Search Results (2,410)

In this study, we investigated the impacts of typhoons on the transformation of anticyclonic eddies (AEs) into subsurface anticyclonic eddies (SAEs) in the northwestern subtropical Pacific Ocean (NWSP) based on an ocean reanalysis product and multiple satellite observations. Results suggest that while the heavy precipitation and strong positive wind stress curl (WSC) induced by the passage of typhoons may be two main driving factors that transformed shallow mixed layer depth (MLD) AEs (i.e., those shallower than 50 m at the eddy core) into SAEs, the latter played a greater role in such transformation. In addition, shallow MLD AEs with a less depressed isopycnal structure near the eddy center before the passage of typhoons were more likely to be transformed into SAEs under the impacts of typhoons. The likely timing of such transformation may be within 9 days after the passage of typhoons. For deep MLD AEs (i.e., those deeper than 80 m at the eddy core), the impacts of typhoons may be much less prominent below the mixed layer. Based on a diagnostic analysis of the vertical potential vorticity (PV) flux at the surface, we examined the mechanism and dynamic processes involved in the transformation of deep MLD AEs into SAEs under the impacts of typhoons. Results show that while typhoons played a positive role in maintaining low PV within deep MLD AEs, which was favorable for further transformation into SAEs, the diabatic process associated with the net air–sea heat flux was the crucial favorable condition for the transformation of deep MLD AEs into SAEs. Full article

Late Pennsylvanian cyclothems are documented from the carbonate platform margin in Guizhou, South China, providing a unique opportunity to study glacio-eustatic fluctuations and their impact on reef development. This paper focuses on a shallow-water, reef-bearing succession and a deep-water succession in the Houchang area of Guizhou. Fourteen microfacies, grouped into seven associations, represent distinct depositional environments. These microfacies associations exhibit vertical cyclicity, interpreted as cyclothems, similar to those observed globally, which are attributed to the waxing and waning of the Gondwana ice sheet. The cyclothems are primarily composed of sediments below the wave base within a shallow-water platform margin and deep-water settings. Those cyclothems show strong correlations with those observed in South China, Ukraine, and the North American Midcontinent, suggesting a potential connection to global glacio-eustatic processes. A brief and rapid sea-level rise during the late Kasimovian may correspond to a recently recognized global warming event. A microfacies analysis indicates that these cyclothems reflect glacial-type sea-level fluctuations ranging from 15 to 35 m. Notably, the reef-bearing cyclothems correspond to intermediate, major cyclothems identified in South China and the Midcontinent from the late Moscovian to early Kasimovian stages. The global cyclothem correlations and reef development patterns in South China suggest that intermediate, major cycles were the primary controls on reef growth and demise, while minor cycles influenced biostromes and community succession within the reefs. These findings underscore the pivotal role of the Late Paleozoic Ice Age (LPIA) in shaping reef development in far-field regions during the Late Pennsylvanian. Full article

The deep ocean harbors a group of highly diversified microbes, while our understanding of the active microbes that are real contributors to the nutrient cycle remains limited. In this study, we report eukaryotic and prokaryotic communities in ~590 m and 1130 m depths using 16S and 18S rRNA Illumina reads (miTags) extracted from 15 metagenomes (MG) and 14 metatranscriptomes (MT). The metagenomic 16S miTags revealed the dominance of Gammaproteobacteria, Alphaproteobacteria, and Nitrososphaeria, while the metatranscriptomic 16S miTags were highly occupied by Gammaproteobacteria, Acidimicrobiia, and SAR324. The consistency of the active taxa between the two depths suggests the homogeneity of the functional microbial groups across the two depths. The eukaryotic microbial communities revealed by the 18S miTags of the metagenomic data are dominated by Polycystinea; however, they were almost all absent in the 18S metatranscriptomic miTags. The active eukaryotes were represented by the Arthropoda class (at 590 m depth), Dinophyceae, and Ciliophora classes. Consistent eukaryotic communities were also exhibited by the 18S miTags of the metatranscriptomic data of the two depths. In terms of biodiversity, the ACE and Shannon indices of the 590 m depth calculated using the 18S metatranscriptomic miTags were much higher than those of the 1130 m depth, while a reverse trend was shown for the indices based on the metagenomic data. Our study reports the active microbiomes functioning in the nutrient utilization and carbon cycle in the deep-sea zone, casting light on the quantification of the ecological processes occurring in the deep ocean. Full article

