Future business models for hydrogen in Swedish road transportation

Hydrogen has emerged as a potential enabler for reducing emissions in the transport sector. To fully harness its potential, stakeholders must adapt their business models to accommodate future business conditions. In our study, we focused on the Swedish road transportation sector and analyzed potential future conditions that will likely impact business models up to 2045. We outlined existing business models for hydrogen producers and hydrogen refueling station owners using the Business Model Canvas as an analytical framework. By considering policy documents, hydrogen roadmaps, scenario reports, and insights from interviews and workshops with industry experts, we identified key future business conditions. These conditions were categorized into four themes: ‘Net-Zero CO2’, ‘Mature Market’, ‘Electricity Price Volatility’, and ‘Heavy-Duty & Long-Haul’. Finally, we applied these conditions to today's business models to propose how future business models for 2045 might evolve. The main differences identified between the current and the future business models were the reduced complexity of the future business model and the opportunity to emphasize additional value offerings to fossil-free hydrogen, since the fossil-free value will be less unique in a future where fossil-free is the norm

Higher target attainment for B-lactam antibiotics in patients with Gram-negative bloodstream infections when four times actual minimum inhibitory concentrations and epidemiological cutoff values are applied compared to clinical breakpoints

IntroductionBeta-lactam antibiotics are essential in the treatment of Gram-negative bloodstream infections. The effect of beta-lactam antibiotics depends on the time of unbound antibiotic concentration above the minimal inhibitory concentration (MIC). An antibiotic concentration above MIC during the whole dosing interval (100% ƒT > MIC) has been suggested as a target for severe infections. The aim of the present study was to compare target attainment using targets derived from known MICs with standard generic targets.MethodsIn this prospective, single-center study, adult patients with Gram-negative bloodstream infection treated with cefotaxime, piperacillin/tazobactam or meropenem were eligible for inclusion. Trough antibiotic concentrations were collected during a single dosing interval and actual MIC values for the antimicrobial agent against the infecting isolate were obtained using E-tests. Epidemiological cut off values, ECOFFs, were applied from European Committee on Antimicrobial Susceptibility Testing, EUCAST, tables for isolates within the wild-type distribution. Antibiotic concentrations were measured using Liquid Chromatography tandem Mass Spectrometry. Free concentrations were estimated based on total concentrations. Two targets based on actual MICs were assessed: free trough concentrations above (1) four times the actual MIC (100% ƒT > 4MIC) or above (2) the ECOFF (100% ƒT > ECOFF). Proportions of target attainment for the MIC-based targets were compared with attainment using clinical breakpoints or PK/PD breakpoints. Treatment response was defined as clinical resolution at day 7 (No persisting signs or symptoms of infection).ResultsWe included 98 patients with a median age of 72 years. The most common microbiological finding was Escherichia coli (63%) followed by Klebsiella pneumoniae (12%). Of all patients, 77/98 patients (79%) attained 100% ƒT > 4MIC and 80/98 (82%) attained 100% ƒT > ECOFF, compared with 57/98 (58%) using 100% ƒT > EUCAST clinical breakpoints. Clinical resolution at day 7 was significantly associated with target attainment applying the target 100% ƒT > 4MIC (p = 0.013), but this was not the case when 100% ƒT > ECOFF was applied (p = 0.50).ConclusionsIn our material, higher target attainment rates were seen using targets derived from actual MICs, compared to EUCAST clinical breakpoints. Attaining 100% ƒT > 4MIC was associated with resolution of infection, but the latter finding should be interpreted cautiously

Touch in language

This study reviews the literature on TOUCH to establish an analytical framework for the study of TOUCH in communication through language. Two questions are at the heart of the study—an ontological and a methodological one: What counts as TOUCH, and how can we investigate the way we talk about TOUCH? Within the broad framework of cognitive semantics, we offer a general approach to TOUCH and identify two main types of Gestalt profiles related to the dynamicity in the Gestalt formation, namely activity and experience, in which case the former is related to external stimulation only, while the latter may be the result of external or internal stimulation

Essential Concepts for Implementing the Sustainable Development Goals : An Introduction

This A-Z Guide offers an accessible and user-friendly overview of the essential concepts and terms needed to understand the implementation of the SDGs. Crafted in the form of an encyclopaedia, the volume presents 105 entries on important concepts and terms and their links to academic and policy debates. Each entry offers basic definitions of the concept or term at issue, followed by a brief discussion with illustrative examples and forward-looking reflections on science or policy. Together, all entries serve as a key reference for a wide global audience, ranging from students and researchers to policymakers, activists, consultants and other practitioners engaged with sustainable development

