The Outer Solar Systems Origins Survey. I. Design and First-quarter Discoveries

We report the discovery, tracking, and detection circumstances for 85 trans-Neptunian objects (TNOs) from the first 42 deg2 of the Outer Solar System Origins Survey. This ongoing r-band solar system survey uses the 0.9 deg2 field of view MegaPrime camera on the 3.6 m Canada–France–Hawaii Telescope. Our orbital elements for these TNOs are precise to a fractional semimajor axis uncertainty <0.1%. We achieve this precision in just two oppositions, as compared to the normal three to five oppositions, via a dense observing cadence and innovative astrometric technique. These discoveries are free of ephemeris bias, a first for large trans-Neptunian surveys. We also provide the necessary information to enable models of TNO orbital distributions to be tested against our TNO sample. We confirm the existence of a cold "kernel" of objects within the main cold classical Kuiper Belt and infer the existence of an extension of the "stirred" cold classical Kuiper Belt to at least several au beyond the 2:1 mean motion resonance with Neptune. We find that the population model of Petit et al. remains a plausible representation of the Kuiper Belt. The full survey, to be completed in 2017, will provide an exquisitely characterized sample of important resonant TNO populations, ideal for testing models of giant planet migration during the early history of the solar system.

Physical characterization of TNOs with the James Webb Space Telescope

Studies of the physical properties of trans-Neptunian objects (TNOs) are a powerful probe into the processes of planetesimal formation and solar system evolution. James Webb Space Telescope (JWST) will provide unique new capabilities for such studies. Here, we outline where the capabilities of JWST open new avenues of investigation, potentially valuable observations and surveys, and conclude with a discussion of community actions that may serve to enhance the eventual science return of JWST's TNO observations.

The occurrence of PAHs and faecal sterols in Dublin Bay and their influence on sedimentary microbial communities

The source, concentration, and potential impact of sewage discharge and incomplete organic matter (OM) combustion on sedimentary microbial populations were assessed in Dublin Bay, Ireland. Polycyclic aromatic hydrocarbons (PAHs) and faecal steroids were investigated in 30 surface sediment stations in the bay. Phospholipid fatty acid (PLFA) content at each station was used to identify and quantify the broad microbial groups present and the impact of particle size, total organic carbon (%TOC), total hydrogen (%H) and total nitrogen (%N) was also considered. Faecal sterols were found to be highest in areas with historical point sources of sewage discharge. PAH distribution was more strongly associated with areas of deposition containing high %silt and %clay content, suggesting that PAHs are from diffuse sources such as rainwater run-off and atmospheric deposition. The PAHs ranged from 12 to 3072 ng/g, with 10 stations exceeding the suggested effect range low (ERL) for PAHs in marine sediments. PAH isomer pair ratios and sterol ratios were used to determine the source and extent of pollution. PLFAs were not impacted by sediment type or water depth but were strongly correlated to, and influenced by PAH and sewage levels. Certain biomarkers such as 10Me16:0, i17:0 and a17:0 were closely associated with PAH polluted sediments, while 16:1ω9, 16:1ω7c, Cy17:0, 18:1ω6, i16:0 and 15:0 all have strong positive correlations with faecal sterols. Overall, the results show that sedimentary microbial communities are impacted by anthropogenic pollution.

A Microbial Link to Weathering of Postglacial Rocks and Sediments, Mount Viso Area, Western Alps, Demonstrated through Analysis of a Soil/Paleosol Bio/Chronosequence

