COMPUTATIONAL PREDICTION OF A PROPELLER PERFORMANCE IN OPEN WATER CONDITION

In presence of hydrodynamics phenomena occur surrounding propeller evidently affects on accuracy’s prediction of thrust, torque and its efficiency. To achieve the objective, a Computational Fluid Dynamics (CFD) simulations approach is then proposed to obtain a reliable prediction of the thrust (KT), torque (KQ) and efficiency (η) coefficients in open water condition. The effect of various blade numbers associated with constant propeller revolution (RPM=1320) and pitch ratio (P/D=1.0); are performed within the range of advance ratio from 0.1J1.0. The results revealed that the increase of blade number from Z=3 to 5 was proportional with the increase of thrust (KT) and torque (KQ) coefficients; meanwhile, it was reduced the maximum efficiency (η) that possibly lead to downgrade the propeller performance. It should be noted here, the propeller with three blade numbers (Z=3) provide the highest efficiency (η) up to 78.8% at J=0.9. These CFD simulation results are very useful as a preliminary study of propeller characteristics

Towards the identification of essential genes using targeted genome sequencing and comparative analysis

BACKGROUND: The identification of genes essential for survival is of theoretical importance in the understanding of the minimal requirements for cellular life, and of practical importance in the identification of potential drug targets in novel pathogens. With the great time and expense required for experimental studies aimed at constructing a catalog of essential genes in a given organism, a computational approach which could identify essential genes with high accuracy would be of great value. RESULTS: We gathered numerous features which could be generated automatically from genome sequence data and assessed their relationship to essentiality, and subsequently utilized machine learning to construct an integrated classifier of essential genes in both S. cerevisiae and E. coli. When looking at single features, phyletic retention, a measure of the number of organisms an ortholog is present in, was the most predictive of essentiality. Furthermore, during construction of our phyletic retention feature we for the first time explored the evolutionary relationship among the set of organisms in which the presence of a gene is most predictive of essentiality. We found that in both E. coli and S. cerevisiae the optimal sets always contain host-associated organisms with small genomes which are closely related to the reference. Using five optimally selected organisms, we were able to improve predictive accuracy as compared to using all available sequenced organisms. We hypothesize the predictive power of these genomes is a consequence of the process of reductive evolution, by which many parasites and symbionts evolved their gene content. In addition, essentiality is measured in rich media, a condition which resembles the environments of these organisms in their hosts where many nutrients are provided. Finally, we demonstrate that integration of our most highly predictive features using a probabilistic classifier resulted in accuracies surpassing any individual feature. CONCLUSION: Using features obtainable directly from sequence data, we were able to construct a classifier which can predict essential genes with high accuracy. Furthermore, our analysis of the set of genomes in which the presence of a gene is most predictive of essentiality may suggest ways in which targeted sequencing can be used in the identification of essential genes. In summary, the methods presented here can aid in the reduction of time and money invested in essential gene identification by targeting those genes for experimentation which are predicted as being essential with a high probability

Pseudorehearsal in value function approximation

Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters

ABO blood group system and placental malaria in an area of unstable malaria transmission in eastern Sudan

<p>Abstract</p> <p>Background</p> <p>Understanding the pathogenesis of malaria in pregnancy and its consequences for both the mother and the baby is fundamental for improving malaria control in pregnant women.</p> <p>Aim</p> <p>The study aimed to investigate the role of ABO blood groups on pregnancy outcomes in an area of unstable malaria transmission in eastern Sudan.</p> <p>Methods</p> <p>A total of 293 women delivering in New Half teaching hospital, eastern Sudan during the period October 2006–March 2007 have been analyzed. ABO blood groups were determined and placental histopathology examinations for malaria were performed. Birth and placental weight were recorded and maternal haemoglobin was measured.</p> <p>Results</p> <p>114 (39.7%), 61 (22.1%) and 118 (38.2%) women were primiparae, secundiparae and multiparae, respectively. The ABO blood group distribution was 82(A), 59 (B), 24 (AB) and 128 (O). Placental histopathology showed acute placental malaria infections in 6 (2%), chronic infections in 6 (2%), 82 (28.0%) of the placentae showed past infection and 199 (68.0%) showed no infection. There was no association between the age (OR = 1.02, 95% CI = 0.45–2.2; <it>P </it>= 0.9), parity (OR = 0.6, 95% CI = 0.3–1.2; <it>P </it>= 0.1) and placental malaria infections. In all parity blood group O was associated with a higher risk of past (OR = 1.9, 95% CI = 1.1–3.2; <it>P </it>= 0.01) placental malaria infection. This was also true when primiparae were considered separately (OR = 2.6, 95% CI = 1.05–6.5, <it>P </it>= 0.03).</p> <p>Among women with all placental infections/past placental infection, the mean haemoglobin was higher in women with the blood group O, but the mean birth weight, foeto-placental weight ratio was not different between these groups and the non-O group.</p> <p>Conclusion</p> <p>These results indicate that women of eastern Sudan are at risk for placental malaria infection irrespective to their age or parity. Those women with blood group O were at higher risk of past placental malaria infection.</p

