From coupled elementary units to the complexity of the glass transition

Supercooled liquids display fascinating properties upon cooling such as the emergence of dynamic length scales. Different models strongly vary with respect to the choice of the elementary subsystems (CRR) as well as their mutual coupling. Here we show via computer simulations of a glass former that both ingredients can be identified via analysis of finite-size effects within the continuous-time random walk framework. The CRR already contain complete information about thermodynamics and diffusivity whereas the coupling determines structural relaxation and the emergence of dynamic length scales

Ac transport studies in polymers by a resistor network and transfer matrix approaches: application to polyaniline

A statistical model of resistor network is proposed to describe a polymer structure and to simulate the real and imaginary components of its ac resistivity. It takes into account the polydispersiveness of the material as well as intrachain and interchain charge transport processes. By the application of a transfer matrix technique, it reproduces ac resistivity measurements carried out with polyaniline films in different doping degrees and at different temperatures. Our results indicate that interchain processes govern the resistivity behavior in the low frequency region while, for higher frequencies, intrachain mechanisms are dominant.Comment: LaTeX file, 15 pages, 5 ps figures, to appear in Phys. Rev.

Spectral and spatial shaping of laser-driven proton beams using a pulsed high-field magnet beamline

Intense laser-driven proton pulses, inherently broadband and highly divergent, pose a challenge to established beamline concepts on the path to application-adapted irradiation field formation, particularly for 3D. Here we experimentally show the successful implementation of a highly efficient (50% transmission) and tuneable dual pulsed solenoid setup to generate a homogeneous (8.5% uniformity laterally and in depth) volumetric dose distribution (cylindrical volume of 5 mm diameter and depth) at a single pulse dose of 0.7 Gy via multi-energy slice selection from the broad input spectrum. The experiments have been conducted at the Petawatt beam of the Dresden Laser Acceleration Source Draco and were aided by a predictive simulation model verified by proton transport studies. With the characterised beamline we investigated manipulation and matching of lateral and depth dose profiles to various desired applications and targets. Using a specifically adapted dose profile, we successfully performed first proof-of-concept laser-driven proton irradiation studies of volumetric in-vivo normal tissue (zebrafish embryos) and in-vitro tumour tissue (SAS spheroids) samples.Comment: Submitted to Scientific Report

Is Aid for Trade Effective? A Quantile Regression Approach

This paper investigates whether Aid for Trade (AfT) improves export performance, i.e. does AfT lead to greater exports? Using panel data and panel quantile regression, our results suggest that overall AfT disbursements promote the export of goods and services mainly for the .50 and .75 quantiles. Our results also show that for some types of AfT this effect essentially vanishes at the lower tail of the conditional distribution of exports. Hence, countries that export more in volume are those benefiting most from AfT. We also investigate which types of AfT are effective. In particular, we find that aid used to build production capacity is effective. This type of aid is associated with higher exports for almost all quantiles, with the effect increasing at the upper tail of the conditional distribution. Aid used to build infrastructure is also found to affect exports at the upper tail of the distribution. In contrast, aid for trade policy and aid disbursed for general budget support (an untargeted type of aid) are not associated with greater export levels. This finding holds true irrespective of the quantile

Assessment of cardiac ischaemia and viability: role of cardiovascular magnetic resonance

Over the past years, cardiovascular magnetic resonance (CMR) has proven its efficacy in large clinical trials, and consequently, the assessment of function, viability, and ischaemia by CMR is now an integrated part of the diagnostic armamentarium in cardiology. By combining these CMR applications, coronary artery disease (CAD) can be detected in its early stages and this allows for interventions with the goal to reduce complications of CAD such as infarcts and subsequently chronic heart failure (CHF). As the CMR examinations are robust and reproducible and do not expose patients to radiation, they are ideally suited for repetitive studies without harm to the patients. Since CAD is a chronic disease, the option to monitor CAD regularly by CMR over many decades is highly valuable. Cardiovascular magnetic resonance also progressed recently in the setting of acute coronary syndromes. In this situation, CMR allows for important differential diagnoses. Cardiovascular magnetic resonance also delineates precisely the different tissue components in acute myocardial infarction such as necrosis, microvascular obstruction (MVO), haemorrhage, and oedema, i.e. area at risk. With these features, CMR might also become the preferred tool to investigate novel treatment strategies in clinical research. Finally, in CHF patients, the versatility of CMR to assess function, flow, perfusion, and viability and to characterize tissue is helpful to narrow the differential diagnosis and to monitor treatment

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level