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In this paper, a novel surrogate model for shape-parametrized vehicle drag force prediction is proposed. It is assumed that only a limited dataset of high-fidelity CFD results is available, typically less than ten high-fidelity CFD solutions for different shape samples. The idea is to take advantage not only of the drag coefficients but also physical fields such as velocity, pressure, and kinetic energy evaluated on a cutting plane in the wake of the vehicle and perpendicular to the road. This additional “augmented” information provides a more accurate and robust prediction of the drag force compared to a standard surface response methodology. As a first step, an original reparametrization of the shape based on combination coefficients of shape principal components is proposed, leading to a low-dimensional representation of the shape space. The second step consists in determining principal components of the x-direction momentum flux through a cutting plane behind the car. The final step is to find the mapping between the reduced shape description and the momentum flux formula to achieve an accurate drag estimation. The resulting surrogate model is a space-parameter separated representation with shape principal component coefficients and spatial modes dedicated to drag-force evaluation. The algorithm can deal with shapes of variable mesh by using an optimal transport procedure that interpolates the fields on a shared reference mesh. The Machine Learning algorithm is challenged on a car concept with a three-dimensional shape design space. With only two well-chosen samples, the numerical algorithm is able to return a drag surrogate model with reasonable uniform error over the validation dataset. An incremental learning approach involving additional high-fidelity computations is also proposed. The leading algorithm is shown to improve the model accuracy. The study also shows the sensitivity of the results with respect to the initial experimental design. As feedback, we discuss and suggest what appear to be the correct choices of experimental designs for the best results.

BackgroundVariants in the MYBPC3 gene are a frequent cause of hypertrophic cardiomyopathy (HCM) but display a large phenotypic heterogeneity. Founder mutations are often believed to be more benign as they prevailed despite potential negative selection pressure. We detected a pathogenic variant in MYBPC3 (del exon 23-26) in several probands. We aimed to assess the presence of a common haplotype and to describe the cardiac characteristics, disease severity and long-term outcome of mutation carriers.MethodsProbands with HCM caused by a pathogenic deletion of exon 23-26 of MYBPC3 were identified through genetic screening using a gene panel encompassing 59 genes associated with cardiomyopathies in a single genetic center in Belgium. Cascade screening of first-degree relatives was performed, and genotype positive relatives were further phenotyped. Clinical characteristics were collected from probands and relatives. Cardiac outcomes included death, heart transplantation, life-threatening arrhythmia, heart failure hospitalization or septal reduction therapy. Haplotype analysis, using microsatellite markers surrounding MYBPC3, was performed in all index patients to identify a common haplotype. The age of the founder variant was estimated based on the size of the shared haplotype using a linkage-disequilibrium based approach.ResultsWe identified 24 probands with HCM harbouring the MYBPC3 exon 23-26 deletion. Probands were on average 51 ± 16 years old at time of clinical HCM diagnosis and 62 ± 10 years old at time of genetic diagnosis. A common haplotype of 1.19 Mb was identified in all 24 probands, with 19 of the probands sharing a 13.8 Mb haplotype. The founder event was estimated to have happened five generations, or 175–200 years ago, around the year 1830 in central Flanders. Through cascade screening, 59 first-degree relatives were genetically tested, of whom 37 (62.7%) were genotype positive (G+) and 22 (37.3%) genotype negative (G-). They were on average 38 ± 19 years old at time of genetic testing. Subsequent clinical assessment revealed a HCM phenotype in 19 (51.4%) G+ relatives. Probands were older (63 ± 10 vs. 42 ± 21 years; p < 0.001) and had more severe phenotypes than G+ family members, presenting with more symptoms (50% vs. 13.5%; p = 0.002), arrhythmia (41.7% vs. 12.9%, p = 0.014), more overt hypertrophy and left ventricular outflow tract obstruction (43.5% vs. 3.0%; p < 0.001). Male G+ relatives more often had a HCM phenotype (78.6% vs. 34.8%; p = 0.010) and were more severely affected than females. At the age of 50, a penetrance of 78.6% was observed, defined as the presence of HCM in 11 of 14 G+ relatives with age ≥50 years. Overall, 20.3% of all variant carriers developed one of the predefined cardiac outcomes after a median follow-up of 5.5 years with an average age of 50 (±21) years.ConclusionA Belgian founder variant, an exon 23-26 deletion in MYBPC3, was identified in 24 probands and 37 family members. The variant is characterized by a high penetrance of 78.6% at the age of 50 years but has variable phenotypic expression. Adverse outcomes were observed in 20.3% of patients during follow-up.

