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Abstract The present work intends to characterise the combination of two netted software defined radios (SDR) and different radio frequency (RF) front‐ends installed in them, together with a two‐stratum time dissemination and synchronisation system. A modified implementation of the Network Time Protocol is used as coarse event synchronisation for either SDR back‐end. The White rabbit light embedded node implementation of the commonly known white rabbit synchronisation system (IEEE 1588 PTP‐2019) or arbitrary wave form generators are used as fine time dissemination system for either SDR. The resulting netted transceiver system is intended to compose a demonstrator for proof‐of‐concept experiments. The findings presented in this article show that the chosen combination of hardware and software is suitable for radar applications operating within L‐, S‐ and C‐bands. A channel coherency throughout the network with a relative modified Allan deviation of less than 80 fs for averaging intervals of 1 s, a phase noise better than −118 dBc/Hz at 10 Hz frequency offset and a fractional frequency lower than ±2.5⋅10−13 was measured. Within a single transceiver node, a fractional frequency lower than ±2⋅10−13 and phase noise of −124 dBc/Hz at 10 Hz frequency offset were measured as well. Multistatic radar systems exploit wide spatial diversity to enhance target detection and tracking, albeit with increased complexity when compared to a monostatic configuration. To exploit these benefits, all participating transceiver nodes within the netted radar need to synchronise to a common time base t0. The achieved synchronisation level increases the accuracy with which the chain of timed events at the transmitter and at the receiver side occur, intending to maximise the signal‐to‐noise ratio available at the receiver. The Universal software radio peripheral model X310 with two different daughterboard models as RF front‐end was used as SDR on either radar node. A network combining data and synchronisation purposes allowed the radar nodes under test to operate synchronously. The two‐stratum synchronisation system used glass fibres between 2 m and 5 km of length or coaxial cables with 2 m in length for network traffic, time and frequency dissemination purposes. The multiple RF front‐ends were stimulated by means of arbitrary waveform generators with calibrated traceability. Up‐chirp and sinusoid waveforms were used as stimuli for measuring the offset of either channel with regards of t0 to ultimately estimate the achievable coherency limits of the system under test. Both analogue and digital evaluation methods were considered.

Abstract Microfluidics and droplet-based assays are the basis for numerous high-throughput experiments, including bio-inspired microreactors and selection platforms for directed evolution. While elaborate techniques are available for the production of picoliter-sized droplets, there is an increasing demand for subsequent manipulation and control of the droplet interior. Here, we report on a straightforward method to rapidly adjust the size of single to several hundred double-emulsion droplets in a microfluidic sieve by varying the carrier fluid’s salt concentration. We show that the concomitant concentration changes in the droplet interior can drive a reversible demixing transition in a biomimetic binary fluid. As another application, we show that growing and shrinking of trapped droplets can be utilized to achieve a reversible dissociation of double-stranded DNA into single strands, i.e. cycles of reversible DNA hybridization, similar to PCR cycles, can be achieved by reversibly changing the droplet size at constant temperature. Altogether, our approach shows how a simple and temporally tunable manipulation of the size and the chemistry in prefabricated droplets can be achieved by an external control parameter.

Abstract Background Device-related bacterial infections account for a large proportion of hospital-acquired infections. The ability of bacteria to form a biofilm as a protective shield usually makes treatment impossible without removal of the implant. Topographic surfaces have attracted considerable attention in studies seeking antibacterial properties without the need for additional antimicrobial substances. As there are still no valid rules for the design of antibacterial microstructured surfaces, a fast, reproducible production technique with good resolution is required to produce test surfaces and to examine their effectiveness with regard to their antibacterial properties. Methods In this work various surfaces, flat and with microcylinders in different dimensions (flat, 1, 3 and 9 μm) with a surface area of 7 × 7 mm were fabricated with a nanoprinter using two-photon lithography and evaluated for their antibiofilm effect. The microstructured surfaces were cultured for 24 h with different strains of Pseudomonas aeruginosa and Staphylococcus aureus to study bacterial attachment to the patterned surfaces. In addition, surface wettability was measured by a static contact angle measurement. Results Contact angles increased with cylinder size and thus hydrophobicity. Despite the difference in wettability, Staphylococcus aureus was not affected by the microstructures, while for Pseudomonas aeruginosa the bacterial load increased with the size of the cylinders, and compared to a flat surface, a reduction in bacteria was observed for one strain on the smallest cylinders. Conclusions Two-photon lithography allowed rapid and flexible production of microcylinders of different sizes, which affected surface wettability and bacterial load, however, depending on bacterial type and strain.