The complex topography of deep sea presents numerous challenges for the accurate exploration of sub-bottom profiles. These include real-time tracking of seafloor reflectors, acquisition and storage of deep-sea long-term reflection data, and splicing of successive profiles. Based on the actual survey data of deep sea, we have developed automatic positioning and noise suppression algorithms, namely the double-difference threshold of proximity points. Furthermore, we have created automatic algorithms, namely content expansion and group data moving, based on extremum in seafloor’s depth. These have been designed to automatically suppress the random noise and effectively splice the sub-bottom profile data in deep water. The aforementioned processing techniques facilitate the enhancement of the quality of deep-water sub-bottom profile data, thereby enabling the provision of a comprehensive and successively long profile for interpretation in the context of deep-water sub-bottom profile data. Full article

In this work, we introduce the first pipeline that combines a refraction-aware structure from motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. We accurately estimate the 3D positions of the submerged points by integrating refraction geometry within the SfM optimization problem. This way, no refraction correction as post-processing is required. Experiments with simulated data that approach real-world capturing conditions demonstrate that SfM with refraction correction is extremely accurate, with submillimeter errors. We integrate our refraction-aware SfM within a deep learning framework that also takes into account radiometrical information, developing a combined spectral and geometry-based approach, with further improvements in accuracy and robustness to different seafloor types, both textured and textureless. We conducted experiments with real-world data at two locations in the southern Mediterranean Sea, with varying seafloor types, which demonstrate the benefits of refraction correction for the deep learning framework. We made our refraction-aware SfM open source, providing researchers in airborne bathymetry with a practical tool to apply SfM in shallow water areas. Full article

Acanthocepola indica, a deep-sea snake fish, is primarily found in the Indo-west Pacific region, including India, Korea, Japan, and the South China Sea. The taxonomic classification of A. indica based on morphological characteristics remains inaccurate and unclear. In this study, we utilized next-generation sequencing to generate comprehensive genomic data for A. indica. The estimated genome size of A. indica was 422.95 Mb, with a heterozygosity ratio of 1.02% and a sequence repeat ratio of 22.43%. Our analysis suggested that A. indica is diploid, and the draft genome assembly consists of 1,059,784 contigs with a contig N50 of 1942 bp. We identified a total of 444,728 simple sequence repeats in the genome of A. indica. Furthermore, we successfully assembled the complete mitochondrial genome (16,439 bp) of A. indica, which included 13 protein-coding genes, 22 tRNA genes and 2 rRNA genes. Phylogenetic analysis based on mitochondrial genomes revealed that A. indica is closely related to Acanthocepola krusensternii and Cepola schlegelii, providing evidence that the family Cepolidae belongs to the order Priacanthiformes. Population size dynamics analysis indicated that A. indica experienced a bottleneck effect during the Pleistocene Glacial Epoch, likely due to the changes in glacial cycles and sea level fluctuations since ~800 Kya. Full article

The shelf-edge trajectory is comprehensively controlled by tectonics, sediment supply, sea level, and climate fluctuations; its migration and evolution have a strong influence on what happens in the deep-water depositional system during the Quaternary. The shelf-edge trajectory pattern, sediment-budget partitioning into deep-water areas, and reservoir evaluations are focused topics in international geosciences. In this paper, the Qiongdongnan Basin (QDNB) in the northern South China Sea is taken as an example to study how shelf-edge trajectory migration patterns can influence the types of deep-water gravity flow which are triggered there. Through quantitatively delineating the Quaternary shelf-edge trajectory in the QDNB, four types of shelf-edge trajectory are identified, including low angle slow rising type, medium angle rising type, high angle sharp rising type, and retrogradation-slump type. A new sequence stratigraphic framework based on the migration pattern of shelf-edge trajectory is established. There are four (third-order) sequences in the Quaternary, and several systems tracts named lowstand systems tract (LST), transgressive systems tract (TST), and highstand system tract (HST) are identified. This study indicates that the type of deep-water gravity flow can be dominated by the shelf-edge trajectory migration patterns. When the shelf-edge trajectory angle (α) ranged between 0° and 4°, the continental canyons were mostly small-scaled and shallowly incised, with multiple large-scale sandy submarine fan deposits with few MTDs found in the deep-water area. When the angle (α) ranged from 4° < α < 35°, the size and incision depth of the continental slope canyons increased, relating to frequently interbedded sandy submarine fan deposits and MTDs. When angle (α) ranged from 35° < α < 90°, only a few deeply-incised canyons were present in the continental slope; in this condition, large-scaled and long-distance MTDs frequently developed, with fewer submarine fans deposits. When angle (α) ranged from 90° < α < 150°, the valley in the slope area was virtually undeveloped, sediments in the deep-sea plain area consisted mainly of large mass transport deposits, and submarine fan development was minimal. Since the Quaternary, the temperature has been decreasing, the sea level has shown a downward trend, and the East Asian winter monsoon has significantly enhanced, resulting in an overall increase in sediment supply in the study area. However, due to the numerous rivers and rich provenance systems in the west of Hainan Island, a growing continental shelf-edge slope has developed. In the eastern part of Hainan Island, due to fewer rivers, weak provenance sources, strong tectonic activity, and the subsidence center, a type of destructive shelf-edge slope has developed. The above results have certain theoretical significance for the study of shelf-edge systems and the prediction of deep-water gravity flow deposition type. Full article

