Cost-effective and accurate interlaminar stress modeling of composite Kirchhoff plates via immersed isogeometric analysis and equilibrium

The interest for composites has constantly grown in recent years, especially in the aerospace and automotive industries, as they can be moulded in complex form and geometry, as well as exhibit enhanced engineering properties. Nevertheless, despite the accelerated diffusion of laminated composites, the design of these materials is often restrained by the lack of cost-effective modeling techniques. In fact, the existing numerical strategies allowing for cheap simulations of laminated structures usually fail to directly capture out-of-plane through-the-thickness stresses, which are typically responsible for failure modes such as delamination. In this context, a stress recovery approach based on equilibrium has been recently shown to be an efficient modeling strategy in the framework of isogeometric analysis. Since immersed approaches like the finite cell method have been proven to be a viable alternative to mesh-conforming discretization for dealing with complex/dirty geometries as well as trimmed surfaces, we herein propose to extend the stress recovery approach combining the finite cell method, isogeometric analysis and equilibrium to model the out-of-plane behavior of Kirchhoff laminated plates. Extensive numerical tests showcase the effectiveness of the proposed approach

Reduced order isogeometric analysis approach for PDEs in parametrized domains

In this contribution, we coupled the isogeometric analysis to a reduced order modelling technique in order to provide a computationally efficient solution in parametric domains. In details, we adopt the free-form deformation method to obtain the parametric formulation of the domain and proper orthogonal decomposition with interpolation for the computational reduction of the model. This technique provides a real-time solution for any parameter by combining several solutions, in this case computed using isogeometric analysis on different geometrical configurations of the domain, properly mapped into a reference configuration. We underline that this reduced order model requires only the full-order solutions, making this approach non-intrusive. We present in this work the results of the application of this methodology to a heat conduction problem inside a deformable collector pipe

Autotrophic and Heterotrophic Growth Conditions Modify Biomolecole Production in the Microalga Galdieria sulphuraria (Cyanidiophyceae, Rhodophyta)

Algae have multiple similarities with fungi, with both belonging to the Thallophyte, a polyphyletic group of non-mobile organisms grouped together on the basis of similar characteristics, but not sharing a common ancestor. The main difference between algae and fungi is noted in their metabolism. In fact, although algae have chlorophyll-bearing thalloids and are autotrophic organisms, fungi lack chlorophyll and are heterotrophic, not able to synthesize their own nutrients. However, our studies have shown that the extremophilic microalga Galderia sulphuraria (GS) can also grow very well in heterotrophic conditions like fungi. This study was carried out using several approaches such as scanning electron microscope (SEM), gas chromatography/mass spectrometry (GC/MS), and infrared spectrophotometry (ATR-FTIR). Results showed that the GS, strain ACUF 064, cultured in autotrophic (AGS) and heterotrophic (HGS) conditions, produced different biomolecules. In particular, when grown in HGS, the algae (i) was 30% larger, with an increase in carbon mass that was 20% greater than AGS; (ii) produced higher quantities of stearic acid, oleic acid, monounsaturated fatty acids (MUFAs), and ergosterol; (iii) produced lower quantities of fatty acid methyl esters (FAMEs) such as methyl palmytate, and methyl linoleate, saturated fatty acids (SFAs), and poyliunsaturated fatty acids (PUFAs). ATR-FTIR and principal component analysis (PCA) statistical analysis confirmed that the macromolecular content of HGS was significantly different from AGS. The ability to produce different macromolecules by changing the trophic conditions may represent an interesting strategy to induce microalgae to produce different biomolecules that can find applications in several fields such as food, feed, nutraceutical, or energy production

Metabolomic profiling of food matrices: Preliminary identification of potential markers of microbial contamination