The metal bipolar plate is a critical component of the hydrogen fuel cell stack used in proton exchange membrane fuel cells. Bipolar plates must have high accuracy micro-channels with a high aspect ratio (AR) between the channel depth and the half periodic width to achieve optimal cell performance. Conventional forming methods, such as micro-stamping, hydroforming, and rubber pad forming, cannot achieve these high ARs given that in these processes, material deformation is dominated by stretch deformation. In micro-roll forming the major deformation mode is bending, and this enables production of channels with higher ARs than is currently possible. However, micro-roll forming uses multiple sets of forming roll stands to form the part and this leads to technological challenges related to tool alignment and roll tool precision that must be overcome before widespread application can be achieved. This study presents a new methodology to achieve tight tool tolerances when producing micro-roll tooling by utilizing wire-EDM and micro-turning techniques. This is combined with a new micro-roll former design that enables high-precision tool alignment across multiple roll stations. Proof of concept is provided through micro-roll forming trials performed on ultra-thin titanium sheets that show that the proposed technology can achieve tight dimensional tolerances in the sub-millimeter scale that suits bipolar plate applications.

Automotive structural components from Advanced High-Strength Steels (AHSS) can be manufactured with Flexible Roll Forming (FRF). The application of FRF in the automotive industry is limited due to flange wrinkling defects that increase with material strength. The new Incremental Shape Rolling process (ISR) has been shown to reduce wrinkling severity compared to FRF and therefore presents a promising alternative for the manufacture of high-strength automotive components. The current work analyzes for the first time the mechanisms that lead to wrinkling reduction in ISR based on the critical stress conditions that develop in the flange. For this, finite element process models are validated with experimental forming trials and used to investigate the material deformation and the forming stresses that occur in FRF and ISR when forming a variable-width automotive component. The results show that in ISR, the undeformed flange height decreases with increasing forming; this increases the critical buckling and wrinkling stresses with each forming pass and prevents the development of wrinkles towards the end of the forming process. In contrast, in FRF, the critical buckling or wrinkling stress is constant, while the longitudinal compressive stress in the flange increases with the number of forming passes and exceeds the critical stress. This leads to the development of severe wrinkles in the flange.

Abstract Drought has a significant impact on plant–insect interactions by altering plant survival, growth, leaf quality, and defense traits. Tropical plants are particularly vulnerable to water depression because of shallow root depth. In the context of climate change, drought events are expected to increase in frequency and intensity; however, their impact on tropical ecosystems remains poorly known. Insect herbivores represent the largest feeding guild of arthropods, and they devour four to five times more plant material than vertebrates do. Understanding how drought affects plant traits and leaf palatability in a keystone and ecologically diverse plant genus, such as Ficus (Moraceae), is crucial for predicting how climate change might alter tropical plant–insect interactions. We examined the impact of drought intensity and duration on the leaf nutritional quality, defensive traits, and herbivory damage by caterpillars in three tropical and one Mediterranean Ficus species in a greenhouse. We also conducted food choice trials with generalist caterpillars to evaluate the impact of drought on herbivores. Drought intensity and duration had no direct effect on leaf palatability across the Ficus species. However, drought indirectly affected leaf palatability via drought‐induced leaf traits in a species‐specific manner. Drought intensity and duration decreased leaf water content, resulting in decreased leaf palatability in F. benjamina and F. lyrata. Leaf defensive traits such as flavonoid concentration were affected by drought intensity and decreased leaf palatability in F. carica. Drought influenced the leaf traits of F. elastica, but none of them affected leaf palatability. Overall, this study establishes the link between drought and insect feeding on plants via leaf traits. The species‐specific responses to drought highlight the significance of climate‐related plant life histories in relation to climate change, underscoring the need for further investigations.

