling shear failure.

In this paper, we design a framework to obtain efficient algorithms for several problems with a global constraint (acyclicity or connectivity) such as Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree, Longest Induced Path, and Feedback Vertex Set. For all these problems, we obtain 2^O(k)* n^O(1), 2^O(k log(k))* n^O(1), 2^O(k^2) * n^O(1) and n^O(k) time algorithms parameterized respectively by clique-width, Q-rank-width, rank-width and maximum induced matching width. Our approach simplifies and unifies the known algorithms for each of the parameters and match asymptotically also the running time of the best algorithms for basic NP-hard problems such as Vertex Cover and Dominating Set. Our framework is based on the d-neighbor equivalence defined in [Bui-Xuan, Telle and Vatshelle, TCS 2013]. The results we obtain highlight the importance and the generalizing power of this equivalence relation on width measures. We also prove that this equivalence relation could be useful for Max Cut: a W[1]-hard problem parameterized by clique-width. For this latter problem, we obtain n^O(k), n^O(k) and n^(2^O(k)) time algorithm parameterized by clique-width, Q-rank-width and rank-width.

International audience

Straw bale building construction is attracting a revived public interest because of its potential for reduced carbon footprint, hygrothermal comfort, and energy savings at an affordable price. The present paper aims to summarize the current knowledge on straw bale construction, using available data from academic, industry, and public agencies sources. The main findings on straw fibers, bales, walls, and buildings are presented. The literature shows a wide variability of results, which reflects the diversity of straw material and of straw construction techniques. It is found that the effective thermal conductivity, density, specific heat, and elastic modulus of straw bales used in construction are in the range 0.033–0.19 W/(m·K), 80–150 kg/m3, 1075–2000 J/(kg·K), and 150–350 kPa respectively. Most straw-based multilayered walls comply with fire resistance regulations, and their U-value and sound reduction index range from 0.11 to 0.28 W/m2 K and 42 to 53 dB respectively, depending on the wall layout. When compared to standard buildings, straw bale buildings do provide yearly reductions in carbon emissions and energy consumption. The reductions often match those obtained after applying energy-saving technologies in standard buildings. The paper ends by discussing the future research needed to foster the dissemination of straw bale construction.

In this article, it is shown that focused ion beam (FIB) systems can be used to study the inner structure of flax fibers, the use of which as a reinforcing material in polymer composites still draws much interest from multiple disciplines. This technique requires none of the specific preparations necessary for scanning electron microscopy or transmission electron microscopy studies. Irradiation experiments performed on FIB prepared cross sections with very low Ga+ ion beam currents revealed the softer material components of fibers. Thus, it confirmed the presence of pectin-rich layers at the interfaces between the fibers of a bundle, but also allowed the precise localization of such layers within the secondary cell wall. Furthermore, it suggested new insights on the transition modes between the sublayers of the secondary cell wall.

BACKGROUND: As the COVID-19 pandemic progressed, disinformation, fake news, and conspiracy theories spread through many parts of society. However, the disinformation spreading through social media is, according to the literature, one of the causes of increased COVID-19 vaccine hesitancy. In this context, the analysis of social media posts is particularly important, but the large amount of data exchanged on social media platforms requires specific methods. This is why machine learning and natural language processing models are increasingly applied to social media data. OBJECTIVE: The aim of this study is to examine the capability of the CamemBERT French-language model to faithfully predict the elaborated categories, with the knowledge that tweets about vaccination are often ambiguous, sarcastic, or irrelevant to the studied topic. METHODS: A total of 901,908 unique French-language tweets related to vaccination published between July 12, 2021, and August 11, 2021, were extracted using Twitter's application programming interface (version 2; Twitter Inc). Approximately 2000 randomly selected tweets were labeled with 2 types of categorizations: (1) arguments for (pros) or against (cons) vaccination (health measures included) and (2) type of content (scientific, political, social, or vaccination status). The CamemBERT model was fine-tuned and tested for the classification of French-language tweets. The model's performance was assessed by computing the F1-score, and confusion matrices were obtained. RESULTS: The accuracy of the applied machine learning reached up to 70.6% for the first classification (pro and con tweets) and up to 90% for the second classification (scientific and political tweets). Furthermore, a tweet was 1.86 times more likely to be incorrectly classified by the model if it contained fewer than 170 characters (odds ratio 1.86; 95% CI 1.20-2.86). CONCLUSIONS: The accuracy of the model is affected by the classification chosen and the topic of the message examined. When the vaccine debate is jostled by contested political decisions, tweet content becomes so heterogeneous that the accuracy of the model drops for less differentiated classes. However, our tests showed that it is possible to improve the accuracy by selecting tweets using a new method based on tweet length.

