The role of negative maternal affective states and infant temperament in early interactions between infants with cleft lip and their mothers

OBJECTIVES: The study examined the early interaction between mothers and their infants with cleft lip, assessing the role of maternal affective state and expressiveness and differences in infant temperament. METHODS: Mother-infant interactions were assessed in 25 2-month-old infants with cleft lip and 25 age-matched healthy infants. Self-report and behavioral observations were used to assess maternal depressive symptoms and expressions. Mothers rated infant temperament. RESULTS: Infants with cleft lip were less engaged and their mothers showed more difficulty in interaction than control group dyads. Mothers of infants with cleft lip displayed more negative affectivity, but did not report more self-rated depressive symptoms than control group mothers. No group differences were found in infant temperament. CONCLUSIONS: In order to support the mother's experience and facilitate her ongoing parental role, findings highlight the importance of identifying maternal negative affectivity during early interactions, even when they seem have little awareness of their depressive symptoms

An Advanced Leakage Scheme for Neutrino Treatment in Astrophysical Simulations

We present an Advanced Spectral Leakage (ASL) scheme to model neutrinos in the context of core-collapse supernovae (CCSNe) and compact binary mergers. Based on previous gray leakage schemes, the ASL scheme computes the neutrino cooling rates by interpolating local production and diffusion rates (relevant in optically thin and thick regimes, respectively) separately for discretized values of the neutrino energy. Neutrino trapped components are also modeled, based on equilibrium and timescale arguments. The better accuracy achieved by the spectral treatment allows a more reliable computation of neutrino heating rates in optically thin conditions. The scheme has been calibrated and tested against Boltzmann transport in the context of Newtonian spherically symmetric models of CCSNe. ASL shows a very good qualitative and a partial quantitative agreement for key quantities from collapse to a few hundreds of milliseconds after core bounce. We have proved the adaptability and flexibility of our ASL scheme, coupling it to an axisymmetric Eulerian and to a three-dimensional smoothed particle hydrodynamics code to simulate core collapse. Therefore, the neutrino treatment presented here is ideal for large parameter-space explorations, parametric studies, high-resolution tests, code developments, and long-term modeling of asymmetric configurations, where more detailed neutrino treatments are not available or are currently computationally too expensive

The role of oxygen vacancies on the structure and the density of states of iron doped zirconia

In this paper we study, both with theoretical and experimental approach, the effect of iron doping in zirconia. Combining density functional theory (DFT) simulations with the experimental characterization of thin films, we show that iron is in the Fe3+ oxidation state and accordingly that the films are rich in oxygen vacancies (VO). VO favor the formation of the tetragonal phase in doped zirconia (ZrO2:Fe) and affect the density of state at the Fermi level as well as the local magnetization of Fe atoms. We also show that the Fe(2p) and Fe(3p) energy levels can be used as a marker for the presence of vacancies in the doped system. In particular the computed position of the Fe(3p) peak is strongly sensitive to the VO to Fe atoms ratio. A comparison of the theoretical and experimental Fe(3p) peak position suggests that in our films this ratio is close to 0.5. Besides the interest in the material by itself, ZrO2:Fe constitutes a test case for the application of DFT on transition metals embedded in oxides. In ZrO2:Fe the inclusion of the Hubbard U correction significantly changes the electronic properties of the system. However the inclusion of this correction, at least for the value U = 3.3 eV chosen in the present work, worsen the agreement with the measured photo-emission valence band spectra.Comment: 24 pages, 8 figure

A constitutive model for the mechanical response of the folding of creased paperboard

AbstractPaperboard is a widely used material in industrial processes, in particular for packaging purposes. Packages are obtained through a forming process, in which a flat laminated sheet is converted into the final 3-D solid. In the package forming process, it is common practice to score the paperboard laminate with crease lines, in order to obtain folds with sharp edges and to minimize the initiation and propagation of flaws during the subsequent folding procedures. In this work, a constitutive model for the mechanical response of crease lines is proposed and validated on the basis of experimental tests available in the literature. The model has been implemented in an interface finite element to be placed between adjacent shell elements and is intended for large-scale computations of package forming processes. For this reason, the material model has been developed at the macroscopic scale in terms of generalized variables, aiming at computational effectiveness

The role of the phosphopantetheinyltransferase enzyme, PswP, in the biosynthesis of antimicrobial secondary metabolites by <em>Serratia marcescens </em>Db10