Recently, OTULIN haploinsufficiency was linked to enhanced susceptibility to Staphylococcus aureus infections accompanied by local necrosis and systemic inflammation. The pathogenesis observed in haploinsufficient patients differs from the hyperinflammation seen in classical OTULIN-related autoinflammatory syndrome (ORAS) patients and is characterized by increased susceptibility of dermal fibroblasts to S. aureus alpha toxin-inflicted cytotoxic damage. Immunological abnormalities were not observed in OTULIN haploinsufficient patients, suggesting a non-hematopoietic basis. In this research report, we investigated an Otulin+/− mouse model after in vivo provocation with lipopolysaccharide (LPS) to explore the potential role of hematopoietic-driven inflammation in OTULIN haploinsufficiency. We observed a hyperinflammatory signature in LPS-provoked Otulin+/− mice, which was driven by CD64+ monocytes and macrophages. Bone marrow-derived macrophages (BMDMs) of Otulin+/− mice demonstrated higher proinflammatory cytokine secretion after in vitro stimulation with LPS or polyinosinic:polycytidylic acid (Poly(I:C)). Our experiments in full and mixed bone marrow chimeric mice suggest that, in contrast to humans, the observed inflammation was mainly driven by the hematopoietic compartment with cell-extrinsic effects likely contributing to inflammatory outcomes. Using an OTULIN haploinsufficient mouse model, we validated the role of OTULIN in the regulation of environmentally directed inflammation.

Abstract Background To understand mechanisms of adaptation and plasticity of pollinators and other insects a better understanding of diversity and function of their key symbionts is required. Commensalibacter is a genus of acetic acid bacterial symbionts in the gut of honey bees and other insect species, yet little information is available on the diversity and function of Commensalibacter bacteria. In the present study, whole-genome sequences of 12 Commensalibacter isolates from bumble bees, butterflies, Asian hornets and rowan berries were determined, and publicly available genome assemblies of 14 Commensalibacter strains were used in a phylogenomic and comparative genomic analysis. Results The phylogenomic analysis revealed that the 26 Commensalibacter isolates represented four species, i.e. Commensalibacter intestini and three novel species for which we propose the names Commensalibacter melissae sp. nov., Commensalibacter communis sp. nov. and Commensalibacter papalotli sp. nov. Comparative genomic analysis revealed that the four Commensalibacter species had similar genetic pathways for central metabolism characterized by a complete tricarboxylic acid cycle and pentose phosphate pathway, but their genomes differed in size, G + C content, amino acid metabolism and carbohydrate-utilizing enzymes. The reduced genome size, the large number of species-specific gene clusters, and the small number of gene clusters shared between C. melissae and other Commensalibacter species suggested a unique evolutionary process in C. melissae, the Western honey bee symbiont. Conclusion The genus Commensalibacter is a widely distributed insect symbiont that consists of multiple species, each contributing in a species specific manner to the physiology of the holobiont host.

Manufacturing industry faces increasing complexity in the performance of assembly tasks due to escalating demand for complex products with a greater number of variations. Operators require robust assistance systems to enhance productivity, efficiency, and safety. However, existing support services often fall short when operators encounter unstructured open questions and incomplete sentences due to primarily relying on procedural digital work instructions. This draws attention to the need for practical application of natural language processing (NLP) techniques. This study addresses these challenges by introducing a domain-specific dataset tailored to assembly tasks, capturing unique language patterns and linguistic characteristics. We explore strategies to process declarative and imperative sentences, including incomplete ones, effectively. Thorough evaluation of three pre-trained NLP libraries—NLTK, SPACY, and Stanford—is performed to assess their effectiveness in handling assembly-related concepts and ability to address the domain’s distinctive challenges. Our findings demonstrate the efficient performance of these open-source NLP libraries in accurately handling assembly-related concepts. By providing valuable insights, our research contributes to developing intelligent operator assistance systems, bridging the gap between NLP techniques and the assembly domain within manufacturing industry.

Abstract In this work, we revisit the problem of finding entanglement islands in 2d Jackiw-Teitelboim (JT) gravity. We implement the following adjustments to the traditional setup: (1) we do not explicitly couple to a non-gravitating system, instead we implement only pure absorption into a fiducial detector, (2) we utilise the operationally defined renormalised matter entanglement entropy, as defined by the boundary observer’s wordline. We show that this leads to a unitary Page curve that we explicitly compute, with an island outside of the event horizon. Next, we extend the analysis to a charged and/or supersymmetric black hole. We find that in a certain regime the charged black hole grows first as it emits superradiation before eventually dissipating. We obtain similar results when embedding the system in a supersymmetric setting.

