Theoretical Study of Molecular Electronic and Rotational Coherences by High-Harmonic Generation

The detection of electron motion and electronic wavepacket dynamics is one of the core goals of attosecond science. Recently, choosing the nitric oxide (NO) molecule as an example, we have introduced and demonstrated a new experimental approach to measure coupled valence electronic and rotational wavepackets using high-harmonic generation (HHG) spectroscopy [Kraus et al., Phys. Rev. Lett. 111, 243005 (2013)]. A short outline of the theory to describe the combination of the pump and HHG probe process was published together with an extensive discussion of experimental results [Baykusheva et al., Faraday Discuss 171, 113 (2014)]. The comparison of theory and experiment showed good agreement on a quantitative level. Here, we present the generalized theory in detail, which is based on a generalized density matrix approach that describes the pump process and the subsequent probing of the wavepackets by a semiclassical quantitative rescattering approach. An in-depth analysis of the different Raman scattering contributions to the creation of the coupled rotational and electronic spin-orbit wavepackets is made. We present results for parallel and perpendicular linear polarizations of the pump and probe laser pulses. Furthermore, an analysis of the combined rotational-electronic density matrix in terms of irreducible components is presented, that facilitates interpretation of the results.Comment: 14 figure

Active split-ring metamaterial slabs for magnetic resonance imaging

In this work, it is analyzed the ability of split-ring metamaterial slabs with zero/high permeability to reject/confine the radiofrequency magnetic field in magnetic resonance imaging systems. Using an homogenization procedure, split-ring slabs have been designed and fabricated to work in a 1.5T system. Active elements consisting of pairs of crossed diodes are inserted in the split-rings. With these elements, the permeability of the slabs can be automatically switched between a unity value when interacting with the strong excitation field of the transmitting body coil, and zero or high values when interacting with the weak field produced by protons in tissue. Experiments are shown for different configurations where these slabs can help to locally increase the signal-to-noise-ratio.Comment: 6 pages, 4 figure

Undersampling reconstruction in parallel and single coil imaging with COMPaS -- COnvolutional Magnetic Resonance Image Prior with Sparsity regularization

Purpose: To propose COMPaS, a learning-free Convolutional Network, that combines Deep Image Prior (DIP) with transform-domain sparsity constraints to reconstruct undersampled Magnetic Resonance Imaging (MRI) data without previous training of the network. Methods: COMPaS uses a U-Net as DIP for undersampledMRdata in the image domain. Reconstruction is constrained by data fidelity to k-space measurements and transform-domain sparsity, such as Total Variation (TV) or Wavelet transform sparsity. Two-dimensional MRI data from the public FastMRI dataset with Cartesian undersampling in phase-encoding direction were reconstructed for different acceleration rates (R) from R = 2 to R = 8 for single coil and multicoil data. Performance of the proposed architecture was compared to Parallel Imaging with Compressed Sensing (PICS). Results: COMPaS outperforms standard PICS algorithms by reducing ghosting artifacts and yielding higher quantitative reconstruction quality metrics in multicoil imaging settings and especially in single coil k-space reconstruction. Furthermore, COMPaS can reconstruct multicoil data without explicit knowledge of coil sensitivity profiles. Conclusion: COMPaS utilizes a training-free convolutional network as a DIP in MRI reconstruction and transforms it with transform-domain sparsity regularization. It is a competitive algorithm for parallel imaging and a novel tool for accelerating single coil MRI.Comment: 13 pages, 8 figures, 2 table

Comparing reverse complementary genomic words based on their distance distributions and frequencies

In this work we study reverse complementary genomic word pairs in the human DNA, by comparing both the distance distribution and the frequency of a word to those of its reverse complement. Several measures of dissimilarity between distance distributions are considered, and it is found that the peak dissimilarity works best in this setting. We report the existence of reverse complementary word pairs with very dissimilar distance distributions, as well as word pairs with very similar distance distributions even when both distributions are irregular and contain strong peaks. The association between distribution dissimilarity and frequency discrepancy is explored also, and it is speculated that symmetric pairs combining low and high values of each measure may uncover features of interest. Taken together, our results suggest that some asymmetries in the human genome go far beyond Chargaff's rules. This study uses both the complete human genome and its repeat-masked version.Comment: Post-print of a paper accepted to publication in "Interdisciplinary Sciences: Computational Life Sciences" (ISSN: 1913-2751, ESSN: 1867-1462

Dissimilar Symmetric Word Pairs in the Human Genome

In this work we explore the dissimilarity between symmetric word pairs, by comparing the inter-word distance distribution of a word to that of its reversed complement. We propose a new measure of dissimilarity between such distributions. Since symmetric pairs with different patterns could point to evolutionary features, we search for the pairs with the most dissimilar behaviour. We focus our study on the complete human genome and its repeat-masked version.Comment: Submitted 13-Feb-2017; accepted, after a minor revision, 17-Mar-2017; 11th International Conference on Practical Applications of Computational Biology & Bioinformatics, PACBB 2017, Porto, Portugal, 21-23 June, 201

