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Do (Not) Tell Me About My Insecurities: Assessing the Status Quo of Coordinated Vulnerability Disclosure in Germany Amid New EU Cybersecurity Regulations
Get PDFValidation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions
Get PDFCurrent land surface temperature (LST) products, estimated by sensors on board satellites,
show a trade-off between their spatial and temporal resolution. If the spatial resolution
is high (i.e., around 100 m), the LST product is delivered every 2 weeks, and for those
LST products estimated daily, its spatial resolution is 1 km. Current spatial and temporal
resolutions are not adequate for disciplines such as high-precision agriculture, urban
decision making, and planning how to mitigate the overheating of cities, for which LST
maps at 50–100 m resolution every few days are desirable. This situation has led to the
development of disaggregation techniques in order to enhance the spatial resolution of
daily LST products. Unfortunately, disaggregation techniques are usually complex since
they rely on a number of external inputs and computer resources and are difficult to apply
in practice. To our knowledge, there are only two operative downscaled 10 m LST products
available to the end user, which are implemented in the Google Earth Engine (GEE) tool.
They are the Daily Ten-ST-GEE and LST-downscaling-GEE systems. This study provides
a critical benchmark by performing the first direct intercomparison and rigorous in situ
validation of these two operative GEE systems. The validation, conducted with reference
temperature data from dedicated field campaigns over contrasting agricultural sites in
Spain, showed a good correlation of both methods with a R2 of 0.74 for Daily Ten-ST-GEE
and 0.94 for LST-downscaling-GEE, but the poor results of the first method in a highly
heterogeneous site (RMSE of 5.8 K) make the second method the most suitable (RMSE of
3.6 K) for obtaining high-spatiotemporal-resolution LST maps
Investigation of Oxide Dispersion Strengthening Effect on the Strength of Diffusion‐Bonded AISI304 Parts
Get PDFIn this article, experiments for reinforcing diffusion-bonded AISI304 parts by the oxide dispersion strengthening (ODS) effect (oxide dispersion strengthened) are performed. Small particles, insoluble with temperature, act as obstacles for the dislocation movement. Thin sheet material as a carrier for ceramic particles of different sizes (0.5 and 50 μm, respectively) is used as an interlayer in diffusion bonding experiments. Furthermore, ceramic particles facilitate penetration of stable passivation layers, enabling atomic diffusion across bonding planes. However, a ceramic–metallic interface cannot transfer mechanical load. Hence, the strengthening effect must exceed the weakening of the cross-sectional area caused by the ceramic particles. It is found that an equal distribution of ceramic particles in the interlayer is challenging. Dip coating for 0.5 μm alumina is more suited than a mechanical arrangement of beads several tens of micrometers in size in etched holes or calottes. Samples fail in the interface region due to imperfect inclusion of ceramic particles. It turns out that it is difficult to separate the impact of the smaller grain size of the thin sheet material compared to round stock (Hall–Petch relation) on the one hand from the reinforcing effect from the incorporation of ceramic particles
Selective Concept Bottleneck Models Without Predefined Concepts
Get PDFConcept-based models like Concept Bottleneck Models (CBMs) have garnered significant interest for improving model interpretability by first predicting human-understandable concepts before mapping them to the output classes. Early approaches required costly concept annotations. To alleviate such, recent methods utilized large language models to automatically generate class-specific concept descriptions and learned mappings from a pretrained black-box model’s raw features to these concepts using vision-language models. However, these approaches assume prior knowledge of which concepts the black-box model has learned. In this work, we discover the concepts encoded by the model through unsupervised concept discovery techniques instead. We further propose an input-dependent concept selection mechanism that dynamically retains a sparse set of relevant concepts for each input, enhancing both sparsity and interpretability. Our approach not only improves downstream performance but also needs significantly fewer concepts for accurate classification. Lastly, we show how large vision-language models can guide the editing of our models\u27 weights to correct errors
Selective hydrogen isotope exchange on sulfonamides, sulfilimides and sulfoximines by electrochemically generated bases
Get PDFWe present a mild, metal-free electrochemical method to selec-
tively add deuterium to the position α of the sulfur atom in sulfo-
namides, sulfilimides, and sulfoximines using a simple two-elec-