Abstract Despite an enormous interest in understanding the bioactivity of extracellular vesicles (EV) in physiology and disease for the development of therapeutic applications, the impact of EV preparation methods remains minimally explored. In this study, we implemented density gradient ultracentrifugation combined with size‐exclusion chromatography (DG‐SEC), differential ultracentrifugation (dUC) and/or stand‐alone SEC (sSEC) to fractionate media conditioned by different cancer cells and/or cancer‐associated fibroblasts (CAF). EV‐enriched but protein‐depleted versus EV‐depleted but protein‐enriched DG‐SEC fractions, and EV‐containing dUC and sSEC preparations were quality controlled for particle number, protein concentration, selected protein composition and ultrastructure, characterized for their cytokine content, and dose‐dependently evaluated for monocyte‐derived dendritic cell (MoDC) maturation by measuring surface marker expression and/or cytokine secretion. EV preparations obtained by DG‐SEC from media conditioned by different cancer cell lines or CAF, were depleted from soluble immune suppressive cytokines such as VEGF‐A and MCP‐1 and potently stimulated MoDC maturation. In contrast, EV‐containing dUC or sSEC preparations were not depleted from these soluble cytokines and were unable to mature MoDC. Subsequent processing of dUC EV preparations by SEC dose‐dependently restored the immunomodulatory bioactivity. Overall, our results demonstrate that method‐dependent off‐target enrichment of soluble cytokines has implications for the study of EV immunomodulatory bioactivity and warrants careful consideration.

The microbiological and metabolic outcomes of good cocoa fermentation practices can be standardized and influenced through the addition of starter culture mixtures composed of yeast and bacterial strains. The present study performed two spontaneous and 10 starter culture-initiated (SCI) cocoa fermentation processes (CFPs) in Costa Rica with local Trinitario cocoa. The yeast strains Saccharomyces cerevisiae IMDO 050523, Hanseniaspora opuntiae IMDO 020003, and Pichia kudriavzevii IMDO 060005 were used to compose starter culture mixtures in combination with the lactic acid bacterium strain Limosilactobacillus fermentum IMDO 0611222 and the acetic acid bacterium strain Acetobacter pasteurianus IMDO 0506386. The microbial community and metabolite dynamics of the cocoa pulp-bean mass fermentation, the metabolite dynamics of the drying cocoa beans, and the volatile organic compound (VOC) profiles of the chocolate production were assessed. An amplicon sequence variant approach based on full-length 16S rRNA gene sequencing instead of targeting the V4 region led to a highly accurate monitoring of the starter culture strains added, in particular the Liml. fermentum IMDO 0611222 strain. The latter strain always prevailed over the background lactic acid bacteria. A similar approach, based on the internal transcribed spacer (ITS1) region of the fungal rRNA transcribed unit, was used for yeast strain monitoring. The SCI CFPs evolved faster when compared to the spontaneous ones. Moreover, the yeast strains applied did have an impact. The presence of S. cerevisiae IMDO 050523 was necessary for successful fermentation of the cocoa pulp-bean mass, which was characterized by the production of higher alcohols and esters. In contrast, the inoculation of H. opuntiae IMDO 020003 as the sole yeast strain led to underfermentation and a poor VOC profile, mainly due to its low competitiveness. The P. kudriavzevii IMDO 060005 strain tested in the present study did not contribute to a richer VOC profile. Although differences in VOCs could be revealed in the cocoa liquors, no significant effect on the final chocolates could be obtained, mainly due to a great impact of cocoa liquor processing during chocolate-making. Hence, optimization of the starter culture mixture and cocoa liquor processing seem to be of pivotal importance.

Industrial production of Gouda cheeses mostly relies on a rotated use of different mixed-strain lactic acid bacteria starter cultures to avoid phage infections. However, it is unknown how the application of these different starter culture mixtures affect the organoleptic properties of the final cheeses. Therefore, the present study assessed the impact of three different starter culture mixtures on the batch-to-batch variations among Gouda cheeses from 23 different batch productions in the same dairy company. Both the cores and rinds of all these cheeses were investigated after 36, 45, 75, and 100 weeks of ripening by metagenetics based on high-throughput full-length 16S rRNA gene sequencing accompanied with an amplicon sequence variant (ASV) approach as well as metabolite target analysis of non-volatile and volatile organic compounds. Up to 75 weeks of ripening, the acidifying Lactococcus cremoris and Lactococcus lactis were the most abundant bacterial species in the cheese cores. The relative abundance of Leuconostoc pseudomesenteroides was significantly different for each starter culture mixture. This impacted the concentrations of some key metabolites, such as acetoin produced from citrate, and the relative abundance of non-starter lactic acid bacteria (NSLAB). Cheeses with the least Leuc. pseudomesenteroides contained more NSLAB, such as Lacticaseibacillus paracasei that was taken over by Tetragenococcus halophilus and Loigolactobacillus rennini upon ripening time. Taken together, the results indicated a minor role of leuconostocs in aroma formation but a major impact on the growth of NSLAB. The relative abundance of T. halophilus (high) and Loil. rennini (low) increased with ripening time from rind to core. Two main ASV clusters of T. halophilus could be distinguished, which were differently correlated with some metabolites, both beneficial (regarding aroma formation) and undesirable ones (biogenic amines). A well-chosen T. halophilus strain could be a candidate adjunct culture for Gouda cheese production.

