Targeting antibodies dissociate from drug delivery liposomes during blood circulation.

Despite three decades of intense research, active targeting of liposomes have not been successfully achieved in a clinical setting. A potential explanation is that the clinically used liposomes lose their targeting abilities upon circulation. Here, we investigated if DSPE-PEG anchored antibody-based targeting ligands dissociate from clinically relevant drug delivery liposomes during circulation in mice.

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-learning model for fetal growth scans using both retrospective and prospective data. We used a modified Progressive Concept Bottleneck Model with pre-established clinical concepts as explanations (feedback on image optimization and presence of anatomical landmarks) as well as segmentations (outlining anatomical landmarks).

Formic acid dehydrogenation catalysed by a novel amino-di(N-heterocyclic carbene) based Ru-CNC pincer complex.

A new Ru(II) complex featuring a novel amino-di(N-heterocyclic carbene) CNC pincer ligand, CNC-RuCl(CO) (Ru-1), has been developed and characterised in depth. Ru-1 forms an efficient and durable catalytic formic acid dehydrogenation system in combination with the ionic liquid 1-ethyl-3-methylimidazolium diethylphosphate (EMIM PO(OEt)).

Improving the accuracy of temperature measurement on TEM samples using plasmon energy expansion thermometry (PEET): Addressing sample thickness effects.

Advances in analytical scanning transmission electron microscopy (STEM) and in microelectronic mechanical systems (MEMS) based microheaters have enabled in-situ materials' characterization at the nanometer scale at elevated temperature. In addition to resolving the structural information at elevated temperatures, detailed knowledge of the local temperature distribution inside the sample is essential to reveal thermally induced phenomena and processes. Here, we investigate the accuracy of plasmon energy expansion thermometry (PEET) as a method to map the local temperature in a tungsten (W) lamella in a range between room temperature and 700 °C.

An overview of approaches for assessing the environmental sustainability of diets - a scoping review for Nordic Nutrition Recommendations 2023.

Assessing the environmental impacts of food, food systems and diets is highly complex due to the multitude of processes involved, the uncertainty in assessment models, the variability in production systems and the large range of products available. No single assessment method alone can provide a complete evidence base. The increasing number of Life Cycle Assessment and food system analyses, and more recently the integration of planetary boundaries offer insights from which we can draw some robust high-level conclusions, whilst recognising there is a need for more detailed analysis to capture the inherent nuances of more location and context-specific situations.

Editorial "Thermodynamic Optimization of Industrial Energy Systems".

Thermodynamic optimization of industrial energy systems is crucial for finding solutions to reduce energy consumption and mitigate losses, leading to environmental and economic benefits [...

A two-level resolution neural network with enhanced interpretability for freeway traffic forecasting.

Deep learning models are widely used for traffic forecasting on freeways due to their ability to learn complex temporal and spatial relationships. In particular, graph neural networks, which integrate graph theory into deep learning, have become popular for modeling traffic sensor networks. However, traditional graph convolutional networks (GCNs) face limitations in capturing long-range spatial correlations, which can hinder accurate long-term predictions.

Predicting fine-scale downstream migratory movement of Atlantic salmon smolt (Salmo salar) in front of a hydropower plant.

The Atlantic salmon (Salmo salar) is an iconic species of significant ecological and economic importance. Their downstream migration as smolts represents a critical life-history stage that exposes them to numerous challenges, including passage through hydropower plants. Understanding and predicting fine-scale movement patterns of smolts near hydropower plants is therefore essential for adaptive and effective management and conservation of this species.

On the effect of precession for magnetic differential phase contrast imaging.

The separation of diffraction effects from phase contrast is a major challenge for differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM). The application of electron beam precession has previously been proven successful in homogenizing the direct beam and improving the imaging of both long-range electric and magnetic fields. However, magnetic STEM-DPC imaging performed in a low magnification (LM) STEM mode suffers from significant aberrations of the probe forming lens and the consequent impediment of small precession angles.

Validation and demonstration of a drone-based method for quantifying fugitive methane emissions.

The development of new measurement methods to assess fugitive methane (CH) emissions from industrial sources is needed to improve our understanding of these emissions and promote mitigation practices. Drone-based measurement methods have rapidly emerged in the last few years, however, there are still challenges in finding accurate drone-based measurement approaches and assessing their suitability. This study aims to validate and demonstrate a drone-based method that simultaneously measures atmospheric gas concentrations and wind vectors while flying downwind of the emission source.

Juno Observations Set New Constraints on the Electrodynamic Interaction Between Io and Jupiter.

Juno's highly elliptical polar orbits provide unprecedented in-situ observations of the electrodynamic interaction between Jupiter and its volcanic moon Io. These observations occur in regions never sampled before both near Io's orbit and near Jupiter's ionosphere and at distances between the two. Magnetic field data obtained during multiple traversals of magnetic field lines mapping to Io's orbit reveal remarkably rich and complex magnetic signatures near flux tubes connected to Io's orbital position.

Engineering the secretome of Aspergillus niger for cellooligosaccharides production from plant biomass.

Background: Fermentation of sugars derived from plant biomass feedstock is crucial for sustainability. Hence, utilizing customized enzymatic cocktails to obtain oligosaccharides instead of monomers is an alternative fermentation strategy to produce prebiotics, cosmetics, and biofuels. This study developed an engineered strain of Aspergillus niger producing a tailored cellulolytic cocktail capable of partially degrading sugarcane straw to yield cellooligosaccharides.

