The Effect of Ice Formations on Propeller Performance

Measurements of propeller efficiency loss due to ice formation are supplemented by an analysis to establish the magnitude of efficiency losses to be anticipated during flight in icing conditions. The measurements were made during flight in natural icing conditions; whereas the analysis consisted of an investIgation of changes in blade-section aerodynamic characteristics caused by ice formation and the resulting propeller efficiency changes. Agreement in the order of magnitude of eff 1- ciency losses to be expected is obtained between measured and analytical results. The results indicate that, in general, efficiency losses can be expected to be less than 10 percent; whereas maximum losses, which will be encountered only rarely, may be as high as 15 or 20 percent. Reported. losses larger than 15 or 20 percent, based on reductions in airplane performance, probably are due to ice accretions on other parts of the airplane. Blade-element theory is used in the analytical treatment, and calculations are made to show the degree to which the aerodynamic characteristics of a blade section. must be altered to produce various propeller efficiency losses. The effects of ice accretions on airfoil-section characteristics at subcritical speeds and their influence on drag-divergence Mach number are examined, and. the attendant maximum efficiency losses are computed. The effect of kinetic heating on the radial extent of ice formation is considered, and its influence on required length of blade heating shoes is discussed. It is demonstrated how the efficiency loss resulting from an icing encounter is influenced by the decisions of the pilot in adjusting the engine and propeller controls

Increasing security of supply by the use of a local power controller during large system disturbances

This paper describes intelligent ways in which distributed generation and local loads can be controlled during large system disturbances, using Local Power Controllers. When distributed generation is available, and a system disturbance is detected early enough, the generation can be dispatched, and its output power can be matched as closely as possible to local microgrid demand levels. Priority-based load shedding can be implemented to aid this process. In this state, the local microgrid supports the wider network by relieving the wider network of the micro-grid load. Should grid performance degrade further, the local microgrid can separate itself from the network and maintain power to the most important local loads, re-synchronising to the grid only after more normal performance is regained. Such an intelligent system would be a suitable for hospitals, data centres, or any other industrial facility where there are critical loads. The paper demonstrates the actions of such Local Power Controllers using laboratory experiments at the 10kVA scale

Removing motion and physiological artifacts from intrinsic BOLD fluctuations using short echo data

AbstractDiffering noise variance across study populations has been shown to cause artifactual group differences in functional connectivity measures. In this study, we investigate the use of short echo time functional MRI data to correct for these noise sources in blood oxygenation level dependent (BOLD)-weighted time series. A dual‐echo sequence was used to simultaneously acquire data at both a short (TE=3.3ms) and a BOLD-weighted (TE=35ms) echo time. This approach is effectively “free,” using dead-time in the pulse sequence to collect an additional echo without affecting overall scan time or temporal resolution. The proposed correction method uses voxelwise regression of the short TE data from the BOLD-weighted data to remove noise variance. In addition to a typical resting state scan, non-compliant behavior associated with patient groups was simulated via increased head motion or physiological fluctuations in 10 subjects. Short TE data showed significant correlations with the traditional motion-related and physiological noise regressors used in current connectivity analyses. Following traditional preprocessing, the extent of significant additional variance explained by the short TE data regressors was significantly correlated with the average head motion across the scan in the resting data (r2=0.93, p<0.0001). The reduction in data variance following the inclusion of short TE regressors was also correlated with scan head motion (r2=0.48, p=0.027). Task-related data were used to demonstrate the effects of the short TE correction on BOLD activation time series with known temporal structure; the size and strength of the activation were significantly decreased, but it is not clear whether this reflects BOLD contamination in the short TE data or correlated changes in blood volume. Finally, functional connectivity maps of the default mode network were constructed using a seed correlation approach. The effects of short TE correction and low-pass filtering on the resulting correlations maps were compared. Results suggest that short TE correction more accurately differentiates artifactual correlations from the correlations of interest in conditions of amplified noise

Discourse and identity in a corpus of lesbian erotica

This article uses corpus linguistic methodologies to explore representations of lesbian desires and identities in a corpus of lesbian erotica from the 1980s and 1990s. We provide a critical examination of the ways in which “lesbian gender,” power, and desire are represented, (re-)produced, and enacted, often in ways that challenge hegemonic discourses of gender and sexuality. By examining word frequencies and collocations, we critically analyze some of the themes, processes, and patterns of representation in the texts. Although rooted in linguistics, we hope this article provides an accessible, interdisciplinary, and timely contribution toward developing understandings of discursive practices surrounding gender and sexuality

Methods for recording and measuring tonic GABAA receptor-mediated inhibition

Tonic inhibitory conductances mediated by GABA(A) receptors have now been identified and characterized in many different brain regions. Most experimental studies of tonic GABAergic inhibition have been carried out using acute brain slice preparations but tonic currents have been recorded under a variety of different conditions. This diversity of recording conditions is likely to impact upon many of the factors responsible for controlling tonic inhibition and can make comparison between different studies difficult. In this review, we will firstly consider how various experimental conditions, including age of animal, recording temperature and solution composition, are likely to influence tonic GABA(A) conductances. We will then consider some technical considerations related to how the tonic conductance is measured and subsequently analyzed, including how the use of current noise may provide a complementary and reliable method for quantifying changes in tonic current

Research Data Management (RDM) Capabilities at the University of Ghana, Legon

The purpose of this study was to assess Research Data Management (RDM) capabilities at the University of Ghana (UG). The study focused on four key capability elements: policy framework, technological infrastructure, skills and knowledge, and support services. It explored the extent to which RDM is embedded in research practices at UG and provides insight into the preparedness of UG to develop RDM. A qualitative case study method was adopted for the study and data was gathered using semi-structured interviews and document analysis. The instrument for the assessment was informed by the Collaborative Assessment for Research Data Infrastructure and Objectives (CARDIO) Matrix tool and respondents were drawn from the Library, IT department, Research Office and senior researchers. The results of the study show that RDM at UG is currently underdeveloped but with immense potential for growth. Though there is no formal RDM infrastructure in place, RDM is considered an essential research integrity issue. Capabilities were generally found to be limited, uncoordinated and not officially instituted. The study recommends that a clear and comprehensive policy framework for RDM should be developed to articulate RDM aspirations and express management’s commitment. It also recommends that research support staff should be supported to build their capacity for RDM promotion and support

Potential pitfalls when denoising resting state fMRI data using nuisance regression

In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the “cleaned” residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series

Tur\'an Numbers of Ordered Tight Hyperpaths

An ordered hypergraph is a hypergraph $G$ whose vertex set $V(G)$ is linearly ordered. We find the Tur\'an numbers for the $r$-uniform $s$-vertex tight path $P^{(r)}_s$ (with vertices in the natural order) exactly when $r\le s < 2r$ and $n$ is even; our results imply $\mathrm{ex}_{>}(n,P^{(r)}_s)=(1-\frac{1}{2^{s-r}} + o(1))\binom{n}{r}$ when r\le s}(n,P^{(r)}_s) remain open. For $r=3$, we give a construction of an $r$-uniform $n$-vertex hypergraph not containing $P^{(r)}_s$ which we conjecture to be asymptotically extremal.Comment: 10 pages, 0 figure