A brachyopid temnospondyl from the lower Cynognathus Assemblage Zone In the northern Karoo Basin, South Africa

Main articleA new brachyopid temnospondyl is described from the Early to Middle Triassic Cynognathus Assemblage Zone of the upper Beaufort Group, Karoo Basin of South Africa. It is the fourth named brachyopid from the Karoo and the first from the northern part of the basin. Despite the incomplete nature of the holotype skull, the new brachyopid apparently shows closest affinities to Batrachosuchus watsoni. However, differences in the width of the sensory sulci, the absence of a transverse occipital sulcus, and the presence of a unique narial morphology, warrants separation at the species level. The holotype skull also provides insight into the morphology of the ventral surface of the skull roof and the configuration of the bones between the orbit and the nostril. A referred right mandibular ramus, the most complete yet recovered of a brachyopid, also shows several unique features. A reconsideration of the taxonomy of the brachyopid genus Batrachosuchus reveals that Batrachosuchus watsoni possesses several characters distinct from the type species, Batrachosuchus browni, and is thus transferred to a new genus. In addition, 'Batrachosuchus' henwoodi and Batrachosuchus concordi probably do not pertain to the genus Batrachosuchus. Brachyopid diversity in the Karoo is exceeded only by the Mastodonsauridae and Rhinesuchidae, and they may eventually prove to be important aids in the biostratigraphy of the Cynognathus Assemblage Zone.Palaeo-Anthropology Scientific Trust; French Embassy in South Africa; Co-operation and Cultural Service

Discovery and analysis of topographic features using learning algorithms: A seamount case study

Identifying and cataloging occurrences of particular topographic features are important but time-consuming tasks. Typically, automation is challenging, as simple models do not fully describe the complexities of natural features. We propose a new approach, where a particular class of neural network (the “autoencoder”) is used to assimilate the characteristics of the feature to be cataloged, and then applied to a systematic search for new examples. To demonstrate the feasibility of this method, we construct a network that may be used to find seamounts in global bathymetric data. We show results for two test regions, which compare favorably with results from traditional algorithms

Shear properties of MgO inferred using neural networks

Shear properties of mantle minerals are vital for interpreting seismic shear wave speeds and therefore inferring the composition and dynamics of a planetary interior. Shear wave speed and elastic tensor components, from which the shear modulus can be computed, are usually measured in the laboratory mimicking the Earth's (or a planet's) internal pressure and temperature conditions. A functional form that relates the shear modulus to pressure (and temperature) is fitted to the measurements and used to interpolate within and extrapolate beyond the range covered by the data. Assuming a functional form provides prior information, and the constraints on the predicted shear modulus and its uncertainties might depend largely on the assumed prior rather than the data. In the present study, we propose a data-driven approach in which we train a neural network to learn the relationship between the pressure, temperature and shear modulus from the experimental data without prescribing a functional form a priori. We present an application to MgO, but the same approach works for any other mineral if there are sufficient data to train a neural network. At low pressures, the shear modulus of MgO is well-constrained by the data. However, our results show that different experimental results are inconsistent even at room temperature, seen as multiple peaks and diverging trends in probability density functions predicted by the network. Furthermore, although an explicit finite-strain equation mostly agrees with the likelihood predicted by the neural network, there are regions where it diverges from the range given by the networks. In those regions, it is the prior assumption of the form of the equation that provides constraints on the shear modulus regardless of how the Earth behaves (or data behave). In situations where realistic uncertainties are not reported, one can become overconfident when interpreting seismic models based on those defined equations of state. In contrast, the trained neural network provides a reasonable approximation to experimental data and quantifies the uncertainty from experimental errors, interpolation uncertainty, data sparsity and inconsistencies from different experiments.</p

Prevalence of Vaccine Type Infections in Vaccinated and Non-Vaccinated Young Women: HPV-IMPACT, a Self-Sampling Study.