Acetobacter species play an import role during cocoa fermentation. However, Acetobacter ghanensis and Acetobacter senegalensis are outcompeted during fermentation of the cocoa pulp-bean mass, whereas Acetobacter pasteurianus prevails. In this paper, an in silico approach aimed at delivering some insights into the possible metabolic adaptations of A. ghanensis LMG 23848T and A. senegalensis 108B, two candidate starter culture strains for cocoa fermentation processes, by reconstructing genome-scale metabolic models (GEMs). Therefore, genome sequence data of a selection of strains of Acetobacter species were used to perform a comparative genomic analysis. Combining the predicted orthologous groups of protein-encoding genes from the Acetobacter genomes with gene-reaction rules of GEMs from two reference bacteria, namely a previously manually curated model of A. pasteurianus 386B (iAp386B454) and two manually curated models of Escherichia coli (EcoCyc and iJO1366), allowed to predict the set of reactions present in A. ghanensis LMG 23848T and A. senegalensis 108B. The predicted metabolic network was manually curated using genome re-annotation data, followed by the reconstruction of species-specific GEMs. This approach additionally revealed possible differences concerning the carbon core metabolism and redox metabolism among Acetobacter species, pointing to a hitherto unexplored metabolic diversity. More specifically, the presence or absence of reactions related to citrate catabolism and the glyoxylate cycle for assimilation of C2 compounds provided not only new insights into cocoa fermentation but also interesting guidelines for future research. In general, the A. ghanensis LMG 23848T and A. senegalensis 108B GEMs, reconstructed in a semi-automated way, provided a proof-of-concept toward accelerated formation of GEMs of candidate functional starter cultures for food fermentation processes.

Summary: Various yeast strains have been proposed as candidate starter cultures for cocoa fermentation, especially strains of Saccharomyces cerevisiae. In the current study, the genome of the cocoa strain S. cerevisiae IMDO 050523 was unraveled based on a combination of long- and short-read sequencing. It consisted of 16 nuclear chromosomes and a mitochondrial chromosome, which were organized in 20 contigs, with only two small gaps. A phylogenomic analysis of this genome together with another 105 S cerevisiae genomes, among which 20 from cocoa strains showed a geographical distribution of the latter, including S. cerevisiae IMDO 050523. Its genome clustered together with that of a West African fermented food population, indicating a wider adaptation to West African food niches than cocoa. Furthermore, S. cerevisiae IMDO 050523 contained genetic signatures involved in sucrose hydrolysis, pectin degradation, osmotolerance, and conserved amino acid changes in key ester-producing enzymes that could point toward specific niche adaptations.

Beer is the result of a multistep brewing process, including a fermentation step using in general one specific yeast strain. Bacterial presence during beer production (or presence in the beer itself) is considered as bad, since bacteria cause spoilage, produce off-flavors, and/or turbidity. Although most problems in the past related to lack of hygiene and/or cleaning, bacteria do still cause problems nowadays. Despite this negative imago, certain bacteria play an irreplaceable role during fermentation and/or maturation of more unique, funky, and especially refreshing sour beers. The term sour beers or sours is not restricted to one definition but covers a wide variety of beers produced via different techniques. This review proposes an uncluttered sour beer classification scheme, which includes all sour beer production techniques and pays special attention to the functional role of acetic acid bacteria. Whereas their oxidation of ethanol and lactate into acetic acid and acetoin usually spoils beer, including sour beers, organoleptically, a controlled growth leads to a desirable acidic flavor in sour beers, such as lambic-style, lambic-based, and red-brown acidic ales.

Gender, sexuality and embodiment in digital spheres have been increasingly studied from various critical perspectives: From research highlighting the articulation of intimacies, desires, and sexualities in and through digital spaces to theoretical explorations of materiality in the digital realm. With such a high level of (inter)disciplinarity, theories, methods, and analyses of gender, sexuality, and embodiment in relation to digital spheres have become highly diversified. Aiming to reflect this diversity, this special issue brings together innovative and newly developed theoretical, empirical, analytical, and critical approaches in the study of gender, sexuality, and embodiment in digital spheres. By connecting intersectionality and digitality to one another, it adopts an integrated approach that reflects the intricacy and interconnectedness of social categories and markers of difference, privilege, performance, and discrimination. The contributions explore a range of differently situated digital cultural practices, including intimate and sexual experiences with(in) digital media, online self-presentation, expressions of digital resistance, and forms of backlash and online attacks. What connects all these articles, is their critical approach to intersectional inequalities and privileges in relation to digitality, plus their nuanced perspective on gender, sexuality, and embodiment interferentially. The final article is based on a roundtable discussion and aims to encourage interdisciplinary connections and suggests ways of doing research that builds bridges between academia and activism.

