340 research outputs found

    Predicting the operability of damaged compressors using machine learning

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    Abstract The application of machine learning to aerospace problems faces a particular challenge. For successful learning a large amount of good quality training data is required, typically tens of thousands of cases. However, due to the time and cost of experimental aerospace testing, this data is scarce. This paper shows that successful learning is possible with two novel techniques: The first technique is rapid testing. Over the last five years the Whittle Laboratory has developed a capability where rebuild and test times of a compressor stage now take 15 minutes instead of weeks. The second technique is to base machine learning on physical parameters, derived from engineering wisdom developed in industry over many decades. The method is applied to the important industry problem of predicting the effect of blade damage on compressor operability. The current approach has high uncertainty, it is based on human judgement and correlation of a handful of experimental test cases. It is shown using 100 training cases and 25 test cases that the new method is able to predict the operability of damaged compressor stages with an accuracy of 2% in a 95% confidence interval; far better than is possible by even the most experienced compressor designers. Use of the method is also shown to generate new physical understanding, previously unknown by any of the experts involved in this work. Using this method in the future offers an exciting opportunity to generate understanding of previously intractable problems in aerospace.Aerospace Technology Institute Rolls-Royce plc

    Hookworm Infection and Environmental Factors in Mbeya Region, Tanzania: A Cross-sectional, Population-based study.

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    Hookworm disease is one of the most common infections and cause of a high disease burden in the tropics and subtropics. Remotely sensed ecological data and model-based geostatistics have been used recently to identify areas in need for hookworm control. Cross-sectional interview data and stool samples from 6,375 participants from nine different sites in Mbeya region, south-western Tanzania, were collected as part of a cohort study. Hookworm infection was assessed by microscopy of duplicate Kato-Katz thick smears from one stool sample from each participant. A geographic information system was used to obtain remotely sensed environmental data such as land surface temperature (LST), vegetation cover, rainfall, and elevation, and combine them with hookworm infection data and with socio-demographic and behavioral data. Uni- and multivariable logistic regression was performed on sites separately and on the pooled dataset. Univariable analyses yielded significant associations for all ecological variables. Five ecological variables stayed significant in the final multivariable model: population density (odds ratio (OR) = 0.68; 95% confidence interval (CI) = 0.63-0.73), mean annual vegetation density (OR = 0.11; 95% CI = 0.06-0.18), mean annual LST during the day (OR = 0.81; 95% CI = 0.75-0.88), mean annual LST during the night (OR = 1.54; 95% CI = 1.44-1.64), and latrine coverage in household surroundings (OR = 1.02; 95% CI = 1.01-1.04). Interaction terms revealed substantial differences in associations of hookworm infection with population density, mean annual enhanced vegetation index, and latrine coverage between the two sites with the highest prevalence of infection. This study supports previous findings that remotely sensed data such as vegetation indices, LST, and elevation are strongly associated with hookworm prevalence. However, the results indicate that the influence of environmental conditions can differ substantially within a relatively small geographic area. The use of large-scale associations as a predictive tool on smaller scales is therefore problematic and should be handled with care

    Multimodal Stimulation of Colorado Potato Beetle Reveals Modulation of Pheromone Response by Yellow Light

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    Orientation of insects to host plants and conspecifics is the result of detection and integration of chemical and physical cues present in the environment. Sensory organs have evolved to be sensitive to important signals, providing neural input for higher order multimodal processing and behavioral output. Here we report experiments to determine decisions made by Colorado potato beetle (CPB), Leptinotarsa decemlineata, in response to isolated stimuli and multimodal combinations of signals on a locomotion compensator. Our results show that in complete darkness and in the absence of other stimuli, pheromonal stimulation increases attraction behavior of CPB as measured in oriented displacement and walking speed. However, orientation to the pheromone is abolished when presented with the alternative stimulation of a low intensity yellow light in a dark environment. The ability of the pheromone to stimulate these diurnal beetles in the dark in the absence of other stimuli is an unexpected but interesting observation. The predominance of the phototactic response over that to pheromone when low intensity lights were offered as choices seems to confirm the diurnal nature of the insect. The biological significance of the response to pheromone in the dark is unclear. The phototactic response will play a key role in elucidating multimodal stimulation in the host-finding process of CPB, and perhaps other insects. Such information might be exploited in the design of applications to attract and trap CPB for survey or control purposes and other insect pests using similar orientation mechanisms

    Nanoparticles in cigarette smoke; real-time undiluted measurements by a scanning mobility particle sizer

