Microbial induced wettability alteration with implications for Underground Hydrogen Storage

Characterization of the microbial activity impacts on transport and storage of hydrogen is a crucial aspect of successful Underground Hydrogen Storage (UHS). Microbes can use hydrogen for their metabolism, which can then lead to formation of biofilms. Biofilms can potentially alter the wettability of the system and, consequently, impact the flow dynamics and trapping mechanisms in the reservoir. In this study, we investigate the impact of microbial activity on wettability of the hydrogen/brine/rock system, using the captive-bubble cell experimental approach. Apparent contact angles are measured for bubbles of pure hydrogen in contact with a solid surface inside a cell filled with living brine which contains sulphate reducing microbes. To investigate the impact of surface roughness, two different solid samples are used: a "rough" Bentheimer Sandstone sample and a "smooth" pure Quartz sample. It is found that, in systems where buoyancy and interfacial forces are the main acting forces, the impact of biofilm formation on the apparent contact angle highly depends on the surface roughness. For the "rough" Bentheimer sandstone, the apparent contact angle was unchanged by biofilm formation, while for the smooth pure Quartz sample the apparent contact angle decreased significantly, making the system more water-wet. This decrease in apparent contact angle is in contrast with an earlier study present in the literature where a significant increase in contact angle due to microbial activity was reported. The wettability of the biofilm is mainly determined by the consistency of the Extracellular Polymeric Substances (EPS) which depends on the growth conditions in the system. Therefore, to determine the impact of microbial activity on the wettability during UHS will require accurate replication of the reservoir conditions including surface roughness, chemical composition of the brine, the microbial community, as well as temperature, pressure and pH-value conditions.

Long-span fiber composite truss made by coreless filament winding for large-scale satellite structural systems demonstrated on a planetary sunshade concept

Climate change necessitates exploring innovative geoengineering solutions to mitigate its effects-one such solution is deploying planetary sunshade satellites at Sun-Earth Lagrange point 1 to regulate solar radiation on Earth directly. However, such long-span space structures present unique technical challenges, particularly structural scalability, on-orbit manufacturing, and in-situ resource utilization. This paper proposes a structural concept for the sunshade's foil support system and derives from that a component-level modular system for long-span fiber composite lightweight trusses using coreless filament winding. Within a laboratory-scale case study, the component scalability, as well as the manufacturing and material impacts, were experimentally investigated by bending deflection testing. Based on these experimental results, FE models of the proposed structural concept were calibrated to estimate the maximum displacement and mass of the foil support structure, while comparing the influences of foil edge length, orbital load case, and material selection.

RepEnTools: an automated repeat enrichment analysis package for ChIP-seq data reveals hUHRF1 Tandem-Tudor domain enrichment in young repeats

BACKGROUND

Repeat elements (REs) play important roles for cell function in health and disease. However, RE enrichment analysis in short-read high-throughput sequencing (HTS) data, such as ChIP-seq, is a challenging task.

RESULTS

Here, we present RepEnTools, a software package for genome-wide RE enrichment analysis of ChIP-seq and similar chromatin pulldown experiments. Our analysis package bundles together various software with carefully chosen and validated settings to provide a complete solution for RE analysis, starting from raw input files to tabular and graphical outputs. RepEnTools implementations are easily accessible even with minimal IT skills (Galaxy/UNIX). To demonstrate the performance of RepEnTools, we analysed chromatin pulldown data by the human UHRF1 TTD protein domain and discovered enrichment of TTD binding on young primate and hominid specific polymorphic repeats (SVA, L1PA1/L1HS) overlapping known enhancers and decorated with H3K4me1-K9me2/3 modifications. We corroborated these new bioinformatic findings with experimental data by qPCR assays using newly developed primate and hominid specific qPCR assays which complement similar research tools. Finally, we analysed mouse UHRF1 ChIP-seq data with RepEnTools and showed that the endogenous mUHRF1 protein colocalizes with H3K4me1-H3K9me3 on promoters of REs which were silenced by UHRF1. These new data suggest a functional role for UHRF1 in silencing of REs that is mediated by TTD binding to the H3K4me1-K9me3 double mark and conserved in two mammalian species.

CONCLUSIONS

RepEnTools improves the previously available programmes for RE enrichment analysis in chromatin pulldown studies by leveraging new tools, enhancing accessibility and adding some key functions. RepEnTools can analyse RE enrichment rapidly, efficiently, and accurately, providing the community with an up-to-date, reliable and accessible tool for this important type of analysis.

Endogenous estrogen metabolites as oxidative stress mediators and endometrial cancer biomarkers

BACKGROUND

Endometrial cancer is the most common gynecologic malignancy found in developed countries. Because therapy can be curative at first, early detection and diagnosis are crucial for successful treatment. Early diagnosis allows patients to avoid radical therapies and offers conservative management options. There are currently no proven biomarkers that predict the risk of disease occurrence, enable early identification or support prognostic evaluation. Consequently, there is increasing interest in discovering sensitive and specific biomarkers for the detection of endometrial cancer using noninvasive approaches.

CONTENT

Hormonal imbalance caused by unopposed estrogen affects the expression of genes involved in cell proliferation and apoptosis, which can lead to uncontrolled cell growth and carcinogenesis. In addition, due to their ability to cause oxidative stress, estradiol metabolites have both carcinogenic and anticarcinogenic properties. Catechol estrogens are converted to reactive quinones, resulting in oxidative DNA damage that can initiate the carcinogenic process. The molecular anticancer mechanisms are still not fully understood, but it has been established that some estradiol metabolites generate reactive oxygen species and reactive nitrogen species, resulting in nitro-oxidative stress that causes cancer cell cycle arrest or cell death. Therefore, identifying biomarkers that reflect this hormonal imbalance and the presence of endometrial cancer in minimally invasive or noninvasive samples such as blood or urine could significantly improve early detection and treatment outcomes.

Prmt6 represses the pro-adipogenic Ppar-gamma-C/ebp-alpha transcription factor loop

The feed-forward loop between the transcription factors Ppar-gamma and C/ebp-alpha is critical for lineage commitment during adipocytic differentiation. Ppar-gamma interacts with epigenetic cofactors to activate C/ebp-alpha and the downstream adipocytic gene expression program. Therefore, knowledge of the epigenetic cofactors associated with Ppar-gamma, is central to understanding adipocyte differentiation in normal differentiation and disease. We found that Prmt6 is present with Ppar-gamma on the Ppar-gamma and C/ebp-alpha promoter. It contributes to the repression of C/ebp-alpha expression, in part through its ability to induce H3R2me2a. During adipocyte differentiation, Prmt6 expression is reduced and the methyltransferase leaves the promoters. As a result, the expression of Ppar-gamma and C/ebp-alpha is upregulated and the adipocytic gene expression program is established. Inhibition of Prmt6 by a small molecule enhances adipogenesis, opening up the possibility of epigenetic manipulation of differentiation. Our data provide detailed information on the molecular mechanism controlling the Ppar-gamma-C/ebp-alpha feed-forward loop. Thus, they advance our understanding of adipogenesis in normal and aberrant adipogenesis.