During the past two decades or so, the emergence and ever-accelerating development of digital media have sparked scholarly interest, debates, and complex challenges across many disciplines in the social sciences and the humanities. Within this diverse scholarship, the research on digitality, gender, sexuality, and embodiment has contributed substantially to many academic fields, such as media studies, sociology, religion, philosophy, and education studies. As a part of the special issue “Gender, Sexuality, and Embodiment in Digital Spheres: Connecting Intersectionality and Digitality,” this roundtable consists of a conversation between five researchers from different (inter)disciplinary locations, all addressing matters of methodology, intersectionality, positionality, and theory in relation to the topics of gender, sexuality, and embodiment in digital spheres. Said roundtable begins with a critical self-positioning of the participants’ (inter)disciplinary and embodied locations using examples from their own research. The conversation then progresses to how these researchers have employed contemporary theories, conceptual vocabularies, methods, and analyses of gender, sexuality, and embodiment in digital spheres to then conclude with some ethico-political notes about collaborations between scholars and (digital) activists.

The fiber, vitamin, and antioxidant contents of fruits contribute to a balanced human diet. In countries such as Argentina, several tropical fruits are witnessing a high yield in the harvest season, with a resulting surplus. Fruit fermentation using autochthonous starter cultures can provide a solution for food waste. However, limited knowledge exists about the microbiota present on the surfaces of fruits and the preceding flowers. In the present exploratory study, the microbiomes associated with the surfaces of tropical fruits from Northern Argentina, such as white guava, passion fruit and papaya were investigated using a shotgun metagenomic sequencing approach. Hereto, one sample composed of 14 white guava fruits, two samples of passion fruits with each two to three fruits representing the almost ripe and ripe stage of maturity, four samples of papaya with each two to three fruits representing the unripe, almost ripe, and ripe stage of maturity were processed, as well as a sample of closed and a sample of open Japanese medlar flowers. A considerable heterogeneity was found in the composition of the fruits’ surface microbiota at the genus and species level. While bacteria dominated the microbiota of the fruits and flowers, a small number of the metagenomic sequence reads corresponded with yeasts and filamentous fungi. A minimal abundance of bacterial species critical in lactic acid and acetic acid fermentations was found. A considerable fraction of the metagenomic sequence reads from the fruits’ surface microbiomes remained unidentified, which suggested that intrinsic species are to be sequenced or discovered.

For eight backslopping steps, eight series of water kefir fermentation processes differing in backslopping time and rinsing of the grains during each backslopping step and eight series of fermentation processes differing in incubation temperature and backslopping time were followed. Short backslopping times resulted in high relative abundances of Liquorilactobacillus nagelii and Saccharomyces cerevisiae, intermediate backslopping times in high relative abundances of Leuconostoc pseudomesenteroides, and long backslopping times in high relative abundances of Oenococcus sicerae and Dekkera bruxellensis. When the grains were rinsed during each backslopping step, the relative abundances of Lentilactobacillus hilgardii and Leuc. pseudomesenteroides increased and those of D. bruxellensis and Liql. nagelii decreased. Furthermore, rinsing of the grains during each backslopping step resulted in a slightly higher water kefir grain growth and lower metabolite concentrations. The relative abundances of Liquorilactobacillus mali were highest at 17°C, those of Leuc. pseudomesenteroides at 21 and 25°C, and those of Liql. nagelii at 29°C. With a kinetic modeling approach, the impact of the temperature and rinsing of the grains during the backslopping step on the volumetric production rates of the metabolites was determined.

Temporal shotgun metagenomics of multiple samples of an Arabica wet coffee fermentation process, which was examined microbiologically and metabolomically before, was performed to complement these microbiological and biochemical data with an in-depth in silico analysis of the structure and functions of the coffee microbiome. The taxonomic analysis of a massive sequence dataset of ca. 16 Gbp identified >150 microbial species and distinguished three successive, microbial phases: (i) enterobacteria, acetic acid bacteria, and some yeasts prevailing at the start; (ii) lactic acid bacteria (LAB) in the second phase; and (iii) acid-tolerant LAB at the end of the fermentation process. The functional analysis of prokaryotic genes, based on ca. 138,000 coding sequences, facilitated the gene repertoire overview of this ecosystem, showcasing differences in each fermentation stage. Initial prototrophic characters, plant cell wall-degrading activities, and pectinolytic activities were followed by a more auxotrophic and saccharolytic microbial profile, due to an increasing relative abundance of LAB. The almost full genome of 22 bacterial species was reconstructed and additional coffee-specific features were identified. This temporal metagenomic analysis of a case of reproducible wet coffee fermentation processes carried out in a coffee plantation near Nanegal, Ecuador, constitutes a breakthrough for the study of wet coffee processing and the contribution of the growth and activities of different microorganisms, in particular LAB, to this process.

