Automated driving system (ADS) deployment requires rigorous validation across safety–critical vehicle–pedestrian interactions, yet real-world datasets rarely capture high-risk scenarios while simulation platforms lack realistic behavior. In response, this study proposes a three-stage framework that combines real-world grounding with adaptive simulation to generate behaviorally realistic safety–critical scenarios at scale. Stage 1 pre-trains multi-agent state-space Transformer-enhanced DDPG (MA-SST-DDPG) agents on real-world safety–critical data to learn human-like interactive evasive behaviors through data-driven learning. Stage 2 deploys pre-trained multi-agents in CARLA for online reinforcement learning to generalize across diverse scenarios, integrating real-world knowledge with simulation experience to produce a refined MA-SST-DDPG model. Stage 3 uses CARLA with the refined model to generate over 198,000 high-resolution interaction episodes from eight intersection scenarios, culminating in the Vehicle–Pedestrian Safety-Critical Interaction (VPSCI) dataset. The Refined MA-SST-DDPG model outperformed baseline methods in reproducing realistic evasive behaviors, achieving the lowest trajectory errors (ADE = 0.072 m, FDE = 0.142 m). Statistical comparison confirmed distributional equivalence between the generated and real-world data in both conflict severity and behavioral response. A Turing test confirmed that the three-stage framework generated evasive behaviors were indistinguishable from real-world interactions. The generated data revealed realistic behavioral patterns: conflict rates rose with speed, and pedestrian yielding increased with vehicle proximity and speed—trends matching real-world observations. These results demonstrate the framework’s effectiveness in producing high-fidelity safety–critical data, offering valuable sources for the development of ADS and simulation-based safety evaluations.
We examine whether and how bidder complexity influences investor reactions to merger and acquisition (M&A) announcements. Using an established measure of complexity, we find a significant positive relationship between acquiring firm complexity and cumulative abnormal returns (CAR). This suggests that investors perceive more complex firms as capable and value-enhancing participants in M&A activities. The association is particularly strong for bidders with high operating risk, greater R&D intensity, and larger firm size. We also find that complex bidders tend to offer higher takeover premiums. Overall, our study contributes to the literature by demonstrating that bidder complexity is an important determinant of market reactions to M&A announcements.
Scorpionate ligands have been advanced significantly through systematic modifications of their apical atoms and heterocyclic arms, expanding their structural diversity and chemical reactivity. Recent biologically inspired variants now enable accurate modeling of complex bioinorganic motifs, such as the Fe4S4 clusters of nitrogenase, and support enzyme-like reactivity under mild aqueous conditions. These developments have broadened the impact of scorpionate chemistry across bioinorganic modeling, homogeneous catalysis, and biorthogonal transformations. In particular, expanded tripodal scaffolds provide modular, tunable platforms for mimicking enzyme active sites and probing biological nitrogen fixation pathways. Beyond fundamental insight, these ligands present practical opportunities for sustainable catalysis by enabling selective transformations in environmentally benign media. This concept article highlights triscatecholates as a new strategy for constructing expanded scorpionate ligand design that can guide future innovation.
Microbialites are biosedimentary structures built by microbial mats. Five microbialite groups are distinguished: stromatolites, thrombolites, dendrolites, leiloites and microbially induced sedimentary structures (MISS). This contribution discusses the two most abundant microbialite groups in marine settings, stromatolites and MISS. Microbial interactions with clastic sediment are very similar in both stromatolite and MISS formation. However, in stromatolites, syngenetic carbonate production caused by photoautotrophic and heterotrophic metabolisms and by calcimicrobes also takes place. More so, carbonate may precipitate within the extracellular polymeric substances. Due to the various carbonate forming processes as well as recrystallisation, the microscopic mat fabrics within stromatolite laminae are rarely preserved. Merely the laminae themselves remain visible. In MISS, syngenetic carbonate production commonly does not take place. However, early diagenetic mineral replacement of organic matter by heterotrophic microbes can be observed. Microscopic mat fabric in ancient MISS is well preserved, composed of minerals such as pyrite, silica and others. The early Archean record displays a high number of morphotypes of both stromatolites and MISS, such as those in the 3.48 Ga Dresser Formation, Pilbara, Western Australia. The earlier evolution of these microbialites is not recorded due to the lack of well-preserved pre-Archean sedimentary rocks. In course of Earth history, stromatolites developed hundreds of morphologies with their greatest variations in the Proterozoic time, where stromatolites were shown to be useful index fossils for biostratigraphy. MISS, however, include only 17 morphotypes that existed since the early Archean with no morphological change until the modern time. However, MISS morphologies reflect environmental and climatic conditions in great detail because their formation is strongly influenced by physical sedimentary dynamics. Therefore, MISS are valuable facies fossils.
In the Western Antarctic Peninsula (WAP), marine plankton dynamics are tightly linked to the interannual variability in environmental conditions, including phenological shifts in sea-ice seasonality. To explore these linkages, we use a 1-dimensional vertical ocean-ice-ecosystem model (KPP-Eco-Ice, or KEI) that simulates physical and ecosystem conditions at a continental shelf mooring location in the Palmer Long Term Ecological Research program sampling grid. KEI allows for year-round examination of the ecosystem in a region where in situ observations on the shelf are limited to January. Comparisons are made between seasonal sea-ice retreat, mixed layer depth, primary productivity, and phytoplankton relative abundance, grazing, and loss rates. KEI successfully captures seasonal patterns in the WAP, demonstrating that total seasonal primary production was highest following a winter with late sea-ice retreat. Stability in the surface mixed layer enables high photosynthetic rates by alleviating light limitation, while wind-induced surface mixing results in lower phytoplankton production and biomass in years with early sea-ice retreat. However, mixing reduces iron limitation in surface waters, which may influence phytoplankton species composition. Small, non-diatom phytoplankton are better-adapted to high light and low iron conditions, thriving longer in a year with late sea-ice retreat and higher seasonal primary production, while larger diatoms are more abundant in the years with early sea-ice retreat and lower seasonal production. These findings have implications for grazer populations and subsequent carbon export from the surface to depth in the WAP region. This study validates the role that sea ice plays in shaping Antarctic ecosystem dynamics.
