Gauge-independent Renormalization of the 2-Higgs-Doublet Model

The 2-Higgs-Doublet Model (2HDM) belongs to the simplest extensions of the Standard Model (SM) Higgs sector that are in accordance with theoretical and experimental constraints. In order to be able to properly investigate the experimental Higgs data and, in the long term to distinguish between possible models beyond the SM, precise predictions for the Higgs boson observables have to be made available on the theory side. This requires the inclusion of the higher order corrections. In this work, we investigate in detail the renormalization of the 2HDM, a pre-requisite for the computation of higher order corrections. We pay particular attention to the renormalization of the mixing angles $\alpha$ and $\beta$, which diagonalize the Higgs mass matrices and which enter all Higgs observables. The implications of various renormalization schemes in next-to-leading order corrections to the sample processes $H^\pm \to W^\pm h/H$ and $H \to ZZ$ are investigated. Based on our findings, we will present a renormalization scheme that is at the same time process independent, gauge independent and numerically stable

Synthesis of clickable macro-porous materials for ultrafast purification of monoclonal antibodies

Porous polymers are topical materials and have gained a lot of interest in both academic and industrial research because they combine particular features of porous materials with those of synthetic polymers. Nowadays, porous polymers are used for a variety of different application fields such as catalysis, gas storage, or as separation materials. Various manufacturing methods can be applied to produce macroscopic porous polymeric particles, but most of them require the utilisation of a suspension polymerisation process in the presence of a porogen. This method often negatively affects the control of the final morphologies and requires a tedious work up as the porogen has to be fully extracted. In previous works, we have already presented “reactive gelation” as an alternative, porogen-free method to produce macro-porous materials by controlled aggregation of colloidal polymer nanoparticles under high shear1,2. Nevertheless, the production of macroporous polymers, which allow an easy post-functionalization had yet to be proven to address relevant applications like the chromatography of therapeutic proteins for instance. Herein, we present the emulsion polymerisation of highly crosslinked styrene-co-vinyl benzyl azide core-shell nanoparticles (~40 nm), their aggregation at high shear rates (106 1/s), and the hardening of the obtained fractal structures by post-polymerisation. This process results in chemically and physically stable macroporous microclusters with average size around 80 microns and pore sizes up to 10 µm. Thanks to the azide groups in the shell, the macroporous polymer scaffold can easily be post-functionalized by exploiting the concept of copper catalysed alkyne-azide cycloaddition (CuAAC). Among a vast number of functionalities that have been clicked onto the porous base material, we have also immobilised staphylococcus aureus protein A, well known as an affinity ligand for the capturing of monoclonal antibodies. By immobilising protein A on a macroporous scaffold, we are addressing the most significant bottleneck of large-scale production of therapeutic proteins, namely the purification of such. Indeed, the separation of the target protein from its cell impurities (host cell proteins, DNA, enzymes, etc.) often consists up to 80 % of the overall production costs because conventional chromatographic materials are not mechanically stable and only possess small pores (up to 150 nm). These smaller pores result in a diffusion-limited flow behaviour, making the downstream process costly and time-consuming. Our base material combines mechanical stability and perfusive flow behaviour, thereby providing protein separation at very high flow rates up to 1800 cm/hr. This excels conventional industrial materials by far, which can usually be used between 300-600 cm/hr. Noteworthy, the dynamic binding capacity is independent of the process rate, giving 10 g/l at 1800 cm/hr. The developed protein A prototype has also been proved stable under alkaline conditions, showing recovery above 80 % after 80 cycles with 0.1 M NaOH solution. However, since the industrial downstream process has a few other chromatographic steps following the capturing (such as ion-exchange chromatography and hydrophobic interaction chromatography), also polyelectrolytes and aliphatic molecules have successfully been attached to the macroporous base material. Addressing all types of chromatography needed during the purification of therapeutic proteins with just one base material highlights the true potential of this material, and might pave the way for perfusive protein chromatography. In summary, we have demonstrated emulsion polymerisation towards clickable core-shell nanoparticles, their aggregation under shear yielding macroporous particles, and their application as chromatography resins for the ultra-fast downstream of therapeutic proteins. Since the click chemistry protocol allows easy functionalization, the proposed process is expected to be suitable for other application fields as well. 1. Brand, B.; Morbidelli, M.; Soos, M., Shear-Induced Reactive Gelation. Langmuir 2015, 31 (46), 12727-12735. 2. Cingolani, A.; Baur, D. ; Caimi, S.; Storti, G.; Morbidelli, M., Preparation of perfusive chromatographic materials via shear-induced reactive gelation. J. Chromatogr. A 2018, in pres