Abstract In the last years, the automotive engineering industry has been deeply influenced by the use of «machine learning» techniques for new design and innovation purposes. However, some specific engineering aspects like numerical optimization study still require the development of suitable high-performance machine learning approaches involving parametrized Finite Elements (FE) structural dynamics simulation data. Weight reduction on a car body is a crucial matter that improves the environmental impact and the cost of the product. The actual optimization process at Renault SA uses numerical Design of Experiments (DOE) to find the right thicknesses and materials for each part of the vehicle that guarantees a reduced weight while keeping a good behavior of the car body, identified by criteria or sensors on the body (maximum displacements, upper bounds of instantaneous acceleration …). The usual DOE methodology generally uses between 3 and 10 times the numbers of parameters of the study (which means, for a 30-parameters study, at least 90 simulations, with typically 10 h per run on a 140-core computer). During the last 2 years, Renault’s teams strived to develop a disruptive methodology to conduct optimization study. By ‘disruptive’, we mean to find a methodology that cuts the cost of computational effort by several orders of magnitude. It is acknowledged that standard DoEs need a number of simulations which is at least proportional to the dimension of the parameter space, leading generally to hundreds of fine simulations for real applications. Comparatively, a disruptive method should require about 10 fine evaluations only. This can be achieved by means of a combination of massive data knowledge extraction of FE crash simulation results and the help of parallel high-performance computing (HPC). For instance, in the recent study presented by Assou et al. (A car crash reduced order model with random forest. In: 4th International workshop on reduced basis, POD and PGD Model Reduction Techniques—MORTech 2017. 2017), it took 10 runs to find a solution of a 34-parameter problem that fulfils the specifications. In order to improve this method, we must extract more knowledge from the simulation results (correlations, spatio-temporal features, explanatory variables) and process them in order to find efficient ways to describe the car crash dynamics and link criteria/quantities of interest with some explanatory variables. One of the improvements made in the last months is the use of the so-called Empirical Interpolation Method (EIM, [Barrault et al.]) to identify the few time instants and spatial nodes of the FE-mesh (referred to as magic points) that “explain” the behavior of the body during the crash, within a dimensionality reduction approach. The EIM method replaces a former K-Means algorithm (Davies et al. in IEEE Trans Pattern Anal Mach Intell, 1(2):224–227, 1979) which was processed online, for each ROM. Instead, the computation of EIM method is done offline, once for all, for each simulation. This new method allows us to compute a ROM quite faster, and to reduce the number of features that we use for the regression step (~ 100). The nonlinear regression step is achieved by a standard Random Forest (RF, [Breiman. Mach Learn 45:5–32, 2001]) algorithm. Another improvement of the method is the characterization of numerical features describing the shape of the body, at a nodal scale. The characteristics of orientation of the elements surrounding a mesh node must be taken into account to describe the behavior of the node during the crash. The actual method integrates some numerical features, computed from the orientation of the elements around each node, to explain the node behavior. The paper is organized as follows: The introduction states the scientific and industrial context of the research. Then, the ReCUR Method is detailed, and the recent improvements are highlighted. Results are presented and discussed before having some concluding remarks on this piece of work.

TSG-6 is a soluble protein secreted in the extracellular matrix by various cell types in response to inflammatory stimuli. TSG-6 interacts with extracellular matrix molecules, particularly hyaluronan (HA), and promotes cutaneous wound closure in mice. Between epidermal cells, the discrete extracellular matrix contains HA and a tiny amount of TSG-6. However, challenges imposed to keratinocytes in reconstructed human epidermis revealed strong induction of TSG-6 expression, after exposure to T helper type 2 cytokines to recapitulate the atopic dermatitis phenotype or after fungal infection that causes secretion of cytokines and antimicrobial peptides. After both types of challenge, enhanced release of TSG-6 happens simultaneously with increased HA production. TSG-6 deficiency in N/TERT keratinocytes was created by inactivating TNFAIP6 using CRISPR/Cas9. Some TSG-6–/– keratinocytes analyzed through scratch assays tend to migrate more slowly but produce reconstructed human epidermis that exhibits normal morphology and differentiation. Few significant alterations were noticed by transcriptomic analysis. Nevertheless, reduced HA content in TSG-6–/– reconstructed human epidermis was observed, along with enhanced HA release into the culture medium, and this phenotype was even more pronounced after the challenging conditions. Reintroduction of cells producing TSG-6 in reconstructed human epidermis reduced HA leakage. Our results show a role for TSG-6 in sequestering HA between epidermal cells in response to inflammation.

We consider the discrete-time G/GI/1 queueing system with multiple exhaustive vacations. By a transform approach, we obtain an expression for the probability generating function of the waiting time of customers in such a system. We then show that the results can be used to assess the performance of G/GI/1 queueing systems with server breakdowns as well as that of the low-priority queue of a preemptive MX+G/GI/1 priority queueing system. By calculating service completion times of low-priority customers, various preemptive breakdown/priority disciplines can be studied, including preemptive resume and preemptive repeat, as well as their combinations. We illustrate our approach with some numerical examples.

