Distribution and isotopic signature of 2-alkyl-1,3,4-trimethylbenzenes in the Lower Paleozoic source rocks and oils of Tarim Basin:Implications for the oil-source correlation

Series of 2-alkyl-1,3,4-trimethylbenzenes(ATMBs)were detected in most of crude oils and source rocks collected from various strata and locations of the Tarim Basin.They appeared to have heavy carbon isotopic signatures(δ13C,up to~-16‰)compared to those hydrocarbons from oxygenic phototrophic organisms,indicating that the unequivocal source of green sulfur bacteria(GSB)and photic zone euxinia(PZE)existed in the original environment.Considering the high paleoproductivity,the PZE may have enhanced the preservation of organic matter,which triggered the formation of extremely organic-rich source rocks with TOC up to 29.8%for the Lower Cambrian Yuertus Formation(€1y).The coexistence of ATMBs and the diagnostic products from secondary alterations(e.g.,abundant 25-norhopanes,thiadiamondoids,and diamondoids)indicated a stronger ability of anti-second-alterations.Combined with the results of quantitatively de-convoluting mixed oil,the oil-source correlation based on ATMBs from a large number of Lower Paleozoic samples of the Tarim Basin suggested that the abundant deep crude oil resources co ntained a dominant contribution(>50%)from the€1y source rocks.Therefore,the ATMBs,as diagnostic biomarkers indicating unequivocal precursors under special habitat conditions,might provide important insights for the exploration of deep Lower Paleozoic crude oils in the Tarim Basin.

Oil-source correlation of Lower-Triassic oil seepages in Ni＇erguan village, Southern Guizhou Depression, China

There are abundant bitumens and oil seepages stored in vugs in a Lower-Triassic Daye formation(T_1d)marlite in Ni'erguan village in the Southern Guizhou Depression. However, the source of those oil seepages has not been determined to date. Multiple suites of source rocks of different ages exist in the depression. Both the oil seepages and potential source rocks have undergone complicated secondary alterations, which have added to the difficulty of an oil-source correlation. For example, the main source rock, a Lower-Cambrian Niutitang Formation"(∈_1n) mudstone, is over mature, and other potential source rocks, both from the Permian and the Triassic, are still in the oil window. In addition, the T_1d oil seepages underwent a large amount of biodegradation. To minimize the influence of biodegradation and thermal maturation, special methods were employed in this oil-source correlation study. These methods included catalytic hydropyrolysis, to release covalently bound biomarkers from the over mature"kerogen of ∈_1n mudstone, sequential extraction, to obtain chloroform bitumen A and chloroform bitumen C from the T_1d marlite, and anhydrous pyrolysis, to release pyrolysates from the kerogen of T_1d marlite. Using the methods above, the biomarkers and n-alkanes releasedfrom the oil samples and source rocks were analysed by GC–MS and GC-C-IRMS. The oil-source correlation indicated that the T_1d oil seepage primarily originated from"the ∈_1n mudstone and was partially mixed with oil generated from the T_1d marlite. Furthermore, the seepage also demonstrated that the above methods were effective for the complicated oil-source correlation in the Southern Guizhou Depression.

Ruthenium-ion-catalyzed oxidation of asphaltenes and oil-source correlation of heavy oils from the Lunnan and Tahe oilfields in the Tarim Basin, NW China

The identification of marine source rocks in the Tarim Basin is debated vigorously. The intention of this paper is to investigate the asphaltenes in heavy oils from the Lunnan and Tahe oilfields and Well TD2 with ruthenium-ions-catalyzed oxidation technique (RICO), in order to explore its role in oil-oil and oil-source correlations. The RICO products included n-alkanoic acids, α, ω-di-n-alkanoic acids, branched alkanoic acids, tricyclic terpanoic acids, hopanoic acids, gammacerane carboxylic acid , regular sterane carboxylic acids and 4-methylsterane carboxylic acids. The n-alkyl chains and biomarkers bounded on the asphaltenes were of unsusceptibility to biodegradation. The distribution and absolute concentrations of n-alkanoic acids in the RICO products of heavy oils from the Lunnan and Tahe oilfields are different from those of Well TD2. The biomarkers bounded on the asphaltenes, especially steranes, have a distribution trend similar to that of the counterparts in saturates. The sterane carboxylic acids and 4-methylsterane carboxylic acids in the RICO products of heavy oils from the Lunnan and Tahe oilfields, dominated by C-{30} sterane and C-{31} 4-methylsterane carboxylic acids, respectively, are significantly different from those of the heavy oils of Well TD2, whose dominating sterane and 4|methylsterane carboxylic acids are C-{28} sterane and C-{29} 4-methylsterane acids, respectively. The RICO products of the asphaltenes further indicate that the Middle-Upper Ordovician may be the main source rocks for heavy oils from the Lunnan and Tahe oilfields.