The sheet metal forming of magnesium is challenging due to the material’s complex springback behaviour, which is due to the tension/compression yield mismatch. In this study, three different AZ31 grain sizes are produced by a special heat treatment, while maintaining the material strength in uniaxial tension at a similar level. Pure, V-die and channel bending tests are combined with roll forming to compare bending scenarios with and without tension applied transverse and parallel to the bending axis. This is complemented with electron backscatter diffraction to measure the twinning type and twinning area fraction (TAF) in the tension and compression bending zones. Our study shows that, like conventional steel, when bending magnesium, springback reduces with the increasing level of the outer fibre bending strain, i.e., when the bend radius is decreased and the TAF increased. It is further shown that when tension is applied, the TAF increases. However, while in some forming cases, the increase in TAF leads to a clear reduction in springback, in other forming cases the effect of the TAF on springback is less pronounced. Overall, this study provides clear evidence that the twinning behaviour in bending magnesium is influenced by the bend deformation mode and that this influences the springback behaviour.

Anomalous-diffusion identifies the departure of diffusive dynamics from the traditional Brownian-motion and is a signature feature of a large number of complex soft-matter and biological systems. This article reports an analysis of an easy to implement method to decide on the type of an apparent anomaly, even in the presence of localisation errors.

Hybrid quantum technologies synergistically combine different types of systems with complementary strengths. Here, the authors show monolithic integration and control of quantum dots and the emitted single photons in a surface acoustic wave-driven GaAs integrated quantum photonic circuit.

Allometric relations between two observables are a widespread phenomenon in biology. The volume of nuclei, for example, has frequently been reported to scale linearly with cell volume, V_{N}∼V_{C}, but conflicting, sublinear power-law correlations have also been found. Given that nuclei are vital organelles that harbor and maintain the DNA of cells, an understanding of allometric nuclear volumes that ultimately define the concentration and accessibility of chromatin is of great interest. Using the model organism Caenorhabditis elegans, we show here that the allometry of nuclei is a dynamically adapting phenomenon; i.e., we find V_{N}∼V_{C}^{α} with a time-dependent scaling exponent α (“dynamic allometry”). This finding is due to relaxation growth of nuclear volumes at a rate that scales with cell size. If cell division stops the relaxation of nuclei in a premature stage, α

Abstract The objective of this study is to examine the association between neighborhood socioeconomic status (nSES) and baseline allostatic load (AL) and clinical trial endpoints in patients enrolled in the E1A11 therapeutic trial in multiple myeloma (MM). Study endpoints were symptom burden (pain, fatigue, and bother) at baseline and 5.5 months, non-completion of induction therapy, overall survival (OS) and progression-free survival (PFS). Multivariable logistic and Cox regression examined associations between nSES, AL and patient outcomes. A 1-unit increase in baseline AL was associated with greater odds of high fatigue at baseline (adjusted OR [95% CI] = 1.21 [1.08–1.36]) and a worse OS (adjusted hazard ratio, [95% CI] = 1.21 [1.06–1.37]). High nSES was associated with worse baseline bother (middle OR = 4.22 [1.11–16.09] and high 4.49 [1.16–17.43]) compared to low nSES. There was no association between AL or nSES and symptom burden at 5.5 months, non-completion of induction therapy or PFS. Additionally, there was no association between nSES and OS. AL may have utility as a predictive marker for OS among patients with MM and may allow individualization of treatment. Future studies should standardize and validate AL patients with MM.

In the near future, humans will increasingly be required to offload tasks to artificial systems to facilitate daily as well as professional activities. Yet, research has shown that humans are often averse to offloading tasks to algorithms (so-called "algorithmic aversion"). In the present study, we asked whether this aversion is also present when humans act under high cognitive load. Participants performed an attentionally demanding task (a multiple object tracking (MOT) task), which required them to track a subset of moving targets among distractors on a computer screen. Participants first performed the MOT task alone (Solo condition) and were then given the option to offload an unlimited number of targets to a computer partner (Joint condition). We found that participants significantly offloaded some (but not all) targets to the computer partner, thereby improving their individual tracking accuracy (Experiment 1). A similar tendency for offloading was observed when participants were informed beforehand that the computer partner's tracking accuracy was flawless (Experiment 2). The present findings show that humans are willing to (partially) offload task demands to an algorithm to reduce their own cognitive load. We suggest that the cognitive load of a task is an important factor to consider when evaluating human tendencies for offloading cognition onto artificial systems.

