Lubrication in cold rolling: Elasto-plasto-hydrodynamic lubrication

A model has been developed with respect to hydrodynamic lubrication in cold rolling. The basic model describes the configuration of a rigid, perfectly plastic sheet rolled by a rigid work roll. The governing equations have been solved throughout the complete contact area, i.e. the inlet, the work zone and the outlet zone. Multi-level techniques have been applied to solve these equations together with boundary conditions, resulting in an algorithm solving the problem in O(n) operations. This means that the distribution of the pressure and the traction force in the lubricant film, and the shape of this film, as well as the plastic deformation of the sheet, can be accurately calculated for a large number of nodal points on a minicomputer. Subsequently elastic deformation, work hardening and dynamic behaviour of the flow stress have been incorporated in the model. It will be shown that the influence of these effects on the film thickness or the pressure distribution is considerable

The use of soil analysis in the interpretation of an early historic landscape at Puxton in Somerset

Reproduced with permission of the publisher. Journal home page http://www.landscapestudies.com/index_files/Volumes.htmSoil samples taken from two adjoining fields close to the village of Puxton in the county of North Somerset, UK, were analysed in 1997 for heavy metals, phosphorus, magnetic susceptibility and loss on ignition as part of an archaeological investigation of the origins and development of a medieval settlement. It had been argued that an oval-shaped field next to the church was the nucleus of marshland reclamation during the early medieval period, though it was unclear whether the enclosure was occupied by a settlement or was simply an area of embanked agricultural land. Soil chemistry shows certain elements, including phosphorus and the heavy metals (Pb, Zn, Cd, Cu, etc), to be concentrated in a restricted part of the enclosure, which earthwork, resistivity and fieldwalking surveys suggest correlates with an area of human occupation associated with the dumping of midden material (a hypothesis confirmed through excavation). This paper demonstrates the value of multifaceted soil chemistry, alongside a range of other survey methods, for characterizing the nature of human activity on archaeological sites, and in the future may be used to locate previously unrecorded sites in more speculative landscape surveys

Kalman filtering for nonlinear atmospheric chemistry models : first experiences

The aim of the {sc eu project {sc riftoz is to analyse regional differences in tropospheric ozone over Europe. One of the key activities within {sc riftoz therefore involves recovering ozone concentrations from available measurements. This will be done by running the atmospheric chemistry model {sc lotos over the selected period using a data assimilation technique to incorporate the measurements. A commonly used data assimilation technique is the (extended) Kalman filter. This filter has proved to be very useful in many applications. However, the models involved in these applications are usually only weakly nonlinear, whereas atmospheric models, like {sc lotos, are often highly nonlinear. The paper presents first results on data assimilation with a highly nonlinear test model using the (extended) Kalman filter algorithm. The test model has been designed such that the essential characteristics of the {sc lotos model, including stiff (photo-)chemistry, have been retained. Application of the standard algorithm for Kalman filtering is infeasible because of the huge computational and storage requirements. Instead, a reduced rank approximation of the covariance matrix is used, which reduces the computational burden to an acceptable amount of CPU time. Also attention is paid to reducing the number of noise parameters in the filter algorithm in order to further restrict the number of model evaluations that is required to solve the filtering problem. The results of the tests are very promising and show that Kalman filtering may be successfully applied to atmospheric chemistry models

Towards explainable metaheuristics: PCA for trajectory mining in evolutionary algorithms.

The generation of explanations regarding decisions made by population-based meta-heuristics is often a difficult task due to the nature of the mechanisms employed by these approaches. With the increase in use of these methods for optimisation in industries that require end-user confirmation, the need for explanations has also grown. We present a novel approach to the extraction of features capable of supporting an explanation through the use of trajectory mining - extracting key features from the populations of NDAs. We apply Principal Components Analysis techniques to identify new methods of population diversity tracking post-runtime after projection into a lower dimensional space. These methods are applied to a set of benchmark problems solved by a Genetic Algorithm and a Univariate Estimation of Distribution Algorithm. We show that the new sub-space derived metrics can capture key learning steps in the algorithm run and how solution variable patterns that explain the fitness function may be captured in the principal component coefficients

Non-deterministic solvers and explainable AI through trajectory mining.

Traditional methods of creating explanations from complex systems involving the use of AI have resulted in a wide variety of tools available to users to generate explanations regarding algorithm and network designs. This however has traditionally been aimed at systems that mimic the structure of human thought such as neural networks. The growing adoption of AI systems in industries has led to research and roundtables regarding the ability to extract explanations from other systems such as Non-Deterministic algorithms. This family of algorithms can be analysed but the explanation of events can often be difficult for non-experts to understand. Mentioned is a potential path to the generation of explanations that would not require expert-level knowledge to be correctly understood

Anodic dissolution growth of metal-organic framework HKUST-1 monitored:Via in situ electrochemical atomic force microscopy

In situ electrochemical atomic force microscopy (ec-AFM) is utilised for the first time to probe the initial stages of metal-organic framework (MOF) coating growth via anodic dissolution. Using the example of the Cu MOF HKUST-1, real time surface analysis is obtained that supports and verifies many of the reaction steps in a previously proposed mechanism for this type of coating growth. No evidence is observed however for the presence or formation of Cu2O, which has previously been suggested to be both key for the formation of the coating and a potential explanation for the anomalously high adhesion strength of coatings obtained via this methodology. Supporting in situ electrochemical Raman spectroscopy also fails to detect the presence of any significant amount of Cu2O before or during the coating's growth process

Nucleon quark distributions in a covariant quark-diquark model

Spin-dependent and spin-independent quark light-cone momentum distributions and structure functions are calculated for the nucleon. We utilize a modified Nambu-Jona-Lasinio model in which confinement is simulated by eliminating unphysical thresholds for nucleon decay into quarks. The nucleon bound state is obtained by solving the Faddeev equation in the quark-diquark approximation, where both scalar and axial-vector diquark channels are included. We find excellent agreement between our model results and empirical data.Comment: 6 pages, 7 figure

Towards explainable metaheuristics: feature extraction from trajectory mining.

Explaining the decisions made by population-based metaheuristics can often be considered difficult due to the stochastic nature of the mechanisms employed by these optimisation methods. As industries continue to adopt these methods in areas that increasingly require end-user input and confirmation, the need to explain the internal decisions being made has grown. In this article, we present our approach to the extraction of explanation supporting features using trajectory mining. This is achieved through the application of principal components analysis techniques to identify new methods of tracking population diversity changes post-runtime. The algorithm search trajectories were generated by solving a set of benchmark problems with a genetic algorithm and a univariate estimation of distribution algorithm and retaining all visited candidate solutions which were then projected to a lower dimensional sub-space. We also varied the selection pressure placed on high fitness solutions by altering the selection operators. Our results show that metrics derived from the projected sub-space algorithm search trajectories are capable of capturing key learning steps and how solution variable patterns that explain the fitness function may be captured in the principal component coefficients. A comparative study of variable importance rankings derived from a surrogate model built on the same dataset was also performed. The results show that both approaches are capable of identifying key features regarding variable interactions and their influence on fitness in a complimentary fashion

Association of FCGR3A and FCGR3B haplotypes with rheumatoid arthritis and primary Sjögren's syndrome [POSTER PRESENTATION]

Background Rheumatoid arthritis (RA) is an autoimmune disease that is thought to arise from a complex interaction between multiple genetic factors and environmental triggers. We have previously demonstrated an association between a Fc gamma receptor (FcγR) haplotype and RA in a cross-sectional cohort of RA patients. We have sought to confirm this association in an inception cohort of RA patients and matched controls. We also extended our study to investigate a second autoanti-body associated rheumatic disease, primary Sjögren's syndrome (PSS). Methods The FCGR3A-158F/V and FCGR3B-NA1/NA2 functional polymorphisms were examined for association in an inception cohort of RA patients (n = 448), and a well-characterised PSS cohort (n = 83) from the United Kingdom. Pairwise disequilibrium coefficients (D') were calculated in 267 Blood Service healthy controls. The EHPlus program was used to estimate haplotype frequencies for patients and controls and to determine whether significant linkage disequilibrium was present. A likelihood ratio test is performed to test for differences between the haplotype frequencies in cases and controls. A permutation procedure implemented in this program enabled 1000 permutations to be performed on all haplotype associations to assess significance. Results There was significant linkage disequilibrium between FCGR3A and FCGR3B (D' = -0.445, P = 0.001). There was no significant difference in the FCGR3A or FCGR3B allele or genotype frequencies in the RA or PSS patients compared with controls. However, there was a significant difference in the FCGR3A-FCGR3B haplotype distributions with increased homozygosity for the FCGR3A-FCGR3B 158V-NA2 haplotype in both our inception RA cohort (odds ratio = 2.15, 95% confidence interval = 1.1–4.2 P = 0.027) and PSS (odds ratio = 2.83, 95% confidence interval = 1.0–8.2, P = 0.047) compared with controls. The reference group for these analyses comprised individuals who did not possess a copy of the FCGR3A-FCGR3B 158V-NA2 haplotype. Conclusions We have confirmed our original findings of association between the FCGR3A-FCGR3B 158V-NA2 haplotype and RA in a new inception cohort of RA patients. This suggests that there may be an RA-susceptibility gene at this locus. The significant increased frequency of an identical haplotype in PSS suggests the FcγR genetic locus may contribute to the pathogenesis of diverse autoantibody-mediated rheumatic diseases