Machine learning enhanced evaluation of semiconductor quantum dots

A key challenge in quantum photonics today is the efficient and on-demand generation of high-quality single photons and entangled photon pairs. In this regard, one of the most promising types of emitters are semiconductor quantum dots, fluorescent nanostructures also described as artificial atoms. The main technological challenge in upscaling to an industrial level is the typically random spatial and spectral distribution in their growth. Furthermore, depending on the intended application, different requirements are imposed on a quantum dot, which are reflected in its spectral properties. Given that an in-depth suitability analysis is lengthy and costly, it is common practice to pre-select promising candidate quantum dots using their emission spectrum. Currently, this is done by hand. Therefore, to automate and expedite this process, in this paper, we propose a data-driven machine-learning-based method of evaluating the applicability of a semiconductor quantum dot as single photon source. For this, first, a minimally redundant, but maximally relevant feature representation for quantum dot emission spectra is derived by combining conventional spectral analysis with an autoencoding convolutional neural network. The obtained feature vector is subsequently used as input to a neural network regression model, which is specifically designed to not only return a rating score, gauging the technical suitability of a quantum dot, but also a measure of confidence for its evaluation. For training and testing, a large dataset of self-assembled InAs/GaAs semiconductor quantum dot emission spectra is used, partially labelled by a team of experts in the field. Overall, highly convincing results are achieved, as quantum dots are reliably evaluated correctly. Note, that the presented methodology can account for different spectral requirements and is applicable regardless of the underlying photonic structure, fabrication method and material composition. We therefore consider it the first step towards a fully integrated evaluation framework for quantum dots, proving the use of machine learning beneficial in the advancement of future quantum technologies.

Optimal feedback improves behavioral focus during self-regulated computer-based work

Distractions are omnipresent and can derail our attention, which is a precious and very limited resource. To achieve their goals in the face of distractions, people need to regulate their attention, thoughts, and behavior; this is known as self-regulation. How can self-regulation be supported or strengthened in ways that are relevant for everyday work and learning activities? To address this question, we introduce and evaluate a desktop application that helps people stay focused on their work and train self-regulation at the same time. Our application lets the user set a goal for what they want to do during a defined period of focused work at their computer, then gives negative feedback when they get distracted, and positive feedback when they reorient their attention towards their goal. After this so-called focus session, the user receives overall feedback on how well they focused on their goal relative to previous sessions. While existing approaches to attention training often use artificial tasks, our approach transforms real-life challenges into opportunities for building strong attention control skills. Our results indicate that optimal attentional feedback can generate large increases in behavioral focus, task motivation, and self-control-benefitting users to successfully achieve their long-term goals.

Enhancing heat transfer at low temperatures by laser functionalization of the inner surface of metal pipes

The latent heat transfer during vapour condensation in the condenser section of passive heat transport devices such as the two-phase closed thermosiphon is limited by film condensation. Dropwise condensation provides an increase of the heat transfer coefficient by up to one order of magnitude and can be achieved with a water-repellant surface. The inner surface of pipes made from stainless steel was functionalized by laser surface texturing with ultrashort laser pulses and subsequent storage in a liquid containing long-chained hydrocarbons. The pipes were separated into half-pipes by wire eroding to enable laser texturing of the inner surface, and were then joined by electron beam welding after laser texturing. As a result, superhydrophobic and water-repellent surfaces with a contact angle of 153° were obtained on the inner surface of the pipes with a length of up to 1 m. The functionalized pipes were used in the condenser section of a two-phase closed thermosiphon to demonstrate a heat transfer rate of 0.92 kW at 45 °C, which is approximately three times the heat transfer rate of 0.31 kW of a smooth reference pipe.

Thermocapillary central lamella recess during droplet impacts onto a heated wall

We experimentally observe a new phenomenon, the formation of a toroidal region of lower film thickness in the center of the lamella formed during high Weber number water droplet impacts onto smooth heated walls. This region forms around the air bubble, which is entrapped during the initial impact phase at the impact center. Our study encompasses a variation of the droplet size, impact velocity, surface wettability and temperature. We show how this phenomenon can be explained considering a two-step process involving thermocapillary convection in two separate regions: The temperature gradient along the surface of the entrapped air bubble caused by heat conduction induces flow that pumps warmer liquid to the lamella-ambient interface due to the Marangoni effect. The non-uniform temperature distribution along it then causes fluid acceleration in the radial direction, depleting the fluid volume around the bubble in a self-amplifying manner. We use direct numerical simulations of a stagnant liquid film with an enclosed bubble at the wall to confirm this theory.

On effects of freezing and thawing cycles of concrete containing nano-[Formula: see text]: experimental study of material properties and crack simulation

Construction during cold weather can lead to freezing accidents in concrete, causing significant hidden threats to the project's performance and safety by affecting the mechanical properties and durability reduction. This study aims to deduce the compressive strength and durability of the concrete containing nano-[Formula: see text] under freezing-thawing cycles with the Caspian seawater curing condition. The specimens were subjected to freezing-thawing cycles according to ASTM C666. Furthermore, crack propagation in the concrete after freezing-thawing cycles is simulated. The results reveal that adding until nano-[Formula: see text] until 6% improved compressive strength before and after freezing-thaw cycles. The water permeability experiences a substantial reduction as the amount of nano-[Formula: see text] increases. Furthermore, the water permeability exhibits a positive correlation with the number of cycles, resulting in significantly higher values after 150 cycles compared to the initial sample. Moreover, adding 8% nano-[Formula: see text] reduced the depth of water permeability and chloride ion penetration after 150 cycles by 57% and 86%, respectively. The crack simulation results indicate that concrete containing 6% nano-[Formula: see text] shows an optimal resistance against crack formation. Concrete with 6% nano-[Formula: see text] requires 13.88% less force for crack initialization after 150 freezing and thawing cycles. Among different nano-[Formula: see text] percentages, 6% shows the best crack resistance and 8% the minimum water permeability and chloride ion penetration.