Secondary infections in coronavirus disease 2019 (COVID-19) patients are difficult to distinguish from inflammation associated with COVID-19 and/or extracorporeal membrane oxygenation (ECMO). Therefore, highly specific and sensitive biomarkers are needed to identify patients in whom antimicrobial therapy can be safely withheld. In this prospective monocentric study, 66 COVID-19 patients admitted to the intensive care unit (ICU) for ECMO evaluation were included. A total of 46 (70%) patients with secondary infections were identified by using broad microbiological and virological panels and standardized diagnostic criteria. Various laboratory parameters including C-reactive protein (CRP), interleukin (IL)-6, procalcitonin (PCT), and IL-10 were determined at time of study inclusion. The best test performance for differentiating bacterial/fungal secondary infections and COVID-19 and/or ECMO associated inflammation was achieved by IL-10 (ROC-AUC 0.84) and a multivariant step-wise regression model including CRP, IL-6, PCT, and IL-10 (ROC-AUC 0.93). Data obtained in the present study highlights the use of IL-10 to differentiate secondary bacterial/fungal infections from COVID-19 and/or ECMO associated inflammation in severely ill COVID-19 patients.

Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. Today’s increased availability of data acquisition hardware in modern aircraft provides continuously sampled in-flight measurements, so-called full-flight data. These full-flight data give access to sufficient data points to detect faults within a single flight, significantly improving the availability and safety of aircraft. Artificial neural networks are considered well suited for the timely analysis of an extensive amount of incoming data. This article proposes uncertainty quantification for artificial neural networks, leading to more reliable and robust fault detection. An existing approach for approximating the aleatoric uncertainty was extended by an Out-of-Distribution Detection in order to take the epistemic uncertainty into account. The method was statistically evaluated, and a grid search was performed to evaluate optimal parameter combinations maximizing the true positive detection rates. All test cases were derived based on in-flight measurements of a commercially operated regional jet. Especially when requiring low false positive detection rates, the true positive detections could be improved 2.8 times while improving response times by approximately 6.9 compared to methods only accounting for the aleatoric uncertainty.

Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.

In all three domains of life, tRNA genes contain introns that must be removed to yield functional tRNA. In archaea and eukarya, the first step of this process is catalyzed by a splicing endonuclease. The consensus structure recognized by the splicing endonuclease is a bulge-helix-bulge (BHB) motif which is also found in rRNA precursors. So far, a systematic analysis to identify all biological substrates of the splicing endonuclease has not been carried out. In this study, we employed CRISPRi to repress expression of the splicing endonuclease in the archaeon Haloferax volcanii to identify all substrates of this enzyme. Expression of the splicing endonuclease was reduced to 1% of its normal level, resulting in a significant extension of lag phase in H. volcanii growth. In the repression strain, 41 genes were down-regulated and 102 were up-regulated. As an additional approach in identifying new substrates of the splicing endonuclease, we isolated and sequenced circular RNAs, which identified excised introns removed from tRNA and rRNA precursors as well as from the 5′ UTR of the gene HVO_1309. In vitro processing assays showed that the BHB sites in the 5′ UTR of HVO_1309 and in a 16S rRNA-like precursor are processed by the recombinant splicing endonuclease. The splicing endonuclease is therefore an important player in RNA maturation in archaea.

Aircraft engine condition monitoring is a key technology for increasing safety and reducing maintenance expenses. Current engine condition monitoring approaches use a minimum of one steady-state snapshot per flight. Whilst being appropriate for trending gradual engine deterioration, snapshots result in a detrimental latency in fault detection. The increased availability of non-mandatory data acquisition hardware in modern airplanes provides so-called full-flight data sampled continuously during flight. These datasets enable the detection of engine faults within one flight by deriving a statistically relevant set of steady-state data points, thus, allowing the application of machine-learning approaches. It is shown that low-pass filtering before steady-state detection significantly increases the success rate in detecting steady-state data points. The application of Principal Component Analysis halves the number of relevant dimensions and provides a coordinate system of principal components retaining most of the variance. Consequently, clusters of data points with and without engine fault can be separated visually and numerically using a One-Class Support Vector Machine. High detection rates are demonstrated for various component faults and even for a minimum instrumentation suite using synthesized datasets derived from full-flight data of commercially operated flights. In addition to the tests conducted with synthesized data, the algorithm is verified based on operational in-flight measurements providing a proof-of-concept. Consequently, the availability of continuously sampled in-flight measurements combined with machine-learning methods allows fault detection within a single flight.

