Bone and Joint Diseases: Prevention and Control

Arthritis is Australia's major cause of disability and chronic pain. In Australian women, osteoarthritis is the third leading cause of years lost due to disability. Osteoporosis affects nearly two million Australians. The Federal government acknowledged the importance of musculoskeletal diseases by designating arthritis and musculoskeletal diseases as the seventh National Health Priority. This decade has been designated by the United Nations and the World Health Organization as the Decade of Bone and Joint Disease. To try to raise awareness, the National Action Network (the committee charged with organising activities in Australia) arranged a summit in 2002 to focus on preventive issues for osteoporosis and arthritis, and the benefits of surgical approaches

Epidemic predictions in an imperfect world : modelling disease spread with partial data

‘Big-data’ epidemic models are being increasingly used to influence government policy to help with control and eradication of infectious diseases. In the case of livestock, detailed movement records have been used to parametrize realistic transmission models. While livestock movement data are readily available in the UK and other countries in the EU, in many countries around the world, such detailed data are not available. By using a comprehensive database of the UK cattle trade network, we implement various sampling strategies to determine the quantity of network data required to give accurate epidemiological predictions. It is found that by targeting nodes with the highest number of movements, accurate predictions on the size and spatial spread of epidemics can be made. This work has implications for countries such as the USA, where access to data is limited, and developing countries that may lack the resources to collect a full dataset on livestock movements

Discovering the True Chrysoperla carnea (Insecta: Neuroptera: Chrysopidae) Using Song Analysis, Morphology, and Ecology

What was once considered a single Holarctic species of green lacewing, Chrysoperla carnea (Stephens), has recently been shown to be a complex of many cryptic, sibling species, the carnea species group, whose members are reproductively isolated by their substrate-borne vibrational songs. Because species in the complex are diagnosed by their song phenotypes and not by morphology, the current systematic status of the type species has become a problem. Here, we attempt to determine which song species corresponds to Stephens' 1835 concept of C. carnea, originally based on a small series of specimens collected in or near London and currently housed in The Natural History Museum. With six European members of the complex from which to choose, we narrow the field to just three that have been collected in England: C. lucasina (Lacroix), Cc2 ‘slow-motorboat', and Cc4 ‘motorboat'. Ecophysiology eliminates C. lucasina, because that species remains green during adult winter diapause, while Cc2 and Cc4 share with Stephens' type a change to brownish or reddish color in winter. We then describe the songs, ecology, adult morphology, and larval morphology of Cc2 and Cc4, making statistical comparisons between the two species. Results strongly reinforce the conclusion that Cc2 and Cc4 deserve separate species status. In particular, adult morphology displays several subtle but useful differences between the species, including the shape of the basal dilation of the metatarsal claw and the genital ‘lip' and ‘chin' of the male abdomen, color and coarseness of the sternal setae at the tip of the abdomen and on the genital lip, and pigment distribution on the stipes of the maxilla. Furthermore, behavioral choice experiments involving playback of conspecific versus heterospecific songs to individuals of Cc2 and Cc4 demonstrate strong reproductive isolation between the two species. Comparison of the adult morphology of song-determined specimens to that of preserved specimens in the original type series and in other collections in The Natural History Museum, London, indicate that the ‘true' Chrysoperla carnea (Stephens) is Cc4. Cc2 cannot be confidently associated with any previously described species and is therefore assigned a new name, Chrysoperla pallida sp. nov., and formally describe

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks

AbstractA new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanal ysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteorology with biases no greater than 0.6% across all variables and variance that was accurate within 1% for all variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output and the expected (original) monthly means exceeded 0.99 for all variables, which indicates that this approach would work well for generating atmospheric forcing data consistent with mass and energy conserved GCM output. Our neural network approach performed well for variables that had correlations to other variables of about 0.3 and better and its skill was increased by downscaling multiple correlated variables together. Poor replication of precipitation intensity however required further post-processing in order to obtain the expected probability distribution. The concurrence of precipitation events with expected changes in sub ordinate variables (e.g., less incident shortwave radiation during precipitation events) were nearly as consistent in the downscaled data as in the training data with probabilities that differed by no more than 6%. Our downscaling approach requires training data at the target time step and relies on a weak assumption that climate variability in the extrapolated data is similar to variability in the training data

Robot Rights? Let's Talk about Human Welfare Instead

The 'robot rights' debate, and its related question of 'robot responsibility', invokes some of the most polarized positions in AI ethics. While some advocate for granting robots rights on a par with human beings, others, in a stark opposition argue that robots are not deserving of rights but are objects that should be our slaves. Grounded in post-Cartesian philosophical foundations, we argue not just to deny robots 'rights', but to deny that robots, as artifacts emerging out of and mediating human being, are the kinds of things that could be granted rights in the first place. Once we see robots as mediators of human being, we can understand how the `robots rights' debate is focused on first world problems, at the expense of urgent ethical concerns, such as machine bias, machine elicited human labour exploitation, and erosion of privacy all impacting society's least privileged individuals. We conclude that, if human being is our starting point and human welfare is the primary concern, the negative impacts emerging from machinic systems, as well as the lack of taking responsibility by people designing, selling and deploying such machines, remains the most pressing ethical discussion in AI.Comment: Accepted to the AIES 2020 conference in New York, February 2020. The final version of this paper will appear in Proceedings of the 2020 AAAI/ACM Conference on AI, Ethics, and Societ

Guest Editorial Special Issue on Medical Imaging and Image Computing in Computational Physiology

