Study on active wheelset steering from the perspective of wheel wear evolution

Active wheelset steering promises an attractive cost–benefit ratio and is highly likely to be implemented in the future. Previous studies investigated the steering effect simply through a wear index like wear number. However, a wear index cannot predict how much the material removal on wheels can be reduced, and it is unable to reveal the wear pattern. This paper builds an iterative wear model to predict wheel wear evaluation under the presence of an active steering system. Three active steering schemes are proposed, and they are compared in terms of wheel wear evolution. To quantify the steering effectiveness, two factors are created to, respectively, evaluate economic impacts and satisfaction of three steering schemes. Finally, a simplified method based on traditional wear indices is compared with the established iterative wear calculation method to examine the applicability and tolerance of the simplified method

Dynamics of railway freight vehicles

This paper summarises the historical development of railway freight vehicles and how vehicle designers have tackled the difficult challenges of producing running gear which can accommodate the very high tare to laden mass of typical freight wagons whilst maintaining stable running at the maximum required speed and good curving performance. The most common current freight bogies are described in detail and recent improvements in techniques used to simulate the dynamic behaviour of railway vehicles are summarised and examples of how these have been used to improve freight vehicle dynamic behaviour are included. A number of recent developments and innovative components and sub systems are outlined and finally two new developments are presented in more detail: the LEILA bogie and the SUSTRAIL bogie

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction

Anisotropic scale invariant cosmology

We study a possibility of anisotropic scale invariant cosmology. It is shown that within the conventional Einstein gravity, the violation of the null energy condition is necessary. We construct an example based on a ghost condensation model that violates the null energy condition. The cosmological solution necessarily contains at least one contracting spatial direction as in the Kasner solution. Our cosmology is conjectured to be dual to, if any, a non-unitary anisotropic scale invariant Euclidean field theory. We investigate simple correlation functions of the dual theory by using the holographic computation. After compactification of the contracting direction, our setup may yield a dual field theory description of the winding tachyon condensation that might solve the singularity of big bang/crunch of the universe.Comment: 12 pages, v2: reference adde

Jacobson generators, Fock representations and statistics of sl(n+1)

The properties of A-statistics, related to the class of simple Lie algebras sl(n+1) (Palev, T.D.: Preprint JINR E17-10550 (1977); hep-th/9705032), are further investigated. The description of each sl(n+1) is carried out via generators and their relations, first introduced by Jacobson. The related Fock spaces W_p (p=1,2,...) are finite-dimensional irreducible sl(n+1)-modules. The Pauli principle of the underlying statistics is formulated. In addition the paper contains the following new results: (a) The A-statistics are interpreted as exclusion statistics; (b) Within each W_p operators B(p)_1^\pm, ..., B(p)_n^\pm, proportional to the Jacobson generators, are introduced. It is proved that in an appropriate topology the limit of B(p)_i^\pm for p going to infinity is equal to B_i^\pm, where B_i^\pm are Bose creation and annihilation operators; (c) It is shown that the local statistics of the degenerated hard-core Bose models and of the related Heisenberg spin models is p=1 A-statistics.Comment: LaTeX-file, 33 page

DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'

Diagnosing bone and soft tissue neoplasms remains challenging because of the large number of subtypes, many of which lack diagnostic biomarkers. DNA methylation profiles have proven to be a reliable basis for the classification of brain tumours and, following this success, a DNA methylation-based sarcoma classification tool from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg has been developed. In this study, we assessed the performance of their classifier on DNA methylation profiles of an independent data set of 986 bone and soft tissue tumours and controls. We found that the 'DKFZ Sarcoma Classifier' was able to produce a diagnostic prediction for 55% of the 986 samples, with 83% of these predictions concordant with the histological diagnosis. On limiting the validation to the 820 cases with histological diagnoses for which the DKFZ Classifier was trained, 61% of cases received a prediction, and the histological diagnosis was concordant with the predicted methylation class in 88% of these cases, findings comparable to those reported in the DKFZ Classifier paper. The classifier performed best when diagnosing mesenchymal chondrosarcomas (CHSs, 88% sensitivity), chordomas (85% sensitivity), and fibrous dysplasia (83% sensitivity). Amongst the subtypes least often classified correctly were clear cell CHSs (14% sensitivity), malignant peripheral nerve sheath tumours (27% sensitivity), and pleomorphic liposarcomas (29% sensitivity). The classifier predictions resulted in revision of the histological diagnosis in six of our cases. We observed that, although a higher tumour purity resulted in a greater likelihood of a prediction being made, it did not correlate with classifier accuracy. Our results show that the DKFZ Classifier represents a powerful research tool for exploring the pathogenesis of sarcoma; with refinement, it has the potential to be a valuable diagnostic tool

Particle-seawater interaction of neodymium in the North Atlantic

Dissolved neodymium (Nd) isotopes (expressed as εNd) have been widely used as a water mass tracer in paleoceanography. However, one aspect of the modern biogeochemical cycle of Nd that has been sparsely investigated is the interplay between dissolved and particulate phases in seawater. We here present the first regional data set on particulate Nd isotope compositions (εNdp) and concentrations ([Nd]p) from five stations in the western North Atlantic Ocean along the GEOTRACES GA02 transect, in conjunction with previously published dissolved Nd isotope compositions (εNdd) and concentrations ([Nd]d)1. Key observations and interpretations from our new particulate data set include the following: (1) A low fractional contributions of [Nd]p to the total Nd inventory per volume unit of seawater (~5%), with significant increases of up to 45% in benthic boundary layers. (2) Increasing Nd concentrations in suspended particulate matter ([Nd]SPM) and fractions of lithogenic material with water depth, suggesting the removal of Nd poor phases. (3) Different provenances of particulates in the subpolar and subtropical gyres as evidenced by their Nd isotope fingerprints reaching from εNdp ≈ -20 near the Labrador Basin (old continental crust), over εNdp ≈ -4 between Iceland and Greenland (young mafic provenance), to values of εNdp ≈-13 in the subtropics (similar to African dust signal). (4) Vertical heterogeneity of εNdp, as well as large deviations from ambient seawater values in the subpolar gyre, indicate advection of lithogenic particles in this area. (5) Vertically homogenous εNdp values in the subtropical gyre, indistinguishable from εNdd values, are indicative of predominance of vertical particulate supply. The process of reversible scavenging only seems to influence particulate signatures below 3 km. Overall, we do not find evidence on enhanced particle dissolution, often invoked to explain the observed increase in dissolved Nd in the North Atlantic