Particle transport in complex environments such as the interior of living cells is often (transiently) non-Fickian or anomalous, that is, it deviates from the laws of Brownian motion. Such anomalies may be the result of small-scale spatio-temporal heterogeneities in, or viscoelastic properties of, the medium, molecular crowding, etc. Often the observed dynamics displays multi-state characteristics, i.e. distinct modes of transport dynamically interconverting between each other in a stochastic manner. Reliably distinguishing between single- and multi-state dynamics is challenging and requires a combination of distinct approaches. To complement the existing methods relying on the analysis of the particle’s mean squared displacement, position- or displacement-autocorrelation function, and propagators, we here focus on ‘scattering fingerprints’ of multi-state dynamics. We develop a theoretical framework for two-state scattering signatures—the intermediate scattering function and dynamic structure factor—and apply it to the analysis of simple model systems as well as particle-tracking experiments in living cells. We consider inert tracer-particle motion as well as systems with an internal structure and dynamics. Our results may generally be relevant for the interpretation of state-of-the-art differential dynamic microscopy experiments on complex particulate systems, as well as inelastic or quasielastic neutron (incl. spin-echo) and x-ray scattering probing structural and dynamical properties of macromolecules, when the underlying dynamics displays two-state transport.

Lightweight modular construction has become an increasing need to meet the housing requirements around the world today. The benefits of modular construction ranging from rapid production, consistency in quality, sustainability, and ease of use have widened the scope for the construction of residential, commercial, and even emergency preparedness facilities. This study introduces novel floor panels that can be flat-packed and built into modular housing components on-site with minimal labour and assistance. The flooring system uses hollow cellular panels made of various configurations of trapezoidal steel sheets. The structural performance of three different configurations of these hollow flooring systems as a modular component is presented in this study by analysing the failure modes, load-displacement parameters, and strain behaviour. The study confirms significant advantages of the proposed hollow floor systems, with multi-cells reporting higher load-carrying capacity. The hollow flooring system performed well in terms of structural performance and ease in fabrication as opposed to the conventional formworks and commercial temporary flooring systems. The proposed flooring system promises efficient application as working platforms or formworks in temporary infrastructural facilities and emergency construction activities.

Quantum technologies that rely on photonic qubits require a precise controllability of their properties. For this purpose hybrid approaches are particularly attractive because they offer a large flexibility to address different aspects of the photonic degrees of freedom. When combining photonics with other quantum platforms like phonons, quantum transducers have to be realized that convert between the mechanical and optical domain. Here, we realize this interface between phonons in the form of surface acoustic waves (SAWs) and single photons, mediated by a single semiconductor quantum dot exciton. In this combined theoretical and experimental study, we show that the different sidebands exhibit characteristic blinking dynamics that can be controlled by detuning the laser from the exciton transition. By developing analytical approximations we gain a better understanding of the involved internal dynamics. Our specific SAW approach allows us to reach the ideal frequency range of around 1 GHz that enables simultaneous temporal and spectral phonon sideband resolution close to the combined fundamental time-bandwidth limit.

Single-particle tracking (SPT) has become a powerful tool to quantify transport phenomena in complex media with unprecedented detail. Based on the reconstruction of individual trajectories, a wealth of informative measures become available for each particle, allowing for a detailed comparison with theoretical predictions. While SPT has been used frequently to explore diffusive transport in artificial fluids and inside living cells, intermediate systems, i.e., biochemically active cell extracts, have been studied only sparsely. Extracts derived from the eggs of the clawfrog Xenopus laevis, for example, are known for their ability to support and mimic vital processes of cells, emphasizing the need to explore also the transport phenomena of nano-sized particles in such extracts. Here, we have performed extensive SPT on beads with 20 nm radius in native and chemically treated Xenopus extracts. By analyzing a variety of distinct measures, we show that these beads feature an anti-persistent subdiffusion that is consistent with fractional Brownian motion. Chemical treatments did not grossly alter this finding, suggesting that the high degree of macromolecular crowding in Xenopus extracts equips the fluid with a viscoelastic modulus, hence enforcing particles to perform random walks with a significant anti-persistent memory kernel.