The research aimed to generate an early warning system highlighting in real-time bacterial contamination of meat matrices and providing information which could support companies in accepting or rejecting batches. Current microorganisms’ detection methods rely on techniques (plate counting), which provide retrospective values for microbial contamination. The purpose of this research was to evaluate the ability of the headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC/MS) methodologies to detect volatile organic carbons (VOCs), which may be associated to a peculiar microbiological contamination of food. The disposal of fast headspace gas chromatography-mass spectrometry (HS-SPME-GC/MS) able to accurately and rapidly (30 min per sample) detect pathogens in raw meat could replace the traditional and time-consuming (3 to 4 days) standardized microbiological analysis required by regulations. Experiments focused on qualitative and quantitative evaluations of VOCs produced by Salmonella Typhimurium, Campylobacter jejuni, and Staphylococcus aureus in different types of raw meat (beef, pork, chicken). HS-SPME-GC/MS allowed to use smaller sample volumes compared to traditional methods with no sample processing and the potentiality for its application on various food matrices for the detection of a wide variety of pathogens. Data analysis showed the identification of unique VOCs’ profiles being possible markers of meat contamination due to their association to specific pathogens. The identification of VOCs markers in association to selected bacterial pathogens and their metabolites could support the rapid determination of specific meat samples contamination. Further research is required to outline-specific metabolic profiles for each microorganism responsible of meat contamination and prevent false positives

Impact of the peptide wmr-k on dual-species biofilm candida albicans/klebsiella pneumoniae and on the untargeted metabolomic profile

In recent years, the scientific community has focused on the development of new antibiotics to address the difficulties linked to biofilm-forming microorganisms and drug-resistant infections. In this respect, synthetic antimicrobial peptides (AMPs) are particularly regarded for their therapeutic potential against a broad spectrum of pathogens. In this work, the antimicrobial and antibiofilm activities of the peptide WMR-K towards single and dual species cultures of Candida albicans and Klebsiella pneumoniae were investigated. We found minimum inhibitory concentration (MIC) values for WMR-K of 10 µM for K. pneumoniae and of 200 µM for C. albicans. Furthermore, sub-MIC concentrations of peptide showed an in vitro inhibition of biofilm formation of mono and polymicrobial systems and also a good biofilm eradication even if higher concentrations of it are needed. In order to provide additional evidence for the effect of the examined peptide, a study of changes in extracellular metabolites excreted and/or uptaken from the culture medium (metabolomic footprinting) in the poly-microbial association of C. albicans and K. pneumoniae in presence and absence of WMR-K was performed. Comparing to the untreated dual species biofilm culture, the metabolomic profile of the WMR-K treated culture appears significantly altered. The differentially expressed compounds are mainly related to the primary metabolic pathways, including amino acids, trehalose, pyruvic acid, glycerol and vitamin B6

An integrated analysis of intracellular metabolites and virulence gene expression during biofilm development of a clinical isolate of Candida tropicalis on distinct surfaces

Emergence of Candida tropicalis, which causes potential life-threatening invasive candidi-asis, is often associated with colonization of medical devices as biofilm. Biofilm plays an important role in the virulence of the pathogen because of its complex structure, which provides resistance to conventional antimicrobials. In this study, the metabolic response of a clinical strain of C. tropicalis colonizing three distinct surfaces (polytetrafluoroethylene (PTFE), polystyrene, and polycarbonate) as well as the expression of virulence and stress related genes (ALS3, Hsp21, SAP1, SAP2, SAP3, and CYR1), were explored. Our results showed that lesser biofilm was developed on PTFE compared to polystyrene and polycarbonate. GS-MS metabolic analysis identified a total of 36 metabolites in the intracellular extract of cells grown on polystyrene, polycarbonate, and PTFE, essentially belonging to central carbon metabolism, amino acids, and lipids metabolism. The metabolic analysis showed that saturated and unsaturated fatty acids are preferentially produced during biofilm development on polycarbonate, whereas trehalose and vitamin B6, known as cellular protectors against a variety of stressors, were characteristic of biofilm on PTFE. The results of the transcriptomic analysis con-sider the different degrees of colonization of the three substrates, being CYR1, which encodes the component of signaling pathway of hyphal formation-cAMP-PKA, downregulated in PTFE biofilm compared to polycarbonate or polystyrene biofilms, while Hsp21 was upregulated in concomitance with the potential unfavorable conditions for biofilm formation on PTFE. Overall, this work provides new insights into the knowledge of C. tropicalis biofilm development on surfaces of medical relevance in the perspective of improving the management of Candida infections

