196746 research outputs found
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Tools to investigate oxygen-related challenges with flavin-dependent enzymes
No full textEnzymes have multiple applications in medicine but during the past decades interest in the application of enzymes as (bio)catalysts to produce a wide range of valuable molecules in various industries has increased. Many chemical compounds (from pharmaceuticals to bulk commodities) can be produced by a series of enzymatically-catalysed chemical steps, and in many cases one of these steps is an oxidation. The use of molecular oxygen as an oxidising agent in biocatalytic processes is a double-edged approach. From one side, the oxygen is supplied to the reactor in the form of air bubbling, which is cheap, highly available and non-toxic. From the other side, bubbling air into the reaction media creates a gas-liquid interface which adsorbs enzymes and compromises their stability. Moreover, the oxygen is quite insoluble in water, which often results in oxygen-limited reactions. These aspects are the main limiting factors for the stability and kinetics of enzymes that perform oxidative biocatalysis and prevent the reaction from happening at a rate that is high/competitive enough for industrial feasibility. Therefore, we need systems to mimic and understand better these factors to try and mitigate their effects upon scale-up. In this review, we present two complementary systems to study these factors: one apparatus that ensures a constant gas-liquid interface and another one that maintains a constant oxygen partial pressure. Both can provide highly valuable information regarding the maximum rate of reaction and about the deactivation profiles of enzymes in the presence of bubbles
BugNIST a Large Volumetric Dataset for Object Detection Under Domain Shift
No full textDomain shift significantly influences the performance of deep learning algorithms, particularly for object detection within volumetric 3D images. Annotated training data is essential for deep learning-based object detection. However, annotating densely packed objects is time-consuming and costly. Instead, we suggest training models on individually scanned objects, causing a domain shift between training and detection data. To address this challenge, we introduce the BugNIST dataset, comprising 9154 micro-CT volumes of 12 bug types and 388 volumes of tightly packed bug mixtures. This dataset is characterized by having objects with the same appearance in the source and target domains, which is uncommon for other benchmark datasets for domain shift. During training, individual bug volumes labeled by class are utilized, while testing employs mixtures with center point annotations and bug type labels. Together with the dataset, we provide a baseline detection analysis, with the aim of advancing the field of 3D object detection methods
Isolation of an exopolysaccharide-producing <i>Weissella confusa</i> strain from lettuce and exploring its application as a texture modifying adjunct culture in a soy milk alternative
No full textConsumers often seek healthier options but still desire the familiar eating experience of traditional dairy. Incorporating exopolysaccharide (EPS)-producing cultures into fermented plant-based milk alternatives (PBMAs) offers a promising approach to improving the textural quality of these products. For this, it is essential that the EPS-producing cultures are able to produce EPS in the plant-based substrate. The present study screened 593 plant-derived lactic acid bacteria (LAB) for their ability to produce EPS on a soy milk agar medium. Fifteen LAB isolates (eight Weissella spp. and seven Leuconostoc spp.) exhibited high EPS production. One of the strongest EPS producers was a Weissella confusa strain, and genome sequencing revealed the presence of two potential related EPS genes. To identify the key gene responsible for EPS production in soy milk, 70,000 colonies were screened on soy milk agar and a spontaneous EPS-defective mutant was isolated. The mutant (W. confusa dsr1) had a mutation in a putative dextransucrase gene, which could encode the enzyme catalysing the transfer of glucose from sucrose into a growing chain of dextran. The mutation introduced a premature stop codon, disrupting the enzyme production. Another mutant (W. confusa sac) found during this screen had impaired acidification and growth in soy milk, which was linked to a mutation in the sucrose metabolism gene cluster. Soy milk fermentations using the W. confusa wild-type or sac mutant, significantly increased water holding capacity and viscosity. This suggests their potential to enhance EPS production in fermented PBMAs, bringing their texture closer to that of traditional dairy.</p
An experimental cascade biorefinery from orange residues: Sequential recovery of bioactive compounds, pectin, and fermentation of sugar-rich side streams using conventional and non-conventional yeasts
No full textThe valorization of fruit-derived residues under the biorefinery concept has been a topic of interest in the last years due to the presence of high value-added substances in their composition. However, feasible alternatives for their implementation at an industrial level are still being developed since the abundance of pectin and extractives has made its biorefining challenging compared to conventional lignocellulosic residues. In this study, the sequential valorization of Orange Residues (OR) in a biorefinery was evaluated following the principles of biomass cascading and considering the composition of residual streams as a valuable input to maximize recovery after each processing step, without focusing on a sole product. To extract full value from the side-streams, fermentation with conventional and non-conventional yeasts was explored. The proposed biorefinery sequence produced essential oils, phenolic compounds, pectin, and fermentable sugars that were later converted to ethanol, xylitol, and single-cell protein. A detailed mass balance allowed to track compositional changes throughout the cascade and identify how extraction substances accumulate after each step, affecting further processing and side-stream utilization. The sequence proposed in this work extracted/transformed ∼85 % of the initial biomass into value-added products
Electric and elastic properties of low-permeability sediments
No full textAs part of the 2020 North Sea Agreement, Denmark will decommission many hydrocarbon-producing wells, necessitating the evaluation of petrophysical and elastic properties of reservoir chalks and overburden diatomaceous shales to ensure safe operations. This PhD research refined geophysical logging interpretations by studying electrolytic conduction and elasticity of fine-grained sediments like chalks and diatomites.Given the high surface area of these fine-grained sediments, initial research focused on understanding electrolytic conduction in porous media by exploring the role of the electrical double layer. This study analyzed ionic adsorption dynamics of diatomite powders which complemented complex conductivity measurements on twenty-six saltwater-saturated diatomite and chalk samples. Results indicated a significant shift in current transmission from being predominately surface-water-dominated or slightly bulkwater-dominated, to being exclusively bulk-water-dominated with increasing NaCl concentration. At high salinity, bulk water governs conduction, raising Archie’s mexponent above 1.5 and enabling the calculation of the proportion of pore space occupied by bulk versus surface water. A model predicting sample conductivity as a function of bulk water conductivity was proposed and enabled the calculation of surface conductivity. Chargeability was found to gradually decrease with increasing salinity, reflecting the dominant role of bulk water in current transmission. Although the phase shift magnitude varied with pore water salinity, the distribution patterns remained consistent, reflecting the distinct mineralogical composition of each sample.Geomechanical uniaxial compaction tests on twelve chalk samples showed that transitions in mechanical behavior could be consistently described by strain under different saturation conditions: dry, isopar-L oil-saturated, and tap-water-saturated. During these tests, significant noise and misleading wave arrivals in the recorded S-wave trains complicated the detection of the actual S-wave arrival. To add confidence in the Swave arrival detection, a method was proposed combining graphical representations of stacked wave trains. The method produced results congruent with the iso-frame modeled P-wave, shear, and bulk moduli.The principles derived from studying the electric and elastic properties of diatomites and chalks were applied to improve well log interpretation in two Danish North Sea wells: the water-saturated diatomaceous shale in the Sten-1 well and the water-wet hydrocarbon-bearing clay-rich chalk reservoir in the Boje-2C well. The composition of formation solids was quantified using cuttings or core sample information, and porosity was assessed from neutron and density logs. Applying the new electrolytic conduction model, petrophysical properties such as surface area, permeability, irreducible water saturation, water saturation, and water salinity were acquired without using Archie's m- or n-exponents. Additionally, elastic moduli calculated by sonic and density logs were substituted to dry state allowing the calculation of Biot's coefficient and vertical elastic strain; the latter facilitated the identification of significant compaction in the Sten-1 well
Data Are Missing Again—Reconstruction of Power Generation Data Using k-Nearest Neighbors and Spectral Graph Theory
No full textThe risk of missing data and subsequent incomplete data records at wind farms increases with the number of turbines and sensors. We propose here an imputation method that blends data-driven concepts with expert knowledge, by using the geometry of the wind farm in order to provide better estimates when performing nearest neighbor imputation. Our method relies on learning Laplacian eigenmaps out of the graph of the wind farm through spectral graph theory. These learned representations can be based on the wind farm layout only or additionally account for information provided by collected data. The related weighted graph is allowed to change with time and can be tracked in an online fashion. Application to the Westermost Rough offshore wind farm shows significant improvement over approaches that do not account for the wind farm layout information
Effect of drum filter mesh size on RAS water quality
