Understanding adhesion at as-deposited interfaces from ab initio thermodynamics of deposition growth: thin-film alumina on titanium carbide

We investigate the chemical composition and adhesion of chemical vapour deposited thin-film alumina on TiC using and extending a recently proposed nonequilibrium method of ab initio thermodynamics of deposition growth (AIT-DG) [Rohrer J and Hyldgaard P 2010 Phys. Rev. B 82 045415]. A previous study of this system [Rohrer J, Ruberto C and Hyldgaard P 2010 J. Phys.: Condens. Matter 22 015004] found that use of equilibrium thermodynamics leads to predictions of a non-binding TiC/alumina interface, despite the industrial use as a wear-resistant coating. This discrepancy between equilibrium theory and experiment is resolved by the AIT-DG method which predicts interfaces with strong adhesion. The AIT-DG method combines density functional theory calculations, rate-equation modelling of the pressure evolution of the deposition environment and thermochemical data. The AIT-DG method was previously used to predict prevalent terminations of growing or as-deposited surfaces of binary materials. Here we extent the method to predict surface and interface compositions of growing or as-deposited thin films on a substrate and find that inclusion of the nonequilibrium deposition environment has important implications for the nature of buried interfaces.Comment: 8 pages, 6 figures, submitted to J. Phys.: Condens. Matte

Effective elastic properties of a van der Waals molecular monolayer at a metal surface

Adsorbing anthracene on a Cu(111) surface results in a wide range of complex and intriguing superstructures spanning a coverage range from 1 per 17 to 1 per 15 substrate atoms. In accompanying first-principles density-functional theory calculations we show the essential role of van der Waals interactions in estimating the variation in anthracene adsorption energy and height across the sample. We can thereby evaluate the compression of the anthracene film in terms of continuum elastic properties, which results in an effective Young's modulus of 1.5 GPa and a Poisson ratio approximate to 0.1. These values suggest interpretation of the molecular monolayer as a porous material-in marked congruence with our microscopic observations

Interaction of metal phthalocyanines with carbon zigzag and armchair nanotubes with different diameters

Quantum-chemical calculations of the association of metal free, cobalt, copper and zinc phthalocyanines (MPc) with carbon zigzag and armchair nanotubes (CNTs) with diameters in the range of 7–14 Å were carried out by the DFT method with the use of BH van der Waals density functional and DZP atomic basis set. It was shown that interaction energy between the phthalocyanine molecules and the CNTs, as a whole, increases with an increase of the diameter of carbon nanotubes. However, in the case of CNT(n,0) the energy reaches its maximal value at n = 16 or 17 depending on the central metal atom and phthalocyanine orientation on the carbon nanotubes surface. Up to diameter of 10.5 Å of the CNTs, stronger binding of the considered MPc macrocyclic molecules is observed with carbon armchair nanotubes. However, in the case of higher diameters the phthalocyanines are associated more strongly with the zigzag CNTs

Evaluation of the impact of pharmaceutical trainings and tools on the proper use of medicines in pediatrics

Introduction: After six years of medication errors’ (MEs) collection and analysis in a pediatric unit of a French University Hospital, the number of MEs was no longer decreasing. We then decided to set up pharmaceutical training and tools and evaluate their impact on the occurrence of ME.Materials and methods: This monocentric prospective study was carried out in the form of audits of prescriptions, preparations, and administrations before and after intervention (A1 and A2). After the analysis of A1 results, feedback was given to the teams, some tools for the proper use of medication (PUM) were distributed, and A2 was conducted. Finally, A1 and A2 results were compared.Results: Each audit included 202 observations. A total of 120 MEs were identified during A1 and 54 for A2 (p < 0.0001). The observation rate with at least 1 ME decreased from 39.11% to 21.29% (p < 0.0001), and no observation had more than two MEs during A2 in contrast to A1 (n = 12). Human factors were responsible for the majority of MEs. The audit feedback allowed professionals to feel concerned about ME. The PUM tools received an average satisfaction rating of 9/10. The staff had never participated in this type of training, and all felt it was useful to apply PUM.Conclusion: This study showed a significant impact of pharmaceutical training and tools on the pediatric PUM. Clinical pharmaceutic actions allowed us to reach our objectives and satisfied all the staff. They must, therefore, be continued to limit human factors’ impact and thus contribute to the safety of drug management in pediatrics

The contrast-enhanced Doppler ultrasound with perfluorocarbon exposed sonicated albumin does not improve the diagnosis of renal artery stenosis compared with angiography

There are no studies investigating the effect of the contrast infusion on the sensitivity and specificity of the main Doppler criteria of renal artery stenosis (RAS). Our aim was to evaluate the accuracy of these Doppler criteria prior to and following the intravenous administration of perfluorocarbon exposed sonicated albumin (PESDA) in patients suspected of having RAS. Thirty consecutive hypertensive patients (13 males, mean age of 57 ± 10 years) suspected of having RAS by clinical clues, were submitted to ultrasonography (US) of renal arteries before and after enhancement using continuous infusion of PESDA. All patients underwent angiography, and haemodynamically significant RAS was considered when ≥50%. At angiography, it was detected RAS ≥50% in 18 patients, 5 with bilateral stenosis. After contrast, the examination time was slightly reduced by approximately 20%. In non-enhanced US the sensitivity was better when based on resistance index (82.9%) while the specificity was better when based on renal aortic ratio (89.2%). The predictive positive value was stable for all indexes (74.0%–88.0%) while negative predictive value was low (44%–51%). The specificity and positive predictive value based on renal aortic ratio increased after PESDA injection respectively, from 89 to 97.3% and from 88 to 95%. In hypertensives suspected to have RAS the sensitivity and specificity of Duplex US is dependent of the criterion evaluated. Enhancement with continuous infusion of PESDA improves only the specificity based on renal aortic ratio but do not modify the sensitivity of any index

Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment

The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations and their relation to the development and progression of various complex diseases. Improved data-analytical tools are needed to exploit all information from these biological datasets, taking into account the peculiarities of microbiome data, i.e., compositional, heterogeneous and sparse nature of these datasets. The possibility of predicting host-phenotypes based on taxonomy-informed feature selection to establish an association between microbiome and predict disease states is beneficial for personalized medicine. In this regard, machine learning (ML) provides new insights into the development of models that can be used to predict outputs, such as classification and prediction in microbiology, infer host phenotypes to predict diseases and use microbial communities to stratify patients by their characterization of state-specific microbial signatures. Here we review the state-of-the-art ML methods and respective software applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on the application of ML in microbiome studies related to association and clinical use for diagnostics, prognostics, and therapeutics. Although the data presented here is more related to the bacterial community, many algorithms could be applied in general, regardless of the feature type. This literature and software review covering this broad topic is aligned with the scoping review methodology. The manual identification of data sources has been complemented with: (1) automated publication search through digital libraries of the three major publishers using natural language processing (NLP) Toolkit, and (2) an automated identification of relevant software repositories on GitHub and ranking of the related research papers relying on learning to rank approach.This study was supported by COST Action CA18131 “Statistical and machine learning techniques in human microbiome studies”. Estonian Research Council grant PRG548 (JT). Spanish State Research Agency Juan de la Cierva Grant IJC2019-042188-I (LM-Z). EO was founded and OA was supported by Estonian Research Council grant PUT 1371 and EMBO Installation grant 3573. AG was supported by Statutory Research project of the Department of Computer Networks and Systems

Challenges for IT-Enabled Formative Assessment of Complex 21st Century Skills

In this article, we identify and examine opportunities for formative assessment provided by information technologies (IT) and the challenges which these opportunities present. We address some of these challenges by examining key aspects of assessment processes that can be facilitated by IT: datafication of learning; feedback and scaffolding; peer assessment and peer feedback. We then consider how these processes may be applied in relation to the assessment of horizontal, general complex 21st century skills (21st CS), which are still proving challenging to incorporate into curricula as well as to assess. 21st CS such as creativity, complex problem solving, communication, collaboration and self-regulated learning contain complex constructs incorporating motivational and affective components. Our analysis has enabled us to make recommendations for policy, practice and further research. While there is currently much interest in and some progress towards the development of learning/assessment analytics for assessing 21st CS, the complexity of assessing such skills, together with the need to include affective aspects means that using IT-enabled techniques will need to be combined with more traditional methods of teacher assessment as well as peer assessment for some time to come. Therefore learners, teachers and school leaders must learn how to manage the greater variety of sorts and sources of feedback including resolving tensions of inconsistent feedback from different sources

Spatial analysis of biomineralization associated gene expression from the mantle organ of the pearl oyster Pinctada maxima

Background: Biomineralization is a process encompassing all mineral containing tissues produced within an organism. One of the most dynamic examples of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this architecture. However general understanding of how this process is achieved remains ambiguous. The mantle is a conserved organ involved in shell formation throughout molluscs. Specifically the mantle is thought to be responsible for secreting the protein component of the shell. This study employs molecular approaches to determine the spatial expression of genes within the mantle tissue to further the elucidation of the shell biomineralization. Results: A microarray platform was custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from mantle tissue. This microarray was used to analyze the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and analyzed for differential gene expression with PmaxArray 1.0. Over 2000 ESTs were determined to be differentially expressed among the tissue sections, identifying five major expression regions. In situ hybridization validated and further localized the expression for a subset of these ESTs. Comparative sequence similarity analysis of these ESTs revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell related genes

Mutations in EPHB4 cause human venous valve aplasia.

Venous valve (VV) failure causes chronic venous insufficiency, but the molecular regulation of valve development is poorly understood. A primary lymphatic anomaly, caused by mutations in the receptor tyrosine kinase EPHB4, was recently described, with these patients also presenting with venous insufficiency. Whether the venous anomalies are the result of an effect on VVs is not known. VV formation requires complex "organization" of valve-forming endothelial cells, including their reorientation perpendicular to the direction of blood flow. Using quantitative ultrasound, we identified substantial VV aplasia and deep venous reflux in patients with mutations in EPHB4. We used a GFP reporter in mice to study expression of its ligand, ephrinB2, and analyzed developmental phenotypes after conditional deletion of floxed Ephb4 and Efnb2 alleles. EphB4 and ephrinB2 expression patterns were dynamically regulated around organizing valve-forming cells. Efnb2 deletion disrupted the normal endothelial expression patterns of the gap junction proteins connexin37 and connexin43 (both required for normal valve development) around reorientating valve-forming cells and produced deficient valve-forming cell elongation, reorientation, polarity, and proliferation. Ephb4 was also required for valve-forming cell organization and subsequent growth of the valve leaflets. These results uncover a potentially novel cause of primary human VV aplasia