Characteristics of the Tan-Lu Strike-Slip Fault and Its Controls on Hydrocarbon Accumulation in the Liaodong Bay Sub-Basin, Bohai Bay Basin, China

The Tan-Lu Fault, one of the major strike-slip structures in China, controlled the development of most of the Meso-Cenozoic NNE trend rifted petroliferous basins in east China. It has cut across the Bohai Bay Basin since the late Cenozoic and played an important role in hydrocarbon accumulation and distribution in the Liaodong Bay sub-basin of the Bohai Bay Basin. The purpose of this paper is to study the geometry of the Tan-Lu strike-slip and how it affected petroleum system development in the Liaodong Bay sub-basin. The innovative seismic interpretation revealed the western branch of the Tan-Lu strike-slip fault cut through the Liaozhong depression of the sub-basin and its eastern branch superimposed on the earlier extensional boundary fault of the sub-basin. The strike-slip movement is characterized by a distinctive strike-slip zone associated with the NE en echelon faults in the central part of the Liaozhong depression and also caused the formation of the Liaodong uplift and the Liaodong depression in the east Liaodong Bay Sub-basin. Rapid movement of the Tan-Lu strike-slip fault has deepened the Liaozhong depression and facilitated the maturation of source rock. Related fault movement formed a series of structural traps and paleotopographic highs and lows that subsequently controlled sediment dispersal and the distribution of stratigraphic-related traps within sequence stratigraphic framework. Exploration practice, geochemical study and petroleum system modeling demonstrate that the Tan-Lu strike-slip and its associated faults acted as good hydrocarbon migration pathways and hydrocarbon accumulated in many traps associated with the Tan-Lu strike-slip zone. Many recent discoveries along the strike-slip zone prove that the petroleum system in Liaodong Bay Sub-basin was mainly controlled by the activity of the Tan-Lu strike-slip. The resulting hydrocarbon accumulation model in this sub-basin may provide a paradigm for the prediction of hydrocarbon accumulation to other east China basins along the Tan-Lu strike-slip fault zone. Key words: Liaodong Bay Sub-basin; Tan-Lu strike-slip fault; Hydrocarbon accumulation; Petroleum system; Sequence stratigraph

DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization

Time series remains one of the most challenging modalities in machine learning research. The out-of-distribution (OOD) detection and generalization on time series tend to suffer due to its non-stationary property, i.e., the distribution changes over time. The dynamic distributions inside time series pose great challenges to existing algorithms to identify invariant distributions since they mainly focus on the scenario where the domain information is given as prior knowledge. In this paper, we attempt to exploit subdomains within a whole dataset to counteract issues induced by non-stationary for generalized representation learning. We propose DIVERSIFY, a general framework, for OOD detection and generalization on dynamic distributions of time series. DIVERSIFY takes an iterative process: it first obtains the "worst-case" latent distribution scenario via adversarial training, then reduces the gap between these latent distributions. We implement DIVERSIFY via combining existing OOD detection methods according to either extracted features or outputs of models for detection while we also directly utilize outputs for classification. In addition, theoretical insights illustrate that DIVERSIFY is theoretically supported. Extensive experiments are conducted on seven datasets with different OOD settings across gesture recognition, speech commands recognition, wearable stress and affect detection, and sensor-based human activity recognition. Qualitative and quantitative results demonstrate that DIVERSIFY learns more generalized features and significantly outperforms other baselines.Comment: Journal version of arXiv:2209.07027; 17 page

Genome-Wide Analysis of mRNAs and lncRNAs of Intramuscular Fat Related to Lipid Metabolism in Two Pig Breeds

