Clinical and pathological factors and outcome of central nervous system metastasis in breast cancer.

Background: In Switzerland, approximately 6000 new breast cancer cases and 1300 deaths are reported annually. Brain metastasis from breast cancer (BMBC) has a major effect on prognosis. This study aimed to identify prognostic factors for overall survival (OS) in a cohort of Swiss patients with BMBC. This study evaluated the prognosis on older BMBC, which has not been completely addressed in the literature. Methods: We performed a retrospective chart review analysis with the primary endpoint of OS after a diagnosis of BMBC. The study population was divided into 2 groups based on an OS cut-off value of 12 months after diagnosis. Univariate and multivariate analyses of several risk factors, including age, were performed. To evaluate differences in OS according to age, we performed a secondary analysis to examine the prognostic value of clinical symptoms, metastatic pattern, and lymph node involvement in an older (≥65 years) vs. younger (<65 years) cohort. Results: From 1989 to 2019, 55 patients were identified as having BMBC, among whom 47 patients were confirmed to be dead. The median patient age was 58 years (range 25-83 years). Comorbidities were present in 45 (81.8%) patients. The median survival in the OS <12 and OS ≥12 months groups was 4.3 and 30.7 months, respectively (p<0.001). Multivariate analysis revealed no significant differences in terms of comorbidities, medication use, M-stage, and symptomatology between the 2 groups. Additionally, there was no significant difference in OS in the 2 subgroups of patients aged <65 and ≥65 years. Discussion: We concluded that age should not be a decisive factor in therapy planning for advanced breast cancer patients with BMBC.

Automated and data-driven plate computation for presurgical cleft lip and palate treatment.

PURPOSE: Presurgical orthopedic plates are widely used for the treatment of cleft lip and palate, which is the most common craniofacial birth defect. For the traditional plate fabrication, an impression is taken under airway-endangering conditions, which recent digital alternatives overcome via intraoral scanners. However, these alternatives demand proficiency in 3D modeling software in addition to the generally required clinical knowledge of plate design. METHODS: We address these limitations with a data-driven and fully automated digital pipeline, endowed with a graphical user interface. The pipeline adopts a deep learning model to landmark raw intraoral scans of arbitrary mesh topology and orientation, which guides the nonrigid surface registration subsequently employed to segment the scans. The plates that are individually fit to these segmented scans are 3D-printable and offer optional customization. RESULTS: With the distance to the alveolar ridges closely centered around the targeted 0.1 mm, our pipeline computes tightly fitting plates in less than 3 min. The plates were approved in 12 out of 12 cases by two cleft care professionals in a printed-model-based evaluation. Moreover, since the pipeline was implemented in clinical routine in two hospitals, 19 patients have been undergoing treatment utilizing our automated designs. CONCLUSION: The results demonstrate that our automated pipeline meets the high precision requirements of the medical setting employed in cleft lip and palate care while substantially reducing the design time and required clinical expertise, which could facilitate access to this presurgical treatment, especially in low-income countries.

News Globe: Visualization of Geolocalized News Articles.

The number of online news articles available nowadays is rapidly increasing. When exploring articles on online news portals, navigation is mostly limited to the most recent ones. The spatial context and the history of topics are not immediately accessible. To support readers in the exploration or research of articles in large datasets, we developed an interactive 3D globe visualization. We worked with datasets from multiple online news portals containing up to 45,000 articles. Using agglomerative hierarchical clustering, we represent the referenced locations of news articles on a globe with different levels of detail. We employ two interaction schemes for navigating the viewpoint on the visualization, including support for hand-held devices and desktop PCs, and provide search functionality and interactive filtering. Based on this framework, we explore additional modules for jointly exploring the spatial and temporal domain of the dataset and incorporating live news into the visualization.

Fluctuations of the critical Casimir force.

The critical Casimir force (CCF) arises from confining fluctuations in a critical fluid and thus it is a fluctuating quantity itself. While the mean CCF is universal, its (static) variance has previously been found to depend on the microscopic details of the system which effectively set a large-momentum cutoff in the underlying field theory, rendering it potentially large. This raises the question how the properties of the force variance are reflected in experimentally observable quantities, such as the thickness of a wetting film or the position of a suspended colloidal particle. Here, based on a rigorous definition of the instantaneous force, we analyze static and dynamic correlations of the CCF for a conserved fluid in film geometry for various boundary conditions within the Gaussian approximation. We find that the dynamic correlation function of the CCF is independent of the momentum cutoff and decays algebraically in time. Within the Gaussian approximation, the associated exponent depends only on the dynamic universality class but not on the boundary conditions. We furthermore consider a fluid film, the thickness of which can fluctuate under the influence of the time-dependent CCF. The latter gives rise to an effective non-Markovian noise in the equation of motion of the film boundary and induces a distinct contribution to the position variance. Within the approximations used here, at short times, this contribution grows algebraically in time whereas, at long times, it saturates and contributes to the steady-state variance of the film thickness.