In this paper, the interaction between residential apartments in the same building is considered by including the occupant behavior. The study is applied to three-floor residential building. First, a multi-zone building model was implemented and validated by comparison with thermal simulation tools. Deterministic study allows us to determine the worst case of energy highest consumption. The interior insulation thickness is then progressively increased to obtain its optimal value with respect to heat loss and equilibrated energy consumption between apartments. Finally, a random variation of family absence number and duration has been applied to evaluate their influence on energy demand considering heat interaction between apartments.

International audience

In recent years, hydrogen production from food waste has attracted interest as a sustainable method for waste valorisation. Many studies were conducted on intensification parameters of fermentation, but very few focus on redox potential influence (ORP). This investigation addressed this challenge by performing discontinuous dark fermentations in bioreactor using synthetic food waste as substrate at different initial ORPs. Reducing the initial ORP of the culture broth to −322 ± 8 mV enhanced biohydrogen yield and productivity, achieving 98 ± 5 mL H 2 g −1 COD initial and 85 ± 3 mL H 2 h −1 L −1 reactor , corresponding to an increase of 57 % and 30 % respectively. Lowering initial ORPs promoted hydrogen-producing metabolic pathways and a higher relative abundance of C. butyricum . This study also demonstrates that controlling the redox potential during fermentation above the ORP range of the 2H + /H 2 redox pair negatively impacts hydrogen production and promotes the growth of undesirable microorganisms. • Initial redox potential regulation improves H 2 productivity from food wastes. • Lowering initial ORP at – 322 mV enhances H 2 production from food wastes by 57 %. • Hydrogen-producing bacteria are promoted by reduced initial ORP. • Lactate and propionate accumulation are limited at low initial ORP. • Distinct HPB develop when controlling the ORP at levels above the optimal range.

Skempton coefficient B is commonly used to evaluate the saturation of a sample before the shearing stage in a triaxial test. For unsaturated soils, measuring the degree of saturation Sr at the end of the consolidation stage is very difficult whereas measuring Skempton coefficient B is very simple. Using this coefficient to obtain Sr of a sample in a triaxial apparatus without complex procedures might be an improvement, especially as regards testing procedures for unsaturated soils. Different authors have proposed a relationship between these two parameters based on the hypothesis that a variation of B coefficient with Sr is mostly due to the compressibility of air in the pores. However, the presence of air as a fluid phase gives rise to suction after the equilibrium is reached inside the sample leading to an increase in stiffness. Based on this observation, this article presents a new relationship that enables Sr to be evaluated with a given Skempton coefficient taking into account not only the initial void ratio and the isotropic elastic modulus but also the suction and the elastoplastic behaviour of the soil. The results of the proposed approach are then confronted with the original relationship and compared to experimental data.

In vitro culture of flax (Linum usitatissimum L.) was exposed to chitosan oligosaccharides (COS) in order to investigate the effects on the growth and secondary metabolites content in roots and shoots. COS are fragments of chitosan released from the fungal cell wall during plant–pathogen interactions. They can be perceived by the plant as pathogen-associated signals, mediating local and systemic innate immune responses. In the present study, we report a novel COS oligosaccharide fraction with a degree of polymerization (DP) range of 2–10, which was produced from fungal chitosan by a thermal degradation method and purified by an alcohol-precipitation process. COS was dissolved in hydroponic medium at two different concentrations (250 and 500 mg/L) and applied to the roots of growing flax seedlings. Our observations indicated that the growth of roots and shoots decreased markedly in COS-treated flax seedlings compared to the control. In addition, the results of a metabolomics analysis showed that COS treatment induced the accumulation of (neo)lignans locally at roots, flavones luteolin C-glycosides, and chlorogenic acid in systemic responses in the shoots of flax seedlings. These phenolic compounds have been previously reported to exhibit a strong antioxidant and antimicrobial activities. COS oligosaccharides, under the conditions applied in this study (high dose treatment with a much longer exposure time), can be used to indirectly trigger metabolic response modifications in planta, especially secondary metabolism, because during fungal pathogen attack, COS oligosaccharides are among the signals exchanged between the pathogen and host plant.