Human case of swine influenza A (H1N1), Aragon, Spain, November 2008

A human case of swine influenza A (H1N1) in a 50-year-old woman from a village near Teruel (Aragon, in the north-east of Spain), with a population of about 200 inhabitants, has been reported in November 2008.S

PhaseGAN a deep learning phase retrieval approach for unpaired datasets

Phase retrieval approaches based on deep learning DL provide a framework to obtain phase information from an intensity hologram or diffraction pattern in a robust manner and in real time. However, current DL architectures applied to the phase problem rely on i paired datasets, i. e., they are only applicable when a satisfactory solution of the phase problem has been found, and ii the fact that most of them ignore the physics of the imaging process. Here, we present PhaseGAN, a new DL approach based on Generative Adversarial Networks, which allows the use of unpaired datasets and includes the physics of image formation. The performance of our approach is enhanced by including the image formation physics and a novel Fourier loss function, providing phase reconstructions when conventional phase retrieval algorithms fail, such as ultra fast experiments. Thus, PhaseGAN offers the opportunity to address the phase problem in real time when no phase reconstructions but good simulations or data from other experiments are availabl

Direct test of time-reversal symmetry in the entangled neutral kaon system at a ϕ\phi-factory

We present a novel method to perform a direct T (time reversal) symmetry test in the neutral kaon system, independent of any CP and/or CPT symmetry tests. This is based on the comparison of suitable transition probabilities, where the required interchange of in out states for a given process is obtained exploiting the Einstein-Podolsky-Rosen correlations of neutral kaon pairs produced at a $\phi$-factory. In the time distribution between the two decays, we compare a reference transition like the one defined by the time ordered decays $(\ell^-,\pi\pi)$ with the T -conjugated one defined by $(3\pi^0, \ell^+)$. With the use of this and other T conjugated comparisons, the KLOE-2 experiment at DA$\Phi$NE could make a significant test

Hard X-ray stereographic microscopy for single-shot differential phase imaging

The characterisation of fast phenomena at the microscopic scale is required for the understanding of catastrophic responses of materials to loads and shocks, the processing of materials by optical or mechanical means, the processes involved in many key technologies such as additive manufacturing and microfluidics, and the mixing of fuels in combustion. Such processes are usually stochastic in nature and occur within the opaque interior volumes of materials or samples, with complex dynamics that evolve in all three dimensions at speeds exceeding many meters per second. There is therefore a need for the ability to record three-dimensional X-ray movies of irreversible processes with resolutions of micrometers and frame rates of microseconds. Here we demonstrate a method to achieve this by recording a stereo phase-contrast image pair in a single exposure. The two images are combined computationally to reconstruct a 3D model of the object. The method is extendable to more than two simultaneous views. When combined with megahertz pulse trains of X-ray free-electron lasers (XFELs) it will be possible to create movies able to resolve 3D trajectories with velocities of kilometers per second

Online dynamic flat-field correction for MHz Microscopy data at European XFEL

The X-ray microscopy technique at the European X-ray free-electron laser (EuXFEL), operating at a MHz repetition rate, provides superior contrast and spatial-temporal resolution compared to typical microscopy techniques at other X-ray sources. In both online visualization and offline data analysis for microscopy experiments, baseline normalization is essential for further processing steps such as phase retrieval and modal decomposition. In addition, access to normalized projections during data acquisition can play an important role in decision-making and improve the quality of the data. However, the stochastic nature of XFEL sources hinders the use of existing flat-flied normalization methods during MHz X-ray microscopy experiments. Here, we present an online dynamic flat-field correction method based on principal component analysis of dynamically evolving flat-field images. The method is used for the normalization of individual X-ray projections and has been implemented as an online analysis tool at the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument of EuXFEL.Comment: 14 pages, 7 figure

Kidney cancer mortality in Spain: geographic patterns and possible hypotheses

<p>Abstract</p> <p>Background</p> <p>Since the second half of the 1990s, kidney cancer mortality has tended to stabilize and decline in many European countries, due to the decrease in the prevalence of smokers. Nevertheless, incidence of kidney cancer is rising across the sexes in some of these countries, a trend which may possibly reflect the fact that improvements in diagnostic techniques are being outweighed by the increased prevalence of some of this tumor's risk factors. This study sought to: examine the geographic pattern of kidney cancer mortality in Spain; suggest possible hypotheses that would help explain these patterns; and enhance existing knowledge about the large proportion of kidney tumors whose cause remains unknown.</p> <p>Methods</p> <p>Smoothed municipal relative risks (RRs) for kidney cancer mortality were calculated in men and women, using the conditional autoregressive model proposed by Besag, York and Molliè. Maps were plotted depicting smoothed relative risk estimates, and the distribution of the posterior probability of RR>1 by sex.</p> <p>Results</p> <p>Municipal maps displayed a marked geographic pattern, with excess mortality in both sexes, mainly in towns along the Bay of Biscay, including areas of Asturias, the Basque Country and, to a lesser extent, Cantabria. Among women, the geographic pattern was strikingly singular, not in evidence for any other tumors, and marked by excess risk in towns situated in the Salamanca area and Extremaduran Autonomous Region. This difference would lead one to postulate the existence of different exposures of environmental origin in the various regions.</p> <p>Conclusion</p> <p>The reasons for this pattern of distribution are not clear, and it would thus be of interest if the effect of industrial emissions on this disease could be studied. The excess mortality observed among women in towns situated in areas with a high degree of natural radiation could reflect the influence of exposures which derive from the geologic composition of the terrain and then become manifest through the agency of drinking water.</p