Investigating rate-limited sorption, sorption to air-water interfaces, and colloid-facilitated transport during PFAS leaching

Various sorption processes affect leaching of per- and polyfluoroalkyl substances (PFAS) such as PFOA and PFOS. The objectives of this study are to (1) compare rate-limited leaching in column and lysimeter experiments, (2) investigate the relevance of sorption to air-water interfaces (AWI), and (3) examine colloid-facilitated transport as a process explaining early experimental breakthrough. A continuum model (CM) with two-domain sorption is used to simulate equilibrium and rate-limited sorption. A random walk particle tracking (PT) model was developed and applied to analyze complex leaching characteristics. Results show that sorption parameters derived from column experiments underestimate long-term PFOA leaching in lysimeter experiments due to early depletion, suggesting that transformation of precursors contributes to the observed long-term leaching in the lysimeters (approximately 0.003 µg/kg/d PFOA). Both models demonstrate that sorption to AWI is the dominant retention mechanism for PFOS in lysimeter experiments, with retardation due to AWI being 3 (CM) to 3.7 (PT) times higher than retardation due to solid phase sorption. Notably, despite a simplified conception of AWI sorption, the PT results are closer to the observations. The PT simulations demonstrate possible colloid-facilitated transport at early time; however, results using substance-specific varying transport parameters align better with the observations, which should be equal if colloid-facilitated transport without additional kinetics is the sole mechanism affecting early breakthrough. Possibly, rate-limited sorption to AWI is relevant during the early stages of the lysimeter experiment. Our findings demonstrate that rate-limited sorption is less relevant for long-term leaching under field conditions compared to transformation of precursors and that sorption to AWI can be the dominant retention mechanism on contaminated sites. Moreover, they highlight the potential of random walk particle tracking as a practical alternative to continuum models for estimating the relative contributions of various retention mechanisms.

Development and verification of a physiologically motivated internal controller for the open-source extended Hill-type muscle model in LS-DYNA

Nowadays, active human body models are becoming essential tools for the development of integrated occupant safety systems. However, their broad application in industry and research is limited due to the complexity of incorporated muscle controllers, the long simulation runtime, and the non-regular use of physiological motor control approaches. The purpose of this study is to address the challenges in all indicated directions by implementing a muscle controller with several physiologically inspired control strategies into an open-source extended Hill-type muscle model formulated as LS-DYNA user-defined umat41 subroutine written in the Fortran programming language. This results in increased usability, runtime performance and physiological accuracy compared to the standard muscle material existing in LS-DYNA. The proposed controller code is verified with extensive experimental data that include findings for arm muscles, the cervical spine region, and the whole body. Selected verification experiments cover three different muscle activation situations: (1) passive state, (2) open-loop and closed-loop muscle activation, and (3) reflexive behaviour. Two whole body finite element models, the 50th percentile female VIVA OpenHBM and the 50th percentile male THUMS v5, are used for simulations, complemented by the simplified arm model extracted from the 50th percentile male THUMS v3. The obtained results are evaluated additionally with the CORrelation and Analysis methodology and the mean squared error method, showing good to excellent biofidelity and sufficient agreement with the experimental data. It was shown additionally how the integrated controller allows simplified mimicking of the movements for similar musculoskeletal models using the parameters transfer method. Furthermore, the Hill-type muscle model presented in this paper shows better kinematic behaviour even in the passive case compared to the existing one in LS-DYNA due to its improved damping and elastic properties. These findings provide a solid evidence base motivating the application of the enhanced muscle material with the internal controller in future studies with Active Human Body Models under different loading conditions.

An interdisciplinary model chain quantifies the footprint of global change on reservoir sedimentation

Global change alters hydro-climatic conditions, affects land use, and contributes to more frequent droughts and floods. Large artificial reservoirs may effectively alleviate hydro-climatic extremes, but their storage capacities are threatened by sedimentation processes, which in turn are exacerbated by land use change. Envisioning strategies for sustainable reservoir management requires interdisciplinary model chains to emulate key processes driving sedimentation under global change scenarios. Therefore, we introduce a model chain for the long-term prediction of complex three-dimensional (3d) reservoir sedimentation considering concurrent catchment, hydro-climatic, and land-use conditions. Applied to a mountainous Mediterranean catchment, the model chain predicts increased sediment production and decreased discharge for high and medium emission pathways. Increased winter precipitation, accompanied by a transition from snowfall to rainfall, is projected to aggravate reduced summer precipitation, emphasizing a growing need for reservoirs. Additionally, higher winter precipitation proliferates sediment production and reservoir sedimentation. Land use change can outweigh the increased reservoir sedimentation originating from hydro-climatic change, which highlights the significance of localized actions to reduce sediment production. Finally, a 3d hydro-morphodynamic model provides insights into interactions between global change and reservoir sedimentation with spatially explicit information on future sedimentation patterns facilitating the implementation of management strategies.

Detecting age-related changes in skeletal muscle mechanics using ultrasound shear wave elastography

Aging leads to a decline in muscle mass and force-generating capacity. Ultrasound shear wave elastography (SWE) is a non-invasive method to capture age-related muscular adaptation. This study assessed biceps brachii muscle (BB) mechanics, hypothesizing that shear elastic modulus reflects (i) passive muscle force increase imposed by length change, (ii) activation-dependent mechanical changes, and (iii) differences between older and younger individuals. Fourteen healthy volunteers aged 60-80 participated. Shear elastic modulus, surface electromyography, and elbow torque were measured at five elbow positions in passive and active states. Data collected from young adults aged 20-40 were compared. The BB passive shear elastic modulus increased from flexion to extension, with the older group exhibiting up to 52.58% higher values. Maximum elbow flexion torque decreased in extended positions, with the older group 23.67% weaker. Significant effects of elbow angle, activity level, and age on total and active shear elastic modulus were found during submaximal contractions. The older group had 20.25% lower active shear elastic modulus at 25% maximum voluntary contraction. SWE effectively quantified passive and activation-dependent BB mechanics, detecting age-related alterations at rest and during low-level activities. These findings suggest shear elastic modulus as a promising biomarker for identifying altered muscle mechanics in aging.

Muscle wobbling mass dynamics: eigenfrequency dependencies on activity, impact strength, and ground material

In legged locomotion, muscles undergo damped oscillations in response to the leg contacting the ground (an impact). How muscle oscillates varies depending on the impact situation. We used a custom-made frame in which we clamped an isolated rat muscle (M. gastrocnemius medialis and lateralis: GAS) and dropped it from three different heights and onto two different ground materials. In fully activated GAS, the dominant eigenfrequencies were 163 Hz, 265 Hz, and 399 Hz, which were signficantly higher (p < 0.05) compared to the dominant eigenfrequencies in passive GAS: 139 Hz, 215 Hz, and 286 Hz. In general, neither changing the falling height nor ground material led to any significant eigenfrequency changes in active nor passive GAS, respectively. To trace the eigenfrequency values back to GAS stiffness values, we developed a 3DoF model. The model-predicted GAS muscle eigenfrequencies matched well with the experimental values and deviated by - 3.8%, 9.0%, and 4.3% from the passive GAS eigenfrequencies and by - 1.8%, 13.3%, and - 1.5% from the active GAS eigenfrequencies. Differences between the frequencies found for active and passive muscle impact situations are dominantly due to the attachment of myosin heads to actin.