MineTime Insight: Visualizing Meeting Habits to Promote Informed Scheduling Decisions.

Corporate meetings are a crucial part of business activities. While numerous academic papers investigated how to make the scheduling process of meetings faster or even automatic, little work has been done yet to facilitate the retrospective reasoning about how time is spent on meetings. Traditional calendar applications do not allow users to extract actionable statistics although it has been shown that reflection-oriented design can increase the users' understanding of their habits and can thereby encourage a shift towards better practices. In this paper, we present MineTime Insight, a tool made of multiple coordinated views for the exploration of personal calendar data, with the overarching goal of improving short and long-term scheduling decisions. Despite being focused on the working environment, our work builds upon recent results in the field of Personal Visual Analytics, as it targets users not necessarily expert in visualization and data analysis. We demonstrate the potential of MineTime Insight, when applied to the agenda of an executive manager. Finally, we discuss the results of an informal user study and a field study. Our results suggest that our visual representations are perceived as easy to understand and helpful towards a change in the scheduling habits.

A Fluid Flow Data Set for Machine Learning and its Application to Neural Flow Map Interpolation.

In recent years, deep learning has opened countless research opportunities across many different disciplines. At present, visualization is mainly applied to explore and explain neural networks. Its counterpart-the application of deep learning to visualization problems-requires us to share data more openly in order to enable more scientists to engage in data-driven research. In this paper, we construct a large fluid flow data set and apply it to a deep learning problem in scientific visualization. Parameterized by the Reynolds number, the data set contains a wide spectrum of laminar and turbulent fluid flow regimes. The full data set was simulated on a high-performance compute cluster and contains 8000 time-dependent 2D vector fields, accumulating to more than 16 TB in size. Using our public fluid data set, we trained deep convolutional neural networks in order to set a benchmark for an improved post-hoc Lagrangian fluid flow analysis. In in-situ settings, flow maps are exported and interpolated in order to assess the transport characteristics of time-dependent fluids. Using deep learning, we improve the accuracy of flow map interpolations, allowing a more precise flow analysis at a reduced memory IO footprint.

Fourier Opacity Optimization for Scalable Exploration.

Over the past decades, scientific visualization became a fundamental aspect of modern scientific data analysis. Across all data-intensive research fields, ranging from structural biology to cosmology, data sizes increase rapidly. Dealing with the growing large-scale data is one of the top research challenges of this century. For the visual exploratory data analysis, interactivity, a view-dependent visibility optimization and frame coherence are indispensable. In this work, we extend the recent decoupled opacity optimization framework to enable a navigation without occlusion of important features through large geometric data. By expressing the accumulation of importance and optical depth in Fourier basis, the computation, evaluation and rendering of optimized transparent geometry become not only order-independent, but also operate within a fixed memory bound. We study the quality of our Fourier approximation in terms of accuracy, memory requirements and efficiency for both the opacity computation, as well as the order-independent compositing. We apply the method to different point, line and surface data sets originating from various research fields, including meteorology, health science, astrophysics and organic chemistry.

Accelerated Monte Carlo Rendering of Finite-Time Lyapunov Exponents.

Time-dependent fluid flows often contain numerous hyperbolic Lagrangian coherent structures, which act as transport barriers that guide the advection. The finite-time Lyapunov exponent is a commonly-used approximation to locate these repelling or attracting structures. Especially on large numerical simulations, the FTLE ridges can become arbitrarily sharp and very complex. Thus, the discrete sampling onto a grid for a subsequent direct volume rendering is likely to miss sharp ridges in the visualization. For this reason, an unbiased Monte Carlo-based rendering approach was recently proposed that treats the FTLE field as participating medium with single scattering. This method constructs a ground truth rendering without discretization, but it is prohibitively slow with render times in the order of days or weeks for a single image. In this paper, we accelerate the rendering process significantly, which allows us to compute video sequence of high-resolution FTLE animations in a much more reasonable time frame. For this, we follow two orthogonal approaches to improve on the rendering process: the volumetric light path integration in gradient domain and an acceleration of the transmittance estimation. We analyze the convergence and performance of the proposed method and demonstrate the approach by rendering complex FTLE fields in several 3D vector fields.

