A maximum-entropy length-orientation closure for short-fiber reinforced composites.

We describe an algorithm for generating fiber-filled volume elements for use in computational homogenization schemes which accounts for a coupling of the fiber-length and the fiber-orientation. For prescribed fiber-length distribution and fiber-orientation tensor of second order, a maximum-entropy estimate is used to produce a fiber-length-orientation distribution which mimics real injection molded specimens, where longer fibers show a stronger alignment than shorter fibers. We derive the length-orientation closure from scratch, discuss its integration into the sequential addition and migration algorithm for generating fiber-filled microstructures for industrial volume fractions and investigate the resulting effective elastic properties.

Imposing Dirichlet boundary conditions directly for FFT-based computational micromechanics.

We discuss how Dirichlet boundary conditions can be directly imposed for the Moulinec-Suquet discretization on the boundary of rectangular domains in iterative schemes based on the fast Fourier transform (FFT) and computational homogenization problems in mechanics. Classically, computational homogenization methods based on the fast Fourier transform work with periodic boundary conditions. There are applications, however, when Dirichlet (or Neumann) boundary conditions are required.

Experimental Characterization of the Mechanical Properties of Filter Media in Solid-Liquid Filtration Processes.

Nonwoven filter media are used in many industrial applications due to their high filtration efficiency and great variety of compositions and structures which can be produced by different processes. During filter operation in the separation process, the fluid flow exerts forces on the filter medium which leads to its deformation, and in extreme cases damage. In order to design or select a reliable filter medium for a given application, it is essential to have a comprehensive understanding of the mechanical properties of the nonwoven material.

Phase shift of coherent magnetization dynamics after ultrafast demagnetization in strongly quenched nickel thin films.

The remagnetization process after ultrafast demagnetization can be described by relaxation mechanisms between the spin, electron, and lattice reservoirs. Thereby, collective spin excitations in form of spin waves and their angular momentum transfer play an important role on the longer timescales. In this work, we address the question whether the magnitude of demagnetization-the so-called quenching-affects the coherency and the phase of the excited spin waves.

Standardized Electric-Field-Resolved Molecular Fingerprinting.

Field-resolved infrared spectroscopy (FRS) of impulsively excited molecular vibrations can surpass the sensitivity of conventional time-integrating spectroscopies, owing to a temporal separation of the molecular signal from the noisy excitation. However, the resonant response carrying the molecular signal of interest depends on both the amplitude and phase of the excitation, which can vary over time and across different instruments. To date, this has compromised the accuracy with which FRS measurements could be compared, which is a crucial factor for practical applications.

Hierarchical Multicriteria Optimization of Molecular Models of Water.

Many widely used molecular models of water are built from a single Lennard-Jones site on which three point charges are positioned, one negative and two positive ones. Models from that class, denoted LJ3PC here, are computationally efficient, but it is well known that they cannot represent all relevant properties of water simultaneously with good accuracy. Despite the importance of the LJ3PC water model class, its inherent limitations in simultaneously describing different properties of water have never been studied systematically.

ViNe-Seg: deep-learning-assisted segmentation of visible neurons and subsequent analysis embedded in a graphical user interface.

Summary: Segmentation of neural somata is a crucial and usually the most time-consuming step in the analysis of optical functional imaging of neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve the speed and consistency of the segmentation process, mostly, using deep learning approaches. Current segmentation tools, while advanced, still encounter challenges in producing accurate segmentation results, especially in datasets with a low signal-to-noise ratio.

Nondestructive material characterization and component identification in sheet metal processing with electromagnetic methods.

Electromagnetic methods for non-destructive evaluation (NDE) are presented, with which sheet metal components can be identified and their material properties can be characterized. The latter is possible with 3MA, the Micromagnetic Multiparametric Microstructure and stress Analyser. This is a combination of several micromagnetic NDE methods that make it possible to analyse the microstructure in a ferromagnetic material and to determine quantitative values of the mechanical material properties or the stress state.

Parasitic mixing in photomixers as continuous wave terahertz sources.

We present observations of parasitic frequency components in the emission spectrum of typical photomixer sources for continuous wave (CW) terahertz generation. Broadband tunable photomixer systems are often used in combination with direct power detectors, e.g.

Simulation and optimization of nutrient uptake and biomass formation using a multi-parameter Monod-type model of tobacco BY-2 cell suspension cultures in a stirred-tank bioreactor.

Introduction: Tobacco () cv Bright Yellow-2 (BY-2) cell suspension cultures enable the rapid production of complex protein-based biopharmaceuticals but currently achieve low volumetric productivity due to slow biomass formation. The biomass yield can be improved with tailored media, which can be designed either by laborious trial-and-error experiments or systematic, rational design using mechanistic models, linking nutrient consumption and biomass formation.

Methods: Here we developed an iterative experiment-modeling-optimization workflow to gradually refine such a model and its predictions, based on collected data concerning BY-2 cell macronutrient consumption (sucrose, ammonium, nitrate and phosphate) and biomass formation.

Designing spiking neural networks for robust and reconfigurable computation.

Networks of spiking neurons constitute analog systems capable of effective and resilient computing. Recent work has shown that networks of symmetrically connected inhibitory neurons may implement basic computations such that they are resilient to system disruption. For instance, if the functionality of one neuron is lost (e.

CT-based evaluation of tissue expansion in cryoablation of kidney.

Objectives: To evaluate tissue expansion during cryoablation, the displacement of markers in kidney tissue was determined using computed tomographic (CT) imaging.