Diffusion of nanoparticles in the cytoplasm of live cells has frequently been reported to exhibit an anomalous and even heterogeneous character, i.e. particles seem to switch gears during their journey. Here we show by means of a hidden Markov model that individual trajectories of quantum dots in the cytoplasm of living cultured cells feature a dichotomous switching between two distinct mobility states with an overall subdiffusive mode of motion of the fractional Brownian motion (FBM) type. Using the extracted features of experimental trajectories as input for simulations of different variants of a two-state FBM model, we show that the trajectory-intrinsic and the ensemble-wise heterogeneity in the experimental data is mostly due to variations in the (local) transport coefficients, with only minor contributions due to locally varying anomaly exponents. Altogether, our approach shows that diffusion heterogeneities can be faithfully extracted and quantified from fairly short trajectories obtained by single-particle tracking in highly complex media.

Fractional Brownian motion (FBM) is a prevalent Gaussian stochastic process that has frequently been linked to subdiffusive motion in complex fluids, e.g. inside living cells. In contrast, examples for a superdiffusive FBM in complex fluids are sparse, and a covering of all FBM regimes in the same sample is basically lacking. Here we show that membraneless organelles in the single-cell state of C. elegans embryos, so-called p-granules, constitute an experimental example in which the whole range of FBM processes, from the sub- to the superdiffusive regime, can be observed. The majority of p-granules is subdiffusive, featuring an antipersistent velocity autocorrelation function (VACF). A smaller fraction of trajectories shows normal diffusion or even superdiffusion with a persistent VACF. For all trajectories, from sub- to superdiffusive, the VACF, its characteristic values, and the trajectories’ power-spectral density are well matched by FBM predictions. Moreover, static localization errors, a frequent problem in single-particle tracking experiments, are shown to not affect the conclusion that p-granule motion is best described by FBM from the sub- to the superdiffusive regime.

This study investigates the effect of grain size and composition on the material properties and forming limits of commercially supplied stainless steel foil for bipolar plate manufacture via tensile, stretch forming and micro-stamping trials. It is shown that in commercially supplied stainless steel the grain size can vary significantly and that ‘size effects’ can be influenced by prior steel processing and composition effects. While the forming limits in micro-stamping appear to be directly linked to the plane strain forming limits of the individual stainless steel alloys, there was a clear effect of the tensile anisotropy. In contrast to previous studies, forming severity and the likelihood of material failure did not increase with a decreasing channel profile radius. This was related to inaccuracies of the forming tool profile shape.

Trapezoidal-shaped thin-walled metallic profiled sheets are used in composite floor construction to enable rapid construction and reduce reinforcement and formwork requirements in concrete casting. However, relevant literature reported the early failure of steel sections due to the buckling and shear of existing trapezoidal and re-entrant decking profiles. There are also limitations regarding design rules for composite flooring systems. Current work aims to develop a new type of composite top-hat section for possible use in composite slim-floor construction. Sinusoidal metallic corrugated sheets that are widely used in building construction were utilized and a new bending technique was used to produce deck components, in which transverse corrugations were introduced along the main direction of the corrugated profile. This paper investigates the structural response of these new sections for several loading and support conditions using a pilot experimental scheme. The developed top-hat sections demonstrated considerable resistance to bending as well as buckling through effective stress re-distributions under considered construction stage loading for single span and continuous span conditions. Currently available design equations recommended by Australian Standards for a similar type of corrugated decks were used to predict the design strength and to compare it with those obtained experimentally. It was concluded that the expressions proposed by the code were inadequate for single span loading cases and would require modifications before being applied to the new profile.