Dynamics of the critical Casimir force for a conserved order parameter after a critical quench.

Fluctuation-induced forces occur generically when long-range correlations (e.g., in fluids) are confined by external bodies. In classical systems, such correlations require specific conditions, e.g., a medium close to a critical point. On the other hand, long-range correlations appear more commonly in certain nonequilibrium systems with conservation laws. Consequently, a variety of nonequilibrium fluctuation phenomena, including fluctuation-induced forces, have been discovered and explored recently. Here we address a long-standing problem of nonequilibrium critical Casimir forces emerging after a quench to the critical point in a confined fluid with order-parameter-conserving dynamics and non-symmetry-breaking boundary conditions. The interplay of inherent (critical) fluctuations and dynamical nonlocal effects (due to density conservation) gives rise to striking features, including correlation functions and forces exhibiting oscillatory time dependences. Complex transient regimes arise, depending on initial conditions and the geometry of the confinement. Our findings pave the way for exploring a wealth of nonequilibrium processes in critical fluids (e.g., fluctuation-mediated self-assembly or aggregation). In certain regimes, our results are applicable to active matter.

Ensemble dependence of critical Casimir forces in films with Dirichlet boundary conditions.

In a recent study [Phys. Rev. E 94, 022103 (2016)2470-004510.1103/PhysRevE.94.022103] it has been shown that, for a fluid film subject to critical adsorption, the resulting critical Casimir force (CCF) may significantly depend on the thermodynamic ensemble. Here we extend that study by considering fluid films within the so-called ordinary surface universality class. We focus on mean-field theory, within which the order parameter (OP) profile satisfies Dirichlet boundary conditions and produces a nontrivial CCF in the presence of external bulk fields or, respectively, a nonzero total order parameter within the film. Additionally, we study the influence of fluctuations by means of Monte Carlo simulations of the three-dimensional Ising model. We show that, in the canonical ensemble, i.e., when fixing the so-called total mass within the film, the CCF is repulsive for large absolute values of the total OP, instead of attractive as in the grand canonical ensemble. Based on the Landau-Ginzburg free energy, we furthermore obtain analytic expressions for the order parameter profiles and analyze the relation between the total mass in the film and the external bulk field.

Extracorporeal Irradiation and Reimplantation of Tumor-bearing Bone Segments Following Diaphyseal Sarcoma Resection at the Tibia.

BACKGROUND/AIM: Reconstruction of diaphyseal tibial sarcomas with extracorporeal irradiated autograft is a rarely applied technique and is analyzed in this study. PATIENTS AND METHODS: Eight patients with malignant sarcomas received local treatment by means of a wide resection and reimplantation of an extracorporeally-irradiated autograft. The graft was combined with an ipsilateral vascularized fibula when a full-thickness segment of the tibia had to be resected and no cortex could be preserved (n=5). Oncological and functional results were recorded. RESULTS: All patients had clear margins after resection, and with no local recurrence 72 months after treatment. Full weight-bearing was allowed at the time of radiological consolidation of the irradiated grafts (after a median of five months). The functional results were good and excellent in 7 of 8 patients, respectively. CONCLUSION: Extracorporeal irradiation grafting is a suitable method for the treatment of localised and resectable tibial sarcomas.

Reliability of a three-dimensional facial camera for dental and medical applications: A pilot study.

STATEMENT OF PROBLEM: Three-dimensional visualization for pretreatment diagnostics and treatment planning is necessary for surgical and prosthetic rehabilitations. The reliability of a novel 3D facial camera is unclear. PURPOSE: The purpose of this clinical study was to evaluate the reliability of a novel medical facial camera system in capturing the 3D geometry of the face in a single exposure. MATERIAL AND METHODS: Twelve edentulous participants (7 women and 5 men; mean age: 74.6 years) were included, and digital images for facial reconstruction were captured using a custom-made static capturing system (Medusa Static; Disney Research Zurich). Eight extraoral soft-tissue facial landmarks were identified, which included the right outer canthus (OCR), left outer canthus (OCL), right cheilion (CmR), left cheilion (CmL), pronasale nostril tip, subnasale, philtrum, and gnathion (GN). Interlandmark distances of OCR-OCL, OCR-CmR, OCL-CmL, OCR-GN, OCL-GN, CmR-CmL, pronasale nostril tip-GN, and subnasale-GN were measured clinically and then on the 3D digital reconstructions. The absolute differences between the digital and clinical measurements were recorded. The intraclass correlation coefficient was applied to evaluate the reliability of digital measurement and interexaminer reliability. RESULTS: The mean ±standard deviation difference between the clinical and digital measurements was 1.95 ±0.33 mm. Intraclass correlation coefficients computed for the 2 examiners against clinical measurements were all above 0.5. The interexaminer reliability coefficient of digital measurement was above 0.909. CONCLUSIONS: The 3D facial geometry obtained from the novel medical facial camera system was found to be reliable and clinically acceptable. Inconsistencies in measurements for a few specific facial landmarks may arise, but these can be avoided by thorough examiner calibration before undertaking the digital measurements.