Background: The human papillomavirus (HPV) vaccination program for young girls aged 11⁻26 years was introduced in Switzerland in 2008. The objective of this study was to evaluate the prevalence of high- and low-risk HPV in a population of undergraduate students using self-sampling for monitoring the HPV vaccination program's effect. Undergraduate women aged between 18⁻31 years, attending the Medical School and University of Applied Sciences in Geneva, were invited to participate in the study. Included women were asked to perform vaginal self-sampling for HPV testing using a dry cotton swab. A total of 409 students participated in the study-aged 18⁻31 years-of which 69% of the participants were vaccinated with Gardasil HPV vaccine and 31% did not received the vaccine. About HPV prevalence, 7.2% of unvaccinated women were HPV 16 or 18 positive, while 1.1% of vaccinated women were infected by HPV 16 or 18 (p &lt; 0.01). Prevalence of HPV 6 and 11 was 8.3% in non-vaccinated women versus 2.1% in vaccinated women (p &lt; 0.02). We observed no cross-protection for the other HPV genotypes of a low- and high-risk strain. Prevalence of HPV 6/11/16/18 was lower in vaccinated women versus unvaccinated women. Continued assessment of HPV vaccine effectiveness in real population is needed

Perspective of Internet Poker Players on Harm-Reduction Strategies: A Cross-Sectional Study.

Background: Internet gambling may increase rates of gambling harm. This current study aimed to assess Internet poker players' views on various harm-reduction (HR) strategies. It also examined differences in these views according to the games played (poker only vs. poker plus other gambling activities), indebtedness, and problem gambling severity. Methods: Internet poker players (n = 311; 94.2% Male) recruited online between 2012 and 2014 were included in the analyses and completed a survey on indebtedness, problem gambling severity index, and ten statements regarding HR features. Results: Among the whole sample, the most frequently endorsed HR strategy was setting money limits, specialized online help, and peer support forums. People who play poker only (70%) are less prone to endorse the utility of information on excessive gambling and specialized healthcare centers. No differences were found between those people with debt versus those without regarding HR assessment. Participants with severe problem gambling were more skeptical about HR strategies based on information on specialized healthcare centers. Conclusion: Setting money limits, online help, and peer support forums are the most commonly endorsed strategies. Future research is needed to evaluate the effectiveness of online harm reduction strategies

Internal structure of matrix-type multilayer capsules templated on porous vaterite CaCO3 crystals as probed by staining with a fluorescence dye

Multilayer capsules templated on decomposable vaterite CaCO3 crystals are widely used as vehicles for drug delivery. The capsule represents typically not a hollow but matrix-like structure due to polymer diffusion into the porous crystals during multilayer deposition. The capsule formation mechanism is not well-studied but its understanding is crucial to tune capsule structure for a proper drug release performance. This study proposes new approach to noninvasively probe and adjust internal capsule structure. Polymer capsules made of poly(styrene-sulfonate) (PSS) and poly(diallyldimethylammonium chloride) (PDAD) have been stained with fluorescence dye rhodamine 6G. Physical-chemical aspects of intermolecular interactions required to validate the approach and adjust capsule structure are addressed. The capsules consist of a defined shell (typically 0.5–2 µm) and an internal matrix of PSS-PDAD complex (typically 10–40% of a total capsule volume). An increase of ionic strength and polymer deposition time leads to the thickening of the capsule shell and formation of a denser internal matrix, respectively. This is explained by effects of a polymer conformation and limitations in polymer diffusion through the crystal pores. We believe that the design of the capsules with desired internal structure will allow achieving effective encapsulation and controlled/programmed release of bioactives for advanced drug delivery applications