As one of the most destructive, hazardous, and frequent marine geohazards, correctly recognizing submarine landslides holds substantial importance for regional risk assessment, disaster prevention, and marine resource development. Many conventional approaches to prediction and mapping necessitate the involvement of expert insights, oversight, and extensive field investigations, which can result in significant time and effort invested in the prediction process. This paper focuses on employing a deep neural network semantic segmentation technique to detect submarine landslides to replace previous methods, such as numerical analysis and physical modeling, to predict and identify the landslide areas quickly. The peripheral zone of the western Iberian Sea is selected as the study area. Since the neural network image recognition task usually requires RGB images as input data, factors such as slope, hillshade, and elevation extracted from digital elevation model (DEM) data are used to synthesize RGB images through band synthesis methods, and the number and diversity of data are increased utilizing data enhancement. Based on the classical semantic segmentation model DeepLabV3, this paper proposes an improved deep learning method, which strengthens the ability of model feature extraction for complex situations by adding an attention mechanism module, improving the spatial pyramid pooling module, and improving the landslide intersection over union metric from 0.4257 to 0.5219 and the F1-score metric from 0.609 to 0.6631 to achieve effective identification of submarine landslides. Full article

This study investigates the spatial and temporal distribution of the artificial radionuclides ¹²⁹I and ²³⁶U in the Western Mediterranean Sea, focusing on their connection to radionuclide sources and circulation dynamics. Taking advantage of unprecedented precision of accelerator mass spectrometry, both tracers were firstly investigated in 2013. Here, we examine tracer observations obtained along four stations (re-)visited during the TAlPro2022 expedition in May 2022. Distributions of both ¹²⁹I and ²³⁶U were related to water masses and clearly linked to local circulation patterns: a tracer-poor surface Atlantic inflow, a thining of the tracer minimum at intermediate depths, and a higher tracer signal in Western Mediterranean Deep Waters due to dense water formation in the Algero-Provençal basin. The comparison to 2013 tracer data indicated recent deep ventilation of the Tyrrhenian Sea, the mixing of deep waters and enhanced stratification in intermediate waters in the Algero-Provençal basin due to a temperature and salinity increase between 2013 and 2022. We estimate an overall ¹²⁹I increase of 20% at all depths between 0 and 500m with respect to 2013, which is not accompanied by ²³⁶U. This suggests either the lateral transport of ¹²⁹I from the Eastern Mediterranean Sea, or an additional source of this tracer. The inventories of ¹²⁹I calculated for each water mass at the four stations point to the deposition of airborne releases from the nuclear reprocessing plants (La Hague and Sellafield) on the surface Mediterranean waters as the more likely explanation for the ¹²⁹I increase. This work demonstrates the great potential of including measurements of anthropogenic radionuclides as tracers of ocean circulation. However, a refinement of the anthropogenic inputs is necessary to improve their use in understanding ventilation changes in the Mediterranean Sea. Full article