Mechanically Robust Supercrystals from Antisolvent-Induced Assembly of Perovskite Nanocrystals

Ordered arrays of nanocrystals, called supercrystals, have attracted significant attention owing to the collective quantum effects arising from the coupling between neighboring nanocrystals. In particular, lead halide perovskite nanocrystals are widely used because of the combination of the optical properties and faceted cubic shape, which enables the formation of highly ordered supercrystals. The most frequently used method for the fabrication of perovskite supercrystals is based on the self-assembly of nanocrystals from solution via slow evaporation of the solvent. However, the supercrystals produced with this technique grow in random positions on the substrate. Moreover, they are mechanically soft due to the presence of organic ligands around the individual nanocrystals. Therefore, such supercrystals cannot be easily manipulated with microgrippers, which hinders their use in applications. In this work, we synthesize mechanically robust supercrystals built from cubic lead halide perovskite nanocrystals by a two-layer phase diffusion self-assembly with acetonitrile as the antisolvent. This method yields highly faceted thick supercrystals, which are robust enough to be picked up and relocated by microgrippers. We employed X-ray nanodiffraction together with high-resolution scanning electron microscopy and atomic force microscopy to reveal the structure of CsPbBr3, CsPbBr2Cl, and CsPbCl3 supercrystals assembled using the two-layer phase diffusion technique and explain their unusual mechanical robustness. Our findings are crucial for further experiments and applications in which supercrystals need to be placed in a precise location, for example, between the electrodes in an electro-optical modulator

Impact of deep learning model uncertainty on manual corrections to MRI-based auto-segmentation in prostate cancer radiotherapy

Background: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy. While methods exist to generate voxel-wise uncertainty maps from DL-based auto-segmentation models, these maps are rarely presented to clinicians. Purpose: This study aimed to evaluate the impact of DL-generated uncertainty maps on experienced radiation oncologists during the manual correction of DL-based auto-segmentation for prostate radiotherapy. Methods: Two nnUNet DL models were trained with 10-fold cross-validation on a dataset of 434 patient cases undergoing ultra-hypofractionated MRI-only radiotherapy for prostate cancer. The models performed prostate clinical target volume (CTV) and rectum segmentation. Each cross-validation model was evaluated on an independent test set of 35 patient cases. Segmentation uncertainty was calculated voxel-wise as the SoftMax standard deviation (0–0.5, n = 10) and visualized as a fixed scale color-coded map. Four experienced oncologists were asked to:. Step 1: Rate the quality of and confidence in the DL segmentations using a four- and five-point Likert scale, respectively, and edit the segmentations without access to the uncertainty map. Step 2: Repeat step 1 after at least 4 weeks, but this time with the color-coded uncertainty map available. Oncologists were asked to blend the uncertainty map with the DL segmentation and MRI volume. Segmentation edit time was recorded for both steps. In step 2, oncologists also provided free-text feedback on the benefits and drawbacks of using the uncertainty map during segmentation. A histogram analysis was performed to compare the number of voxels edited between step 1 and step 2 for different uncertainty levels (bins with 0.1 intervals). Results: The DL models achieved high-quality segmentations with a mean Dice coefficient per oncologist of 0.97–0.99, calculated between edited and unedited segmentation in step 1 for the prostate CTV and rectum. While the overall quality rating for rectum segmentations decreased slightly on a group level in step 2 compared to step 1, individual responses varied. Some oncologists rated the quality higher for the prostate CTV segmentation with the uncertainty map present, while others rated it lower. Similarly, confidence ratings varied across oncologists for prostate CTV and rectum. Decreased segmentation time was recorded for three oncologists using uncertainty maps, saving 1–2 min per patient case, corresponding to 14%–33% time reduction. Three oncologists found the uncertainty maps helpful, and one reported benefit was the ability to identify regions of interest more quickly. The histogram analysis had fewer voxel edits in regions of low uncertainty in step 2 compared to step 1. Specifically, 50% fewer voxel edits were recorded for the uncertainty region 0.0–0.1, suggesting increased trust in the DL model's prediction in these areas. Conclusions: Presenting DL uncertainty information to experienced radiation oncologists influences their decision-making, quality perception, and confidence in the DL segmentations. Regions with low uncertainty were less likely to be edited, indicating increased reliance on the model's predictions. Additionally, uncertainty maps can improve efficiency by reducing segmentation time. DL-based segmentation uncertainty can be a valuable tool in clinical practice, enhancing the efficiency of radiotherapy planning

