Prediction of landing gear loads using machine learning techniques

This article investigates the feasibility of using machine learning algorithms to predict the loads experienced by a landing gear during landing. For this purpose, the results on drop test data and flight test data will be examined. This article will focus on the use of Gaussian process regression for the prediction of loads on the components of a landing gear. For the learning task, comprehensive measurement data from drop tests are available. These include measurements of strains at key locations, such as on the side-stay and torque link, as well as acceleration measurements of the drop carriage and the gear itself, measurements of shock absorber travel, tyre closure, shock absorber pressure and wheel speed. Ground-to-tyre loads are also available through measurements made with a drop test ground reaction platform. The aim is to train the Gaussian process to predict load at a particular location from other available measurements, such as accelerations, or measurements of the shock absorber. If models can be successfully trained, then future load patterns may be predicted using only these measurements. The ultimate aim is to produce an accurate model that can predict the load at a number of locations across the landing gear using measurements that are readily available or may be measured more easily than directly measuring strain on the gear itself (for example, these may be measurements already available on the aircraft, or from a small number of sensors attached to the gear). The drop test data models provide a positive feasibility test which is the basis for moving on to the critical task of prediction on flight test data. For this, a wide range of available flight test measurements are considered for potential model inputs (excluding strain measurements themselves), before attempting to refine the model or use a smaller number of measurements for the prediction

Education and transfer of water competencies: An ecological dynamics approach

© The Author(s) 2020. To cope in various aquatic environments (i.e. swimming pools, lakes, rivers, oceans), learners require a wide repertoire of self-regulatory behaviours such as awareness of obstacles and water properties, floating and moving from point to point with different strokes, decision making, emotional control and breathing efficiently. By experiencing different learning situations in stable indoor pool environments, it is assumed that children strengthen aquatic competencies that should be transferable to functioning in open water environments, where prevalence of drowning is high. However, this fundamental assumption may be misleading. Here, we propose the application of a clear, related methodology and theoretical framework that could be useful to help physical education curriculum specialists (re)shape and (re)design appropriate aquatic learning situations to facilitate better transfer of learning. We discuss the need for more representativeness in a learning environment, proposing how the many different task and environmental constraints on aquatic actions may bound the emergence of functional, self-regulatory behaviours in learners. Ideas in ecological dynamics suggest that physical educators should design learning environments that offer a rich landscape of opportunities for action for learners. As illustration, three practice interventions are described for developing functional and transferrable skills in indoor aquatic environments. It is important that aquatic educators focus not just upon ‘learning to swim’, but particularly on relevant transferable skills and self-regulatory behaviours deemed necessary for functioning in dynamic, outdoor aquatic environments

Education and transfer of water competencies: An ecological dynamics approach

© The Author(s) 2020. To cope in various aquatic environments (i.e. swimming pools, lakes, rivers, oceans), learners require a wide repertoire of self-regulatory behaviours such as awareness of obstacles and water properties, floating and moving from point to point with different strokes, decision making, emotional control and breathing efficiently. By experiencing different learning situations in stable indoor pool environments, it is assumed that children strengthen aquatic competencies that should be transferable to functioning in open water environments, where prevalence of drowning is high. However, this fundamental assumption may be misleading. Here, we propose the application of a clear, related methodology and theoretical framework that could be useful to help physical education curriculum specialists (re)shape and (re)design appropriate aquatic learning situations to facilitate better transfer of learning. We discuss the need for more representativeness in a learning environment, proposing how the many different task and environmental constraints on aquatic actions may bound the emergence of functional, self-regulatory behaviours in learners. Ideas in ecological dynamics suggest that physical educators should design learning environments that offer a rich landscape of opportunities for action for learners. As illustration, three practice interventions are described for developing functional and transferrable skills in indoor aquatic environments. It is important that aquatic educators focus not just upon ‘learning to swim’, but particularly on relevant transferable skills and self-regulatory behaviours deemed necessary for functioning in dynamic, outdoor aquatic environments

Scattering AMplitudes from Unitarity-based Reduction Algorithm at the Integrand-level

SAMURAI is a tool for the automated numerical evaluation of one-loop corrections to any scattering amplitudes within the dimensional-regularization scheme. It is based on the decomposition of the integrand according to the OPP-approach, extended to accommodate an implementation of the generalized d-dimensional unitarity-cuts technique, and uses a polynomial interpolation exploiting the Discrete Fourier Transform. SAMURAI can process integrands written either as numerator of Feynman diagrams or as product of tree-level amplitudes. We discuss some applications, among which the 6- and 8-photon scattering in QED, and the 6-quark scattering in QCD. SAMURAI has been implemented as a Fortran90 library, publicly available, and it could be a useful module for the systematic evaluation of the virtual corrections oriented towards automating next-to-leading order calculations relevant for the LHC phenomenology.Comment: 35 pages, 7 figure

A Novel Xenograft Model in Zebrafish for High-Resolution Investigating Dynamics of Neovascularization in Tumors