Ultrasound cavitation and exfoliation dynamics of 2D materials re-vealed in operando by X-ray free electron laser megahertz imaging

Ultrasonic liquid phase exfoliation is a promising method for the production of two-dimensional (2D) layered materials. A large number of studies have been made in investigating the underlying ultrasound exfoliation mechanisms. However, due to the experimental challenges for capturing the highly transient and dynamic phenomena in real-time at sub-microsecond time and micrometer length scales simultaneously, most theories reported to date still remain elusive. Here, using the ultra-short X-ray Free Electron Laser pulses (~25ps) with a unique pulse train structure, we applied MHz X-ray Microscopy and machine-learning technique to reveal unambiguously the full cycles of the ultrasound cavitation and graphite layer exfoliation dynamics with sub-microsecond and micrometer resolution. Cyclic fatigue shock wave impacts produced by ultrasound cloud implosion were identified as the dominant mechanism to deflect and exfoliate graphite layers mechanically. For the graphite flakes, exfoliation rate as high as ~5 angstroms per shock wave impact was observed. For the HOPG graphite, the highest exfoliation rate was ~0.15 angstroms per impact. These new findings are scientifically and technologically important for developing industrial upscaling strategies for ultrasonic exfoliation of 2D materials

Measurement of ISR-FSR interference in the processes e+ e- --> mu+ mu- gamma and e+ e- --> pi+ pi- gamma

Charge asymmetry in processes e+ e- --> mu+ mu- gamma and e+ e- --> pi+ pi- gamma is measured using 232 fb-1 of data collected with the BABAR detector at center-of-mass energies near 10.58 GeV. An observable is introduced and shown to be very robust against detector asymmetries while keeping a large sensitivity to the physical charge asymmetry that results from the interference between initial and final state radiation. The asymmetry is determined as afunction of the invariant mass of the final-state tracks from production threshold to a few GeV/c2. It is compared to the expectation from QED for e+ e- --> mu+ mu- gamma and from theoretical models for e+ e- --> pi+ pi- gamma. A clear interference pattern is observed in e+ e- --> pi+ pi- gamma, particularly in the vicinity of the f_2(1270) resonance. The inferred rate of lowest order FSR production is consistent with the QED expectation for e+ e- --> mu+ mu- gamma, and is negligibly small for e+ e- --> pi+ pi- gamma.Comment: 32 pages,29 figures, to be submitted to Phys. Rev.

Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis

Background &amp; Aims: In individuals with compensated advanced chronic liver disease (cACLD), the severity of portal hypertension (PH) determines the risk of decompensation. Invasive measurement of the hepatic venous pressure gradient (HVPG) is the diagnostic gold standard for PH. We evaluated the utility of machine learning models (MLMs) based on standard laboratory parameters to predict the severity of PH in individuals with cACLD. Methods: A detailed laboratory workup of individuals with cACLD recruited from the Vienna cohort (NCT03267615) was utilised to predict clinically significant portal hypertension (CSPH, i.e., HVPG ≥10 mmHg) and severe PH (i.e., HVPG ≥16 mmHg). The MLMs were then evaluated in individual external datasets and optimised in the merged cohort. Results: Among 1,232 participants with cACLD, the prevalence of CSPH/severe PH was similar in the Vienna (n = 163, 67.4%/35.0%) and validation (n = 1,069, 70.3%/34.7%) cohorts. The MLMs were based on 3 (3P: platelet count, bilirubin, international normalised ratio) or 5 (5P: +cholinesterase, +gamma-glutamyl transferase, +activated partial thromboplastin time replacing international normalised ratio) laboratory parameters. The MLMs performed robustly in the Vienna cohort. 5P-MLM had the best AUCs for CSPH (0.813) and severe PH (0.887) and compared favourably to liver stiffness measurement (AUC: 0.808). Their performance in external validation datasets was heterogeneous (AUCs: 0.589-0.887). Training on the merged cohort optimised model performance for CSPH (AUCs for 3P and 5P: 0.775 and 0.789, respectively) and severe PH (0.737 and 0.828, respectively). Conclusions: Internally trained MLMs reliably predicted PH severity in the Vienna cACLD cohort but exhibited heterogeneous results on external validation. The proposed 3P/5P online tool can reliably identify individuals with CSPH or severe PH, who are thus at risk of hepatic decompensation. Impact and implications: We used machine learning models based on widely available laboratory parameters to develop a non-invasive model to predict the severity of portal hypertension in individuals with compensated cirrhosis, who currently require invasive measurement of hepatic venous pressure gradient. We validated our findings in a large multicentre cohort of individuals with advanced chronic liver disease (cACLD) of any cause. Finally, we provide a readily available online calculator, based on 3 (platelet count, bilirubin, international normalised ratio) or 5 (platelet count, bilirubin, activated partial thromboplastin time, gamma-glutamyltransferase, choline-esterase) widely available laboratory parameters, that clinicians can use to predict the likelihood of their patients with cACLD having clinically significant or severe portal hypertension