(1) Background: Detecting people and technical objects in various situations, such as natural disasters and warfare, is critical to search and rescue operations and the safety of civilians. A fast and accurate detection of people and equipment can significantly increase the effectiveness of search and rescue missions and provide timely assistance to people. Computer vision and deep learning technologies play a key role in detecting the required objects due to their ability to analyze big volumes of visual data in real-time. (2) Methods: The performance of the neural networks such as You Only Look Once (YOLO) v4-v8, Faster R-CNN, Single Shot MultiBox Detector (SSD), and EfficientDet has been analyzed using COCO2017, SARD, SeaDronesSee, and VisDrone2019 datasets. The main metrics for comparison were mAP, Precision, Recall, F1-Score, and the ability of the neural network to work in real-time. (3) Results: The most important metrics for evaluating the efficiency and performance of models for a given task are accuracy (mAP), F1-Score, and processing speed (FPS). These metrics allow us to evaluate both the accuracy of object recognition and the ability to use the models in real-world environments where high processing speed is important. (4) Conclusion: Although different neural networks perform better on certain types of metrics, YOLO outperforms them on all metrics, showing the best results of mAP-0.88, F1-0.88, and FPS-48, so the focus was on these models. Full article

Four new glycosides of polyhydroxysteroids, ceramasterosides A, B, D, and E (1–4), and two previously known compounds, ceramasteroside C₁ (5) and attenuatoside B-I (6), were isolated from an extract of a deep-sea sea star species, the orange cookie star Ceramaster patagonicus. The structures of 1–4 were elucidated by the extensive NMR and ESIMS methods. Steroid monoglycosides 1 and 2 had a common 3β,6α,8,15β,16β-pentahydroxysteroid nucleus and a C–29 oxidized stigmastane side chain and differed from each other only in monosaccharide residues. Ceramasteroside A (1) contained 3-O-methyl-4-O-sulfated β-D-xylopyranose, while ceramasteroside B (2) had 3-O-methyl-4-O-sulfated β-D-glucopyranose, recorded from starfish-derived steroid glycosides for the first time. Their biological activity was studied using a model of lipopolysaccharide-induced (LPS) inflammation in a SIM-A9 murine microglial cell line. During the LPS-induced activation of microglial cells, 1, 3, and 5, at a non-toxic concentration of 1 µM, showed the highest efficiency in reducing the production of intracellular NO, while 4 proved to be most efficient in reducing the extracellular nitrite production. All the test compounds reduced the LPS-induced malondialdehyde (MDA) production. The in vitro experiments have demonstrated, for the first time, the antioxidant activity of the compounds under study. Full article

The summer of 2024 witnessed record-high sea surface temperatures (SST) across the Aegean, Ionian, and Cretan Seas (AICS), following unprecedented air heatwaves over the sea under a long-term warming trend of 0.46 °C/decade for the mean atmospheric temperature (1982–2024). The respective mean SST trend for the same period is even steeper, increasing by 0.59 °C/decade. With mean summer surface waters surpassing 28 °C, particularly in the Ionian Sea, the southern Cretan, and northern Aegean basins, this summer marked the warmest ocean conditions over the past four decades. Despite a relatively lower number of marine heatwaves (MHWs) compared to previous warm years, the duration and cumulative intensity of these events in 2024 were the highest on record, reaching nearly twice the levels seen in 2018, which was the warmest until now. Intense MHWs were recorded, especially in the northern Aegean, with extensive biological consequences to ecosystems like the Thermaikos Gulf, a recognized MHW hotspot. The strong downward atmospheric heat fluxes in the summer of 2024, following an interannual increasing four-decade trend, contributed to the extreme warming of the water masses together with other met-ocean conditions such as lateral exchanges and vertical processes. The high temperatures were not limited to the surface but extended to depths of 50 m in some regions, indicating a deep and widespread warming of the upper ocean. Mechanisms typically mitigating SST rises, such as the Black Sea water (BSW) inflow and coastal upwelling over the eastern Aegean Sea, were weaker in 2024. Cooler water influx from the BSW decreased, as indicated by satellite-derived chlorophyll-a concentrations, while upwelled waters from depths of 40 to 80 m at certain areas showed elevated temperatures, likely limiting their cooling effects on the surface. Prolonged warming of ocean waters in a semi-enclosed basin such as the Mediterranean and its marginal sea sub-basins can have substantial physical, biological, and socioeconomic impacts on the AICS. This research highlights the urgent need for targeted monitoring and mitigation strategies to address the growing impact of MHWs in the region. Full article