Development of super-specific epigenome editing by targeted allele-specific DNA methylation

BACKGROUND

Epigenome editing refers to the targeted reprogramming of genomic loci using an EpiEditor which may consist of an sgRNA/dCas9 complex that recruits DNMT3A/3L to the target locus. Methylation of the locus can lead to a modulation of gene expression. Allele-specific DNA methylation (ASM) refers to the targeted methylation delivery only to one allele of a locus. In the context of diseases caused by a dominant mutation, the selective DNA methylation of the mutant allele could be used to repress its expression but retain the functionality of the normal gene.

RESULTS

To set up allele-specific targeted DNA methylation, target regions were selected from hypomethylated CGIs bearing a heterozygous SNP in their promoters in the HEK293 cell line. We aimed at delivering maximum DNA methylation with highest allelic specificity in the targeted regions. Placing SNPs in the PAM or seed regions of the sgRNA, we designed 24 different sgRNAs targeting single alleles in 14 different gene loci. We achieved efficient ASM in multiple cases, such as ISG15, MSH6, GPD1L, MRPL52, PDE8A, NARF, DAP3, and GSPT1, which in best cases led to five to tenfold stronger average DNA methylation at the on-target allele and absolute differences in the DNA methylation gain at on- and off-target alleles of > 50%. In general, loci with the allele discriminatory SNP positioned in the PAM region showed higher success rate of ASM and better specificity. Highest DNA methylation was observed on day 3 after transfection followed by a gradual decline. In selected cases, ASM was stable up to 11 days in HEK293 cells and it led up to a 3.6-fold change in allelic expression ratios.

CONCLUSIONS

We successfully delivered ASM at multiple genomic loci with high specificity, efficiency and stability. This form of super-specific epigenome editing could find applications in the treatment of diseases caused by dominant mutations, because it allows silencing of the mutant allele without repression of the expression of the normal allele thereby minimizing potential side-effects of the treatment.

Lateral heat flux reduction using a lock-in thermography compensation method

The naturally diffusive heat flow in solids often results in differences in surface temperatures. Active thermography (AT) exploits such differences to gain information on the internal structure, morphology, or geometry of technical components or biological specimens. In contrast to sound or light waves, thermal waves are lossy; consequently, it is difficult to interpret measured 2D temperature fields. Most AT evaluation methods are based on 1D approaches, and measured 3D heat fluxes are frequently not considered, which is why edges, small features, or gradients are often blurred. Herein, we present a method for reducing the local temperature gradients at feature areas and minimizing the induced lateral heat flux in optical lock-in thermography (LT) measurements through spatial- and temporal-structured heating. The vanishing lateral gradients convert the problem into a 1D problem, which can be adequately solved by the LT approach. The proposed compensation method can bypass the blind frequency of LT and make the inspection largely independent of the excitation frequency. Furthermore, the edge sharpness and separability of features are improved, ultimately improving the feature-detection efficiency.

Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem

Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the [Formula: see text] relative error by [Formula: see text] after 25,000 epochs for a one-dimensional consolidation problem based on Biot's theory, and an average improvement by [Formula: see text] with a transfer approach to the theory of porous media.

Non-adaptive measurement-based quantum computation on IBM Q

We test the quantumness of IBM's quantum computer IBM Quantum System One in Ehningen, Germany. We generate generalised n-qubit GHZ states and measure Bell inequalities to investigate the n-party entanglement of the GHZ states. The implemented Bell inequalities are derived from non-adaptive measurement-based quantum computation (NMQC), a type of quantum computing that links the successful computation of a non-linear function to the violation of a multipartite Bell-inequality. The goal is to compute a multivariate Boolean function that clearly differentiates non-local correlations from local hidden variables (LHVs). Since it has been shown that LHVs can only compute linear functions, whereas quantum correlations are capable of outputting every possible Boolean function it thus serves as an indicator of multipartite entanglement. Here, we compute various non-linear functions with NMQC on IBM's quantum computer IBM Quantum System One and thereby demonstrate that the presented method can be used to characterize quantum devices. We find a violation for a maximum of seven qubits and compare our results to an existing implementation of NMQC using photons.

Bioinspired preactivation reflex increases robustness of walking on rough terrain

Walking on unknown and rough terrain is challenging for (bipedal) robots, while humans naturally cope with perturbations. Therefore, human strategies serve as an excellent inspiration to improve the robustness of robotic systems. Neuromusculoskeletal (NMS) models provide the necessary interface for the validation and transfer of human control strategies. Reflexes play a crucial part during normal locomotion and especially in the face of perturbations, and provide a simple, transferable, and bio-inspired control scheme. Current reflex-based NMS models are not robust to unexpected perturbations. Therefore, in this work, we propose a bio-inspired improvement of a widely used NMS walking model. In humans, different muscles show an increase in activation in anticipation of the landing at the end of the swing phase. This preactivation is not integrated in the used reflex-based walking model. We integrate this activation by adding an additional feedback loop and show that the landing is adapted and the robustness to unexpected step-down perturbations is markedly improved (from 3 to 10 cm). Scrutinizing the effect, we find that the stabilizing effect is caused by changed knee kinematics. Preactivation, therefore, acts as an accommodation strategy to cope with unexpected step-down perturbations, not requiring any detection of the perturbation. Our results indicate that such preactivation can potentially enable a bipedal system to react adequately to upcoming unexpected perturbations and is hence an effective adaptation of reflexes to cope with rough terrain. Preactivation can be ported to robots by leveraging the reflex-control scheme and improves the robustness to step-down perturbation without the need to detect the perturbation. Alternatively, the stabilizing mechanism can also be added in an anticipatory fashion by applying an additional knee torque to the contralateral knee.

Novel heat flux controlled surface cooling for hypersonic flight

This paper presents a new method in theory and experiment to adjust the transpiration cooling based on the actual measured heat flux. This is particularly useful in extreme heating environments, e.g. atmospheric entry flight or combustion chamber applications. In such environments, usually cooling is set constant based on the vehicle design, yet a mass efficient and performant cooling is sought after. We present a method with real-time surface heat flux determination of the transpiration cooled wall and an automatic adjustment of the cooling. The heat flux is determined based on a system identification process. The heat flux measurement itself is derived non-intrusively from the measurement of pressure inside the plenum, i.e. the region between mass flow controller and porous wall. The particular advantage of this system is that the heat shield material is not weakened by any sensor system and its performance is optimized with respect to cooling needed at a certain heating level. Another new feature of the pressure heat flux transformation is the attenuation of a destabilizing positive feedback loop, where the transpiration cooling controller's output (i.e. mass flow rate) strongly influences its input (i.e. plenum pressure). We describe the identification of the model parameters for the heat flux determination, which are found and verified by a calibration approach. The controlled cooling was demonstrated in a hot air plasma flow with a reference heat flux of up to 1.4 MW/m[Formula: see text]. The results show the performance and verify the applicability in a real flight environment.

