Depth-dependent critical behavior in V2H

Using X-ray diffuse scattering, we investigate the critical behavior of an order-disorder phase transition in a defective "skin-layer" of V2H. In the skin-layer, there exist walls of dislocation lines oriented normal to the surface. The density of dislocation lines within a wall decreases continuously with depth. We find that, because of this inhomogeneous distribution of defects, the transition effectively occurs at a depth-dependent local critical temperature. A depth-dependent scaling law is proposed to describe the corresponding critical ordering behavior.Comment: 5 pages, 4 figure

Depth-dependent ordering, two-length-scale phenomena and crossover behavior in a crystal featuring a skin-layer with defects

Structural defects in a crystal are responsible for the "two length-scale" behavior, in which a sharp central peak is superimposed over a broad peak in critical diffuse X-ray scattering. We have previously measured the scaling behavior of the central peak by scattering from a near-surface region of a V2H crystal, which has a first-order transition in the bulk. As the temperature is lowered toward the critical temperature, a crossover in critical behavior is seen, with the temperature range nearest to the critical point being characterized by mean field exponents. Near the transition, a small two-phase coexistence region is observed. The values of transition and crossover temperatures decay with depth. An explanation of these experimental results is here proposed by means of a theory in which edge dislocations in the near-surface region occur in walls oriented in the two directions normal to the surface. The strain caused by the dislocation lines causes the ordering in the crystal to occur as growth of roughly cylindrically shaped regions. After the regions have reached a certain size, the crossover in the critical behavior occurs, and mean field behavior prevails. At a still lower temperature, the rest of the material between the cylindrical regions orders via a weak first-order transition.Comment: 12 pages, 8 figure

X-ray scattering study of two length scales in the critical fluctuations of CuGeO3

The critical fluctuations of CuGeO$_3$ have been measured by synchrotron x-ray scattering, and two length scales are clearly observed. The ratio between the two length scales is found to be significantly different along the $a$ axis, with the $a$ axis along the surface normal direction. We believe that such a directional preference is a clear sign that surface random strains, especially those caused by dislocations, are the origin of the long length scale fluctuations.Comment: 5 pages, 4 figures, submitted to PR

The lattice of the CERN Large Hadron Collider

The lattice of the CERN Large Hadron Collider is designed with 23 regular cells per arc, each containing 6 tightly packed 14.2 m long dipoles. This allows to reach 7 TeV per beam with a dipole field of 8.4 Tesla. There are four experimental insertions, two of which are devoted to high luminosity experiments with ± 23 m of free space for the detector. The other two experimental insertions are combined with injection. The value of ß* at the interaction points is tunable from 6 m at injection to 0.5 m in collision. The energy deposition in the inner triplets is carefully reduced to sustain the nominal luminosity of 1034 cm-2s-1. Two insertions are devoted to collect the halo particles with large emittance and momentum spread surrounding the beam core: escaping rates of the protons are estimated to be less than 4·106 sec-1m-1. Finally, one insertion is used to extract the particles in the vertical direction with a minimized deflecting strength

European Multicenter Study for the Evaluation of a Dual-Layer Flow-Diverting Stent for Treatment of Wide-Neck Intracranial Aneurysms: The European Flow-Redirection Intraluminal Device Study

BACKGROUND AND PURPOSE: Endoluminal reconstruction with flow-diverting stents represents a widely accepted technique for the treatment of complex intracranial aneurysms. This European registry study analyzed the initial experience of 15 neurovascular centers with the Flow-Redirection Intraluminal Device (FRED) system. MATERIALS AND METHODS: Consecutive patients with intracranial aneurysms treated with the FRED between February 2012 and March 2015 were retrospectively reviewed. Complications and adverse events, transient and permanent morbidity, mortality, and occlusion rates were evaluated. RESULTS: During the defined study period, 579 aneurysms in 531 patients (median age, 54 years;range, 13-86 years) were treated with the FRED. Seven percent of patients were treated in the acute phase (3 days) of aneurysm rupture. The median aneurysm size was 7.6 mm (range, 1-36.6 mm), and the median neck size 4.5 mm (range, 1-30 mm). Angiographic follow-up of >3 months was available for 516 (89.1%) aneurysms. There was progressive occlusion witnessed with time, with complete occlusion in 18 (20%) aneurysms followed for up to 90 14 days, 141 (82.5%) for 180 +/- 20 days, 116 (91.3%) for 1 year +/- 24 days, and 122 (95.3%) aneurysms followed for >1 year. Transient and permanent morbidity occurred in 3.2% and 0.8% of procedures, respectively. The overall mortality rate was 1.5%. CONCLUSIONS: This retrospective study in real-world patients demonstrated the safety and efficacy of the FRED for the treatment of intracranial aneurysms. In most cases, treatment with a single FRED resulted in complete angiographic occlusion at 1 year

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing