A data-driven two-microphone method for in situ sound absorption measurements of porous materialsa).

This work presents a data-driven approach to estimating the sound absorption coefficient of an infinite porous slab using a neural network and a two-microphone measurement on a finite porous sample. A one-dimensional-convolutional network predicts the sound absorption coefficient from the complex-valued transfer function between the sound pressure measured at the two microphone positions. The network is trained and validated with numerical data generated by a boundary element model using the Delany-Bazley-Miki model, demonstrating accurate predictions for various numerical samples.

DARTS: Multi-year database of AI-detected retrogressive thaw slumps in the circum-arctic permafrost region.

Retrogressive Thaw Slumps (RTS) are widespread mass-wasting hillslope failures triggered by thawing permafrost. While regional studies have provided insights into the spatial distribution and dynamics of RTS, a consistent and unbiased quantification and monitoring remains unsolved at pan-arctic scales. We present the Database of AI-detected Arctic RTS footprints (DARTS), comprising ~43,000 individual footprints of active RTS or active areas within larger RTS landforms.

Patient-specific prediction of regional lung mechanics in ARDS patients with physics-based models: A validation study.

Lung-protective ventilation significantly influences outcomes in ARDS patients, but identifying optimal settings remains a challenge due to pronounced inter- and intra-patient variability in lung anatomy and pathophysiology. This study demonstrates that physics-based computational lung models tailored to individual patients can predict otherwise unobservable local lung states, enabling a quantitative analysis of regional ventilation and the mechanical load experienced by lung parenchyma during ventilation. For seven mechanically ventilated ARDS patients, patient-specific computational models were generated using chest CT scan and ventilatory waveform data.

Optimal passive metamaterial selection for electric-Vertical-Take-Off-and-Landing aircraft: A filtering concepta).

Electric-Vertical-Take-Off-and-Landing (eVTOL) aircraft represent a cutting-edge innovation in modern aviation, potentially transforming future mobility. Among the key propulsion technologies for eVTOLs, ducted fans offer efficiency and compact design. However, controlling the noise from these fans remains a significant challenge due to space and weight constraints.

Red noise in continuous-time stochastic modelling.

The concept of time-correlated noise is important to applied stochastic modelling. Nevertheless, there is no generally agreed-upon definition of the term red noise in continuous-time stochastic modelling settings. We present here a rigorous argumentation for the Ornstein-Uhlenbeck process integrated against time ( ) as a uniquely appropriate red noise implementation.

Monitoring of the Single-Cell Behavior of an Reporter Strain Producing L-phenylalanine in a Scale-Down Bioreactor by Automated Real-Time Flow Cytometry.

Large-scale bioprocesses often suffer from spatial heterogeneities, which impact microbial performance and often lead to phenotypic population heterogeneity. To better understand these effects at the single-cell level, this study applied, for the first time, automated real-time flow cytometry (ART-FCM) to monitor L-phenylalanine production with an triple reporter strain in a fed-batch process with glycerol as the carbon source. The strain was cultivated in both a well-mixed stirred-tank bioreactor (STR) and a scale-down two-compartment bioreactor (TCB), consisting of an STR and a coiled flow inverter (CFI) in bypass, to simulate spatial heterogeneities.

chemtrain-deploy: A Parallel and Scalable Framework for Machine Learning Potentials in Million-Atom MD Simulations.

Machine Learning Potentials (MLPs) have advanced rapidly and show great promise to transform Molecular Dynamics (MD) simulations. However, most existing software tools are tied to specific MLP architectures, lack integration with standard MD packages, or are not parallelizable across GPUs. To address these challenges, we present chemtrain-deploy, a framework that enables the model-agnostic deployment of MLPs in LAMMPS.

OASIS-UROS: Open acquisition system for IEPE sensors - upgraded, refined, and overhauled software.

continues the previously published . While still building on the microcontroller, this version improves the overall performance by switching to an SD card caching system and upgrading the analog-digital converter to an , which has a higher resolution, provides eight channels, oversampling, and software-adjustable voltage ranges. Also improved is the IEPE front-end and power supply, as well as the firmware of the acquisition system, which can now achieve a sample rate of up to 36 kHz while sampling all eight channels.

Computational Dynamic Analysis of Medial Meniscus with Redial Tear, Repair, and Meniscectomy.

Purpose: To investigate the influences of radial tears of the medial meniscus and subsequent surgical treatment (repair or meniscectomy) on the knee joint mechanics during normal walking.

Methods: An original multiscale finite element musculoskeletal model was developed to model and study an intact knee model (no RT), four meniscal RT knee models (30% RT, 45% RT, 60% RT, and 90% RT) and 3 treatment option models for 60% RT.

Results: The magnitude and location of peak contact pressure on tibial cartilage were minimally affected (within 0.

Comprehensive river cleaning: PTV analysis of a novel plastic debris removal concept in a large-scale physical model.

Plastic pollution in rivers represents a significant environmental threat, particularly in small- and medium-sized urban rivers, which account for major global riverine plastic emissions. This necessitates developing and optimizing effective countermeasures. However, limited research on existing clean-up technologies, precisely their plastic removal capabilities and hydraulic impacts on river systems, makes selecting and properly designing effective plastic removal measures challenging.

Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements.

Machine learning potentials (MLPs) can enable simulations of ab initio accuracy at orders of magnitude lower computational cost. However, their effectiveness hinges on the availability of considerable data sets to ensure robust generalization across chemical space and thermodynamic conditions. The generation of such data sets can be labor-intensive, highlighting the need for innovative methods to train MLPs in data-scarce scenarios.

Effects of Additive Manufacturing and Sterilization on Poly(p-Dioxanone) for Short-Term Application in the Intestinal Environment.

Additive manufacturing of patient specific implants made of biodegradable polymers is receiving increasing attention in the medical sector, including the trend towards manufacturing at the point-of-care. Despite this, the changes of the polymer structure and their effects on mechanical properties and degradation behavior caused by the additive manufacturing process and subsequent sterilization are still insufficiently investigated, although of key relevance for the implant's functionality. In this study, poly(p-dioxanone) (PPDO) was processed by fused filament fabrication (FFF).

Assessing the techno-economic benefits of LEMs for different grid topologies and prosumer shares.

The shift toward decentralized and renewable energy sources has introduced significant challenges to traditional power systems, necessitating innovative market designs. Local energy markets present a viable solution for integrating distributed energy resources such as photovoltaic systems, electric vehicles, and heat pumps. This study investigates the techno-economic implications of local energy markets compared to conventional market designs, focusing on their impact on average energy prices and operational peak power.

Pulverized Sewage Sludge Combustion with Potassium Chloride AdditionFate of Phosphorus, Potassium, Sulfur, and Heavy Metals.

Sewage sludge is a sink for heavy metals and plant nutrients. Thermal treatment of sewage sludge can remove heavy metals, providing a potential raw material for fertilizer production. Stationary fluidized bed combustion is a common thermal treatment for sewage sludge, with its process-related maximum temperature of 850 °C.

Impact of sensory distractions on reaction time: a comprehensive modeling approach.

Auditory distractions can significantly impact driving safety by affecting a driver's ability to focus, react, and make decisions, and consequently increase Driver's Reaction Time. The present study aims to examine the impact of such distractions using experimental data employing the Vienna Test System (VTS). Eighty drivers (70% male, 30% female) from mixed traffic environments participated, resulting in 240 data samples across two age groups (young and mature).

Application of a Rational Crystal Contact Engineering Strategy on a Poly(ethylene terephthalate)-Degrading Cutinase.

Industrial biotechnology offers a potential ecological solution for PET recycling under relatively mild reaction conditions via enzymatic degradation, particularly using the leaf branch compost cutinase (LCC) quadruple mutant ICCG. To improve the efficient downstream processing of this biocatalyst after heterologous gene expression with a suitable production host, protein crystallization can serve as an effective purification/capture step. Enhancing protein crystallization was achieved in recent studies by introducing electrostatic (and aromatic) interactions in two homologous alcohol dehydrogenases (/ADH) and an ene reductase (ER1-L1,5) produced with .

A Lightweight Bioinspired SMA-Based Grasping Mechanism for Flapping Wing MAVs.

This study presents a novel, bioinspired perching mechanism designed to enhance the landing and takeoff capabilities of flapping wing micro aerial vehicles (FWMAVs). Drawing inspiration from the human hand, the lightweight gripper integrates a compliant claw structure actuated by shape memory alloys (SMAs) that mimic muscle movement. These SMA springs act as compact, lightweight substitutes for traditional actuators like motors or solenoids.

Quantitative comparison of the total focusing method, reverse time migration, and full waveform inversion for ultrasonic imaging.

Phased array ultrasound is a widely used technique in non-destructive testing. Using piezoelectric elements as both sources and receivers provides a significant gain in information and enables more accurate defect detection. The process is called full matrix capture when all source-receiver combinations are used.

Experiment-driven simplification of Johnson-Champoux-Allard-Lafarge model for fibrous materialsa).

Widely used empirical and semi-phenomenological models lack practicality due to unstable predictions, which exhibit poor reproducibility, or reliance on numerous parameters that are not directly measurable. This paper presents an experiment-driven method to simplify the Johnson-Champoux-Allard-Lafarge (JCAL) model using a two-microphone impedance tube. Bayesian inference is applied to determine the non-acoustical parameters (i.

Rational Introduction of Electrostatic Interactions at Crystal Contacts to Enhance Protein Crystallization of an Ene Reductase.

Protein crystallization is an alternative to well-established but cost-intensive and time-consuming chromatography in biotechnological processes, with protein crystallization defined as an essential unit operation for isolating proteins, e.g., active pharmaceutical ingredients.

Automation of RNA-Seq Sample Preparation and Miniaturized Parallel Bioreactors Enable High-Throughput Differential Gene Expression Studies.

A powerful strategy to accelerate bioprocess development is to complement parallel bioreactor systems with an automated approach, often achieved using liquid handling stations. The benefit of such high-throughput experiments is determined by the employed monitoring procedures. To gain a molecular understanding of the microbial production strains in miniaturized parallel single-use bioreactors, we extended the at-line monitoring procedures to transcriptome analysis in a parallel approach using RNA-Seq.

Constitutive Models for Active Skeletal Muscle: Review, Comparison, and Application in a Novel Continuum Shoulder Model.

The shoulder joint is one of the functionally and anatomically most sophisticated articular systems in the human body. Both complex movement patterns and the stabilization of the highly mobile joint rely on intricate three-dimensional interactions among various components. Continuum-based finite element models can capture such complexity and are thus particularly relevant in shoulder biomechanics.

Improved Setup for Decolourization Experiments with Granular and Powdered Adsorbent Materials Using UV-VIS Flow-through Cells.

Textile wastewater treatment poses global challenges due to complex and costly processes, particularly in the adsorption-based decolourization step. Existing experimental methodologies for adsorption suffer from inconsistencies, hindering comparability across studies. To address this, we developed a universal setup integrating conventional adsorption methods with pharmaceutical dissolution techniques.

Agricultural load cycles: Tractor mission profiles from recorded GNSS and CAN bus data.

Agriculture is one of the main sources of greenhouse gas emissions, with agricultural machinery playing an important role through the combustion of fossil fuels. On the upside, many farmers invest in their own renewable energy generation. To leverage the renewable produced energy and cut emissions, a promising solution is the electrification of tractors.