Model-predicted geometry variations to compensate material variability in the design of classical guitars

Musical instrument making is often considered a mysterious form of art, its secrets still escaping scientific quantification. There is not yet a formula to make a good instrument, so historical examples are regarded as the pinnacle of the craft. This is the case of Stradivari's violins or Torres guitars that serve as both models and examples to follow. Geometric copies of these instruments are still the preferred way of building new ones, yet reliably making acoustic copies of them remains elusive. One reason for this is that the variability of the wood used for instruments makes for a significant source of uncertainty-no two pieces of wood are the same. In this article, using state-of-the-art methodologies, we show a method for matching the vibrational response of two guitar top plates made with slightly different materials. To validate our method, we build two guitar soundboards: one serving as a reference and the second acting as a copy to which we apply model-predicted geometry variations. The results are twofold. Firstly, we can experimentally validate the predictive capabilities of our numerical model regarding geometry changes. Secondly, we can significantly reduce the deviation between the two plates by these precisely predicted geometry variations. Although applied to guitars here, the methodology can be extended to other instruments, e.g. violins, in a similar fashion. The implications of such a methodology for the craft could be far-reaching by turning instrument-making more into a science than artistic craftsmanship and paving the way to accurately copy historical instruments of a high value.

Preparation of multifunctional hydrogels with accessible isothiouronium groups via radical cross-linking copolymerization

Hydrogels can be equipped with functional groups for specific purposes. Isothiouronium groups can enhance adsorptivity, or allow coupling of other functional groups through mild reactions after transformation to thiol groups. Here we present a method to prepare multifunctional hydrogels by introducing isothiouronium groups into poly(ethylene glycol) diacrylate (PEGDA) hydrogels, and convert them into thiol-functionalized hydrogels by the reduction of the isothiouronium groups. For this purpose, the amphiphilic monomer 2-(11-(acryloyloxy)-undecyl)isothiouronium bromide (AUITB), containing an isothiouronium group, was synthesized and copolymerized with PEGDA. In this convenient way, it was possible to incorporate up to 3 wt% AUITB into the hydrogels without changing their equilibrium swelling degree. The successful functionalization was demonstrated by surface analysis of the hydrogels with water contact angle measurements and increased isoelectric points of the hydrogel surfaces from 4.5 to 9.0 due to the presence of the isothiouronium groups. The hydrogels showed a suitability as an adsorbent, as exemplified by the pronounced adsorption of the anionic drug diclofenac. The potential of the functionalization for (bio)conjugation reactions was demonstrated by the reduction of isothiouronium groups to thiols and subsequent immobilization of the functional enzyme horseradish peroxidase on the hydrogels. The results show that fully accessible isothiouronium groups can be introduced into radically cross-linked hydrogels.

Urban foraging in Brazilian public greenspaces

Urban foraging, i.e., the gathering of wild edible plants, plays a key role in nature connection within cities. Its integration in planning could contribute to the conservation of urban biodiversity. However, we have little understanding of the interactions between the motivations for and barriers to foraging, and the role of legislation, especially in biodiversity hotspots. Through an online questionnaire and policy review, we explored the practice of urban foraging in Recife, Brazil, across social, spatial and regulatory dimensions. We found that most non-foragers would forage if pollution risks were addressed and knowledge was improved. Foragers collected up to 31 species, none of which are threatened. By integrating the social, spatial and regulatory dimensions of the practice, we highlighted the importance of the local context for targeting foraging incentives. In all, regulation had little impact on where the practice is carried out, and foraging seemed to have little negative impact on biodiversity, as no threatened species were collected and foragers were conscious of their impact. This knowledge can contribute to better integrate the practice of foraging within legislation and develop forager-led greenspace planning and management. In biodiversity hotspots threatened by urban expansion, foraging can contribute to slowing down the biodiversity crisis and improve urban residents' contact with biodiversity.

A method for evaluating population and infrastructure exposed to natural hazards: tests and results for two recent Tonga tsunamis

BACKGROUND

Coastal communities are highly exposed to ocean- and -related hazards but often lack an accurate population and infrastructure database. On January 15, 2022 and for many days thereafter, the Kingdom of Tonga was cut off from the rest of the world by a destructive tsunami associated with the Hunga Tonga Hunga Ha'apai volcanic eruption. This situation was made worse by COVID-19-related lockdowns and no precise idea of the magnitude and pattern of destruction incurred, confirming Tonga's position as second out of 172 countries ranked by the World Risk Index 2018. The occurrence of such events in remote island communities highlights the need for (1) precisely knowing the distribution of buildings, and (2) evaluating what proportion of those would be vulnerable to a tsunami.

METHODS AND RESULTS

A GIS-based dasymetric mapping method, previously tested in New Caledonia for assessing and calibrating population distribution at high resolution, is improved and implemented in less than a day to jointly map population clusters and critical elevation contours based on runup scenarios, and is tested against destruction patterns independently recorded in Tonga after the two recent tsunamis of 2009 and 2022. Results show that ~ 62% of the population of Tonga lives in well-defined clusters between sea level and the 15 m elevation contour. The patterns of vulnerability thus obtained for each island of the archipelago allow exposure and potential for cumulative damage to be ranked as a function of tsunami magnitude and source area.

CONCLUSIONS

By relying on low-cost tools and incomplete datasets for rapid implementation in the context of natural disasters, this approach works for all types of natural hazards, is easily transferable to other insular settings, can assist in guiding emergency rescue targets, and can help to elaborate future land-use planning priorities for disaster risk reduction purposes.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40677-023-00235-8.

Efficient simulation strategy to design a safer motorcycle

This work presents models and simulations of a numerical strategy for a time and cost-efficient virtual product development of a novel passive safety restraint concept for motorcycles. It combines multiple individual development tasks in an aggregated procedure. The strategy consists of three successive virtual development stages with a continuously increasing level of detail and expected fidelity in multibody and finite element simulation environments. The results show what is possible with an entirely virtual concept study-based on the clever combination of multibody dynamics and nonlinear finite elements-that investigates the structural behavior and impact dynamics of the powered two-wheeler with the safety systems and the rider's response. The simulations show a guided and controlled trajectory and deceleration of the motorcycle rider, resulting in fewer critical biomechanical loads on the rider compared to an impact with a conventional motorcycle. The numerical research strategy outlines a novel procedure in virtual motorcycle accident research with different levels of computational effort and model complexity aimed at a step-by-step validation of individual components in the future.

Sustainable Husbandry?-A Comparative LCA of Three Lamb Breeding Systems in Turkey

The agricultural sector has historically been the forefront economic sector in Turkey and is crucial for the rural sustainability and the pastures that are critical for biodiversity. However, inadequate policies and factors such as climate change and malpractices result in brittle pastures, rural-urban migration, and a declining agricultural sector. Also, pastures have been left without function and appropriated to other land uses such as quarries, energy power plants, and mines. Although the husbandry sector produces significant greenhouse gas emissions, pastures have a significant capacity of CO2 sequestration. In this study, Life cycle assessment (LCA) is applied to quantify the advantages and disadvantages of the transition between extensive and intensive production. The methodology presents a holistic analysis of the several impact categories and amounts of relevant products, services, and resource emissions along their life cycles. In order to assess the environmental effects of the lamb meat production, three sheep breeding systems in Turkey are evaluated. The study aims to promote a sustainable use of natural resources/assets without compromising the quality, competitiveness, or animal welfare and obtain recommendations for the future husbandry systems and rural development in Turkey. As an overall result, it can be stated that the intensification of sheep farming can lead to a decrease of greenhouse gas emissions per kg of meat. However, extensive sheep farming shows less impacts on soil acidification or eutrophication and can even be beneficial for erosion resistance or biodiversity if properly managed.

China's environmental solutions

China emits unproportionately high concentrations of CO₂ and, due to rapid population growth and industrialization, suffers from air, water, and soil pollution. However, many of these challenges for sustainable growth are being vigorously addressed, and China aims at a CO₂ emission peak by 2030 and carbon neutrality by 2060 ("dual carbon policy"). In addition, nation-wide programs attempt to achieve reforestation and ecological restoration. By 2025, core elements of a "bioeconomy" and a circular economy are expected to be ready. Many of these programs extend into China's international "belt-and-road" initiative (BRI). In this article, we briefly describe the present achievements of China's environmental solutions and the country's visions for a "digital, eco-friendly civilization." KEY POINTS: • China's steps towards environmental cleaning, eco-protection, and decarbonization. • Steps towards a future bioeconomy.

Modelling motor units in 3D: influence on muscle contraction and joint force via a proof of concept simulation

Functional heterogeneity is a skeletal muscle’s ability to generate diverse force vectors through localised motor unit (MU) recruitment. Existing 3D macroscopic continuum-mechanical finite element (FE) muscle models neglect MU anatomy and recruit muscle volume simultaneously, making them unsuitable for studying functional heterogeneity. Here, we develop a method to incorporate MU anatomy and information in 3D models. Virtual fibres in the muscle are grouped into MUs via a novel “virtual innervation” technique, which can control the units’ size, shape, position, and overlap. The discrete MU anatomy is then mapped to the FE mesh via statistical averaging, resulting in a volumetric MU distribution. Mesh dependency is investigated using a 2D idealised model and revealed that the amount of MU overlap is inversely proportional to mesh dependency. Simultaneous recruitment of a MU’s volume implies that action potentials (AP) propagate instantaneously. A 3D idealised model is used to verify this assumption, revealing that neglecting AP propagation results in a slightly less-steady force, advanced in time by approximately 20 ms, at the tendons. Lastly, the method is applied to a 3D, anatomically realistic model of the masticatory system to demonstrate the functional heterogeneity of masseter muscles in producing bite force. We found that the MU anatomy significantly affected bite force direction compared to bite force magnitude. MU position was much more efficacious in bringing about bite force changes than MU overlap. These results highlight the relevance of MU anatomy to muscle function and joint force, particularly for muscles with complex neuromuscular architecture.

The effect of Caspian Sea water on mechanical properties and durability of concrete containing rice husk ash, nano [Formula: see text], and nano [Formula: see text]

Various studies have been recently conducted aiming at developing more sustainable cementitious systems so that concrete structures may not have a negative effect on the environment and are decomposed. It has been attempted to build sustainable binders by substituting silica fume, cement with fly ash, nano-silica, nano-alumina, and rice husk ash. In this paper, a series of experiments on concrete with different contents of rice husk ash (10%, 15%, and 20%), nano[Formula: see text] (1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%), and nano[Formula: see text] (1%, 2%, 3%, 4%) are performed to analyze the durability and mechanical properties of samples under the curing condition of Caspian seawater. The workability, density, water penetration, chloride ion penetration, and compressive strength (at 7, 14, 28, and 90 day) of the samples were determined. The experimental results showed that workability decreased gradually with increasing additives content, while the compressive gradually increased. Among the additives, adding 8% of the nano[Formula: see text] had the most significant effect on the improvement of compressive strength. Adding 8% nano[Formula: see text] and 4% nano[Formula: see text] reduced the depth of water permeability by 53% and 30%, respectively. Furthermore, adding 8% nano[Formula: see text] reduced chloride ion penetration by 85%.

Research on Rhetorical Devices in German: The Use of Rhetorical Questions in Sales Presentations

Previous literature recommends using stylistic (or rhetorical) devices in presentations such as rhetorical questions (RQs: Does anyone want bad teeth?) to make them more professional, to appear more charismatic, and to convince an audience. However, in oral presentations, it is not only the what that matters in using stylistic devices like RQs, but also the how, i.e., the RQs' prosodic realization. To date, however, virtually no handbook on the way of giving a good presentation scrutinizes this prosodic how. Therefore, our investigation focuses on the prosodic realization of German RQs in sales pitches. Specifically, we carry out a perception experiment in which 72 listeners rated both the sales pitch and its speaker based on presentations that contained questions that were lexically biased towards a rhetorical interpretation. They were realized with either the prosody of RQs or information-seeking questions (ISQs: What time is it?). An additional baseline condition was constituted by regular declarative statements with the corresponding prosody. More precisely, we investigate whether particular identified prosodic realizations-previously found for German RQs and ISQs-meet the listeners' expectation in the context of a presentation situation. We found that listeners prefer lexically marked RQs that are produced with a prosody that is characteristic of German ISQs. We therefore suggest that handbooks should provide their readers not only with clear definitions of RQs as a stylistic device in presentations (i.e., the what), but also with the respective prosodic realization (i.e., the how) to make them a properly implemented stylistic device.

Glioblastoma, from disease understanding towards optimal cell-based in vitro models

Background

Glioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and treatment options initially can be evaluated pre-clinically. Here, we provide a concise overview of glioblastoma epidemiology, disease classification, the challenges faced in the treatment of glioblastoma and current novel treatment strategies. From this, we lead into a description and assessment of advanced cell-based models that aim to narrow the gap between pre-clinical and clinical studies. Such invitro models are required to deliver reliable and meaningful data for the development and pre-validation of novel therapeutics and treatments.

Conclusions

The toolbox for GBM cell-based models has expanded substantially, with the possibility of 3D printing tumour tissues and thereby replicating invivo tissue architectures now looming on the horizon. A comparison of experimental cell-based model systems and techniques highlights advantages and drawbacks of the various tools available, based on which cell-based models and experimental approaches best suited to address a diversity of research questions in the glioblastoma research field can be selected.