Background/Aims: Long non-coding RNAs (lncRNAs) can regulate adipogenesis and lipid accumulation. Intramuscular fat deposition appears to vary in different pig breeds, and the regulation mechanism has not yet been fully elucidated at molecular level. Moreover, little is known about the function and profile of lncRNAs in intramuscular fat deposition and metabolism in pig. The aim of this study was thus to explore the regulatory functions of lncRNAs in intramuscular fat deposition. Methods: In this study, Laiwu (LW) pig and Large White (LY) pig with significant difference in fat deposition were selected for use. RNA-seq technology and bioinformatics methods were used to comparatively analyze the gene expression profiles of intramuscular fat between LW and LY pigs to identify key mRNAs and lncRNAs associated with lipid metabolism and adipogenesis. Real-time fluorescence-based quantitative PCR was applied to verify the expression level of the differentially expressed mRNAs and lncRNAs. Results: A total of 513 mRNAs and 55 lncRNAs were differentially expressed between two pig breeds. By co-expression network construction as well as cis- and trans-regulated target gene analysis, 31 key lncRNAs were identified. Gene Ontology and KEGG pathway analyses revealed that differentially expressed genes and lncRNAs were mainly involved in the biological processes and pathways related to adipogenesis and lipid metabolism. Conclusion: XLOC_046142, XLOC_004398 and XLOC_015408 may target MAPKAPK2, NR1D2 and AKR1C4, respectively, and play critical regulatory roles in intramuscular adipogenesis and lipid accumulation in pig. XLOC_064871 and XLOC_011001 may play a role in lipid metabolism-related disease via regulating TRIB3 and BRCA1. This study provides a valuable resource for lncRNA study and improves our understanding of the biological roles of lipid metabolism- related genes and molecular mechanism of intramuscular fat metabolism and deposition

Integrated Diagenesis Study of Tight Gas Sandstone: The Permian Lower Shihezi Formation, Northern Ordos Basin, China

AbstractDiagenesis varies greatly from basin to basin and has been considered as the key control of the reservoir quality of tight sandstones. In this study, we analyzed the petrographic characteristics, diagenesis, and pore types and characteristics of the Permian Lower Shihezi Formation in the Ordos Basin. Results show that most of sandstones are litharenites with minor sublitharenites and feldspathic litharenites. The tight sandstones have ultralow permeabilities (averaging 0.67 mD) and porosities (averaging 8.35%), with pore-throat sizes ranging from 0.035 to 13.29 μm with 94.12% less than 5 μm. Overall, the tight sandstone reservoirs have undergone complex diagenetic alteration. Compaction and clay mineral cements are the two crucial diagenetic factors that controlled the tightness of the reservoirs. The compaction destroyed most of primary porosity, and the effective pores are mainly dissolved micropores, intragranular dissolved micropores, and micropores in clay minerals and mineral grains. The chlorite coating might have helped preserve a certain amount of porosity, but pore-lining chlorites significantly obstructed pore throats and reduced permeability. Results of the study provide insights and direct implications for the future success of exploration and production of the tight gas sandstone in the Ordos Basin and other similar tight sandstone reservoirs

Identification and Characterization of CircRNAs of Two Pig Breeds as a New Biomarker in Metabolism-Related Diseases

Background/Aims: CircRNAs, as miRNA sponges, participate in many important biological processes. However, it remains unclear whether circRNAs can regulate lipid metabolism. This paper aims to study the molecular mechanism of fat deposition and provide useful information for the prevention and therapy of lipid metabolism-related diseases. Methods: CircRNA sequencing was performed to investigate the expression of circRNAs in the subcutaneous adipose tissues of Large White pig and Laiwu pig. The expression of circRNAs was further validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, circRNA-microRNAs (miRNA)-mRNA interaction networks were constructed using bioinformatics tools. In addition, GO and KEGG enrichment analyses were performed for the target genes of circRNAs. Results: In the subcutaneous adipose tissue of Laiwu pig, 70 up-regulated circRNAs and 205 down-regulated circRNAs were identified. Two circRNAs (up-regulated circRNA_26852 and down-regulated circRNA_11897), the expressions of which were confirmed by qRT-PCR, were selected for subsequent analysis. CircRNA-miRNA-mRNA interaction networks were constructed for circRNA_26852 and its target genes as well as circRNA_11897 and its target genes. GO and KEGG enrichment analyses reveal that the target genes of circRNA_26852 and circRNA_11897 are enriched in pathways related to adipocyte differentiation and lipid metabolism, as well as in disease-related pathways. Conclusions: In this study, circRNA sequencing and bioinformatics technique were used to analyze, for the first time, the expression of circRNAs in the subcutaneous adipose tissues of Large White pig and Laiwu pig. It is inferred that circRNAs might regulate adipogenic differentiation and lipid metabolism. The results provide a theoretical basis for further study on fat deposition mechanism and provide potential therapy targets for metabolism-related diseases

One-step Iterative Estimation of Effective Atomic Number and Electron Density for Dual Energy CT