Methods: CT-guided cryoablation was performed in nine porcine kidneys over a 10 min period. Markers and fiber optic temperature probes were positioned perpendicular to the cryoprobe shaft in an axial orientation.

Rapid-prototyping of microscopic thermal landscapes in Brillouin light scattering spectroscopy.

Since temperature and its spatial, and temporal variations affect a wide range of physical properties of material systems, they can be used to create reconfigurable spatial structures of various types in physical and biological objects. This paper presents an experimental optical setup for creating tunable two-dimensional temperature patterns on a micrometer scale. As an example of its practical application, we have produced temperature-induced magnetization landscapes in ferrimagnetic yttrium iron garnet films and investigated them using micro-focused Brillouin light scattering spectroscopy.

Quantum range-migration-algorithm for synthetic aperture radar applications.

The 3D range-migration algorithm (RMA) and its 2D equivalent, the omega-k algorithm, are employed in a wide range of applications where reconstruction of synthetic aperture data is required, from satellite radar imaging of planets over seismic imaging of the earth crust, down to phased-array ultrasound and ultrasonic application, and recently in-line synthetic aperture radar for non-destructive testing. These algorithms are based on Fourier transforms and share their time-complexity. This limits highly-resolved measurement data to be processed at high speeds which would be advantageous for modern production feed lines.

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study.

Background: During the COVID-19 pandemic, local health authorities were responsible for managing and reporting current cases in Germany. Since March 2020, employees had to contain the spread of COVID-19 by monitoring and contacting infected persons as well as tracing their contacts. In the EsteR project, we implemented existing and newly developed statistical models as decision support tools to assist in the work of the local health authorities.

Nanoval Technology-An Intermediate Process between Meltblown and Spunbond.

The idea of "Nanoval technology" origins in the metal injection molding for gas atomization of metal powders and the knowledge of spunbond technologies for the creation of thermoplastic nonwovens using the benefits of both techniques. In this study, we evaluated processing limits experimentally for the spinning of different types of polypropylene, further standard polymers, and polyphenylene sulfide, marked by defect-free fiber creation. A numerical simulation study of the turbulent air flow as well as filament motion in the process visualized that the turnover from uniaxial flow (initial stretching caused by the high air velocity directed at the spinning die) to turbulent viscoelastic behavior occurs significantly earlier than in the melt-blown process.

Calibrated simplex-mapping classification.

We propose a novel methodology for general multi-class classification in arbitrary feature spaces, which results in a potentially well-calibrated classifier. Calibrated classifiers are important in many applications because, in addition to the prediction of mere class labels, they also yield a confidence level for each of their predictions. In essence, the training of our classifier proceeds in two steps.

Direct laser writing of 3D metallic mid- and far-infrared wave components.

A method for direct fabrication of 3D silver microstructures with high fabrication throughput on virtually any substrate is presented. The method is based on laser-induced photoreduction of silver ions to silver atoms, supported by nucleation, substrate functionalization and a multiple exposure fabrication process. The combination of the novel photosensitive suspension and the novel fabrication scheme enables effective fabrication speeds of up to 1 cm per second, with a minimum structure size of less than 1 μm, a resolution of more than 750 lines/mm and a resistivity of 3.

Terahertz and Millimeter Wave Sensing and Applications.

The field of terahertz and millimeter wave science and technology has evolved in recent years into an area attracting a lot of attention from all sides of science, industry, and the public [...

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.

Background: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021.

Methods: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland.

Photonic quadrupole topological insulator using orbital-induced synthetic flux.

The rich physical properties of multiatomic crystals are determined, to a significant extent, by the underlying geometry and connectivity of atomic orbitals. The mixing of orbitals with distinct parity representations, such as s and p orbitals, has been shown to be useful for generating systems that require alternating phase patterns, as with the sign of couplings within a lattice. Here we show that by breaking the symmetries of such mixed-orbital lattices, it is possible to generate synthetic magnetic flux threading the lattice.

Fiber-tip endoscope for optical and microwave control.

We present a robust, fiber-based endoscope with a silver direct-laser-written structure for radio frequency (RF) emission next to the optical fiber facet. Thereby, we are able to excite and probe a sample, such as nitrogen-vacancy (NV) centers in diamond, with RF and optical signals simultaneously and specifically measure the fluorescence of the sample fully through the fiber. At our targeted frequency range of around 2.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach.

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data.

Making thermodynamic models of mixtures predictive by machine learning: matrix completion of pair interactions.

Predictive models of thermodynamic properties of mixtures are paramount in chemical engineering and chemistry. Classical thermodynamic models are successful in generalizing over (continuous) conditions like temperature and concentration. On the other hand, matrix completion methods (MCMs) from machine learning successfully generalize over (discrete) binary systems; these MCMs can make predictions without any data for a given binary system by implicitly learning commonalities across systems.

Observation of bound states in the continuum embedded in symmetry bandgaps.

In the past decade, symmetry-protected bound states in the continuum (BICs) have proven to be an important design principle for creating and enhancing devices reliant upon states with high-quality () factors, such as sensors, lasers, and those for harmonic generation. However, as we show, current implementations of symmetry-protected BICs in photonic crystal slabs can only be found at the center of the Brillouin zone and below the Bragg diffraction limit, which fundamentally restricts their use to single-frequency applications. By microprinting a three-dimensional (3D) photonic crystal structure using two-photon polymerization, we demonstrate that this limitation can be overcome by altering the radiative environment surrounding the slab to be a 3D photonic crystal.