Zixiaocheng Wang, Yan Zheng, Alexandr P. Rasnitsyn
et al.
Two new species assigned to the genus <i>Myanmarina</i> of the family Myanmarinidae are described and figured from male specimens preserved in Upper Cretaceous ambers from the Hukawng Valley of northern Myanmar. <i>Myanmarina simplex</i> sp. nov. can be distinguished by a small head, 13-segmented antennae, the first flagellomere equal to the second one in length and protibiae with a bifurcated spur. <i>Myanmarina grandis</i> sp. nov. is established based on a large head, 11-segmented antennae, the first flagellomere shorter than the second one and all tibiae with a spur and dorso-apical tooth. In addition, the key to known species of <i>Myanmarina</i> was updated.
Mu’ayyad Al Hseinat, Malek AlZidaneen, Ghassan Sweidan
The Karak Wadi Al Fayha Fault (KWF) is a major NW-trending intraplate wrench fault system extending over 325 km from Western Karak in Jordan to Wadi Al Fayha in Saudi Arabia. Structurally linked to the Precambrian Najd Fault System, the KWF has been previously mapped using field observations, gravity, magnetic, and reflection seismic methods. However, these approaches lacked the vertical resolution necessary to characterize its shallow structure, leaving its influence on recent deposits and surface topography poorly understood. This study employs reflection seismic sections integrated with a Digital Elevation Model to refine terrain analysis and enhance fault mechanism solutions for determining the regional stress field pattern. Our results provide compelling evidence of the KWF’s upward propagation into the surface, as demonstrated by deformation of the uppermost Cretaceous and Cenozoic successions, distinct geomorphic features in the Digital Elevation Model, alignment of earthquake epicenters along the fault, and active landslides associated with its movement. We suggest that the reactivation of the KWF has been influenced by changing stress fields from the Late Cretaceous (Turonian) to the present. The Northwestern Arabian plate has undergone multiple tectonic stress transitions, including WNW–ESE compression associated with the Syrian Arc Fold-Belt system (Turonian–Plio-Pleistocene) and subsequent NNE–SSW extension linked to Red Sea rifting (Neogene–present). The analysis of fault mechanism solutions suggests that the latest fault movements result from the continued activity of the Irbid Rift event (Eocene) and the Dead Sea Transform Fault since the Miocene.
Giulia Bosio, Alberto Collareta, Matteo Pedini
et al.
The Miocene Pisco Formation (East Pisco Basin, Peru) is renowned for its abundant, well-preserved fossils of marine vertebrates, representing one of the most spectacular and complete records of Neogene marine vertebrates worldwide. Here, we present a geological map at 1:10,000 scale investigating the spatial and temporal distribution of fossil vertebrates at Cerros Cadena de los Zanjones, in the Ica River Valley. Stratigraphic and paleontological analyses reveal the widespread occurrence of marine vertebrate remains in the Tortonian (10.0–8.6 Ma) P1 and Tortonian – Messinian (8.4–6.9 Ma) P2 sequences. These include 91 specimens preserved as bony elements, including cetaceans (both Odontoceti and Mysticeti), seals (Pinnipedia) and bony fishes (Osteichthyes). Elasmobranchs, including Carcharhiniformes, Lamniformes and Myliobatiformes, are represented by some 300 teeth. The P1-P2 passage is marked by faunal novelties such as the first appearance of seals. Overall, the assemblage taxonomically resembles that of the nearby, well-investigated site of Cerro Colorado.
Well-log interpretation is fundamental for subsurface characterization but remains challenged by heterogeneous tool responses, noisy signals, and limited labels. We propose WLFM, a foundation model pretrained on multi-curve logs from 1200 wells, comprising three stages: tokenization of log patches into geological tokens, self-supervised pretraining with masked-token modeling and stratigraphy-aware contrastive learning, and multi-task adaptation with few-shot fine-tuning. WLFM consistently outperforms state-of-the-art baselines, achieving 0.0041 MSE in porosity estimation and 74.13\% accuracy in lithology classification, while WLFM-Finetune further improves to 0.0038 MSE and 78.10\% accuracy. Beyond predictive accuracy, WLFM exhibits emergent layer-awareness, learns a reusable geological vocabulary, and reconstructs masked curves with reasonable fidelity, though systematic offsets are observed in shallow and ultra-deep intervals. Although boundary detection is not explicitly evaluated here, clustering analyses suggest strong potential for future extension. These results establish WLFM as a scalable, interpretable, and transferable backbone for geological AI, with implications for multi-modal integration of logs, seismic, and textual data.