No full textDrum filters play an important role in recirculating aquaculture systems (RAS) by removing particulate matter from production units. Optimizing their performance has significant importance for water quality as well as investment and running costs. One important parameter affecting both issues is the mesh size applied. This study investigates the impact of drum filter mesh size (70, 45, and 30 µm mesh size and a control group without drum filters) on water quality and system performance in a triplicate trial using rainbow trout (Oncorhynchus mykiss), for a period of eight weeks. The use of drum filters led to significantly less particulate organic matter in the RAS water (more than 60 % reduction in particles, particulate BOD, and particulate COD) as well as reduced microbial activity (50 % reduction of microbial activity in water), while no significant reduction in dissolved organic matter was observed. The removal of particulate organic matter led to improvements across most metrics studied. The study demonstrated that mechanical filters had positive effects on water quality parameters and that reducing mesh size from 70 µm to 45 µm led to further improvements in most water quality parameters, while an additional reduction to a 30 µm mesh did not further improve water quality. The findings underscore the importance of particle removal, mesh size selection, and system design to ensure the best removal rates while maintaining maximum filtration capacity. Interestingly, the changes in water quality achieved by the drum filters led to an improvement in feed utilization resulting in increased biomass production. The results suggest that optimizing drum filter mesh size, particularly utilizing 45 µm mesh, can enhance water quality and perhaps operational profitability in RAS
From density to geometry: Instance segmentation for reverse engineering of optimized structures
No full textThis paper introduces You Only Look Once v8 for Topology Optimization (YOLOv8-TO), a novel approach for reverse engineering topology-optimized structures into interpretable geometric parameters using the YOLOv8 instance segmentation model. Density-based topology optimization methods require post-processing to convert the optimal density distribution into a parametric representation for design exploration and integration with computer-aided design tools. Traditional methods such as skeletonization struggle with complex geometries and require manual intervention. YOLOv8-TO addresses these challenges by training a custom YOLOv8 model to automatically detect and reconstruct structural components from binary density distributions. The model is trained on a diverse dataset of both optimized and random structures generated using the Moving Morphable Components method. A custom reconstruction loss function based on the dice coefficient of the predicted geometry is used to train the new regression head of the model via self-supervised learning. The method is evaluated on test sets generated from different topology optimization methods, including out-of-distribution samples, and compared against a skeletonization approach. Results show that YOLOv8-TO significantly outperforms skeletonization in reconstructing visually and structurally similar designs. The method showcases an average improvement of 13.84% in the Dice coefficient, with peak enhancements reaching 20.78%. The method demonstrates good generalization to complex geometries and fast inference times, making it suitable for integration into design workflows using regular workstations. Limitations include the sensitivity to non-max suppression thresholds. YOLOv8-TO represents a significant advancement in topology optimization post-processing, enabling efficient and accurate reverse engineering of optimized structures for design exploration and manufacturing
Oil-in-water emulsion stabilized by hydrolysed black soldier fly larvae proteins:reproduction of experimental data via phase-field modelling
No full textA phase field model based on the Cahn-Hilliard equation was validated experimentally by comparison of the numerical data with experimental data of emulsions of oil in water stabilized with Black Soldier Fly Larvae Proteins (BSFLP) and protein hydrolysates. Among the model parameters, the surface tension was determined by the pendant drop method, and the mobility by two different experiments, one based on the Turbiscan Stability Index, and another one based on the history of the average d3,2, both of them throughout a 48 h period. The initial condition was built from an experimental droplet size distribution measured prior to phase separation. Results show that the model is able to quantitatively reproduce the phase separation kinetics, and provide an intuitive graphical representation of the droplet growth. Application of this procedure to other systems will allow the generalization of phase field modelling as a predictive tool for food applications
A 3D numerical investigation of the influence of the geometrical parameters of an I-beam attenuator OWC on its performance at the resonance period
No full textThe oscillating water column (OWC) is the oldest and most reliable concept for wave energy conversion. This paper investigates the hydrodynamic performance of one chamber of an I-Beam attenuator OWC at its natural frequency using fully nonlinear CFD. The effects of chamber geometry on the hydrodynamic performance are investigated by solving the unsteady Reynolds averaged Navier-Stokes equations using ANSYS-Fluent. Comparisons are made with experimental results in both a terminator and an attenuator orientation. The effects of PTO damping, chamber length, and chamber height on the hydrodynamic efficiency are investigated. Increasing the length of the chamber with constant PTO ratio improves the quality of the wave entering the chamber, while decreased length leads to stronger vortices. The optimum PTO coefficient is found to be close to that chosen for the experiments. Reducing the inner skirt height of the chamber significantly reduces all hydrodynamic parameters while a 20 % increase in the chamber's inner skirt height improves the efficiency of the OWC by about 15 %. Observations of the flow field make it clear that reducing the chamber's length can create vortices at the inlet of the OWC. The calculations highlight important nonlinear and viscous effects on the performance of an OWC chamber