Evaluation of Software-Optimized Protocols for Acoustic Noise Reduction During Brain MRI at 7 Tesla

Background: MR-generated acoustic noise may be particularly concerning at 7-Tesla (T) systems. Noise levels can be reduced by altering gradient output using software optimization. However, such alterations might influence image quality or prolong scan times, and these optimizations have not been well characterized. Purpose: To evaluate image quality, sound pressure levels (SPLs), and perceived noise levels when using the acoustic noise reduction technique SofTone for T2-weighted fast spin echo (T2W FSE) and three-dimensional T1-weighted turbo field echo (3D T1W TFE), and to compare with conventional imaging during 7-T brain MRI. Study Type: Prospective. Subjects: Twenty-eight volunteers underwent brain MRI, with n = 26 for image quality evaluations. Field Strength/Sequence: Conventional and SofTone versions of T2W FSE and 3D T1W TFE at 7 T. Assessment: Peak SPLs (A-weighted decibels, dBA), participant-perceived noise levels (Borg CR10-scale), qualitative image assessments by three neuroradiologists (four-graded ordinal scales), interrater reliability, and percentage agreement. Statistical Test: Paired t-test, Wilcoxon's Signed-Rank Test, and Krippendorff's alpha; p < 0.05 were considered statistically significant. Results: SofTone significantly reduced peak SPLs: from 116.3 to 97.0 dBA on T2W FSE, and from 123.7 to 101.5 dBA on 3D T1W TFE. SofTone was perceived as significantly quieter than conventional scanning. T2W FSE showed no significant differences in image quality assessments (p = 0.21–1.00), except one radiologist noting significantly less artifact interference with SofTone. General image quality remained acceptable for 3D T1W TFE, though one radiologist scored it significantly lower with SofTone (mean scores: 3.08 vs. 3.65), and two radiologists observed significantly worse white and gray matter differentiation with SofTone (mean scores: 3.19 vs. 3.54; 2.27 vs. 2.81). Data Conclusion: SofTone can significantly reduce sound intensity and perceived noise levels while maintaining acceptable image quality with T2W FSE and 3D T1W TFE in brain MRI. It appears to be an effective tool for providing a safer, quieter 7-T scan environment. Evidence Level: 4. Technical Efficacy: Stage 5

Der Iran-Israel-Krieg: Ein massives Versagen der Gegenspionage und das strategische Auseinanderbrechen der Islamischen Republik

The Iran-Israel war, launched on June 13, 2025, marked a historic intelligence failure for the Islamic Republic. Israel’s surprise offensive devastated Iran’s military leadership and exposed deep systemic flaws in its counterintelligence apparatus. The strategic collapse of the regime now raises urgent questions about its survivability and the necessity of regime change

River flow response to changing electricity demand and centralized hydropower operations in the Paranapanema River basin, Brazil

Study region: The Paranapanema River Basin, located in southeastern Brazil, is characterized by a cascade of large hydropower plants regulated by a nationally coordinated dispatch system. This basin is a representative case of reservoir-regulated rivers in the country, where multiple dams interact to supply electricity while reshaping natural flow regimes. Study focus: This study examines hydropower-induced variability in river discharge and reservoir volumes using multiresolution wavelet decomposition and signal reconstruction. By analyzing continuous records under operational conditions, the method isolates fluctuations from sub-daily to multi-annual scales. This approach moves beyond average-based analyses, providing a scale-specific view of hydropower modulation. It shows how discharge dynamics arise not only from cascade configuration but also from dispatch coordination, plant design, and hydrological conditions. New hydrological insights for the region: Results show that flow variability patterns align with electricity demand profiles, drought episodes, and institutional milestones in the Brazilian power sector. Hydropower operations display distinct signatures at different time scales, highlighting the responsiveness and complexity of reservoir management. Reconstructing signals in original units improves interpretability and supports regulatory evaluation and energy planning. The proposed framework provides a standardized and reproducible way to assess variability in reservoir-regulated systems, enhancing comparability of hydropower assessments and identifying operational dynamics that shape river flow regimes. It also supports more adaptive and ecologically grounded approaches to hydropower governance in the Paranapanema Basin and beyond