Tumor neovascularization is a highly complex process including multiple steps. Understanding this process, especially the initial stage, has been limited by the difficulties of real-time visualizing the neovascularization embedded in tumor tissues in living animal models. In the present study, we have established a xenograft model in zebrafish by implanting mammalian tumor cells into the perivitelline space of 48 hours old Tg(Flk1:EGFP) transgenic zebrafish embryos. With this model, we dynamically visualized the process of tumor neovascularization, with unprecedented high-resolution, including new sprouts from the host vessels and the origination from VEGFR2+ individual endothelial cells. Moreover, we quantified their contributions during the formation of vascular network in tumor. Real-time observations revealed that angiogenic sprouts in tumors preferred to connect each other to form endothelial loops, and more and more endothelial loops accumulated into the irregular and chaotic vascular network. The over-expression of VEGF165 in tumor cells significantly affected the vascularization in xenografts, not only the number and size of neo-vessels but the abnormalities of tumor vascular architecture. The specific inhibitor of VEGFR2, SU5416, significantly inhibited the vascularization and the growth of melanoma xenografts, but had little affects to normal vessels in zebrafish. Thus, this zebrafish/tumor xenograft model not only provides a unique window to investigate the earliest events of tumoral neoangiogenesis, but is sensitive to be used as an experimental platform to rapidly and visually evaluate functions of angiogenic-related genes. Finally, it also offers an efficient and cost-effective means for the rapid evaluation of anti-angiogenic chemicals

Gluon-gluon contributions to W+ W- production and Higgs interference effects

In this paper we complete our re-assessment of the production of W boson pairs at the LHC, by calculating analytic results for the gg -> W+ W- -> (\nu l l\nu) process including the effect of massive quarks circulating in the loop. Together with the one-loop amplitudes containing the first two generations of massless quarks propagating in the loop, these diagrams can give a significant contribution with a large flux of gluons. One of the component parts of this calculation is the production of a standard model Higgs boson, gg -> H and its subsequent decay, H -> W+(-> \nu l) W-(-> l \nu). We will quantify the importance of the interference between the Higgs boson production process and the gluon-induced continuum production in the context of searches for the Higgs boson at the Tevatron and the LHC. For instance, for mH < 140 GeV the effect of the interference typically results in around a 10% reduction in the expected number of Higgs signal events. The majority of this interference is due to non-resonant contributions. Therefore cuts on the transverse mass such as those currently used by the ATLAS collaboration reduce the destructive interference to about a 1% effect. We advocate that a cut on the maximum transverse mass be used in future Higgs searches in this channel

Obesity and immune function relationships.

The immunological processes involved in the collaborative defence of organisms are affected by nutritional status. Thus, a positive chronic imbalance between energy intake and expenditure leads to situations of obesity, which may influence unspecific and specific immune responses mediated by humoral and cell mediated mechanisms. Furthermore, several lines of evidence have supported a link between adipose tissue and immunocompetent cells. This interaction is illustrated in obesity, where excess adiposity and impaired immune function have been described in both humans and genetically obese rodents. However, limited and often controversial information exist comparing immunity in obese and non-obese subjects as well as about the cellular and molecular mechanisms implicated. In general terms, clinical and epidemiological data support the evidence that the incidence and severity of specific types of infectious illnesses are higher in obese persons as compared to lean individuals together with the occurrence of poor antibody responses to antigens in overweight subjects. Leptin might play a key role in linking nutritional status with T-cell function. The complexities and heterogeneity of the host defences concerning the immune response in different nutritional circumstances affecting the energy balance require an integral study of the immunocompetent cells, their subsets and products as well as specific and unspecific inducer/regulator systems. In this context, more research is needed to clarify the clinical implications of the alterations induced by obesity on the immune function

Complex exon-intron marking by histone modifications is not determined solely by nucleosome distribution

It has recently been shown that nucleosome distribution, histone modifications and RNA polymerase II (Pol II) occupancy show preferential association with exons (“exon-intron marking”), linking chromatin structure and function to co-transcriptional splicing in a variety of eukaryotes. Previous ChIP-sequencing studies suggested that these marking patterns reflect the nucleosomal landscape. By analyzing ChIP-chip datasets across the human genome in three cell types, we have found that this marking system is far more complex than previously observed. We show here that a range of histone modifications and Pol II are preferentially associated with exons. However, there is noticeable cell-type specificity in the degree of exon marking by histone modifications and, surprisingly, this is also reflected in some histone modifications patterns showing biases towards introns. Exon-intron marking is laid down in the absence of transcription on silent genes, with some marking biases changing or becoming reversed for genes expressed at different levels. Furthermore, the relationship of this marking system with splicing is not simple, with only some histone modifications reflecting exon usage/inclusion, while others mirror patterns of exon exclusion. By examining nucleosomal distributions in all three cell types, we demonstrate that these histone modification patterns cannot solely be accounted for by differences in nucleosome levels between exons and introns. In addition, because of inherent differences between ChIP-chip array and ChIP-sequencing approaches, these platforms report different nucleosome distribution patterns across the human genome. Our findings confound existing views and point to active cellular mechanisms which dynamically regulate histone modification levels and account for exon-intron marking. We believe that these histone modification patterns provide links between chromatin accessibility, Pol II movement and co-transcriptional splicing

Value Creation from Big Data: Looking Inside the Black Box

The advent of big data is fundamentally changing the business landscape. We open the ‘black box’ of the firm to explore how firms transform big data in order to create value and why firms differ in their abilities to create value from big data. Grounded in detailed evidence from China, the world’s largest digital market, where many firms actively engage in value creation activities from big data, we identify several novel features. We find that it is not the data itself, or individual data scientists, that generate value creation opportunities. Rather, value creation occurs through the process of data management, where managers are able to democratize, contextualize, experiment and execute data insights in a timely manner. We add richness to current theory by developing a conceptual framework of value creation from big data. We also identify avenues for future research and implications for practicing managers