Hetero-Supramolecular Modification of Nanocrystalline TiO₂-Film Electrodes: Photoassisted Electrocatalysis at B₁₂-on-TiO₂

Nanocrystalline TiO2-film electrodes exhibit a unique set of intrinsic properties (transparency for visible light, electric conductivity in the doped state, semiconductor properties, large surface area, surface affinity towards organic anchoring groups). These can be combined with those of TiO2-surface-anchored molecular subunits such as light emitters or absorbers, redoxactive–possibly electrochromic–compounds, and electroactive molecular hosts or catalysts. The number of macroscopic devices resulting from such a hetero-supramolecular architecture includes photovoltaic cells, erasable photochromic devices, electrochromic displays and filters, and electrocatalytically active surfaces. The principals behind these applications are reviewed with special emphasis on a new type of photo assisted electrocatalysis using vitamin B12-modified TiO2

Censorship in democracy

The spread of propaganda, misinformation, and biased narratives from autocratic regimes, especially on social media, is a growing concern in many democracies. Can censorship be an effective tool to curb the spread of such slanted narratives? In this paper, we study the European Union’s ban on Russian state-led news outlets after the 2022 Russian invasion of Ukraine. We analyze 775,616 tweets from 133,276 users on Twitter/X, employing a difference-in-differences strategy. We show that the ban reduced pro-Russian slant among users who had previously directly interacted with banned outlets. The impact is most pronounced among users with the highest pre-ban slant levels. However, this effect was short-lived, with slant returning to its pre-ban levels within two weeks post-enforcement. Additionally, we find a detectable albeit less pronounced indirect effect on users who had not directly interacted with the outlets before the ban. We provide evidence that other suppliers of propaganda may have actively sought to mitigate the ban’s influence by intensifying their activity, effectively counteracting the persistence and reach of the ban

Pathology Synthesis of 3D-Consistent Cardiac MR Images using 2D VAEs and GANs

We propose a method for synthesizing cardiac magnetic resonance (MR) images with plausible heart pathologies and realistic appearances for the purpose of generating labeled data for the application of supervised deep-learning (DL) training. The image synthesis consists of label deformation and label-to-image translation tasks. The former is achieved via latent space interpolation in a VAE model, while the latter is accomplished via a label-conditional GAN model. We devise three approaches for label manipulation in the latent space of the trained VAE model; i) \textbf{intra-subject synthesis} aiming to interpolate the intermediate slices of a subject to increase the through-plane resolution, ii) \textbf{inter-subject synthesis} aiming to interpolate the geometry and appearance of intermediate images between two dissimilar subjects acquired with different scanner vendors, and iii) \textbf{pathology synthesis} aiming to synthesize a series of pseudo-pathological synthetic subjects with characteristics of a desired heart disease. Furthermore, we propose to model the relationship between 2D slices in the latent space of the VAE prior to reconstruction for generating 3D-consistent subjects from stacking up 2D slice-by-slice generations. We demonstrate that such an approach could provide a solution to diversify and enrich an available database of cardiac MR images and to pave the way for the development of generalizable DL-based image analysis algorithms. We quantitatively evaluate the quality of the synthesized data in an augmentation scenario to achieve generalization and robustness to multi-vendor and multi-disease data for image segmentation. Our code is available at https://github.com/sinaamirrajab/CardiacPathologySynthesis.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://www.melba-journal.org/2023:01

