4,922 research outputs found
Searching edges in the overlap of two plane graphs
Consider a pair of plane straight-line graphs, whose edges are colored red
and blue, respectively, and let n be the total complexity of both graphs. We
present a O(n log n)-time O(n)-space technique to preprocess such pair of
graphs, that enables efficient searches among the red-blue intersections along
edges of one of the graphs. Our technique has a number of applications to
geometric problems. This includes: (1) a solution to the batched red-blue
search problem [Dehne et al. 2006] in O(n log n) queries to the oracle; (2) an
algorithm to compute the maximum vertical distance between a pair of 3D
polyhedral terrains one of which is convex in O(n log n) time, where n is the
total complexity of both terrains; (3) an algorithm to construct the Hausdorff
Voronoi diagram of a family of point clusters in the plane in O((n+m) log^3 n)
time and O(n+m) space, where n is the total number of points in all clusters
and m is the number of crossings between all clusters; (4) an algorithm to
construct the farthest-color Voronoi diagram of the corners of n axis-aligned
rectangles in O(n log^2 n) time; (5) an algorithm to solve the stabbing circle
problem for n parallel line segments in the plane in optimal O(n log n) time.
All these results are new or improve on the best known algorithms.Comment: 22 pages, 6 figure
Seasonal predictability of the 2010 Russian heat wave
The atmospheric blocking over eastern Europe and western Russia that
prevailed during July and August of 2010 led to the development of a
devastating Russian heat wave. Therefore the question of whether the event
was predictable or not is highly important. The principal aim of this study
is to examine the predictability of this high-impact atmospheric event on a
seasonal timescale. To this end, a set of dynamical seasonal simulations have
been carried out using an atmospheric global circulation model (AGCM). The
impact of various model initializations on the predictability of this
large-scale event and its sensitivity to the initial conditions has been also
investigated. The ensemble seasonal simulations are based on a modified
version of the lagged-average forecast method using different lead-time
initializations of the model. The results indicated that only a few
individual members reproduced the main features of the blocking system 3
months ahead. Most members missed the phase space and the propagation of the
system, setting limitations in the predictability of the event
Prediction of atrial fibrillation and stroke using machine learning models in UK Biobank
Objective: Atrial fibrillation (AF) is the most common cardiac arrythmia, and it is associated with increased risk for ischemic stroke, which is underestimated, as AF can be asymptomatic. The aim of this study was to develop optimal ML models for prediction of AF in the population, and secondly for ischemic stroke in AF patients. Methods: To develop ML models for prediction of 1) AF in the general population and 2) ischemic stroke in patients with AF we constructed XGBoost, LightGBM, Random Forest, Deep Neural Network, Support Vector Machine and Lasso penalised logistic regression models using UK-Biobank's extensive real-world clinical data, questionnaires, as well as biochemical and genetic data, and their predictive performances were compared. Ranking and contribution of the different features was assessed by SHapley Additive exPlanations (SHAP) analysis. The clinical tool CHA2DS2-VASc for prediction of ischemic stroke among AF patients, was used for comparison to the best performing ML model. Findings: The best performing model for AF prediction was LightGBM, with an area-under-the-roc-curve (AUROC) of 0.729 (95% confidence intervals (CI): 0.719, 0.738). The best performing model for ischemic stroke prediction in AF patients was XGBoost with AUROC of 0.631 (95% CI: 0.604, 0.657). The improved AUROC in the XGBoost model compared to CHA2DS2-VASc was statistically significant based on DeLong's test (p-value = 2.20E-06). In addition, the SHAP analysis showed that several peripheral blood biomarkers (e.g. creatinine, glycated haemoglobin, monocytes) were associated with ischemic stroke, which are not considered by CHA2DS2-VASc. Implications: The best performing ML models presented have the potential for clinical use, but further validation in independent studies is required. Our results endorse the incorporation of some routinely measured blood biomarkers for ischemic stroke prediction in AF patients
Negative Giant Longitudinal Magnetoresistance in NiMnSb/InSb: An interface effect
We report on the electrical and magneto-transport properties of the contact
formed between polycrystalline NiMnSb thin films grown using pulsed laser
deposition (PLD) and n-type degenerate InSb (100) substrates. A negative giant
magnetoresistance (GMR) effect is observed when the external magnetic field is
parallel to the surface of the film and to the current direction. We attribute
the observed phenomenon to magnetic precipitates formed during the magnetic
film deposition and confined to a narrow layer at the interface. The effect of
these precipitates on the magnetoresistance depends on the thermal processing
of the system.Comment: 14 pages, 4 figure
Cytogenetic behavior of cryoprotectant DMSO
IVF (in vitro fertilization) is now used worldwide to overcome female or male infertility. Cryopreservation of human embryos provides the clearest opportunity to improve the clinical results obtained with IVF. Cryoprotective agents (CPA) are used to minimize freezing injuries. DMSO has been the most widely used CPA, however, high concentrations of CPAs in the vitrification solution have been shown to be detrimental to the cell. In order to determine the effect of DMSO solutions (5%, 10% and 20%) on genetic stability and/or subsequent DNA repair, we have investigated its ability to induce Sister Chromatid Exchanges (SCEs) and Proliferation Rate Index (PRI) in normal human lymphocyte cultures of peripheral blood, due to the fact that the study cannot be conducted on embryos and to the limited number of spare available embryos, the corresponding accessible experimental material was T lymphocyte. The blood samples were taken from three different healthy donors (conducting experimental procedure in triplicate). After the effect of DMSO solutions on blood according to the instructions of kit K-SIBV-500, lymphocytes are harvested and cultured with suitable technique to assess SCEs and PRI. The results show that all three DMSO concentrations cause a statistically dose depended significant increase of SCE frequency of the lymphocytes (p<0.001) and raise the need for more research regarding the safe and effective use of cryoprotectant
Illumination diagnosis for retrieval of reflections from ambient-noise seismic data in the Siilinjärvi mining site, Finland
Reflection seismic methods are becoming popular in mineral exploration, because they allow high-resolution delineation of the exploration targets, even at great depths. Seismic interferometry can be used to retrieve reflections from passive seismic data, removing the need for active seismic sources and, therefore, reducing the cost and environmental impact of exploration. The retrieval of reflections can be challenging, since passive seismic records are typically dominated by surface waves. Therefore, illumination diagnosis, a method which allows the isolation of the portions of the passive data where body-wave signals are stronger, can be a valuable step that improves the quality of the reflections retrieved from seismic interferometry and reduces the overall computational cost of the processing stage. Here, we validate the performance of the method to effectively isolate the portions of the passive data dominated by body waves and apply it on an ambient-noise seismic dataset acquired in the Siilinjärvi mining site in Finland
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