Eleven series of water kefir fermentation processes differing in the presence of oxygen and the type and concentration of inoculum and substrate, were followed as a function of time to quantify the impact of these parameters on the kinetics of this process via a modeling approach. Increasing concentrations of the water kefir grain inoculum increased the water kefir fermentation rate, so that the metabolic activity during water kefir fermentation was mainly associated with the grains. Water kefir liquor could also be used as an alternative means of inoculation, but the resulting fermentation process progressed slower than the one inoculated with water kefir grains, and the production of water kefir grain mass was absent. Substitution of sucrose with glucose and/or fructose reduced the water kefir grain growth, whereby glucose was fermented faster than fructose. Lacticaseibacillus paracasei (formerly known as Lactobacillus paracasei), Lentilactobacillus hilgardii (formerly known as Lactobacillus hilgardii), Liquorilactobacillus nagelii (formerly known as Lactobacillus nagelii), Saccharomyces cerevisiae, and Dekkera bruxellensis were the main microorganisms present. Acetic acid bacteria were present in low abundances under anaerobic conditions and only proliferated under aerobic conditions. Visualization of the water kefir grains through scanning electron microscopy revealed that the majority of the microorganisms was attached onto their surface. Lactic acid bacteria and yeasts were predominantly associated with the grains, whereas acetic acid bacteria were predominantly associated with the liquor.

Cocoa fermentation is the first step in the post-harvest processing chain of cocoa and is important for the removal of the cocoa pulp surrounding the beans and the development of flavor and color precursors. In the present study, metagenomic and metatranscriptomic sequencing were applied to Costa Rican cocoa fermentation processes to unravel the microbial diversity and assess the function and transcription of their genes, thereby increasing the knowledge of this spontaneous fermentation process. Among 97 genera found in these fermentation processes, the major ones were Acetobacter, Komagataeibacter, Limosilactobacillus, Liquorilactobacillus, Lactiplantibacillus, Leuconostoc, Paucilactobacillus, Hanseniaspora, and Saccharomyces. The most prominent species were Limosilactobacillus fermentum, Liquorilactobacillus cacaonum, and Lactiplantibacillus plantarum among the LAB, Acetobacter pasteurianus and Acetobacter ghanensis among the AAB, and Hanseniaspora opuntiae and Saccharomyces cerevisiae among the yeasts. Consumption of glucose, fructose, and citric acid, and the production of ethanol, lactic acid, acetic acid, and mannitol were linked to the major species through metagenomic binning and the application of metatranscriptomic sequencing. By using this approach, it was also found that Lacp. plantarum consumed mannitol and oxidized lactic acid, that A. pasteurianus degraded oxalate, and that species such as Cellvibrio sp., Pectobacterium spp., and Paucilactobacillus vaccinostercus could contribute to pectin degradation. The data generated and results presented in this study could enhance the ability to select and develop appropriate starter cultures to steer the cocoa fermentation process toward a desired course.

Starter culture-initiated cocoa fermentation processes can be applied to improve the quality of cured cocoa beans. However, an accurate monitoring of the microbial strains inoculated in fresh cocoa pulp-bean mass to assess their contribution to the cocoa bean curing process is still lacking. In the present study, eight different cocoa fermentation processes were carried out with Trinitario cocoa in vessels in Costa Rica to assess the contribution of two candidate yeast starter culture strains, namely Saccharomyces cerevisiae IMDO 050523 and Pichia kudriavzevii IMDO 020508, inoculated in combination with Limosilactobacillus fermentum IMDO 0611222 and Acetobacter pasteurianus IMDO 0506386. A multiphasic approach, consisting of culture-dependent selective plating and incubation, rRNA-PCR-DGGE community profiling of agar plate washes, and culture-independent high-throughput amplicon sequencing, combined with a metabolite target analysis of non-volatile and volatile organic compounds (VOCs), was performed on samples from the fermentation and/or drying steps. The different starter culture mixtures applied effectively steered the cocoa fermentation processes performed. Moreover, the use of an amplicon sequence variant (ASV) approach, aligning these ASVs to the whole-genome sequences of the inoculated strains, allowed the monitoring of these inoculated strains and their differentiation from very closely related variants naturally present in the background or spontaneous fermentation processes. Further, traits such as malolactic fermentation during the fermentation step and acetoin and tetramethylpyrazine formation during the drying step could be unraveled. Finally, the yeast strains inoculated influenced the substrate consumption and metabolite production during all starter culture-initiated fermentation processes. This had an impact on the VOC profiles of the cured cocoa beans. Whereas the P. kudriavzevii strain produced a wide range of VOCs in the cocoa pulp, the S. cerevisiae strain mostly influenced the VOC composition of the cured cocoa beans.

