A polarimetric study of the reflection nebulae NGC 2068 and NGC 2023 in the Orion R1 association

Polarimetry studies of two reflection nebulae in the Orion R1 association are used to determine the nature of the dust in which recently formed stars are embedded in, and show the geometry of the surrounding dust cloud. The data reductions presented are on NGC 2068 and NGC 2023, which are centres of recent low-mass star formation and are embedded on the nearside of LI 630. In the case of NGC 2068, it appears that there is a single illuminating star which illuminates a foreground tilted slab of varying dust density from the rear. A simple tilted slab model assuming single Mie scattering from homogeneous spherical grains was used to fit visual data of traces of polarization, polarized intensity and total intensity through HD 38563N in a north-south direction. The model favoured metallic grains; the best fit being for iron grains and a slab 0.5 parsecs in front of HD 38563N tilted at an angle 55 degrees to the line-of-sight. In the case of NGC 2023, multicolour polarimetry is presented in B,V,R,I and Z. The star HD 37903 was found to be the sole illuminating star. A model to fit the spectral dependence of polarization gave low refractive index grains assuming a power law size distribution. Associated with NGC 2023 are Herbig-Haro objects HH-1, 4, which were found not to be polarized

Free Fatty Acids Quantification in Dairy Products

Quantification of free fatty acids in dairy products is not only important due to their (fatty acids) impact on the flavour and texture of dairy products but also because of their potential impact on nutrition and health, and as anti-microbial agents. This chapter provides an overview of the practical issues associated with existing lipid extraction techniques and quantification procedures using gas chromatography flame-ionization detection. The most widely used methods are compared and recent advancements in the quantification of free fatty acids in dairy products are discussed

The Role of Legal Services in the Antipoverty Program

Large-scale adaptive radiations might explain the runaway success of a minority of extant vertebrate clades. This hypothesis predicts, among other things, rapid rates of morphological evolution during the early history of major groups, as lineages invade disparate ecological niches. However, few studies of adaptive radiation have included deep time data, so the links between extant diversity and major extinct radiations are unclear. The intensively studied Mesozoic dinosaur record provides a model system for such investigation, representing an ecologically diverse group that dominated terrestrial ecosystems for 170 million years. Furthermore, with 10,000 species, extant dinosaurs (birds) are the most speciose living tetrapod clade. We assembled composite trees of 614-622 Mesozoic dinosaurs/birds, and a comprehensive body mass dataset using the scaling relationship of limb bone robustness. Maximum-likelihood modelling and the node height test reveal rapid evolutionary rates and a predominance of rapid shifts among size classes in early (Triassic) dinosaurs. This indicates an early burst niche-filling pattern and contrasts with previous studies that favoured gradualistic rates. Subsequently, rates declined in most lineages, which rarely exploited new ecological niches. However, feathered maniraptoran dinosaurs (including Mesozoic birds) sustained rapid evolution from at least the Middle Jurassic, suggesting that these taxa evaded the effects of niche saturation. This indicates that a long evolutionary history of continuing ecological innovation paved the way for a second great radiation of dinosaurs, in birds. We therefore demonstrate links between the predominantly extinct deep time adaptive radiation of non-avian dinosaurs and the phenomenal diversification of birds, via continuing rapid rates of evolution along the phylogenetic stem lineage. This raises the possibility that the uneven distribution of biodiversity results not just from large-scale extrapolation of the process of adaptive radiation in a few extant clades, but also from the maintenance of evolvability on vast time scales across the history of life, in key lineages

Optimized deep encoder-decoder methods for crack segmentation

Continuous maintenance of concrete infrastructure is an important task which is needed to continue safe operations of these structures. One kind of defect that occurs on surfaces in these structures are cracks. Automatic detection of those cracks poses a challenging computer vision task as background, shape, colour and size of cracks vary. In this work we propose optimized deep encoder-decoder methods consisting of a combination of techniques which yield an increase in crack segmentation performance. Specifically, we propose a new design for the decoder-part in encoder-decoder based deep learning architectures for semantic segmentation. We study its composition and how to achieve increased performance by exploring components such as deep supervision and upsampling strategies. Then we examine the optimal encoder to go in conjunction with this decoder and determine that pretrained encoders lead to an increase in performance. We propose a data augmentation strategy to increase the amount of available training data and carry out the performance evaluation of the designed architecture on four publicly available crack segmentation datasets. Additionally, we introduce two techniques into the field of surface crack segmentation, previously not used there: Generating results using test-time-augmentation and performing a statistical result analysis over multiple training runs. The former approach generally yields increased performance results, whereas the latter allows for more reproducible and better representability of a methods results. Using those aforementioned strategies with our proposed encoder-decoder architecture we are able to achieve new state of the art results in all datasets

Alternative Sample Loading Preparation for Thermal Ionization Mass Spectrometry

This contribution describes a new sample loading method for Thermal Ionization Mass Spectrometry (TIMS), which is used in nuclear safeguards and non-proliferation efforts worldwide and is known as the “gold standard” in isotopic ratio measurements of plutonium. TIMS analysis is used to determine grades of nuclear material and the extent of enrichment at production sites. The current sample loading method for TIMS analysis is known as “bead-loading”. While it provides the lowest detection limit of any known method for plutonium analysis, bead-loading is a difficult, time consuming, and expensive method that results in up to 20% sample loss. The major encumbrance of the method is the need to manually place a small polymer bead (~40 μm diameter) containing the plutonium sample onto a narrow and fragile ionization filament. We have developed an alternative sample loading method that eliminates the difficult and time-consuming steps by pre-coating the ionization filaments with a thin polymer film. Sample loading times have been reduced from hours to minutes. The films remain stably anchored to the filament, thus preventing sample loss. Ongoing TIMS measurements are testing our hypothesis that the method will increase overall measurement efficiency/sensitivity by isolating the sample in close proximity to the filament