Oil-source correlation of the pre-Tertiary in the Huanghua Depression:Insights from stable carbon isotopes and molecular markers

Stable carbon isotopes were used together with molecular markers to constrain genetic relationships between sandstone extracts and potential source rocks in the pre-Tertiary in the Huanghua Depression,North China.Comparison of the extracts from Permo-Carboniferous terrigenous mudstones and Ordovician marine carbonates indicated that their prominent differences are in stable carbon isotopes,molecular markers and thermal maturity.Although the extracts of the Mesozoic and Lower Permian Xiashihezi Formation sandstones have some similar iso-topic characteristics,molecular markers data provide a good correlation between the Upper Jurassic-Lower Cretaceous oils and the Upper Carboniferous Taiyuan Formation mudstones,and between the Lower Permian Xiashihezi Formation oils and the Lower Permian mudstones.The results showed that the Upper Jurassic-Lower Cretaceous sandstone oils were derived chiefly from the Upper Carboniferous Taiyuan Formation terrigenous mudstones and that the Lower Permian Xiashihezi Formation oils were sourced from the Lower Permian Shanxi Formation and Xiashihezi Formation terrigenous mudstones.

Oil-source correlation and Paleozoic source rock analysis in the Siwa Basin,Western Desert:Insights from well-logs,Rock-Eval pyrolysis,and biomarker data

Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source correlation investigation.This objective is achieved through a meticulous analysis of well-log responses,Rock-Eval pyrolysis,and biomarker data.The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen.Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter.Notably,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is observed.Contrarily,the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II kerogen.Through analysis of five oil samples from different wells—SIWA L-1X,SIWA R-3X,SIWA D-1X,PTAH 5X,and PTAH 6X,it is evident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III kerogen.Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments.Noteworthy is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon generation.The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir,suggesting potential links to Paleozoic sources or even originating from the Safa Member itself.These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin.By illuminating the processes of hydrocarbon genesis in the region,this study significantly enriches our knowledge base.

The Occurrence of Oleananes in the Beibuwan Basin and Its Application to the Study of Maturity and Oil-Source Rock Correlation

The oleanane parameter, i.e., OP （oleananes/（oleananes＋C30hopanes）） in the two sedimentary columns of the Beibuwan Basin, South China Sea, can be used to delimit the top of oil generation window, with Ro （/%） of 0.53 in Well M1 and 0.55 in Wells H1/Hd1/Hd2, respectively. Comparing with vitrinite reflectance （Ro/%）, the OP features a dynamic range and can indicate the oil generation window more precisely. By using OP and other geochemical indices, the oil-source correlation is also conducted. It suggests that the oils in wells M1 and M2 are derived from the source rocks in situ. The mudstone in Huachang uplift is not the main source rocks for oils in this area, The OP is also a useful oil-source correlation parameter in some Tertiary lacustrine basins.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Structural identification and antioxidative activity evaluation of flaxseed lignan macromolecules: structure-activity correlation

Flaxseed lignan macromolecules(FLM)are a class of important secondary metabolites in fl axseed,which have been widely concerned due to their biological and pharmacological properties,especially for their antioxidative activity.For the composition and structure of FLM,our results confirmed that ferulic acid glycoside(FerAG)was directly ester-linked with herbacetin diglucoside(HDG)or pinoresinol diglucoside(PDG),which might determine the beginning of FLM biosynthesis.Additionally,p-coumaric acid glycoside(CouAG)might determine the end of chain extension during FLM synthesis in fl axseed.FLM exhibited higher antioxidative activity in polar systems,as shown by its superior 1,1-diphenyl-2-picrylhydrazyl(DPPH)free radical scavenging capacity compared to the 2,2’-azinobis(3-ehtylbenzothiazolin-6-sulfnic acid)(ABTS)cation free radical scavenging capacity in non-polar systems.Moreover,the antioxidative activity of FLM was found to be highly dependent on its composition and structure.In particular,it was positively correlated with the number of phenolic hydroxyl groups(longer FLM chains)and inversely related to the steric hindrance at the ends(lower levels of FerAG and CouAG).These fi ndings verifi ed the potential application of FLM in nonpolar systems,particularly in functional food emulsions。

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

Study of baryon number transport dynamics and strangeness conservation effects using Ω-hadron correlations

In nuclear collisions at RHIC energies, an excess of Ω hyperons over ■ is observed, indicating that Ω has a net baryon number despite s and s quarks being produced in pairs. The baryon number in Ω may have been transported from the incident nuclei and/or produced in the baryon-pair production of Ω with other types of anti-hyperons such as Ξ. To investigate these two scenarios, we propose to measure the correlations between Ω and K and between Ω and anti-hyperons. We use two versions, the default and string-melting, of a multiphase transport(AMPT) model to illustrate the method for measuring the correlation and to demonstrate the general shape of the correlation. We present the Ω-hadron correlations from simulated Au+Au collisions at ■ =7.7 and 14.6 Ge V and discuss the dependence on the collision energy and on the hadronization scheme in these two AMPT versions. These correlations can be used to explore the mechanism of baryon number transport and the effects of baryon number and strangeness conservation on nuclear collisions.

