Acoustic features of song categories and their possible implications for communication in the common nightingale (Luscinia megarhynchos)

In many passerine species, males sing more than one distinct song type. Commonly, songs are assigned to different song types or song categories based on phonological and syntactical dissimilarities. However, temporal aspects, such as song length and song rate, also need to be considered to understand the possible functions of different songs. Common nightingales (Luscinia megarhynchos) have large vocal repertoires of different song types but their songs additionally can be grouped into two distinct categories (particular groups of song types): whistle songs and nonwhistle songs. Whistle songs are hypothesised to be important to attract migrating females. We studied temporal properties of whistle songs and nonwhistle songs and examined the relationship between those song parameters and song output parameters, such as song rate and song length. To investigate how song parameters vary among males, we calculated the coefficients of variation for different song traits. We found that the variation in the proportion of whistle songs was significantly higher among males than variation in other song parameters. Furthermore, the proportion of whistle songs was negatively correlated with other sona output patterns. These findings suggest that the production of whistle songs might be constrained and/or that whistle songs and their succeeding pauses may act as a functional unit in communication.

Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Demographics and landscape features determine intrariver population structure in Atlantic salmon (Salmo salar L.): the case of the River Moy in Ireland

Contemporary genetic structure of Atlantic salmon (Salmo salar L.) in the River Moy in Ireland is shown here to be strongly related to landscape features and population demographics, with populations being defined largely by their degree of physical isolation and their size. Samples of juvenile salmon were collected from the 17 major spawning areas on the river Moy and from one spawning area in each of five smaller nearby rivers. No temporal allele frequency differences were observed within locations for 12 microsatellite loci, whereas nearly all spatial samples differed significantly, suggesting that each was a separate population. Bayesian clustering and landscape genetic analyses suggest that these populations can be combined hierarchically into five genetically informative larger groupings. Lakes were found to be the single most important determinant of the observed population structure. Spawning area size was also an important factor. The salmon population of the closest nearby river resembled genetically the largest Moy population grouping. In addition, we showed that anthropogenic influences on spawning habitats, in this case arterial drainage, can affect relationships between populations. Our results show that Atlantic salmon biodiversity can be largely defined by geography, and thus, knowledge of landscape features (for example, as characterized within Geographical Information Systems) has the potential to predict population structure in other rivers without an intensive genetic survey, or at least to help direct sampling. This approach of combining genetics and geography, for sampling and in subsequent statistical analyses, has wider application to the investigation of population structure in other freshwater/anadromous fish species and possibly in marine fish and other organisms.

Fatigue performance of aircraft panels with novel skin buckling containment features

To increase structural efficiency of stiffened panels in an aircraft, it is plausible to introduce skin buckling containment features to increase the local skin stability and thus static strength performance. Introducing buckling containment features may also significantly influence the fatigue crack growth performance of the stiffened panel. This study focuses on the experimental demonstration of panel durability with skin bay buckling containment features. Through a series of fatigue crack growth tests on integrally machined aluminium alloy stiffened panels, the potential to simultaneously improve static strength performance and crack propagation behaviour is demonstrated. The introduction of prismatic buckling containment features which have yielded significant static strength performance gains have herein demonstrated potential fatigue life gains of up to + 63 per cent.

Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

In this paper, a novel motion-tracking scheme using scale-invariant features is proposed for automatic cell motility analysis in gray-scale microscopic videos, particularly for the live-cell tracking in low-contrast differential interference contrast (DIC) microscopy. In the proposed approach, scale-invariant feature transform (SIFT) points around live cells in the microscopic image are detected, and a structure locality preservation (SLP) scheme using Laplacian Eigenmap is proposed to track the SIFT feature points along successive frames of low-contrast DIC videos. Experiments on low-contrast DIC microscopic videos of various live-cell lines shows that in comparison with principal component analysis (PCA) based SIFT tracking, the proposed Laplacian-SIFT can significantly reduce the error rate of SIFT feature tracking. With this enhancement, further experimental results demonstrate that the proposed scheme is a robust and accurate approach to tackling the challenge of live-cell tracking in DIC microscopy.