Ultra-stable metal-organic framework-derived carbon nanocontainers with defect-induced pore enlargement for anti-corrosive epoxy coatings.

Zeolitic imidazolate frameworks-8 (ZIF-8) have recently gained attention as nanocontainers for encapsulating corrosion inhibitors. However, two main challenges remain unsolved, casting doubt on their suitability as nanocontainers. The first challenge is their instability in acidic and basic environments, leading to structural decomposition and the second challenge is their mass diffusion limitation caused by micropore dominance and a small aperture size of 0.

Computational Fluid Dynamics Modeling of Pressure-Retarded Osmosis: Towards a Virtual Lab for Osmotic-Driven Process Simulations.

Pressure-Retarded Osmosis (PRO) is an osmotically driven membrane-based process that has recently garnered significant attention from researchers due to its potential for clean energy harvesting from salinity gradients. The complex interactions between mixed-mode channel flows and osmotic fluxes in real PRO membrane modules necessitate high-fidelity modeling approaches. In this work, an efficient CFD framework is developed for the 3D simulation of osmotically driven membrane processes.

Setting the standard for machine learning in phase field prediction: a benchmark dataset and baseline metrics.

Phase field models are an important mesoscale method that serves as a bridge between the atomic scale and the macroscale, used for modeling complex phenomena at the microstructure level. Machine learning can be employed to accelerate these simulations, enabling faster and more efficient analyses. However, the development of new machine learning algorithms depends on access to extensive datasets.

The fabrication of freestanding complex oxide membranes: Can we avoid using water?

Unlabelled: Recent advances in fabricating scalable two-dimensional or freestanding functional materials have shown promise for their use in modern silicon-based electronics and future technologies. A growing interest is in creating freestanding complex oxide membranes using new methods like epitaxial lift-off and mechanical exfoliation to enhance their quality and integrity. Despite these advances, it remains challenging to consistently produce high-quality freestanding oxide membranes on a large scale for practical use.

Environmental sustainability of food production and consumption in the Nordic and Baltic region - a scoping review for Nordic Nutrition Recommendations 2023.

This scoping review examines environmental impacts related to food production and consumption in Nordic and Baltic countries. The overarching advice to all Nordic and Baltic countries, in line with the current body of scientific literature, is to shift to a more plant-based dietary pattern and avoid food waste. Taking into account current consumption patterns, there is a high potential and necessity to shift food consumption across the countries to minimise its environmental impact.

Formic acid dehydrogenation using Ruthenium-POP pincer complexes in ionic liquids.

Formic acid is one of the most promising candidates for the long-term storage of hydrogen in liquid form. Herein, we present a new collection of ruthenium pincer complexes of the general formula [RuHCl(POP)(PPh)] using commercially available or easy-to-synthesize tridentate xantphos-type POP pincer ligands. We applied these complexes in the dehydrogenation of formic acid to CO and H using the ionic liquid BMIM OAc (1-butyl-3-methylimidazolium acetate) as solvent under mild, reflux-free conditions.

The Role of Interface Band Alignment in Epitaxial SrTiO/GaAs Heterojunctions.

Correlated oxides are known to have remarkable properties, with a range of electronic, magnetic, optoelectronic, and photonic functionalities. A key ingredient in realizing these properties into practical technology is the effective and scalable integration of oxides with conventional semiconductors. Unlocking the full spectrum of functionality requires atomically abrupt oxide-semiconductor interfaces and intimate knowledge of their potential landscape and charge transport.

From Wet to Protective: Film Formation in Waterborne Coatings.

The importance of anticorrosive coatings cannot be overstated, as they play a vital role in safeguarding assets and infrastructure across various industries. Within this context, the emergence of waterborne (WB) coatings stands out for their paramount significance, offering a sustainable alternative to traditional solvent-based (SB) coatings and addressing pressing environmental concerns. Despite their eco-friendliness, the complexity of their film formation mechanism and the lack of understanding present challenges in enhancing the performance of waterborne coatings for corrosion protection.

Point-Spread Function Deformations Unlock 3D Localization Microscopy on Spherical Nanoparticles.

Nanoparticles (NPs) have proven their applicability in biosensing, drug delivery, and photothermal therapy, but their performance depends critically on the distribution and number of functional groups on their surface. When studying surface functionalization using super-resolution microscopy, the NP modifies the fluorophore's point-spread function (PSF). This leads to systematic mislocalizations in conventional analyses employing Gaussian PSFs.

Computationally Efficient Direction Finding for Conformal MIMO Radar.

The use of conformal arrays offers a significant advancement in Multiple-Input-Multiple-Output (MIMO) radar, enabling the placement of antennas on irregular surfaces. For joint Direction-of-Departure (DOD) and Direction-of-Arrival (DOA) estimation in conformal-array MIMO radar, the current spectrum-searching methods are computationally too expensive, while the existing rotation-invariant method may suffer from phase ambiguity caused by the non-Nyquist spacing of the sensors. In this paper, an improved rotationally invariant technique is proposed.

Dataset on Electric Road Mobility: Historical and Evolution Scenarios until 2050.

An increasing adoption of electric vehicles (EVs) is expected in the coming decades mainly due to the need to achieve carbon neutrality until 2050. However, predicting electric mobility's future is challenging due to three main factors: technological advancements, regulatory policies, and consumer behaviour. The projections presented in this study are based on several scenarios driven mainly from reports published by public entities and consultants.