Dual-energy computed tomography (DECT) is a promising technology that has shown a number of clinical advantages over conventional X-ray CT, such as improved material identification, artifact suppression, etc. For proton therapy treatment planning, besides material-selective images, maps of effective atomic number (Z) and relative electron density to that of water ($\rho_e$) can also be achieved and further employed to improve stopping power ratio accuracy and reduce range uncertainty. In this work, we propose a one-step iterative estimation method, which employs multi-domain gradient $L_0$-norm minimization, for Z and $\rho_e$ maps reconstruction. The algorithm was implemented on GPU to accelerate the predictive procedure and to support potential real-time adaptive treatment planning. The performance of the proposed method is demonstrated via both phantom and patient studies

Image-Domain Material Decomposition for Dual-energy CT using Unsupervised Learning with Data-fidelity Loss

Background: Dual-energy CT (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise amplification, leading to severely degraded image signal-to-noise ratios (SNRs). While existing iterative algorithms perform noise suppression using different image priors, these heuristic image priors cannot accurately represent the features of the target image manifold. Although deep learning-based decomposition methods have been reported, these methods are in the supervised-learning framework requiring paired data for training, which is not readily available in clinical settings. Purpose: This work aims to develop an unsupervised-learning framework with data-measurement consistency for image-domain material decomposition in DECT

Ultrahigh Numerical Aperture Metalens at Visible Wavelengths

Subwavelength imaging requires the use of high numerical aperture (NA) lenses together with immersion liquids in order to achieve the highest possible resolution. Following exciting recent developments in metasurfaces that have achieved efficient focusing and novel beam-shaping, the race is on to demonstrate ultrahigh-NA metalenses. The highest NA that has been demonstrated so far is NA = 1.1, achieved with a TiO2 metalens and back-immersion. Here, we introduce and demonstrate a metalens with a high NA and high transmission in the visible range, based on crystalline silicon (c-Si). The higher refractive index of silicon compared to TiO2 allows us to push the NA further. The design uses the geometric phase approach also known as the Pancharatnam-Berry (P-B) phase, and we determine the arrangement of nanobricks using a hybrid optimization algorithm (HOA). We demonstrate a metalens with NA = 0.98 in air, a bandwidth (full width at half-maximum, fwhm) of 274 nm, and a focusing efficiency of 67% at 532 nm wavelength, which is close to the transmission performance of a TiO2 metalens. Moreover, and uniquely so, our metalens can be front-immersed into immersion oil and achieve an ultrahigh NA of 1.48 experimentally and 1.73 theoretically, thereby demonstrating the highest NA of any metalens in the visible regime reported to the best of our knowledge. The fabricating process is fully compatible with microelectronic technology and therefore scalable. We envision the front-immersion design to be beneficial for achieving ultrahigh-NA metalenses as well as immersion metalens doublets, thereby pushing metasurfaces into practical applications such as high resolution, low-cost confocal microscopy and achromatic lenses

True volumes of slope failure estimated from a Quaternary mass-transport deposit in the northern South China Sea

Submarine slope failure can mobilize large amounts of seafloor sediment, as shown in varied offshore locations around the world. Submarine landslide volumes are usually estimated by mapping their tops and bases on seismic data. However, two essential components of the total volume of failed sediments are overlooked in most estimates: a) the volume of sub-seismic turbidites generated during slope failure and b) the volume of shear compaction occurring during the emplacement of failed sediment. In this study, the true volume of a large submarine landslide in the northern South China Sea is estimated using seismic, multibeam bathymetry and ODP/IODP well data. The submarine landslide was evacuated on the continental slope and deposited in an ocean basin connected to the slope through a narrow moat. This particular character of the sea floor provides an opportunity to estimate the amount of strata remobilized by slope instability. The imaged volume of the studied landslide is ~1035±64 km3, ~406±28 km3 on the slope and ~629±36 km3 in the ocean basin. The volume of sub-seismic turbidites is ~86 km3 (median value) and the volume of shear compaction is ~100 km3, which are ~8.6% and ~9.7% of the landslide volume imaged on seismic data, respectively. This study highlights that the original volume of the failed sediments is significantly larger than that estimated using seismic and bathymetric data. Volume loss related to the generation of landslide-related turbidites and shear compaction must be considered when estimating the total volume of failed strata in the submarine realm