AMHSs (Automated Material Handling Systems) are widely used in major Fabs (semiconductor fabrication plants). The OHT in an AMHS is responsible for handling the FOUP (Front Opening Unified Pod) within the Fabs. Due to the unidirectional track, the movement path of the OHT aims to avoid congested areas caused by operations or malfunctions as much as possible, to improve the overall FOUP handling efficiency. To do so, we propose a dynamic path planning method, MI-DDQN (Map Information Double Deep Q-Network), driven by deep reinforcement learning and based on map information. Firstly, we design and establish a map information state space model based on the core elements of the OHT path planning in the AMHS. Then, we design an OHT motion simulator to simulate the position coordinate transformation of the OHT, providing real-time coordinate update data for the OHT during the algorithm training process. We design a deep reinforcement learning algorithm structure based on map information model and a convolutional neural network model structure and use the algorithm to train the network model. Finally, the designed task generation module and OHT motion simulator are used to randomly generate the starting position and task position of the OHT during the training process to enhance the richness of the data. The addition of a “fault” OHT verifies the method’s ability to plan routes in complex road conditions such as congestion that may occur at any time. Full article

The Central Anticline Belt of the Xihu Sag is one of the structural units with the most abundant natural gas in the East China Sea Shelf Basin. However, there are significant differences among the anticline units in terms of the scale of natural gas enrichment, occurrence horizons, types of gas reservoirs, accumulation processes, and gas-bearing properties of different strata, which influence the optimization of exploration zones and the orientation of exploration in deep-buried areas. This study conducted a comprehensive analysis in terms of the structural evolution, fault activity, hydrocarbon charging stages, and process of hydrocarbon accumulation. It clarifies that (1) the preservation condition is one of the core factors for the differential enrichment of natural gas in the Central Anticline Belt. Under the background of differential compression of the Longjing Movement, late-stage and E-W-trending faults are commonly developed in the anticline cores of the strong compression area in the south, which damage the effectiveness of traps, resulting in a large amount of natural gas escaping and being locally adjusted and accumulated in shallow effective traps. The gas reservoirs show the characteristics of multiple accumulation horizons and a small scale. In the moderately strong compression area in the north, the E-W-trending faults have weak activities and shallow incision horizons. The original gas reservoirs are not damaged, and the structures are fully filled. (2) The coupling between faults and sand bodies determines the degree of oil and gas enrichment. In the weakly compressed area in the west, late-stage E-W-trending faults are not developed, and the preservation conditions are good. The main controlled faults on the flanks of the anticline are highly active, and the coupling degree between faults and sand bodies is good, resulting in a high gas saturation. However, the transport capacity in the anticline cores is relatively poor, with a low gas saturation. (3) The differences in the paleo-structural characteristics affect the degree of oil and gas enrichment. The paleo-structures formed before the Longjing Movement provided favorable conditions for the early convergence of oil and gas. Natural gas has the characteristics of multi-stage charging, and the deep gas reservoirs have higher gas saturation than the shallow ones. On this basis, this study proposed two natural gas accumulation processes developed in the Central Anticline Belt of the Xihu Sag under the background of differential compression. One is where the hydrocarbon convergence occurs first and then oil and gas transport and accumulate into the reservoirs; the other one is where the hydrocarbon convergence and accumulation occur simultaneously, followed by gas adjustment. This paper also concludes three differential accumulation models: the local enrichment and accumulation model of gas in the strongly compressed zone, the integrated enrichment and accumulation model in the medium-strongly compressed zone, and the fault–sand coupling accumulation model in the weakly compressed zone. The results of this research have great significance for the subsequent exploration, hydrocarbon enrichment style analysis, and further strategy in the deep-buried, tight to low-permeable reservoirs in ocean exploration areas. Full article

Dense polymetallic nodule fields are found in different areas of the Pacific and Indian Oceans. However, limited knowledge exists about microbial diversity, processes and functions in deep-sea polymetallic nodule sediments. This study investigated microbial diversity, composition and function in sediments from various locations and depths in a western Pacific polymetallic nodule province. Sediment cores were collected, DNA extracted, and the V3–V4 regions of the 16S rRNA gene were sequenced using Illumina MiSeq. The test results show that the abundance and diversity of microbial communities in sediments from different sites vary significantly. The dominant microbial communities at the family level in the three sediment samples were all mainly Marinobacteraceae and Alcanivoracaceae. Sediment samples from core 1 had similar microbial structures and microbial community functions. Surface sediment had higher species richness, diversity and evenness than the middle layer. The dominant phylum at different depths was consistent. There was significant spatial heterogeneity in the microbial community within sediments from polymetallic nodule regions. This study expands on our knowledge of the spatial and vertical distribution of microbial community diversity beneath polymetallic nodules in deep-sea settings. Full article