Degradation of Cadmium Yellow Paint: New Evidence from Photoluminescence Studies of Trap States in Picasso's Femme ( Époque des "Demoiselles d'Avignon").

Paints based on cadmium sulfide (CdS) were popular among artists beginning in the mid-19th century. Some paint formulations are prone to degrade, discoloring and disfiguring paintings where they have been used. Pablo Picasso's Femme (Époque des "Demoiselles d'Avignon") (1907) includes two commercial formulations of CdS: one is visibly degraded and now appears brownish yellow, while the other appears relatively intact and is vibrant yellow. This observation inspired the study reported here of the photoluminescence emission from trap states of the two CdS paints, complemented by data from multispectral imaging, X-ray fluorescence spectroscopy, micro-FTIR, and SEM-EDS. The two paints exhibit trap state emissions that differ in terms of spectrum, intensity, and decay kinetics. In the now-brownish yellow paint, trap state emission is highly favored with respect to near band edge optical recombination. This observation suggests a higher density of surface defects in the now-brownish yellow paint that promotes the surface reactivity of CdS particles and their subsequent paint degradation. CdS is a semiconductor, and surface defects in semiconductors can trap free charge carriers; this interaction becomes stronger at reduced particle size or, equivalently, with increased surface to volume ratio. Here, we speculate that the strong trap state emission in the now-brownish cadmium yellow paint is linked to the presence of CdS particles with a nanocrystalline phase, possibly resulting from a low degree of calcination during pigment synthesis. Taken together, the results presented here demonstrate how photoluminescence studies can probe surface defects in CdS paints and lead to an improved understanding of their complex degradation mechanisms.

Comparison of user satisfaction and image quality of fixed and mobile camera systems for 3-dimensional image capture of edentulous patients: A pilot clinical study.

STATEMENT OF PROBLEM: An evaluation of user satisfaction and image quality of a novel handheld purpose-built mobile camera system for 3-dimensional (3D) facial acquisition is lacking. PURPOSE: The purpose of this pilot clinical study was to assess and compare the effectiveness between a handheld mobile camera system designed for facial acquisition and a fixed static camera arrangement by comparing the time effectiveness and the operator and participant preference for the 2 techniques of image capture. MATERIAL AND METHODS: Completely edentulous participants (n=12: women=7, men=5; mean age: 74.6 years) were included in this pilot study. Images were captured with and without the prostheses in situ while maintaining "serious" and "full-smile" facial expressions. Images were captured using a mobile and a static system. The working times for the participant installation and image captures were recorded. Operator and participant perceptions of the entire experience were recorded by using visual analog scale questionnaires. Nonparametric tests were used for statistical analyses (α=.05). RESULTS: The installation time was significantly shorter for the mobile system (static=24 ±13 seconds; mobile=10 ±10 seconds), but the differences in the image capture times were not statistically significant (static: 29 ±5 seconds; mobile: 40 ±18 seconds). Operator preference was in favor of the mobile system with regard to working time (P=.002), difficulty in using (installation: P=.002; handling: P=.045), and camera weight (P=.002); however, they preferred the static arrangement for image quality (P=.003) and comfort (P=.013). The participants rated the entire photographic experience favorably, and 10 of 12 participants preferred the static camera over the mobile one. CONCLUSIONS: Despite the complexity of the installation, the static system was evaluated better for image quality; the mobile system was easier in installation and handling. The operators preferred the mobile system, and the participants preferred the static system.

Management of Cerebral Aneurysm Descriptors based on an Automatic Ostium Extraction.

We present a framework to manage cerebral aneurysms. Rupture risk evaluation is based on manually extracted descriptors, which is time-consuming. Thus, we provide an automatic solution by considering several questions: How can expert knowledge be integrated? How should meta data be defined? Which interaction techniques are needed for data exploration.

Shear-density coupling for a compressible single-component yield-stress fluid.