A novel image space formalism of Fourier domain interpolation neural networks for noise propagation analysis

Purpose: To develop an image space formalism of multi-layer convolutional neural networks (CNNs) for Fourier domain interpolation in MRI reconstructions and analytically estimate noise propagation during CNN inference. Theory and Methods: Nonlinear activations in the Fourier domain (also known as k-space) using complex-valued Rectifier Linear Units are expressed as elementwise multiplication with activation masks. This operation is transformed into a convolution in the image space. After network training in k-space, this approach provides an algebraic expression for the derivative of the reconstructed image with respect to the aliased coil images, which serve as the input tensors to the network in the image space. This allows the variance in the network inference to be estimated analytically and to be used to describe noise characteristics. Monte-Carlo simulations and numerical approaches based on auto-differentiation were used for validation. The framework was tested on retrospectively undersampled invivo brain images. Results: Inferences conducted in the image domain are quasi-identical to inferences in the k-space, underlined by corresponding quantitative metrics. Noise variance maps obtained from the analytical expression correspond with those obtained via Monte-Carlo simulations, as well as via an auto-differentiation approach. The noise resilience is well characterized, as in the case of classical Parallel Imaging. Komolgorov-Smirnov tests demonstrate Gaussian distributions of voxel magnitudes in variance maps obtained via Monte-Carlo simulations. Conclusion: The quasi-equivalent image space formalism for neural networks for k-space interpolation enables fast and accurate description of the noise characteristics during CNN inference, analogous to geometry-factor maps in traditional parallel imaging methods

Swiss Sepsis National Action Plan: A coordinated national action plan to stop sepsis-related preventable deaths and to improve the support of people affected by sepsis in Switzerland

Background: Sepsis is a devastating disease which causes yearly over 10 million deaths worldwide. In 2017, the World Health Organization (WHO) issued a resolution prompting member states to improve the prevention, recognition, and management of sepsis. The 2021 European Sepsis Report revealed that-contrary to other European countries-Switzerland had not yet actioned the sepsis resolution. Methods: A panel of experts convened at a policy workshop to address how to improve awareness, prevention, and treatment of sepsis in Switzerland. Goal of the workshop was to formulate a set of consensus recommendations toward creating a Swiss Sepsis National Action Plan (SSNAP). In a first part, stakeholders presented existing international sepsis quality improvement programs and national health programs relevant for sepsis. Thereafter, the participants were allocated into three working groups to identify opportunities, barriers, and solutions on (i) prevention and awareness, (ii) early detection and treatment, and (iii) support for sepsis survivors. Finally, the entire panel summarized the findings from the working groups and identified priorities and strategies for the SSNAP. All discussions during the workshop were transcribed into the present document. All workshop participants and key experts reviewed the document. Results: The panel formulated 14 recommendations to address sepsis in Switzerland. These focused on four domains, including (i) raising awareness in the community, (ii) improving healthcare workforce training on sepsis recognition and sepsis management; (iii) establishing standards for rapid detection, treatment and follow-up in sepsis patients across all age groups; and (iv) promoting sepsis research with particular focus on diagnostic and interventional trials. Conclusion: There is urgency to tackle sepsis. Switzerland has a unique opportunity to leverage from lessons learnt during the COVID-19 pandemic to address sepsis as the major infection-related threat to society. This report details consensus recommendations, the rationale thereof, and key discussion points made by the stakeholders on the workshop day. The report presents a coordinated national action plan to prevent, measure, and sustainably reduce the personal, financial and societal burden, death and disability arising from sepsis in Switzerland

Control groups in recent septic shock trials : a systematic review

The interpretation of septic shock trial data is profoundly affected by patients, control intervention, co-interventions and selected outcome measures. We evaluated the reporting of control groups in recent septic shock trials. We searched for original articles presenting randomized clinical trials (RCTs) in adult septic shock patients from 2006 to 2016. We included RCTs focusing on septic shock patients with at least two parallel groups and at least 50 patients in the control group. We selected and evaluated data items regarding patients, control group characteristics, and mortality outcomes, and calculated a data completeness score to provide an overall view of quality of reporting. A total of 24 RCTs were included (mean n = 287 patients and 71 % of eligible patients were randomized). Of the 24 studies, 14 (58 %) presented baseline data on vasopressors and 58 % the proportion of patients with elevated lactate values. Five studies (21 %) provided data to estimate the proportion of septic shock patients fulfilling the Sepsis-3 definition. The mean data completeness score was 19 out of 36 (range 8-32). Of 18 predefined control group characteristics, a mean of 8 (range 2-17) were reported. Only 2 (8 %) trials provided adequate data to confirm that their control group treatment represented usual care. Recent trials in septic shock provide inadequate data on the control group treatment and hemodynamic values. We propose a standardized trial dataset to be created and validated, comprising characteristics of patient population, interventions administered, hemodynamic values achieved, surrogate organ dysfunction, and mortality outcomes, to allow better analysis and interpretation of future trial results.Peer reviewe