Surface wave dispersion curve inversion plays a critical role in both shallow resource exploration and deep geological studies, yet it remains hindered by sensitivity to initial models and low computational efficiency. Recently, data-driven deep learning methods, inspired by advances in computer vision, have shown promising potential to address these challenges. However, the lack of large-scale, diverse benchmark datasets remains a major obstacle to their development and evaluation. To bridge this gap, we present OpenSWI, a comprehensive benchmark dataset generated through the Surface Wave Inversion Dataset Preparation (SWIDP) pipeline. OpenSWI includes two synthetic datasets tailored to different research scales and scenarios, OpenSWI-shallow and OpenSWI-deep, and an AI-ready real-world dataset for generalization evaluation, OpenSWI-real. OpenSWI-shallow, derived from the 2-D OpenFWI geological model dataset, contains over 22 million 1-D velocity profiles paired with fundamental-mode phase and group velocity dispersion curves, spanning a wide range of shallow geological structures (e.g., flat layers, faults, folds, realistic stratigraphy). OpenSWI-deep, built from 14 global and regional 3-D geological models, comprises 1.26 million high-fidelity 1-D velocity-dispersion pairs for deep-Earth studies. OpenSWI-real, compiled from open-source projects, contains two sets of observed dispersion curves with corresponding reference models, serving as a benchmark for evaluating model generalization. To demonstrate utility, we trained models on OpenSWI-shallow and -deep and evaluated them on OpenSWI-real, demonstrating strong agreement between predictions and references, which confirms the diversity and representativeness of the dataset. To advance intelligent surface wave inversion, we release the SWIDP toolbox, OpenSWI datasets, and trained models for the research community.
In this article, we comprehensively reviewed Argentina’s Vaca Muerta formation, which encompasses a geological overview, advances in extraction technologies, the potential environmental impact, and economic analysis. Detailed geological analysis is discussed, emphasizing the stratigraphy, lithology, and depositional environments of the formation, which is crucial for understanding the distribution and quality of hydrocarbon resources. The latest advancements in hydraulic fracturing and horizontal drilling are explored, which have significantly improved efficiency and increased recoverable resources. The environmental implications of these extraction methods are critically examined. This includes a discussion of the necessity of sustainable practices in hydrocarbon extraction, highlighting the balance between resource development and environmental stewardship. The economic viability of the Vaca Muerta formation is analyzed, with a focus on cost-effectiveness, market trends, and investment patterns. This section assesses the formation’s potential as a profitable venture and its impact on the global energy market. Finally, the review anticipates future technological and policy developments. The strategic importance of the Vaca Muerta formation in the global energy sector is underscored, and its potential role in shaping future hydrocarbon exploration and production strategies is examined. In short, this essay not only presents data and findings, but also contextualizes them within the broader scope of energy production, environmental sustainability, and economic viability. This comprehensive approach provides a multi-faceted understanding of the Vaca Muerta formation’s significance in the global energy landscape.
The Eastern Paratethys Konkian sedimentary successions of the Zelensky section (Taman peninsula, Russia) were investigated by cyclostratigraphy methods based on magnetic susceptibility measurements. Cyclostratigraphy is a new scientific direction in stratigraphy and sedimentology, the purpose of which is to identify astronomical cyclicity for the reconstruction geochronology using high-precision technologies. Time series analysis (Lomb-Scargle and REDFIT periodograms, wavelet) revealed statistically significant signals corresponding most likely to long-term insolation periodicities in studied sediments. In the deep-water Konkian sediments of the Zelensky section, the signal at 3.3 m corresponds to the 100-kyr eccentricity cycle. The astronomically tuned these sediments result in an average sedimentation rate of about 3.3 cm/kyr with the duration of accumulation of the Sartaganian and Veselyankian beds about 200 kyr. The obtained cyclostratigraphic results generally do not contradict the new data about the possible duration of the Konkian (Kartvelian, Sartaganian and Veselyankian beds) of about 750 kyr [Palcu et al., 2017].
Matthew Andres Moreno, Santiago Rodriguez Papa, Emily Dolson
Since the advent of modern bioinformatics, the challenging, multifaceted problem of reconstructing phylogenetic history from biological sequences has hatched perennial statistical and algorithmic innovation. Studies of the phylogenetic dynamics of digital, agent-based evolutionary models motivate a peculiar converse question: how to best engineer tracking to facilitate fast, accurate, and memory-efficient lineage reconstructions? Here, we formally describe procedures for phylogenetic analysis in both serial and distributed computing scenarios. With respect to the former, we demonstrate reference-counting-based pruning of extinct lineages. For the latter, we introduce a trie-based phylogenetic reconstruction approach for "hereditary stratigraphy" genome annotations. This process allows phylogenetic relationships between genomes to be inferred by comparing their similarities, akin to reconstruction of natural history from biological DNA sequences. Phylogenetic analysis capabilities significantly advance distributed agent-based simulations as a tool for evolutionary research, and also benefit application-oriented evolutionary computing. Such tracing could extend also to other digital artifacts that proliferate through replication, like digital media and computer viruses.