Life cycle performance assessment tool development and application with a focus on maintenance aspects

Ships are among the most complex systems in the world. The always increasing interest in environmental aspects, the evolution of technologies and the introduction of new rule constraints in the maritime field have compelled the innovation of the ship design approach. At an early design stage, there is the need to compare different design solutions, also in terms of environmental performance, building and operative costs over the whole ship life cycle. In this context, the Life Cycle Performance Assessment (LCPA) tool allows an integrated design approach merging the evaluation of both costs and environmental performances on a comparative basis, among different design solutions. Starting from the first tool release, this work aims to focus on the maintenance of the propulsion system, developing a flexible calculation method for maintenance costs prediction, based on the ship operational profiles and the selected technical solution. After the improvement, the whole LCPA tool has been applied on a research vessel to evaluate, among different propulsion layout solutions, the one with the more advantageous performance in terms of costs during the whole vessel operating life. The identification of the best design solution is strictly dependent on the selection criterion and the point of view of the interested parties using the LCPA tool, e.g., the shipbuilder or the ship-owner

The influence of gender stereotype threat on mathematics test scores of Dutch high school students:A registered report

The effects of gender stereotype threat on mathematical test performance in the classroom have been extensively studied in several cultural contexts. Theory predicts that stereotype threat lowers girls’ performance on mathematics tests, while leaving boys’ math performance unaffected. We conducted a large-scale stereotype threat experiment in Dutch high schools (N = 2064) to study the generalizability of the effect. In this registered report, we set out to replicate the overall effect among female high school students and to study four core theoretical moderators, namely domain identification, gender identification, math anxiety, and test difficulty. Among the girls, we found neither an overall effect of stereotype threat on math performance, nor any moderated stereotype threat effects. Most variance in math performance was explained by gender, domain identification, and math identification. We discuss several theoretical and statistical explanations for these findings. Our results are limited to the studied population (i.e. Dutch high school students, age 13–14) and the studied domain (mathematics)

Influence of Different Evolutive Forces on GDF5 Gene Variability

The GDF5 gene is involved in the development of skeletal elements, synovial joint formation, tendons, ligaments, and cartilage. Several polymorphisms are present within the gene, and two of them, rs143384 and 143383, were reported to be correlated with osteoarticular disease or muscle flexibility. The aim of this research is to verify if the worldwide distribution of the rs143384 polymorphism among human populations was shaped by selective pressure, or if it was the result of random genetic drift events. Ninety-four individuals of both the male and female sexes, 18–28 years old, from Sardinia were analyzed. We observed the following genotype frequencies: 28.72% of AA homozygotes, 13.83% of GG homozygotes, and 57.45% of AG heterozygotes. The allele frequencies were 0.574 for allele A and 0.426 for allele G. The relationships between the populations were verified via Multidimensional Scaling (MDS). Our data show (i) a clear heterogeneity within the African populations; (ii) a strong differentiation between the African populations and the other populations; and that (iii) the Sardinian population is placed within the European cluster. To reveal possible traces of selective pressure, the Population Branch Statistic (PBS) was calculated; both the rs143384 and 143383 SNPs have low PBS values, suggesting that there are no signals of selective pressure in those areas of the gene

HIF-1 alpha-independent hypoxia-induced rapid PTK6 stabilization is associated with increased motility and invasion

© 2014 Landes Bioscience. PTK6/Brk is a non-receptor tyrosine kinase overexpressed in cancer. Here we demonstrate that cytosolic PTK6 is rapidly and robustly induced in response to hypoxic conditions in a HIF-1-independent manner. Furthermore, a proportion of hypoxic PTK6 subsequently re-localized to the cell membrane. We observed that the rapid stabilization of PTK6 is associated with a decrease in PTK6 ubiquitylation and we have identified c-Cbl as a putative PTK6 E3 ligase in normoxia. The consequences of hypoxia-induced PTK6 stabilization and subcellular re-localization to the plasma membrane include increased cell motility and invasion, suggesting PTK6 targeting as a therapeutic approach to reduce hypoxia-regulated metastatic potential. This could have particular significance for breast cancer patients with triple negative disease

Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed

Assessing signals of TMD physics in SIDIS azimuthal asymmetries and in the extraction of the Sivers function

New data on the Sivers azimuthal asymmetry measured in semi-inclusive deep-inelastic scattering processes have recently been released by the COMPASS Collaboration at CERN. Their increased precision and their particular binning, in terms of $Q^2$ as well as $x$, motivates a new extraction of the Sivers function, within the framework of a simple and transparent parametrization. Signals of TMD effects visible in the Sivers asymmetries are critically assessed. A thorough study of the uncertainties affecting the extracted Sivers function is presented, including the low-$x$ and large-$x$ regions.Comment: 20 pages, 13 figure

Worldwide variation of the COL14A1 gene is shaped by genetic drift rather than selective pressure

Background: The aim of this study is to analyze the worldwide distribution of SNP rs4870723 in COL14A1 gene to check if there are significant genetic differences among different populations and to test if the gene is a trait under selection. Methods: Genomic DNA was extracted from 69 unrelated individuals from Sardinia and genotyped for SNP rs4870723. Data were compared with 26 different populations, clustered in 5 super-populations, from the public 1000 genomes database. Allele frequency and heterozygosity were calculated with Genepop. The Hardy–Weinberg equilibrium and pairwise population differentiation through analysis of molecular variance (AMOVA FST) were determined with Arlequin. Results: Allele frequencies of COL14A1 rs4870723 were compared in 27 populations clustered in 5 super-populations. All populations were in the Hardy–Weinberg equilibrium. In almost all populations, allele C was the most frequent allele, reaching the highest values in East Asia. The 27 populations showed an appreciable structure, with significant differences observed between European, African, and Asian populations. Conclusion: Significant differences were observed in the rs4870723 SNP distribution among the populations studied. However, we found no evidence for a selective pressure. Rather, the differentiation among the populations is likely the result of founder effect, genetic drift, and cultural factors, all events known to establish and maintain genetic diversity between populations

Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease

Chronic kidney disease (CKD) is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR) at mild (59.9±16.5 mL/min/1.73 m2; n = 10) or advanced (8.9±4.5 mL/min/1.73 m2; n = 10) CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = −0.8031; p<0.0001 and ρ = −0.6009; p = 0.0019, respectively). Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = −0.6557; p = 0.0001 and ρ = −0.6574; p = 0.0005). A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = −0.7752; p<0.0001 and ρ = −0.8400; p<0.0001). The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In conclusion, we found excellent association of plasma and urinary metabolites and urinary peptides with kidney function, and disease progression, but no added value in combining the different biomarkers data