Track correlation algorithm based on CNN-LSTM for swarm targets

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for correlation.In this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm targets.Precisely, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation

News media profiling is helpful in preventing the spread of fake news at the source and maintaining a good media and news ecosystem.Most previous works only extract features and evaluate media from one dimension independently,ignoring the interconnections between different aspects.This paper proposes a novel news media bias and factuality profiling framework assisted by correlated features.This framework models the relationship and interaction between media bias and factuality,utilizing this relationship to assist in the prediction of profiling results.Our approach extracts features independently while aligning and fusing them through recursive convolu-tion and attention mechanisms,thus harnessing multi-scale interactive information across different dimensions and levels.This method improves the effectiveness of news media evaluation.Experimental results indicate that our proposed framework significantly outperforms existing methods,achieving the best performance in Accuracy and F1 score,improving by at least 1%compared to other methods.This paper further analyzes and discusses based on the experimental results.

Anomalous Hall effect and electronic correlation in a spin-reoriented kagome antiferromagnet LuFe_(6)Sn_(6)

The kagome lattice system has been identified as a fertile ground for the emergence of a number of new quantumstates,including superconductivity,quantum spin liquids,and topological electronic states.This has attracted significantinterest within the field of condensed matter physics.Here,we present the observation of an anomalous Hall effect in aniron-based kagome antiferromagnet LuFe_(6)Sn_(6),which implies a non-zero Berry curvature in this compound.By means ofextensive magnetic measurements,a high Neel temperature,T_(N)=552 K,and a spin reorientation behavior were identifiedand a simple temperature-field phase diagram was constructed.Furthermore,this compound was found to exhibit a largeSommerfeld coefficient ofγ=87 mJ·mol^(-1)·K^(-2),suggesting the presence of a strong electronic correlation effect.Ourresearch indicates that LuFe_(6)Sn_(6)is an intriguing compound that may exhibit magnetism,strong correlation,and topologicalstates.

Dynamics of Non-Markovianity, Quantum Correlations and Information Scrambling of Three Qubits Systems Interacting via Rashba Interaction

The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.

Evaluation of frictional pressure drop correlations for air-water and air-oil two-phase flow in pipeline-riser system

Accurate prediction of the frictional pressure drop is important for the design and operation of subsea oil and gas transporting system considering the length of the pipeline. The applicability of the correlations to pipeline-riser flow needs evaluation since the flow condition in pipeline-riser is quite different from the original data where they were derived from. In the present study, a comprehensive evaluation of 24prevailing correlation in predicting frictional pressure drop is carried out based on experimentally measured data of air-water and air-oil two-phase flows in pipeline-riser. Experiments are performed in a system having different configuration of pipeline-riser with the inclination of the downcomer varied from-2°to-5°to investigated the effect of the elbow on the frictional pressure drop in the riser. The inlet gas velocity ranges from 0.03 to 6.2 m/s, and liquid velocity varies from 0.02 to 1.3 m/s. A total of885 experimental data points including 782 on air-water flows and 103 on air-oil flows are obtained and used to access the prediction ability of the correlations. Comparison of the predicted results with the measured data indicate that a majority of the investigated correlations under-predict the pressure drop on severe slugging. The result of this study highlights the requirement of new method considering the effect of pipe layout on the frictional pressure drop.

Correlation Study on Grain Size Characteristics and Geotechnical Properties of Surface Sediments in Qingdao Offshore Area

The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study delineated the sedimentary environment zoning in the northern sea area of Qingdao through cluster analysis of grain size parameters derived from 123 surface sediment samples.The study analyzed the correlation between sediment geotechnical indices and grain size parameters across diverse sedimentary environments.A correlation equation was established for samples exhibiting a strong correlation.The study found four distinct sedimentary environments in the study area:coastal,transitional,shallow sea,and residual.Within the same sedimentary environment,the average grain size and sorting coefficient exhibit significant correlations with geotechnical indices such as water content,density,shear strength,plastic limit,liquid limit,and plastic index.However,notable disparities in the correlation between grain size parameters and geotechnical indices emerge across different sedimentary environments.

Variational data encoding and correlations in quantum-enhanced machine learning

Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Longitudinal investigation of mineral composition in human milk and its correlation with infant anthropometric outcomes among Tibetan mother-infant dyads during the first 6 months postpartum

Nutrients in human milk,including minerals,relate growth and development of breast-fed infants.Tibetan mother-infant dyads possess unique characteristics on early nutrition due to their featured long-lasting lifestyle.This study longitudinally investigated the relationship between the mineral composition in human milk and the Z-scores of infants among Tibetan mother-infant dyads during their first 6 months postpartum through a prospective cohort study.The results show that the minerals of Na,Mg,K,Ca,Cu,Zn,and Se were of higher levels in colostrum than other lactation stages.Several minerals were below the recommended values for infants according to Chinese dietary guidelines.Besides,a large proportion of infant Z-scores were below-2 as lactation period continued.Multivariate statistical analysis revealed that classifications and correlations in varying degrees were observed between minerals in human milk and infant Z-scores.These findings will be advantageous for research upon Chinese early nutrition and progress of tailor-made infant formula.