This article presents the statistical analysis of bistatic radar rural ground clutter for different terrain types under low grazing angles. Compared to most state-of-the-art analysis, we present country-specific clutter analysis for subgroups of rural environments rather than for the rural environment as a whole. Therefore, the rural environment analysis is divided into four dominant subgroup terrain types, namely fields with low vegetation, fields with high vegetation, plantations of small trees and forest environments representing a typical rural German environment. We will present the results for both the summer and the winter vegetation. Therefore, bistatic measurement campaigns have been carried out during the summer 2019 and the winter of 2019/20 in the aforementioned four different rural terrain types. The measurements were performed in the radar relevant X-band at a center frequency of 8.85 GHz and over a bandwidth of 100 MHz according to available transmit permission. The distinction of the rural terrain into different subgroups enables a more precise and accurate clutter analysis and modeling of the statistical properties as will be shown in the presented results. The statistical properties are derived from the calculated clutter amplitudes probability density functions and corresponding cumulative distribution functions for each of the four terrain types and the corresponding season. The data basis for the clutter analysis are the processed range-Doppler maps from the bistatic radar measurements. According to the authors’ current knowledge, a similar investigation based on real bistatic radar measurement data with the division into terrain subgroups has not yet been carried out and published for a German rural environment.

Time-dependent processes are often analyzed using the power spectral density (PSD) calculated by taking an appropriate Fourier transform of individual trajectories and finding the associated ensemble average. Frequently, the available experimental datasets are too small for such ensemble averages, and hence, it is of a great conceptual and practical importance to understand to which extent relevant information can be gained from S(f,T), the PSD of a single trajectory. Here we focus on the behavior of this random, realization-dependent variable parametrized by frequency f and observation time T, for a broad family of anomalous diffusions—fractional Brownian motion with Hurst index H—and derive exactly its probability density function. We show that S(f,T) is proportional—up to a random numerical factor whose universal distribution we determine—to the ensemble-averaged PSD. For subdiffusion (H1/2) S(f,T)∼BT^{2H-1}/f^{2} with random amplitude B. Remarkably, for H>1/2 the PSD exhibits the same frequency dependence as Brownian motion, a deceptive property that may lead to false conclusions when interpreting experimental data. Notably, for H>1/2 the PSD is ageing and is dependent on T. Our predictions for both sub- and superdiffusion are confirmed by experiments in live cells and in agarose hydrogels and by extensive simulations.

OBJECTIVE:The finer scale patterns of arthropod vertical stratification in forests are rarely studied and poorly understood. Further, there are no studies investigating whether and how altitude affects arthropod vertical stratification in temperate forests. We therefore investigated the fine-scale vertical stratification of diversity and guild structure of saproxylic beetles in temperate lowland and montane forests and compared the resulting patterns between the two habitats. METHODS:The beetles were sampled with flight intercept traps arranged into vertical transects (sampling heights 0.4, 1.2, 7, 14, and 21 m). A triplet of such transects was installed in each of the five sites in the lowland and in the mountains; 75 traps were used in each forest type. RESULTS:381 species were collected in the lowlands and 236 species in the mountains. Only 105 species (21%) were found at both habitats; in the montane forest as well as in the lowlands, the species richness peaked at 1.2 m, and the change in assemblage composition was most rapid near the ground. The assemblages clearly differed between the understorey (0.4 m, 1.2 m) and the canopy (7 m, 14 m, 21 m) and between the two sampling heights within the understorey, but less within the canopy. The stratification was better pronounced in the lowland, where canopy assemblages were richer than those near the forest floor (0.4 m). In the mountains the samples from 14 and 21 m were more species poor than those from the lower heights. The guild structure was similar in both habitats. CONCLUSIONS:The main patterns of vertical stratification and guild composition were strikingly similar between the montane and the lowland forest despite the low overlap of their faunas. The assemblages of saproxylic beetles were most stratified near ground. The comparisons of species richness between canopy and understorey may thus give contrasting results depending on the exact sampling height in the understorey.

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package "traitor" to facilitate assessments of missing trait data.