International audienceThe January 2013 Special Issue of IEEE transactions on medical imaging discusses papers on medical imaging and image computing in computational physiology. Aslanid and co-researchers present an experimental technique based on stained micro computed tomography (CT) images to construct very detailed atrial models of the canine heart. The paper by Sebastian proposes a model of the cardiac conduction system (CCS) based on structural information derived from stained calf tissue. Ho, Mithraratne and Hunter present a numerical simulation of detailed cerebral venous flow. The third category of papers deals with computational methods for simulating medical imagery and incorporate knowledge of imaging physics and physiology/biophysics. The work by Morales showed how the combination of device modeling and virtual deployment, in addition to patient-specific image-based anatomical modeling, can help to carry out patient-specific treatment plans and assess alternative therapeutic strategies

Song Analysis Reveals a Permanent Population of the Mediterranean Lacewing Chrysoperla agilis (Neuroptera: Chrysopidae) Living in Central Alaska

Chrysoperla agilis Henry et al. (Neuroptera: Chrysopidae) is a widespread, nomadic lacewing in the carnea group of cryptic species. C. agilis has previously been found only in the warm parts of Europe, western Asia, and a few oceanic islands. Like others of the carnea group, C. agilis is identifiable only by its unique courtship song. Recently, a population with by the C. agilis song was discovered in central Alaska; based on its persistence over several years and its distribution over a wide area near Fairbanks, it seems to be permanent rather than transitory. To assess the relationship of this Western Hemisphere population to C. agilis in the Eastern Hemisphere, we 1) analyzed its courtship song, comparing it to the Eurasian song; 2) compared larval and adult morphology of Alaskan and Eurasian specimens; 3) inferred phylogenetic relationships of Alaskan and Eurasian specimens, by using sequences from the cox2 gene; and 4) crossed Alaskan with European individuals, raising their progeny and analyzing their "hybrid” songs. Alaskan C. agilis generally fell within the range of variation of Eurasian individuals for all acoustic and morphological traits, and their hybrid progeny were also acoustically indistinguishable. Phylogenetically, and despite current geographical isolation, Alaskan individuals clustered with Eurasian C. agilis rather than with Western Hemisphere taxa of the carnea group. We conclude that the Alaskan population is a bona fide member of C. agilis. Examination of the geographical pattern of song variation suggests that dispersal to Alaska took place quite recently in a west to east direction, via eastern Asia and the Bering Strai

Angular momentum evolution in dark-matter haloes

We have analysed high-resolution N-body simulations of dark-matter (DM) haloes, focusing specifically on the evolution of angular momentum. We find that not only is individual particle angular momentum not conserved, but the angular momentum of radial shells also varies over the age of the Universe by up to factors of a few. We find that torques from external structure are the most likely cause for this distribution shift. Since the model of adiabatic contraction that is often applied to model the effects of galaxy evolution on the DM density profile in a halo assumes angular momentum conservation, this variation implies that there is a fundamental limit on the possible accuracy of the adiabatic contraction model in modelling the response of DM haloes to the growth of galaxies

In-situ characterization of the thermal state of resonant optical interferometers via tracking of their higher-order mode resonances

Thermal lensing in resonant optical interferometers such as those used for gravitational wave detection is a concern due to the negative impact on control signals and instrument sensitivity. In this paper we describe a method for monitoring the thermal state of such interferometers by probing the higher-order spatial mode resonances of the cavities within them. We demonstrate the use of this technique to measure changes in the Advanced LIGO input mode cleaner cavity geometry as a function of input power, and subsequently infer the optical absorption at the mirror surfaces at the level of 1 ppm per mirror. We also demonstrate the generation of a useful error signal for thermal state of the Advanced LIGO power recycling cavity by continuously tracking the first order spatial mode resonance frequency. Such an error signal could be used as an input to thermal compensation systems to maintain the interferometer cavity geometries in the presence of transients in circulating light power levels, thereby maintaining optimal sensitivity and maximizing the duty-cycle of the detectors

Boolean analysis identifies CD38 as a biomarker of aggressive localized prostate cancer.

The introduction of serum Prostate Specific Antigen (PSA) testing nearly 30 years ago has been associated with a significant shift towards localized disease and decreased deaths due to prostate cancer. Recognition that PSA testing has caused over diagnosis and over treatment of prostate cancer has generated considerable controversy over its value, and has spurred efforts to identify prognostic biomarkers to distinguish patients who need treatment from those that can be observed. Recent studies show that cancer is heterogeneous and forms a hierarchy of tumor cell populations. We developed a method of identifying prostate cancer differentiation states related to androgen signaling using Boolean logic. Using gene expression data, we identified two markers, CD38 and ARG2, that group prostate cancer into three differentiation states. Cancers with CD38-, ARG2- expression patterns, corresponding to an undifferentiated state, had significantly lower 10-year recurrence-free survival compared to the most differentiated group (CD38+ARG2+). We carried out immunohistochemical (IHC) staining for these two markers in a single institution (Stanford; n = 234) and multi-institution (Canary; n = 1326) cohorts. IHC staining for CD38 and ARG2 in the Stanford cohort demonstrated that combined expression of CD38 and ARG2 was prognostic. In the Canary cohort, low CD38 protein expression by IHC was significantly associated with recurrence-free survival (RFS), seminal vesicle invasion (SVI), extra-capsular extension (ECE) in univariable analysis. In multivariable analysis, ARG2 and CD38 IHC staining results were not independently associated with RFS, overall survival, or disease-specific survival after adjusting for other factors including SVI, ECE, Gleason score, pre-operative PSA, and surgical margins