Phosphopantetheinyltransferase (PPTase) enzymes fulfil essential roles in primary and secondary metabolism in prokaryotes, archaea and eukaryotes. PPTase enzymes catalyse the essential modification of the carrier protein domain of fatty acid synthases, polyketide synthases (PKSs) and non-ribosomal peptide synthetases (NRPSs). In bacteria and fungi, NRPS and PKS enzymes are often responsible for the biosynthesis of secondary metabolites with clinically relevant properties; these secondary metabolites include a variety of antimicrobial peptides. We have previously shown that in the Gram-negative bacterium Serratia marcescens Db10, the PPTase enzyme PswP is essential for the biosynthesis of an NRPS-PKS dependent antibiotic called althiomycin. In this work we utilize bioinformatic analyses to classify PswP as belonging to the F/KES subfamily of Sfp type PPTases and to putatively identify additional NRPS substrates of PswP, in addition to the althiomycin NRPS-PKS, in Ser. marcescens Db10. We show that PswP is required for the production of three diffusible metabolites by this organism, each possessing antimicrobial activity against Staphylococcus aureus. Genetic analyses identify the three metabolites as althiomycin, serrawettin W2 and an as-yet-uncharacterized siderophore, which may be related to enterobactin. Our results highlight the use of an individual PPTase enzyme in multiple biosynthetic pathways, each contributing to the ability of Ser. marcescens to inhibit competitor bacteria by the production of antimicrobial secondary metabolites

GAM Forest Explanation

Most accurate machine learning models unfortunately produce black-box predictions, for which it is impossible to grasp the internal logic that leads to a specific decision. Unfolding the logic of such black-box models is of increasing importance, especially when they are used in sensitive decision-making processes. In this work we focus on forests of decision trees, which may include hundreds to thousands of decision trees to produce accurate predictions. Such complexity raises the need of developing explanations for the predictions generated by large forests. We propose a post hoc explanation method of large forests, named GAM-based Explanation of Forests (GEF), which builds a Generalized Additive Model (GAM) able to explain, both locally and globally, the impact on the predictions of a limited set of features and feature interactions. We evaluate GEF over both synthetic and real-world datasets and show that GEF can create a GAM model with high fidelity by analyzing the given forest only and without using any further information, not even the initial training dataset

Diagnostic evaluation of a point-of-care test for culture and microbial susceptibility testing in canine dermatological infections in clinical practice

Background and Aim: Empirical antimicrobial therapy is frequently given in superficial bacterial folliculitis (SBF) and otitis externa (OE) in dogs, especially for the initial clinical presentation. Culture and subsequent antimicrobial susceptibility testing (AST) are generally limited to chronic cases with poor response to initial therapy. Several factors contribute to the failure to implement the use of AST in veterinary practice, i.e., long laboratory turnaround time or special requirements for sample shipping. Point-of-care (PoC) testing might reduce laboratory turnaround time and costs and the risk of emergence of multidrug-resistant pathogens. This study evaluated the Speed Biogram\u2122 PoC test in canine SBF and OE compared with conventional methods for culture and AST. Materials and Methods: Thirty-four canine samples were analyzed: eleven from SBF, seven from bacterial OE, four from mixed OE, six from Malassezia spp. OE, and six negative controls. Sensitivity (Se) and specificity (Sp) of the PoC test and the agreement between the PoC test and conventional methods were evaluated. Results: Se and Sp of PoC test in discriminating between healthy and unhealthy subjects were 100% (95% confidence interval [CI] 87.66-100.00) and 100% (95% CI 54.1-100.0), respectively. For bacterial identification, the k value was 0.532. Se and Sp of PoC tests for AST were 81.73% (95% CI 72.95-88.63) and 93.10% (95% CI 88.86-96.98), respectively with a total good agreement between tests (mean k=0.714), but major (8/27) and very major (19/27) errors were observed in 55% of bacterial conventional culture-positive samples. Conclusion: PoC test can identify dogs with SBF and OE, but AST is not sufficiently accurate. The lack of susceptibility testing for methicillin makes this test inappropriate for use in small animal practice

An incremental prefix filtering approach for all pairs similarity search

Given a set of records, a threshold value t and a similarity function, we investigate the problem of finding all pairs of records such that similarity between each pair is above t. We propose several optimizations on the existing approaches to solve the problem. Our algorithm outperforms the state-of-the-art algorithms in the case with large and high-dimensional datasets. The speedup we achieved varied from 30% to 4-x depending on the similarity threshold and the dataset properties