Thermodynamic evaluation of a solar based kalina cycle

Solar energy has enormous potential in the world. It can produce energy generation several times larger than the overall world energy demand. However, a major challenge to implement it is the high costs of electricity generation from solar sources. These costs can be reduced by improving the conversion efficiency from solar energy to electrical energy. Currently, the Rankine cycle is the most frequently used power cycle for generating electricity from solar energy. An interesting alternative to the commonly used Rankine cycle that uses solar heat energy as its input is the Kalina cycle. The Kalina cycle uses a mixture of ammonia and water as its working fluid. When using a mixture of ammonia and water as a working fluid, temperature varies while heat is added and rejected during phase change. This theoretically would be more efficient than a power cycle who only uses water as its working fluid. This paper examines the performance of a Kalina cycle with solar energy from concentrating solar plant as the input heat. A solution algorithm is developed and programmed to evaluate the thermodynamic properties of a Kalina cycle with inlet turbine temperature of 400 °C. Parametric analysis was done to study the effects of turbine inlet pressure and turbine inlet ammonia concentration on cycle efficiency. Results shows that both parameters have a positive relationship with cycle efficiency. Turbine outlet pressure was found to be a major influence on cycle efficiency. Maximum efficiency was found to be 33% at a turbine inlet pressure of 140 bar and turbine inlet ammonia concentration of 0.8

Characteristics of HPV-unvaccinated undergraduate health students in Switzerland, a cross sectional study.

Human Papillomavirus (HPV) vaccination, intended for young women aged 11-14 years old, has been introduced in Switzerland in 2007. Ten years after its introduction, only a few studies have explored the reasons associated with uptake and non-uptake of the vaccination. Our objective was to identify the sociodemographic characteristics of a population of vaccinated and unvaccinated undergraduate healthcare female students, to define the reasons of non-uptake of vaccination, and compare our findings with those found in other Swiss cantons. Between January and November 2017, women studying in Health Sciences School and Medical School in Geneva, aged 18-31 years old, were recruited in a large trial assessing HPV prevalence. As part of a smaller, observational study nested in this larger trial, women were invited to complete a questionnaire. Self-reported HPV vaccination uptake or non-uptake, as well as knowledge and attitude about HPV vaccination were assessed. T-Test and Chi square test were used to compare characteristics of vaccinated and unvaccinated women. Overall, 409 women were recruited in the study. The majority of them (69.1%) reported having been vaccinated for HPV, while 30.9% of them had never received any dose of the HPV vaccine. The only factor associated with a higher vaccination rate was the participants' origin, as women from Geneva were more represented in the vaccinated group than women from other Swiss regions or countries. Unvaccinated women were more likely to consider HPV vaccination as less important than the vaccinated ones (50.4% vs 3.5% p &lt; 0.001). Although no typical profile can be established in this studied population of unvaccinated women, a lack of information was a major reason of non-uptake of vaccination among the study participants. An effort by health authorities and carefully designed messages are essential to increase the population's awareness over cervical cancer and its prevention. The trial was registered under cliniclatrials.gov with the identifier: NCT03474211

On the Benefits of Transparent Compression for Cost-Effective Cloud Data Storage

International audienceInfrastructure-as-a-Service (IaaS) cloud computing has revolutionized the way we think of acquiring computational resources: it allows users to deploy virtual machines (VMs) at large scale and pay only for the resources that were actually used throughout the runtime of the VMs. This new model raises new challenges in the design and development of IaaS middleware: excessive storage costs associated with both user data and VM images might make the cloud less attractive, especially for users that need to manipulate huge data sets and a large number of VM images. Storage costs result not only from storage space utilization, but also from bandwidth consumption: in typical deployments, a large number of data transfers between the VMs and the persistent storage are performed, all under high performance requirements. This paper evaluates the trade-off resulting from transparently applying data compression to conserve storage space and bandwidth at the cost of slight computational overhead. We aim at reducing the storage space and bandwidth needs with minimal impact on data access performance. Our solution builds on BlobSeer, a distributed data management service specifically designed to sustain a high throughput for concurrent accesses to huge data sequences that are distributed at large scale. Extensive experiments demonstrate that our approach achieves large reductions (at least 40%) of bandwidth and storage space utilization, while still attaining high performance levels that even surpass the original (no compression) performance levels in several data-intensive scenarios