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    Cigarette smoke is a complex mixture of smoke constituents, often characterised by size-resolved particle distributions. Since descriptions of ultrafine particles <50 nm are absent, our aim was to explore the existence of these nanoparticles in fresh and undiluted cigarette smoke. We measured undiluted smoke particles real-time by a scanning mobility particle sizer with Faraday cup electrometer, integrated in our custom-made smoking machine. Cigarettes were smoked by 2 s puffs, 30 s puff intervals and 50 ml puff volume. We tested six different cigarettes (1–10 mg tar per cigarette) at ten particle size-ranges between 6 and 50 nm, and repeated measurements five times. The formation of nanoparticles in fresh cigarette smoke was observed over the entire range between 6 and 50 nm, and reproduced in all cigarettes. The highest mean yield was 8.8 × 109 (SD = 1.1 × 109) particles per cigarette at the largest particle size range by high-tar cigarettes. Nanoparticle counts appear to increase with particle size, claimed tar values and blocking of filter ventilation holes, and inversely with butt length. Fresh undiluted cigarette smoke contains large amounts of potentially toxic nanoparticles <50 nm. We recommend to further study nanoparticles in the characterisation of cigarette smoke

    Characterization of an Enantioselective Odorant Receptor in the Yellow Fever Mosquito Aedes aegypti

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    Enantiomers differ only in the left or right handedness (chirality) of their orientations and exhibit identical chemical and physical properties. In chemical communication systems, enantiomers can be differentially active at the physiological and behavioral levels. Only recently were enantioselective odorant receptors demonstrated in mammals while their existence in insects has remained hypothetical. Using the two-microelectrode voltage clamp of Xenopus oocytes, we show that the yellow fever mosquito, Aedes aegypti, odorant receptor 8 (AaOR8) acts as a chiral selective receptor for the (R)-(—)-enantiomer of 1-octen-3-ol, which in the presence of other kairomones is an attractant used by blood-sucking insects to locate their hosts. In addition to steric constraints, chain length and degree of unsaturation play important roles in this recognition process. This is the first characterization of an enantioselective odorant receptor in insects and the results demonstrate that an OR alone, without helper proteins, can account for chiral specificity exhibited by olfactory sensory neurons (OSNs)

    Quantifying Relative Diver Effects in Underwater Visual Censuses

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    Diver-based Underwater Visual Censuses (UVCs), particularly transect-based surveys, are key tools in the study of coral reef fish ecology. These techniques, however, have inherent problems that make it difficult to collect accurate numerical data. One of these problems is the diver effect (defined as the reaction of fish to a diver). Although widely recognised, its effects have yet to be quantified and the extent of taxonomic variation remains to be determined. We therefore examined relative diver effects on a reef fish assemblage on the Great Barrier Reef. Using common UVC methods, the recorded abundance of seven reef fish groups were significantly affected by the ongoing presence of SCUBA divers. Overall, the diver effect resulted in a 52% decrease in the mean number of individuals recorded, with declines of up to 70% in individual families. Although the diver effect appears to be a significant problem, UVCs remain a useful approach for quantifying spatial and temporal variation in relative fish abundances, especially if using methods that minimise the exposure of fishes to divers. Fixed distance transects using tapes or lines deployed by a second diver (or GPS-calibrated timed swims) would appear to maximise fish counts and minimise diver effects

    Treatment with a BH3 mimetic overcomes the resistance of latency III EBV (+) cells to p53-mediated apoptosis

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    P53 inactivation is often observed in Burkitt's lymphoma (BL) cells due to mutations in the p53 gene or overexpression of its negative regulator, murine double minute-2 (MDM2). This event is now considered an essential part of the oncogenic process. Epstein–Barr virus (EBV) is strongly associated with BL and is a cofactor in its development. We previously showed that nutlin-3, an antagonist of MDM2, activates the p53 pathway in BL cell lines harboring wild-type p53. However, nutlin-3 strongly induced apoptosis in EBV (−) or latency I EBV (+) cells, whereas latency III EBV (+) cells were much more resistant. We show here that this resistance to apoptosis is also observed in latency III EBV (+) lymphoblastoid cell lines. We also show that, in latency III EBV (+) cells, B-cell lymphona 2 (Bcl-2) is selectively overproduced and interacts with Bcl-2-associated X protein (Bax), preventing its activation. The treatment of these cells with the Bcl-2-homology domain 3 mimetic ABT-737 disrupts Bax/Bcl-2 interaction and allows Bax activation by nutlin-3. Furthermore, treatment with these two compounds strongly induces apoptosis. Thus, a combination of Mdm2 and Bcl-2 inhibitors might be a useful anti-cancer strategy for diseases linked to EBV infection
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