The membranotropic peptide gh625 to combat mixed candida albicans/klebsiella pneumoniae biofilm: Correlation between in vitro anti-biofilm activity and in vivo antimicrobial protection

The antibiofilm activity of a gH625 analogue was investigated to determine the in vitro inhibition and eradication of a dual-species biofilm of Candida albicans and Klebsiella pneumoniae, two leading opportunistic pathogens responsible for several resistant infections. The possibility of effectively exploiting this peptide as an alternative anti-biofilm strategy in vivo was assessed by the investigation of its efficacy on the Galleria mellonella larvae model. Results on larvae survival demonstrate a prophylactic efficacy of the peptide towards the infection of each single microorganism but mainly towards the co-infection. The expression of biofilm-related genes in vivo showed a possible synergy in virulence when these two species co-exist in the host, which was effectively prevented by the peptide. These findings provide novel insights into the treatment of medically relevant bacterial–fungal interaction

Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions

How do cardiologists select patients for dual antiplatelet therapy continuation beyond 1 year after a myocardial infarction? Insights from the EYESHOT Post-MI Study

Background: Current guidelines suggest to consider dual antiplatelet therapy (DAPT) continuation for longer than 12 months in selected patients with myocardial infarction (MI). Hypothesis: We sought to assess the criteria used by cardiologists in daily practice to select patients with a history of MI eligible for DAPT continuation beyond 1 year. Methods: We analyzed data from the EYESHOT Post-MI, a prospective, observational, nationwide study aimed to evaluate the management of patients presenting to cardiologists 1 to 3 years from the last MI event. Results: Out of the 1633 post-MI patients enrolled in the study between March and December 2017, 557 (34.1%) were on DAPT at the time of enrolment, and 450 (27.6%) were prescribed DAPT after cardiologist assessment. At multivariate analyses, a percutaneous coronary intervention (PCI) with multiple stents and the presence of peripheral artery disease (PAD) resulted as independent predictors of DAPT continuation, while atrial fibrillation was the only independent predictor of DAPT interruption for patients both at the second and the third year from MI at enrolment and the time of discharge/end of the visit. Conclusions: Risk scores recommended by current guidelines for guiding decisions on DAPT duration are underused and misused in clinical practice. A PCI with multiple stents and a history of PAD resulted as the clinical variables more frequently associated with DAPT continuation beyond 1 year from the index MI

Two-level method part-scale thermal analysis of laser powder bed fusion additive manufacturing

Numerical simulations of a complete laser powder bed fusion (LPBF) additive manufacturing (AM) process are extremely challenging, or even impossible, to achieve without a radical model reduction of the complex physical phenomena occurring during the process. However, even when we adopt a reduced model with simplified physics, the complex geometries of parts usually produced by the LPBF AM processes make this kind of analysis computationally expensive. In fact, small geometrical features-which might be generated when the part is designed following the principle of the so-called design for AM, for instance, by means of topology optimization procedures-often require complex conformal meshes. Immersed boundary methods offer an alternative to deal with this kind of complexity, without requiring complicated meshing strategies. The two-level method lies within this family of numerical methods and presents a flexible tool to deal with multi-scale problems. In this contribution, we apply a modified version of the recently introduced two-level method to part-scale thermal analysis of LPBF manufactured components. We first validate the proposed part-scale model with respect to experimental measurements from the literature. Then, we apply the presented numerical framework to simulate a complete LPBF process of a topologically optimized structure, showing the capability of the method to easily deal with complex geometrical features