Detailed Spectroscopic and Photometric Analysis of DQ White Dwarfs

We present an analysis of spectroscopic and photometric data for cool DQ white dwarfs based on improved model atmosphere calculations. In particular, we revise the atmospheric parameters of the trigonometric parallax sample of Bergeron et al.(2001), and discuss the astrophysical implications on the temperature scale and mean mass, as well as the chemical evolution of these stars. We also analyze 40 new DQ stars discovered in the first data release of the Sloan Digital Sky Survey.Comment: 6 pages,3 figures, 14th European Workshop on White Dwarfs, ASP Conference Series, in pres

Methodology to Forecast Road Surface Temperature with Principal Components Analysis and Partial Least-Square Regression: Application to an Urban Configuration

A forecast road surface temperature (RST) helps winter services to optimize costs and to reduce the deicers environmental impacts. Data from road weather information systems (RWIS) and thermal mapping are considered inputs for forecasting physical numerical models. Statistical models include many meteorological parameters along routes and provide a spatial approach. It is based on typical combinations resulting from treatment and analysis of a database from measurements of road weather stations or thermal mapping, easy, reliable, and cost effective to monitor RST, and many meteorological parameters. A forecast dedicated to road networks should combine both spatial and time forecasts needs. This study contributed to building a reliable RST forecast based on principal component analysis (PCA) and partial least-square (PLS) regression. An urban stretch with various weather conditions and seasons was monitored over several months to generate an appropriate number of samples. The study first consisted of the identification of its optimum number to establish a reliable forecast. A second aspect is aimed at comparing RST forecasts from PLS model to measurements. Comparison indicated a forecast over an urban stretch with up to 94% of values within ±1°C and over 80% within ±3°C

Neuroinflammation in post-acute sequelae of COVID-19 (PASC) as assessed by [11C]PBR28 PET correlates with vascular disease measures

The COVID-19 pandemic caused by SARS-CoV-2 has triggered a consequential public health crisis of post-acute sequelae of COVID-19 (PASC), sometimes referred to as long COVID. The mechanisms of the heterogeneous persistent symptoms and signs that comprise PASC are under investigation, and several studies have pointed to the central nervous and vascular systems as being potential sites of dysfunction. In the current study, we recruited individuals with PASC with diverse symptoms, and examined the relationship between neuroinflammation and circulating markers of vascular dysfunction. We used [ 11C]PBR28 PET neuroimaging, a marker of neuroinflammation, to compare 12 PASC individuals versus 43 normative healthy controls. We found significantly increased neuroinflammation in PASC versus controls across a wide swath of brain regions including midcingulate and anterior cingulate cortex, corpus callosum, thalamus, basal ganglia, and at the boundaries of ventricles. We also collected and analyzed peripheral blood plasma from the PASC individuals and found significant positive correlations between neuroinflammation and several circulating analytes related to vascular dysfunction. These results suggest that an interaction between neuroinflammation and vascular health may contribute to common symptoms of PASC

Digital technologies, legal design and the future of the legal profession

Legal Technology – or “Legal Tech” – is disrupting the traditional operations and self-understanding of the legal profession. This chapter introduces the central claim of this book, namely that these developments are having and will continue to have a disruptive effect on the work of lawyers and that adapting to this new operating environment is crucial for legal professionals remaining relevant in an increasingly technology-driven world. This introductory chapter outlines some of the main features of this on-going transformation process, introduces some of the pressures it is creating for lawyers, and provides short summaries of the chapters that comprise this collection.fi=vertaisarvioitu|en=peerReviewed