Understanding the mechanism associated with rates of weathering and evolution of rocks→sediment→soil→paleosol in alpine environments raises questions related to the impact of microbial mediation versus various diverse abiotic chemical/physical processes, even including the overall effect of cosmic impact/airburst during the early stage of weathering in Late Glacial (LG) deposits. This study is of a chronosequence of soils/paleosols, with an age range that spans the post–Little Ice Age (post-LIA; <150 yr), the Little Ice Age (LIA; AD 1500–1850), the middle Neoglacial (∼3 ka)–Younger Dryas (YD; <12.8 ka), and the LG (<15 ka). The goal is to elicit trends in weathering, soil morphogenesis, and related eubacterial population changes over the past 13–15 k.yr. The older LG/YD paleosols in the sequence represent soil morphogenesis that started during the closing stage of Pleistocene glaciation. These are compared with undated soils of midto late Neoglacial age, the youngest of LIA and post-LIA age. All profiles formed in a uniform parentmaterial ofmetabasalt composition and in moraine, rockfall, protalus, and alluvial fan deposits. Elsewhere in Europe,North America, and Asia, the cosmic impact/airburst event at 12.8 ka often produced a distinctive, carbon-rich “black mat” layer that shows evidence of high-temperature melting. At this alpine site, older profiles of similar LG age contain scorched and melted surface sediments that are otherwise similar in composition to the youngest/thinnest profiles developing in the catchment today. Moreover, microbial analysis of the sediments offers new insight into the genesis of these sediments: the C and Cu (u = unweathered) horizons in LG profiles present at 12.8 ka (now Ah/Bw) show bacterial population structures that differ markedly from recent alluvial/protalus sample bacterial populations. We propose here that these differences are, in part, a direct consequence of the age/cosmic impact/weathering processes that have occurred in the chronosequence. Of the several questions that emerge from these sequences, perhaps the most important involve the interaction of biotic-mineral factors, which need to be understood if we are to generally fully appreciate the role played by microbes in rock weathering.

Physico-geochemical and mineral composition of neem tree soils and relation to organic properties

The Neem tree, the oil of which has a long history of pesticide, fertilizer and medicinal use in India, has been studied extensively for its organic compounds. Here we present a physical, mineralogical and geochemical database resulting from the analyses of two Neem soil profiles (epipedons) in India. Neem tree derivatives are used in the manufacture of a variety of products, from anti-bacterial drugs and insecticides to fertilizers and animal feeds. A preliminary geochemical and mineralogical analysis of Neem soils is made to explore the potential for chemical links between Neem tree derivatives and soils. Physical soil characteristics, including colour, texture and clay mineralogy, suggest the two pedons formed under different hydrological regimes, and hence, are products of different leaching environments, one well-drained site, the other poorly drained. Geochemically, the two Neem soils exhibit similarities, with elevated concentrations of Th and rare earth elements. These elements are of interest because of their association with phosphates, especially monazite and apatite, and the potential link to fertilizer derivatives. Higher concentrations of trace elements in the soils may be linked to nutritional derivatives and to cell growth in the Neem tree.

Thomson scattering on non-thermal atmospheric pressure plasma jets

To characterize non-thermal atmospheric pressure plasmas experimentally, a large variety of methods and techniques is available, each having its own specific possibilities and limitations. A rewarding method to investigate these plasma sources is laser Thomson scattering. However, that is challenging. Non-thermal atmospheric pressure plasmas (gas temperatures close to room temperature and electron temperatures of a few eV) have usually small dimensions (below 1 mm) and a low degree of ionization (below 10^-4). Here an overview is presented of how Thomson scattering can be applied to such plasmas and used to measure directly spatially and temporally resolved the electron density and energy distribution. A general description of the scattering of photons and the guidelines for an experimental setup of this active diagnostic are provided. Special attention is given to the design concepts required to achieve the maximum signal photon flux with a minimum of unwanted signals. Recent results from the literature are also presented and discussed.

Application of low temperature plasmas for restoration/conservation of archaeological objects

The low-temperature low-pressure hydrogen based plasmas were used to study the influence of processes and discharge conditions on corrosion removal. The capacitive coupled RF discharge in the continuous or pulsed regime was used at operating pressure of 100-200 Pa. Plasma treatment was monitored by optical emission spectroscopy. To be able to study influence of various process parameters, the model corroded samples with and without sandy incrustation were prepared. The SEM-EDX analyzes were carried out to verify corrosion removal efficiency. Experimental conditions were optimized for the selected most frequent materials of original metallic archaeological objects (iron, bronze, copper, and brass). Chlorides removal is based on hydrogen ion reactions while oxides are removed mainly by neutral species interactions. A special focus was kept for the samples temperature because it was necessary to avoid any metallographic changes in the material structure. The application of higher power pulsed regime with low duty cycle seems be the best treatment regime. The low pressure hydrogen plasma is not applicable for objects with a very broken structure or for nonmetallic objects due to the non-uniform heat stress. Due to this fact, the new developed plasmas generated in liquids were applied on selected original archaeological glass materials.