Hundreds of sourdoughs have been investigated in the last decades. However, many studies used a culture-dependent and/or culture-independent microbiological approach [mainly based on denaturing gradient gel electrophoresis (DGGE) of PCR amplicons], seldomly combined with a metabolite target analysis, to characterize the microbial species communities of the sourdoughs examined. Moreover, attention was mainly paid on lactic acid bacteria (LAB) and yeast species. In the present study, distinct household-scale (including an artisan lambic brewery) and artisan bakery-scale backslopped sourdoughs (17 in total), obtained from different regions (Belgium, France, United Kingdom, and USA), were examined through a multiphasic approach, encompassing a culture-dependent analysis [targeting LAB, acetic acid bacteria (AAB), and yeasts], different culture-independent techniques [rRNA-PCR-DGGE, metagenetics, and metagenomics (four bakery sourdoughs)], and metabolite target analysis. It turned out that the microbial species diversity of the sourdoughs was influenced by the house microbiota of the producer. Further, when the producer made use of different flours, the sourdoughs harbored similar microbial communities, independent of the flour used. AAB were only present in the Belgian sourdoughs, which might again be related to the processing environment. Fructilactobacillus sanfranciscensis (formerly known as Lactobacillus sanfranciscensis) was the prevalent LAB species of the eight sourdoughs produced by two of the three bakeries of different countries analyzed. These sourdoughs were characterized by the presence of either Saccharomyces cerevisiae or Kazachstania humilis. Moreover, the presence of Fl. sanfranciscensis was positively correlated with the production of mannitol and negatively correlated with the presence of other LAB or AAB species. Sourdoughs produced in an artisan lambic brewery were characterized by the presence of the yeast species Dekkera anomala and Pichia membranifaciens. One household sourdough was characterized by the presence of uncommon species, such as Pediococcus parvulus and Pichia fermentans. Metagenomic sequencing allowed the detection of many more LAB and AAB species than the other methods applied, which opened new frontiers for the understanding of the microbial communities involved during sourdough production processes.

Lambic beer production processes are characterized by a temporal succession of well-adapted microbial species. Temporal metagenomic analysis of a Belgian, traditional, lambic beer production process, which was examined microbiologically and metabolomically before, confirmed that the microbial diversity is limited. Moreover, it allowed to link the consumption and production of certain compounds to specific microbial groups or species. Fermentation characteristics, such as the conversion of malic acid into lactic acid and acetoin production, were retrieved and could be attributed to specific microorganisms, namely Pediococcus damnosus and Acetobacter species, respectively. Traits previously ascribed to brewery-specific Dekkera bruxellensis strains were confirmed during the lambic beer production process examined multiphasically; in particular, the higher production of 4-ethylguaiacol compared to 4-ethylphenol was further shown by mass spectrometric analysis. Moreover, the absence of phenolic acid decarboxylase in Brettanomyces custersianus was shown culture-independently and could explain its late occurrence during the maturation phase. Furthermore, the potential of maltooligosaccharide degradation could be ascribed metagenomically to not only Brettanomyces species but also Saccharomyces kudriavzevii, possibly explaining their degradation early in the lambic beer production process. Also, acetic acid bacteria (AAB) seemed to be able to consume maltooligosaccharides via their conversion into trehalose. Furthermore, these AAB possessed esterase genes, potentially capable of forming ethyl acetate, which may contribute to the flavor of lambic beer. Improved knowledge on the reasons behind certain community dynamics and the role of the different microorganisms in terms of potential functionality could improve brewery practices to assure to produce more quality-stable end-products.

Introduction We aimed to quantify health outcomes and programmatic implications of scaling up cervical cancer (CC) screening and treatment options for women living with HIV in care aged 18–65 in Kenya.Methods Mathematical model comparing from 2020 to 2040: (1) visual inspection with acetic acid (VIA) and cryotherapy (Cryo); (2) VIA and Cryo or loop excision electrical procedure (LEEP), as indicated; (3) human papillomavirus (HPV)-DNA testing and Cryo or LEEP; and (4) enhanced screening technologies (either same-day HPV-DNA testing or digitally enhanced VIA) and Cryo or LEEP. Outcomes measured were annual number of CC cases, deaths, screening and treatment interventions, and engaged in care (numbers screened, treated and cured) and five yearly age-standardised incidence.Results All options will reduce CC cases and deaths compared with no scale-up. Options 1–3 will perform similarly, averting approximately 28 000 (33%) CC cases and 7700 (27%) deaths. That is, VIA screening would yield minimal losses to follow-up (LTFU). Conversely, LTFU associated with HPV-DNA testing will yield a lower care engagement, despite better diagnostic performance. In contrast, option 4 would maximise health outcomes, averting 43 200 (50%) CC cases and 11 800 (40%) deaths, given greater care engagement. Yearly rescreening with either option will impose a substantial burden on the health system, which could be reduced by spacing out frequency to three yearly without undermining health gains.Conclusions Beyond the specific choice of technologies to scale up, efficiently using available options will drive programmatic success. Addressing practical constraints around diagnostics’ performance and LTFU will be key to effectively avert CC cases and deaths.