Flow behavior of a single-component yield stress fluid is addressed on the hydrodynamic level. A basic ingredient of the model is a coupling between fluctuations of density and velocity gradient via a Herschel-Bulkley-type constitutive model. Focusing on the limit of low shear rates and high densities, the model approximates well-but is not limited to-gently sheared hard sphere colloidal glasses, where solvent effects are negligible. A detailed analysis of the linearized hydrodynamic equations for fluctuations and the resulting cubic dispersion relation reveals the existence of a range of densities and shear rates with growing flow heterogeneity. In this regime, after an initial transient, the velocity and density fields monotonically reach a spatially inhomogeneous stationary profile, where regions of high shear rate and low density coexist with regions of low shear rate and high density. The steady state is thus maintained by a competition between shear-induced enhancement of density inhomogeneities and relaxation via overdamped sound waves. An analysis of the mechanical equilibrium condition provides a criterion for the existence of steady state solutions. The dynamical evolution of the system is discussed in detail for various boundary conditions, imposing either a constant velocity, shear rate, or stress at the walls.

Visualizing Nonlinear Narratives with Story Curves.

In this paper, we present story curves, a visualization technique for exploring and communicating nonlinear narratives in movies. A nonlinear narrative is a storytelling device that portrays events of a story out of chronological order, e.g., in reverse order or going back and forth between past and future events. Many acclaimed movies employ unique narrative patterns which in turn have inspired other movies and contributed to the broader analysis of narrative patterns in movies. However, understanding and communicating nonlinear narratives is a difficult task due to complex temporal disruptions in the order of events as well as no explicit records specifying the actual temporal order of the underlying story. Story curves visualize the nonlinear narrative of a movie by showing the order in which events are told in the movie and comparing them to their actual chronological order, resulting in possibly meandering visual patterns in the curve. We also present Story Explorer, an interactive tool that visualizes a story curve together with complementary information such as characters and settings. Story Explorer further provides a script curation interface that allows users to specify the chronological order of events in movies. We used Story Explorer to analyze 10 popular nonlinear movies and describe the spectrum of narrative patterns that we discovered, including some novel patterns not previously described in the literature. Feedback from experts highlights potential use cases in screenplay writing and analysis, education and film production. A controlled user study shows that users with no expertise are able to understand visual patterns of nonlinear narratives using story curves.

Statistical field theory with constraints: Application to critical Casimir forces in the canonical ensemble.

The effect of imposing a constraint on a fluctuating scalar order parameter field in a system of finite volume is studied within statistical field theory. The canonical ensemble, corresponding to a fixed total integrated order parameter (e.g., the total number of particles), is obtained as a special case of the theory. A perturbative expansion is developed which allows one to systematically determine the constraint-induced finite-volume corrections to the free energy and to correlation functions. In particular, we focus on the Landau-Ginzburg model in a film geometry (i.e., in a rectangular parallelepiped with a small aspect ratio) with periodic, Dirichlet, or Neumann boundary conditions in the transverse direction and periodic boundary conditions in the remaining, lateral directions. Within the expansion in terms of ε=4-d, where d is the spatial dimension of the bulk, the finite-size contribution to the free energy of the confined system and the associated critical Casimir force are calculated to leading order in ε and are compared to the corresponding expressions for an unconstrained (grand canonical) system. The constraint restricts the fluctuations within the system and it accordingly modifies the residual finite-size free energy. The resulting critical Casimir force is shown to depend on whether it is defined by assuming a fixed transverse area or a fixed total volume. In the former case, the constraint is typically found to significantly enhance the attractive character of the force as compared to the grand canonical case. In contrast to the grand canonical Casimir force, which, for supercritical temperatures, vanishes in the limit of thick films, in the canonical case with fixed transverse area the critical Casimir force attains for thick films a negative value for all boundary conditions studied here. Typically, the dependence of the critical Casimir force both on the temperaturelike and on the fieldlike scaling variables is different in the two ensembles.

A Virtual Try-On System for Prescription Eyeglasses.

Corrective lenses introduce distortion caused by the refraction effect, which changes the wear's appearance. To give users a more realistic experience, a virtual try-on system for prescription eyeglasses modifies an input video and virtually inserts prescription eyeglasses, producing an output similar to a virtual mirror. The proposed system generates a 3D representation of the corrective lenses mounted into the eyeglasses frame and modifies the video sequence to virtually insert the eyeglasses through image-based rendering. Unlike existing virtual try-on systems, this approach simulates the refraction effects due to the corrective lens and takes into account reflections and shading.

Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location.