Efficient and Selectable Production of Reactive Species Using a Nanosecond Pulsed Discharge in Gas Bubbles in Liquid

A plasma gas bubble-in-liquid method for high production of selectable reactive species using a nanosecond pulse generator has been developed. The gas of choice is fed through a hollow needle in a point-to-plate bubble discharge, enabling improved selection of reactive species. The increased interface reactions, between the gas-plasma and water through bubbles, give higher productivity. H₂O₂ was the predominant species produced using Ar plasma, while predominantly  and NO₂ were generated using air plasma, in good agreement with the observed emission spectra. This method has nearly 100% selectivity for H₂O₂, with seven times higher production, and 92% selectivity for , with nearly twice the production, compared with a plasma above the water.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

Ion-acoustic envelope modes in a degenerate relativistic electron-ion plasma

A self-consistent relativistic two-fluid model is proposed for one-dimensional electron-ion plasma dynamics. A multiple scales perturbation technique is employed, leading to an evolution equation for the wave envelope, in the form of a nonlinear Schrödinger type equation (NLSE). The inclusion of relativistic effects is shown to introduce density-dependent factors, not present in the non-relativistic case - in the conditions for modulational instability. The role of relativistic effects on the linear dispersion laws and on envelope soliton solutions of the NLSE is discussed.

To breathe or fight? Siamese fighting fish differ when facing a real opponent or mirror image

Displays are a feature of animal contest behaviour and have been interpreted as a means of gathering information on opponent fighting ability, as well as signalling aggressive motivation. In fish, contest displays often include frontal and lateral elements, which in the latter involves contestants showing their flanks to an opponent. Previous work in a range of fish species has demonstrated population-level lateralization of these displays, preferentially showing one side to their opponent. Mirrors are commonly used in place of a real opponent to study aggression in fish, yet they may disrupt the normal pattern of display behaviour. Here, using Siamese fighting fish, Betta splendens, we compare the aggressive behaviour of males to a mirror image and real opponent behind a transparent barrier. As this species is a facultative air-breather, we also quantify surface breathing, providing insights into underlying fight motivation. Consistent with previous work, we found evidence of population-level lateralization, with a bias to present the left side and use the left eye when facing a real opponent. Contrary to expectations, there were no differences in the aggressive displays to a mirror and real opponent, with positive correlations between the behaviour in the two scenarios. However, there were important differences in surface breathing, which was more frequent and of longer duration in the mirror treatment. The reasons for these differences are discussed in relation to the repertoire of contest behaviour and motivation when facing a real opponent.

No discrimination shock avoidance with sequential presentation of stimuli but shore crabs still reduce shock exposure

Insights into the potential for pain may be obtained from examination of behavioural responses to noxious stimuli. In particular, prolonged responses coupled with long-term motivational change and avoidance learning cannot be explained by nociceptive reflex but are consistent with the idea of pain. Here, we placed shore crabs alternately in two halves of a test area divided by an opaque partition. Each area had a dark shelter and in one repeated small electric shocks were delivered in an experimental but not in a control group. Crabs showed no specific avoidance of the shock shelter either during these trials or in a subsequent test in which both were offered simultaneously; however they often emerged from the shock shelter during a trial and thus avoided further shock. More crabs emerged in later trials and took less time to emerge than in early trials. Thus, despite the lack of discrimination learning between the two shelters they used other tactics to markedly reduce the amount of shock received. We note that a previous experiment using simultaneous presentation of two shelters demonstrated rapid discrimination and avoidance learning but the paradigm of sequential presentation appears to prevent this. Nevertheless, the data show clearly that the shock is aversive and tactics, other than discrimination learning, are used to avoid it. Thus, the behaviour is only partially consistent with the idea of pain.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.