trode setup under galvanostatic conditions. Our method is based
on readily available NMR solvent DMSO-d6 as the deuterium
source and reusable glassy carbon electrodes. A low current
density ensures functional group tolerance and enables selective
incorporation of deuterium into pharmaceutically relevant moi-
eties. With deuterium incorporation up to 97% the method stands
out as a new possibility to label molecules electrochemically
without the use of toxic and expensive transition-metal catalysts
Terbium and Vanadium Metal Nanoparticles Reactive Starting Materials for Liquid‐Phase Syntheses
Get PDFLanthanide metals and early transition metals – although in principle highly reactive – only show a limited reactivity due to small surface, low solubility, and/or passivation. To this regard, small-sized metal nanoparticles can give the opportunity for reactions near room temperature in the liquid phase. With terbium-metal nanoparticles (2.8 ± 0.4 nm) and vanadium-metal nanoparticles (1.2±0.2 nm), representative lanthanide and early-transition metals are presented with different reactivity. Both are prepared by reduction of simple precursors (TbCl, VCl) in THF. The Tb(0)/V(0) nanoparticles are highly reactive and used as starting materials in the liquid phase (THF, toluene, n-dodecane, ionic liquid) to perform reactions with cyclopentadienyl precursors [CpMCl] and carbonyl precursors [M(CO)] (M = Mo, W). As a result, the novel compounds [BMIm][CpMo(GaCl)] 1), [BMIm][CpW(GaCl)] 2), [CpMo{GaCl(THF)}] 3), [BMIm][CpMoGaCl] 4), [VO(HCyclal)Mo(CO)] 5) and [VO(HCyclal)W(CO)] 6) are obtained, containing metal-metal bonding (Mo–Ga, W–Ga) and/or low-valent metals (Mo(0/I), W(0/I), Ga(III)). Profound characterization of structure and bonding is performed (including TEM, XRD, FT-IR, DFT, MS, and ESR). Tb(0)/V(0) nanoparticles, in general, offer high potential for reactions/compounds different from the bulk lanthanide/transition metals and, specifically, for obtaining metal-metal bonding and low-valent metal compounds via a novel redox approach
Global Heatwaves Dynamics Under Climate Change Scenarios: Multidimensional Drivers and Cascading Impacts
Get PDFHeatwaves are intensifying globally due to climate change. However, the contributions of large-scale atmospheric processes and land-atmosphere interactions to heatwave dynamics and their cascading impacts on water resources and human exposure are not fully understood. This study investigates heatwave frequency (HWF) across 50 global regions, spanning historical (1979–2014) and future periods (2025–2060 and 2065–2100) under SSP 370 (regional rivalry) and SSP 585 (fossil-fuel development) scenarios. Using bias-corrected general circulation model simulations and reconstructed terrestrial water storage (TWS) data, we quantify the contributions of atmospheric processes to HWF modulation and assess the impacts of HWF and temperature changes on water storage deficits using TWS drought severity index (TWS-DSI) and standardized temperature index (STI). We show that Western Central Asia exhibits moisture divergence driven by significant positive thermodynamic effects, which correlates with increased HWF. In West Africa, moisture flux divergence at 1,000 hPa accounts for 45% of HWF variability, while relative humidity at 300 hPa explains 58% of HWF changes in East Asia. HWF and STI strongly influence TWS-DSI, with high STI intensifying TWS deficits. Concurrent high HWF and wet conditions in Western North America are linked to atmospheric blocking and hydrological persistence, highlighting complex illative mechanisms. We project population exposure to HWF to rise tenfold globally by 2100, with regions such as South Asia experiencing over 100% increases due to combined climate and population effects. These findings emphasize the need for tailored adaptation strategies to mitigate heatwave impacts and ensure resilience in a warming worl
Theoretical calculations to identify and design transition metal-based additives for hydrogen storage materials
Get PDFThis study demonstrates the successful design of transition metal boride-based additives to enhance the hydrogen absorption and desorption kinetics of hydrogen storage materials. Density functional theory (DFT) was used to predict a range of boride compounds, with (Ta:Ti)B2 and (Nb:Ti)B2 identified as promising candidates. In particular, the Nb1/2Ti1/2B2 and Ta1/2Ti1/2B2 compositions significantly improve the kinetic properties of the 2LiH-MgB2 (LiMgB) system. When small amount of these additives is incorporated into LiMgB, its kinetics is improved twice in comparison to the undoped material while maintaining stable reversibility. This substantial improvement is attributed to the presence of Nb1/2Ti1/2B2 and Ta1/2Ti1/2B2 nanoparticles, which act as heterogeneous nucleation sites for MgB2. The study highlights how computational methods can accelerate the design and discovery of optimal additive compositions for hydrogen storage, minimizing the need for extensive experimental testing
