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

Demystifying Data Science Projects: A Look on the People and Process of Data Science Today

Peer reviewe

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

INTRODUCTION: More than 70 common alleles are known to be involved in breast cancer (BC) susceptibility, and several exhibit significant heterogeneity in their associations with different BC subtypes. Although there are differences in the association patterns between BRCA1 and BRCA2 mutation carriers and the general population for several loci, no study has comprehensively evaluated the associations of all known BC susceptibility alleles with risk of BC subtypes in BRCA1 and BRCA2 carriers. METHODS: We used data from 15,252 BRCA1 and 8,211 BRCA2 carriers to analyze the associations between approximately 200,000 genetic variants on the iCOGS array and risk of BC subtypes defined by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and triple-negative- (TN) status; morphologic subtypes; histological grade; and nodal involvement. RESULTS: The estimated BC hazard ratios (HRs) for the 74 known BC alleles in BRCA1 carriers exhibited moderate correlations with the corresponding odds ratios from the general population. However, their associations with ER-positive BC in BRCA1 carriers were more consistent with the ER-positive associations in the general population (intraclass correlation (ICC) = 0.61, 95% confidence interval (CI): 0.45 to 0.74), and the same was true when considering ER-negative associations in both groups (ICC = 0.59, 95% CI: 0.42 to 0.72). Similarly, there was strong correlation between the ER-positive associations for BRCA1 and BRCA2 carriers (ICC = 0.67, 95% CI: 0.52 to 0.78), whereas ER-positive associations in any one of the groups were generally inconsistent with ER-negative associations in any of the others. After stratifying by ER status in mutation carriers, additional significant associations were observed. Several previously unreported variants exhibited associations at P <10(-6) in the analyses by PR status, HER2 status, TN phenotype, morphologic subtypes, histological grade and nodal involvement. CONCLUSIONS: Differences in associations of common BC susceptibility alleles between BRCA1 and BRCA2 carriers and the general population are explained to a large extent by differences in the prevalence of ER-positive and ER-negative tumors. Estimates of the risks associated with these variants based on population-based studies are likely to be applicable to mutation carriers after taking ER status into account, which has implications for risk prediction.published_or_final_versio

Differential radiosensitisation by ZD1839 (Iressa), a highly selective epidermal growth factor receptor tyrosine kinase inhibitor in two related bladder cancer cell lines

The epidermal growth factor receptor (EGFR) is expressed in a wide variety of epithelial tumours including carcinoma of the bladder. Stimulation of the EGFR pathway is blocked by ZD1839 (Iressa), a highly selective EGFR tyrosine kinase inhibitor. Radical radiotherapy is an established organ sparing treatment option for muscle invasive bladder cancer and this study has explored the possibility for the use of ZD1839 as a radiosensitiser in this scenario. The effect of combination treatment with ZD1839 (0.01 μM) and ionising radiation in the established bladder cancer cell lines MGH-U1 and its radiosensitive mutant clone S40b was measured by clonogenic assays. A highly significant radiosensitising effect was seen in both cell lines (P<0.001 for MGH-U1 and S40b cell lines). This effect was independent of the concentration of the drug and the duration of exposure prior to treatment with ionising radiation. Cell cycle kinetics of both cell lines was not significantly altered with ZD1839 (0.01 μM) as a single agent. A modest induction of apoptosis was observed with ZD1839 (0.01 μM) as a single agent, but a marked induction was observed with the combination treatment of ZD1839 and ionising radiation. These results suggest a potentially important role for ZD1839 in combination with radiotherapy in the treatment of muscle invasive bladder cancer

Associations between food group intakes and circulating insulin-like growth factor-I in the UK Biobank: a cross-sectional analysis