Autonomous robotic additive manufacturing through distributed model-free deep reinforcement learning in computational design environments

The objective of autonomous robotic additive manufacturing for construction in the architectural scale is currently being investigated in parts both within the research communities of computational design and robotic fabrication (CDRF) and deep reinforcement learning (DRL) in robotics. The presented study summarizes the relevant state of the art in both research areas and lays out how their respective accomplishments can be combined to achieve higher degrees of autonomy in robotic construction within the Architecture, Engineering and Construction (AEC) industry. A distributed control and communication infrastructure for agent training and task execution is presented, that leverages the potentials of combining tools, standards and algorithms of both fields. It is geared towards industrial CDRF applications. Using this framework, a robotic agent is trained to autonomously plan and build structures using two model-free DRL algorithms (TD3, SAC) in two case studies: robotic block stacking and sensor-adaptive 3D printing. The first case study serves to demonstrate the general applicability of computational design environments for DRL training and the comparative learning success of the utilized algorithms. Case study two highlights the benefit of our setup in terms of tool path planning, geometric state reconstruction, the incorporation of fabrication constraints and action evaluation as part of the training and execution process through parametric modeling routines. The study benefits from highly efficient geometry compression based on convolutional autoencoders (CAE) and signed distance fields (SDF), real-time physics simulation in CAD, industry-grade hardware control and distinct action complementation through geometric scripting. Most of the developed code is provided open source.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41693-022-00069-0.

Investigating the spatial resolution of EMG and MMG based on a systemic multi-scale model

While electromyography (EMG) and magnetomyography (MMG) are both methods to measure the electrical activity of skeletal muscles, no systematic comparison between both signals exists. Within this work, we propose a novel in silico model for EMG and MMG and test the hypothesis that MMG surpasses EMG in terms of spatial selectivity, i.e. the ability to distinguish spatially shifted sources. The results show that MMG provides a slightly better spatial selectivity than EMG when recorded directly on the muscle surface. However, there is a remarkable difference in spatial selectivity for non-invasive surface measurements. The spatial selectivity of the MMG components aligned with the muscle fibres and normal to the body surface outperforms the spatial selectivity of surface EMG. Particularly, for the MMG’s normal-to-the-surface component the influence of subcutaneous fat is minimal. Further, for the first time, we analyse the contribution of different structural components, i.e. muscle fibres from different motor units and the extracellular space, to the measurable biomagnetic field. Notably, the simulations show that for the normal-to-the-surface MMG component, the contribution from volume currents in the extracellular space and in surrounding inactive tissues, is negligible. Further, our model predicts a surprisingly high contribution of the passive muscle fibres to the observable magnetic field.

Metrics and Algorithms for Locally Fair and Accurate Classifications using Ensembles

To obtain accurate predictions of classifiers, model ensembles comprising multiple trained machine learning models are nowadays used. In particular, dynamic model ensembles pick the most accurate model for each query object, by applying the model that performed best on similar data. Dynamic model ensembles may however suffer, similarly to single machine learning models, from bias, which can eventually lead to unfair treatment of certain groups of a general population. To mitigate unfair classification, recent work has thus proposed fair model ensembles, that instead of focusing (solely) on accuracy also optimize global fairness. While such global fairness globally minimizes bias, imbalances may persist in different regions of the data, e.g., caused by some local bias maxima leading to local unfairness.

Therefore, we extend our previous work by including a framework that bridges the gap between dynamic model ensembles and fair model ensembles. More precisely, we investigate the problem of devising locally fair and accurate dynamic model ensembles, which ultimately optimize for equal opportunity of similar subjects. We propose a general framework to perform this task and present several algorithms implementing the framework components. In this paper we also present a runtime-efficient framework adaptation that keeps the quality of the results on a similar level. Furthermore, new fairness metrics are presented as well as detailed informations about necessary data preparations.

Our evaluation of the framework implementations and metrics shows that our approach outperforms the state-of-the art for different types and degrees of bias present in training data in terms of both local and global fairness, while reaching comparable accuracy.

Addressing Single Nuclear Spins Quantum Memories by a Central Electron Spin

Nuclei surrounding single electron spins are valuable resources for quantum technology. For application in this area, one is often interested in weakly coupled nuclei with coupling strength on the order of a few 10-100 kHz. In this paper, we compare methods to address single nuclear spins with this type of hyperfine coupling to a single electron spin. To achieve the required spectral resolution, we specifically focus on two methods, namely dynamical decoupling and correlation spectroscopy. We demonstrate spectroscopy of two single nuclear spins and present a method to derive components of their hyperfine coupling tensor from those measurements.

Cross-bridge mechanics estimated from skeletal muscles' work-loop responses to impacts in legged locomotion

Legged locomotion has evolved as the most common form of terrestrial locomotion. When the leg makes contact with a solid surface, muscles absorb some of the shock-wave accelerations (impacts) that propagate through the body. We built a custom-made frame to which we fixated a rat (Rattus norvegicus, Wistar) muscle (m. gastrocnemius medialis and lateralis: GAS) for emulating an impact. We found that the fibre material of the muscle dissipates between 3.5 and [Formula: see text] ranging from fresh, fully active to passive muscle material, respectively. Accordingly, the corresponding dissipated energy in a half-sarcomere ranges between 10.4 and [Formula: see text], respectively. At maximum activity, a single cross-bridge would, thus, dissipate 0.6% of the mechanical work available per ATP split per impact, and up to 16% energy in common, submaximal, activities. We also found the cross-bridge stiffness as low as [Formula: see text], which can be explained by the Coulomb-actuating cross-bridge part dominating the sarcomere stiffness. Results of the study provide a deeper understanding of contractile dynamics during early ground contact in bouncy gait.

Soft Urinary Bladder Phantom for Endoscopic Training

Bladder cancer (BC) is the main disease in the urinary tract with a high recurrence rate and it is diagnosed by cystoscopy (CY). To train the CY procedures, a realistic bladder phantom with correct anatomy and physiological properties is highly required. Here, we report a soft bladder phantom (FlexBlad) that mimics many important features of a human bladder. Under filling, it shows a large volume expansion of more than 300% with a tunable compliance in the range of 12.2 ± 2.8 - 32.7 ± 5.4 mL cmH2O-1 by engineering the thickness of the bladder wall. By 3D printing and multi-step molding, detailed anatomical structures are represented on the inner bladder wall, including sub-millimeter blood vessels and reconfigurable bladder tumors. Endoscopic inspection and tumor biopsy were successfully performed. A multi-center study was carried out, where two groups of urologists with different experience levels executed consecutive CYs in the phantom and filled in questionnaires. The learning curves reveal that the FlexBlad has a positive effect in the endourological training across different skill levels. The statistical results validate the usability of the phantom as a valuable educational tool, and the dynamic feature expands its use as a versatile endoscopic training platform.