Pathology Synthesis of 3D Consistent Cardiac MR Images Using 2D VAEs and GANs

We propose a method for synthesizing cardiac MR images with plausible heart shapes and realistic appearances for the purpose of generating labeled data for deep-learning (DL) training. It breaks down the image synthesis into label deformation and label-to-image translation tasks. The former is achieved via latent space interpolation in a VAE model, while the latter is accomplished via a conditional GAN model. We devise an approach for label manipulation in the latent space of the trained VAE model, namely pathology synthesis, aiming to synthesize a series of pseudo-pathological synthetic subjects with characteristics of a desired heart disease. Furthermore, we propose to model the relationship between 2D slices in the latent space of the VAE via estimating the correlation coefficient matrix between the latent vectors and utilizing it to correlate elements of randomly drawn samples before decoding to image space. This simple yet effective approach results in generating 3D consistent subjects from 2D slice-by-slice generations. Such an approach could provide a solution to diversify and enrich the available database of cardiac MR images and to pave the way for the development of generalizable DL-based image analysis algorithms. The code will be available at https://github.com/sinaamirrajab/CardiacPathologySynthesis

Shaped Laser Pulses for Microsecond Time-Resolved Cryo-EM: Outrunning Crystallization During Flash Melting

Water vitrifies if cooled at rates above $3 \cdot 10^5$ K/s. Surprisingly, this process cannot simply be reversed by heating the resulting amorphous ice at a similar rate. Instead, we have recently shown that the sample transiently crystallizes even if the heating rate is more than one order of magnitude higher. This may present an issue for microsecond time-resolved cryo-electron microscopy experiments, in which vitreous ice samples are briefly flash melted with a laser pulse, since transient crystallization could potentially alter the dynamics of the embedded proteins. Here, we demonstrate how shaped microsecond laser pulses can be used to increase the heating rate and outrun crystallization during flash melting of amorphous solid water (ASW) samples. We use time-resolved electron diffraction experiments to determine that the critical heating rate is about $10^8$ K/s, more than two orders of magnitude higher than the critical cooling rate. Our experiments add to the toolbox of the emerging field of microsecond time-resolved cryo-electron microscopy by demonstrating a straightforward approach for avoiding crystallization during laser melting and for achieving significantly higher heating rates, which paves the way for nanosecond time-resolved experiments

Prediction Along a Developmental Perspective in Psychiatry: How Far Might We Go?

Most mental disorders originate in childhood, and once symptoms present, a variety of psychosocial and cognitive maladjustments may arise. Although early childhood problems are generally associated with later mental health impairments and psychopathology, pluripotent transdiagnostic trajectories may manifest. Possible predictors range from behavioral and neurobiological mechanisms, genetic predispositions, environmental and social factors, and psychopathological comorbidity. They may manifest in altered neurodevelopmental trajectories and need to be validated capitalizing on large-scale multi-modal epidemiological longitudinal cohorts. Moreover, clinical and etiological variability between patients with the same disorders represents a major obstacle to develop effective treatments. Hence, in order to achieve stratification of patient samples opening the avenue of adapting and optimizing treatment for the individual, there is a need to integrate data from multi-dimensionally phenotyped clinical cohorts and cross-validate them with epidemiological cohort data. In the present review, we discuss these aspects in the context of externalizing and internalizing disorders summarizing the current state of knowledge, obstacles, and pitfalls. Although a large number of studies have already increased our understanding on neuropsychobiological mechanisms of mental disorders, it became also clear that this knowledge might only be the tip of the Eisberg and that a large proportion still remains unknown. We discuss prediction strategies and how the integration of different factors and methods may provide useful contributions to research and at the same time may inform prevention and intervention

Visualizing Nanoscale Dynamics with Time-resolved Electron Microscopy

The large number of interactions in nanoscale systems leads to the emergence of complex behavior. Understanding such complexity requires atomic-resolution observations with a time resolution that is high enough to match the characteristic timescale of the system. Our laboratory’s method of choice is time-resolved electron microscopy. In particular, we are interested in the development of novel methods and instrumentation for high-speed observations with atomic resolution. Here, we present an overview of the activities in our laboratory

Electron Diffraction of Water in No Man's Land

A generally accepted understanding of the anomalous properties of water will only emerge if it becomes possible to systematically characterize water in the deeply supercooled regime, from where the anomalies appear to emanate. This has largely remained elusive because water crystallizes rapidly between 160 K and 232 K. Here, we present an experimental approach to rapidly prepare deeply supercooled water at a well-defined temperature and probe it with electron diffraction before crystallization occurs. We show that as water is cooled from room temperature to cryogenic temperature, its structure evolves smoothly, approaching that of amorphous ice just below 200 K. Our experiments narrow down the range of possible explanations of the origin for the water anomalies and open up new avenues for studying supercooled water