PURPOSE: Circulating insulin-like growth factor-I (IGF-I) concentrations have been positively associated with risk of several common cancers and inversely associated with risk of bone fractures. Intakes of some foods have been associated with increased circulating IGF-I concentrations; however, evidence remains inconclusive. Our aim was to assess cross-sectional associations of food group intakes with circulating IGF-I concentrations in the UK Biobank. METHODS: At recruitment, the UK Biobank participants reported their intake of commonly consumed foods. From these questions, intakes of total vegetables, fresh fruit, red meat, processed meat, poultry, oily fish, non-oily fish, and cheese were estimated. Serum IGF-I concentrations were measured in blood samples collected at recruitment. After exclusions, a total of 438,453 participants were included in this study. Multivariable linear regression was used to assess the associations of food group intakes with circulating IGF-I concentrations. RESULTS: Compared to never consumers, participants who reported consuming oily fish or non-oily fish ≥ 2 times/week had 1.25 nmol/L (95% confidence interval:1.19–1.31) and 1.16 nmol/L (1.08–1.24) higher IGF-I concentrations, respectively. Participants who reported consuming poultry ≥ 2 times/week had 0.87 nmol/L (0.80–0.94) higher IGF-I concentrations than those who reported never consuming poultry. There were no strong associations between other food groups and IGF-I concentrations. CONCLUSIONS: We found positive associations between oily and non-oily fish intake and circulating IGF-I concentrations. A weaker positive association of IGF-I with poultry intake was also observed. Further research is needed to understand the mechanisms which might explain these associations

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

Analysis of acute vascular damage after photodynamic therapy using benzoporphyrin derivative (BPD)

Benzoporphyrin derivative monoacid ring A (BPD-MA, verteporfin) is currently under investigation as a photosensitizer for photodynamic therapy (PDT). Since BPD exhibits rapid pharmacokinetics in plasma and tissues, we assessed damage to tumour and muscle microvasculature when light treatment for PDT was given at short times after injection of photosensitizer. Groups of rats with chondrosarcoma were given 2 mg kg−1 of BPD intravenously 5 min to 180 min before light treatment of 150 J cm−2 690 nm. Vascular response was monitored using intravital microscopy and tumour cure was monitored by following regrowth over 42 days. For treatment at 5 or 30 min after BPD injection, blood flow stasis was limited to tumour microvasculature with lesser response in the surrounding normal microvasculature, indicating selective targeting for damage. No acute changes were observed in vessels when light was given 180 min after BPD injection. Tumour regression after light treatment occurred in all animals given PDT with BPD. Long-term tumour regression was greater in animals treated 5 min after BPD injection and least in animals given treatment 180 min after drug injection. The correlation between the timing for vascular damage and cure implies that blood flow stasis plays a significant role in PDT-induced tumour destruction. © 1999 Cancer Research Campaig

Heavy-quark mass effects in Higgs boson production at the LHC

We study the impact of heavy-quark masses in Higgs boson production through gluon fusion at the LHC. We extend previous computations of the fully differential cross section and of the transverse momentum spectrum of the Higgs boson by taking into account the finite top- and bottom-quark masses up to O(alpha_S^3). We also discuss the issues arising when the heavy-quark mass is much smaller than the Higgs mass. Our results are implemented in updated versions of the HNNLO and HRes numerical programs.Comment: Minor modifications, results unchanged. Discussion on uncertainties added. Version published on JHE

The 'At-risk mental state' for psychosis in adolescents : clinical presentation, transition and remission.

Despite increased efforts over the last decade to prospectively identify individuals at ultra-high risk of developing a psychotic illness, limited attention has been specifically directed towards adolescent populations (<18 years). In order to evaluate how those under 18 fulfilling the operationalised criteria for an At-Risk Mental State (ARMS) present and fare over time, we conducted an observational study. Participants (N = 30) generally reported a high degree of functional disability and frequent and distressing perceptual disturbance, mainly in the form of auditory hallucinations. Seventy percent (21/30) were found to fulfil the criteria for a co-morbid ICD-10 listed mental health disorder, with mood (affective; 13/30) disorders being most prevalent. Overall transition rates to psychosis were low at 24 months follow-up (2/28; 7.1 %) whilst many participants demonstrated a significant reduction in psychotic-like symptoms. The generalisation of these findings may be limited due to the small sample size and require replication in a larger sample