Influence of layer separation on the determination of stomach smooth muscle properties

Uniaxial tensile experiments are a standard method to determine the contractile properties of smooth muscles. Smooth muscle strips from organs of the urogenital and gastrointestinal tract contain multiple muscle layers with different muscle fiber orientations, which are frequently not separated for the experiments. During strip activation, these muscle fibers contract in deviant orientations from the force-measuring axis, affecting the biomechanical characteristics of the tissue strips. This study aimed to investigate the influence of muscle layer separation on the determination of smooth muscle properties. Smooth muscle strips, consisting of longitudinal and circumferential muscle layers (whole-muscle strips [WMS]), and smooth muscle strips, consisting of only the circumferential muscle layer (separated layer strips [SLS]), have been prepared from the fundus of the porcine stomach. Strips were mounted with muscle fibers of the circumferential layer inline with the force-measuring axis of the uniaxial testing setup. The force-length (FLR) and force-velocity relationships (FVR) were determined through a series of isometric and isotonic contractions, respectively. Muscle layer separation revealed no changes in the FLR. However, the SLS exhibited a higher maximal shortening velocity and a lower curvature factor than WMS. During WMS activation, the transversally oriented muscle fibers of the longitudinal layer shortened, resulting in a narrowing of this layer. Expecting volume constancy of muscle tissue, this narrowing leads to a lengthening of the longitudinal layer, which counteracted the shortening of the circumferential layer during isotonic contractions. Consequently, the shortening velocities of the WMS were decreased significantly. This effect was stronger at high shortening velocities.

An extensible lattice Boltzmann method for viscoelastic flows: complex and moving boundaries in Oldroyd-B fluids

 Most biological fluids are viscoelastic, meaning that they have elastic properties in addition to the dissipative properties found in Newtonian fluids. Computational models can help us understand viscoelastic flow, but are often limited in how they deal with complex flow geometries and suspended particles. Here, we present a lattice Boltzmann solver for Oldroyd-B fluids that can handle arbitrarily shaped fixed and moving boundary conditions, which makes it ideally suited for the simulation of confined colloidal suspensions. We validate our method using several standard rheological setups and additionally study a single sedimenting colloid, also finding good agreement with the literature. Our approach can readily be extended to constitutive equations other than Oldroyd-B. This flexibility and the handling of complex boundaries hold promise for the study of microswimmers in viscoelastic fluids.

Synthesis of (R)-mandelic acid and (R)-mandelic acid amide by recombinant E. coli strains expressing a (R)-specific oxynitrilase and an arylacetonitrilase

OBJECTIVES

Chiral 2-hydroxycarboxylic acids and 2-hydroxycarboxamides are valuable synthons for the chemical industry.

RESULTS

The biocatalytic syntheses of (R)-mandelic acid and (R)-mandelic acid amide by recombinant Escherichia coli clones were studied. Strains were constructed which simultaneously expressed a (R)-specific oxynitrilase (hydroxynitrile lyase) from the plant Arabidopsis thaliana together with the arylacetonitrilase from the bacterium Pseudomonas fluorescens EBC191. In addition, recombinant strains were constructed which expressed a previously described acid tolerant variant of the oxynitrilase and an amide forming variant of the nitrilase. The whole cell catalysts which simultaneously expressed the (R)-specific oxynitrilase and the wild-type nitrilase transformed in slightly acidic buffer systems benzaldehyde plus cyanide preferentially to (R)-mandelic acid with ee-values > 95%. The combination of the (R)-specific oxynitrilase with the amide forming nitrilase variant gave whole cell catalysts which converted at pH-values ≤ pH 5 benzaldehyde plus cyanide with a high degree of enantioselectivity (ee > 90%) to (R)-mandelic acid amide. The acid and the amide forming catalysts also converted chlorinated benzaldehydes with cyanide to chlorinated mandelic acid or chlorinated mandelic acid amides.

CONCLUSIONS

Efficient systems for the biocatalytic production of (R)-2-hydroxycarboxylic acids and (R)-2-hydroxycarboxamides were generated.

A universal polyphosphate kinase: PPK2c of Ralstonia eutropha accepts purine and pyrimidine nucleotides including uridine diphosphate

Polyphosphosphate kinases (PPKs) catalyse the reversible transfer of the γ-phosphate group of a nucleoside-triphosphate to a growing chain of polyphosphate. Most known PPKs are specific for ATP, but some can also use GTP as a phosphate donor. In this study, we describe the properties of a PPK2-type PPK of the β-proteobacterium Ralstonia eutropha. The purified enzyme (PPK2c) is highly unspecific and accepts purine nucleotides as well as the pyridine nucleotides including UTP as substrates. The presence of a polyP primer is not necessary for activity. The corresponding nucleoside diphosphates and microscopically detectable polyphosphate granules were identified as reaction products. PPK2c also catalyses the formation of ATP, GTP, CTP, dTTP and UTP from the corresponding nucleoside diphosphates, if polyP is present as a phosphate donor. Remarkably, the nucleoside-tetraphosphates AT(4)P, GT(4)P, CT(4)P, dTT(4)P and UT(4)P were also detected in substantial amounts. The low nucleotide specificity of PPK2c predestines this enzyme in combination with polyP to become a powerful tool for the regeneration of ATP and other nucleotides in biotechnological applications. As an example, PPK2c and polyP were used to replace ATP and to fuel the hexokinase-catalysed phosphorylation of glucose with only catalytic amounts of ADP. KEY POINTS: • PPK2c of R. eutropha can be used for regeneration of any NTP or dNTP. • PPK2c is highly unspecific and accepts all purine and pyrimidine nucleotides. • PPK2c forms polyphosphate granules in vitro from any NTP.

Enhanced composting as a way to a climate-friendly management of coffee by-products

This study investigated the performance of aerobic windrow systems by using coffee by-products and green waste to reduce gaseous emissions. Thereafter, a comparison with the current treatment and gaseous emissions at a Coffee Mill in Costa Rica was made. Two different studies where performed in Germany (pile I and II) and one study in a Coffee Mill in Costa Rica (pile III). Temperature, water content, and pH were the key parameters controlled over 35 days in all the systems. Moreover, CH₄ emission rates were quantified by a FTIR and by a portable gas detector device where the emissions reached values 100 times higher when coffee by-products as a unique material for the composting process was used. Results show that highest emission rates during the composting process for pile I was 0.007 g(m²)^-1 h^-1, for pile II 0.006 g(m²)^-1 h^-1, and for pile III 3.1 g(m²)^-1 h^-1. It was found that CH₄ emissions could be avoided if the mixture and the formation of the windrow piles were performed following the key parameter for composting, and the usage of additional material is used. With this, the reduction of CH₄ emissions at the Mill in Costa Rica could be achieved in the future.