Organizing cell divisions in an embryo, especially coordinating cell cycles across larger distances, is of crucial importance for the development of an animal. Here we show that cell-cycle times and cell volumes are anti-correlated during all phases of embryogenesis in the simple model organism Caenorhabditis elegans . By revisiting and significantly extending a previously proposed model, based on a limiting component, we arrive at a quantitative agreement with the experimental data for all stages of embryogenesis. The model not only rationalizes the average anti-correlation but also captures most of the cell-to-cell variations observed in experiments. Our findings suggest that inter-cell communication may not be mandatory to coordinate cell-cycle times in the embryogenesis of C. elegans . Rather, cells in this simple organism might decide autonomously about the next mitosis event by estimating their own volume via a limiting component. Together with several asymmetric cell divisions, a rather homogenous distribution of cell sizes is obtained at the onset of gastrulation, hence facilitating the inward motion of cells during subsequent stages of development.

Trophoblast stem cells (TSCs) represent the multipotent progenitors that give rise to the different cells of the embryonic portion of the placenta. Here, we analysed the expression of key TSC transcription factors Cdx2, Eomes, and Elf5 in the early developing placenta of mouse embryos and in cultured TSCs and reveal surprising heterogeneity in protein levels. We analysed persistence of TSCs in the early placenta and find that TSCs remain in the chorionic hinge until E9.5 and are lost shortly afterwards. To define the transcriptional signature of bona fide TSCs, we used inducible gain- and loss-of-function alleles of Eomes or Cdx2, and EomesGFP, to manipulate and monitor the core maintenance factors of TSCs, followed by genome-wide expression profiling. Combinatorial analysis of resulting expression profiles allowed for defining novel TSC marker genes that might functionally contribute to the maintenance of the TSC state. Analyses by qRT-PCR and in situ hybridisation validated novel TSC- and chorion-specific marker genes, such as Bok/Mtd, Cldn26, Duox2, Duoxa2, Nr0b1, and Sox21. Thus, these expression data provide a valuable resource for the transcriptional signature of bona fide and early differentiating TSCs and may contribute to an increased understanding of the transcriptional circuitries that maintain and/or establish stemness of TSCs.

Telomeres are vital nucleotide sequences at both ends of each chromosome, and their motion reports on the local dynamics of decondensed chromatin in the nucleus of interphase cells. Here, we show that the previously reported subdiffusive motion of telomeres is driven by non-equilibrium cytoskeletal forces. In particular, breaking down microtubules leads to a significantly reduced generalized diffusion coefficient of telomeres. This translates into a markedly reduced effective temperature in the stochastic forces that govern the telomeres’ random walk. Moreover, telomere motion in cells that lack microtubules is well described by the monomer dynamics of a Rouse polymer that is embeddded in a viscoelastic medium. In contrast, active cytoskeletal forces in untreated cells override the environment’s elastic contributions, resulting in the well-known scaling for conventional Rouse dynamics in viscous media. Our data highlight that even subdiffusive motion in cells in most cases may not be a simple thermal transport process but rather is driven by non-equilibrium events.

Using coarse-grained membrane simulations we show here that peripheral membrane proteins can form a multitude of higher-order structures due to membrane-mediated interactions. Peripheral membrane proteins characteristically perturb the lipid bilayer in their vicinity which supports the formation of protein assemblies not only within the same but surprisingly also across opposing leaflets of a bilayer. In addition, we also observed the formation of lipid-protein domains on heteregeneous membranes. The clustering ability of proteins, as quantified via the potential of mean force, is enhanced when radius and hydrophobic penetration depth of the proteins increases. Based on our data, we propose that membrane-mediated cluster formation of peripheral proteins supports protein assembly in vivo and hence may play a pivotal role in the formation of templates for signaling cascades and in the emergence of transport intermediates in the secretory pathway.

Biochemical reactions in crowded fluids have been predicted to differ strongly from those in aqueous solutions. Both excluded-volume interactions with surrounding macromolecules and crowding-induced subdiffusion have been predicted to stabilize complex formation of reaction partners. Here we show that both facets of crowding strongly alter the stochastic opening and closing of a single-stranded DNA hairpin. Crowding not only slows down the kinetics but also increases the steady-state fraction of closed hairpins significantly. The latter is shown to be enhanced if crowding is associated with subdiffusion. Biochemical reactions in crowded fluids are therefore sensistive to both excluded-volume interactions and changes of the reactants' diffusion characteristics.