Evidence for variation in the effective population size of animal mitochondrial DNA

Background: It has recently been shown that levels of diversity in mitochondrial DNA are remarkably constant across animals of diverse census population sizes and ecologies, which has led to the suggestion that the effective population of mitochondrial DNA may be relatively constant. Results: Here we present several lines of evidence that suggest, to the contrary, that the effective population size of mtDNA does vary, and that the variation can be substantial. First, we show that levels of mitochondrial and nuclear diversity are correlated within all groups of animals we surveyed. Second, we show that the effectiveness of selection on non-synonymous mutations, as measured by the ratio of the numbers of non-synonymous and synonymous polymorphisms, is negatively correlated to levels of mitochondrial diversity. Finally, we estimate the effective population size of mitochondrial DNA in selected mammalian groups and show that it varies by at least an order of magnitude. Conclusions: We conclude that there is variation in the effective population size of mitochondria. Furthermore we suggest that the relative constancy of DNA diversity may be due to a negative correlation between the effective population size and the mutation rate per generation

The role of mutation rate variation and genetic diversity in the architecture of human disease

Background We have investigated the role that the mutation rate and the structure of genetic variation at a locus play in determining whether a gene is involved in disease. We predict that the mutation rate and its genetic diversity should be higher in genes associated with disease, unless all genes that could cause disease have already been identified. Results Consistent with our predictions we find that genes associated with Mendelian and complex disease are substantially longer than non-disease genes. However, we find that both Mendelian and complex disease genes are found in regions of the genome with relatively low mutation rates, as inferred from intron divergence between humans and chimpanzees, and they are predicted to have similar rates of non-synonymous mutation as other genes. Finally, we find that disease genes are in regions of significantly elevated genetic diversity, even when variation in the rate of mutation is controlled for. The effect is small nevertheless. Conclusions Our results suggest that gene length contributes to whether a gene is associated with disease. However, the mutation rate and the genetic architecture of the locus appear to play only a minor role in determining whether a gene is associated with disease

Strong Water Absorption in the Dayside Emission Spectrum of the Planet HD 189733b

Recent observations of the extrasolar planet HD 189733b did not reveal the presence of water in the emission spectrum of the planet. Yet models of such 'Hot Jupiter' planets predict an abundance of atmospheric water vapour. Validating and constraining these models is crucial for understanding the physics and chemistry of planetary atmospheres in extreme environments. Indications of the presence of water in the atmosphere of HD 189733b have recently been found in transmission spectra, where the planet's atmosphere selectively absorbs the light of the parent star, and in broadband photometry. Here we report on the detection of strong water absorption in a high signal-to-noise, mid-infrared emission spectrum of the planet itself. We find both a strong downturn in the flux ratio below 10 microns and discrete spectral features that are characteristic of strong absorption by water vapour. The differences between these and previous observations are significant and admit the possibility that predicted planetary-scale dynamical weather structures might alter the emission spectrum over time. Models that match the observed spectrum and the broadband photometry suggest that heat distribution from the dayside to the night side is weak. Reconciling this with the high night side temperature will require a better understanding of atmospheric circulation or possible additional energy sources.Comment: 11 pages, 1 figure, published in Natur

Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

Massive End-to-end Models for Short Search Queries

In this work, we investigate two popular end-to-end automatic speech recognition (ASR) models, namely Connectionist Temporal Classification (CTC) and RNN-Transducer (RNN-T), for offline recognition of voice search queries, with up to 2B model parameters. The encoders of our models use the neural architecture of Google's universal speech model (USM), with additional funnel pooling layers to significantly reduce the frame rate and speed up training and inference. We perform extensive studies on vocabulary size, time reduction strategy, and its generalization performance on long-form test sets. Despite the speculation that, as the model size increases, CTC can be as good as RNN-T which builds label dependency into the prediction, we observe that a 900M RNN-T clearly outperforms a 1.8B CTC and is more tolerant to severe time reduction, although the WER gap can be largely removed by LM shallow fusion