Electrical conductivity of plasmas of DB white dwarf atmospheres

The static electrical conductivity of non-ideal, dense, partially ionized helium plasma was calculated over a wide range of plasma parameters: temperatures $1\cdot 10^{4}\textrm{K} \lesssim T \lesssim 1\cdot 10^{5}\textrm{K}$ and mass density $1 \times 10^{-6} \textrm{g}/\textrm{cm}^{3} \lesssim \rho \lesssim 2 \textrm{g}/\textrm{cm}^{3}$. Calculations of electrical conductivity of plasma for the considered range of plasma parameters are of interest for DB white dwarf atmospheres with effective temperatures $1\cdot 10^{4}\textrm{K} \lesssim T_{eff} \lesssim 3\cdot 10^{4}\textrm{K}$. Electrical conductivity of plasma was calculated by using the modified random phase approximation and semiclassical method, adapted for the case of dense, partially ionized plasma. The results were compared with the unique existing experimental data, including the results related to the region of dense plasmas. In spite of low accuracy of the experimental data, the existing agreement with them indicates that results obtained in this paper are correct

Managing maize under pest species competition: is Bt (Bacillus thuringiensis) maize the solution?

Transgenic crops that contain Cry genes from Bacillus thuringiensis (Bt) have been adopted by farmers over the last 17 years. Unlike traditional broad spectrum chemical insecticides, Bt's toxicity spectrum is relatively narrow and selective, which may indirectly benefit secondary insects that may become important pests. The economic damage caused by the rise of secondary pests could offset some or all of the benefits associated with the use of Bt varieties. We develop a bioeconomic model to analyze the interactions between primary and secondary insect populations and the impact of different management options on insecticide use and economic impact over time. Results indicate that some of the benefits associated with the adoption of genetically engineered insect resistant crops may be eroded when taking into account ecological dynamics. It is suggested that secondary pests could easily become key insect pests requiring additional measures - such as insecticide applications or stacked traits – to keep their populations under the economic threshold

Modelling small block aperture in an in-house developed GPU-accelerated Monte Carlo-based dose engine for pencil beam scanning proton therapy

Purpose: To enhance an in-house graphic-processing-unit (GPU) accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both dose calculation and optimization for pencil beam scanning proton therapy (PBSPT)-based stereotactic radiosurgery (SRS). Methods and Materials: A block aperture module was integrated into VPMC. VPMC was validated by an opensource code, MCsquare, in eight water phantom simulations with 3cm thick brass apertures: four were with aperture openings of 1, 2, 3, and 4cm without a range shifter, while the other four were with same aperture opening configurations with a range shifter of 45mm water equivalent thickness. VPMC was benchmarked with MCsquare and RayStation MC for 10 patients with small targets (average volume 8.4 cc). Finally, 3 patients were selected for robust optimization with aperture blocks using VPMC. Results: In the water phantoms, 3D gamma passing rate (2%/2mm/10%) between VPMC and MCsquare were 99.71$\pm$0.23%. In the patient geometries, 3D gamma passing rates (3%/2mm/10%) between VPMC/MCsquare and RayStation MC were 97.79$\pm$2.21%/97.78$\pm$1.97%, respectively. The calculation time was greatly decreased from 112.45$\pm$114.08 seconds (MCsquare) to 8.20$\pm$6.42 seconds (VPMC), both having statistical uncertainties of about 0.5%. The robustly optimized plans met all the dose-volume-constraints (DVCs) for the targets and OARs per our institutional protocols. The mean calculation time for 13 influence matrices in robust optimization by VPMC was 41.6 seconds. Conclusion: VPMC has been successfully enhanced to model aperture blocks in dose calculation and optimization for the PBSPT-based SRS.Comment: 3 tables, 3 figure

Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy

Purpose: To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning. Methods: PBSPT plans of 103 prostate cancer patients and 83 lung cancer patients previously treated at our institution were included in the study, each with CTs, structure sets, and plan doses calculated by the in-house developed Monte-Carlo dose engine. For the ablation study, we designed three experiments corresponding to the following three methods: 1) Experiment 1, the conventional region of interest (ROI) method. 2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. 3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D-Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates, and dice coefficients for the structures enclosed by the iso-dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency. Results: Compared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices. For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method can improve the passing rates in these regions and the sliding window method further improved them. A similar trend was also observed for the dice coefficients. In fact, this trend was especially remarkable for relatively low prescription isodose lines. The dose predictions for all the testing cases were completed within 0.25s