Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

AAV2-PDE6B restores retinal structure and function in the retinal degeneration 10 mouse model of retinitis pigmentosa by promoting phototransduction and inhibiting apoptosis

Retinitis pigmentosa is a group of inherited diseases that lead to retinal degeneration and photoreceptor cell death.However,there is no effective treatment for retinitis pigmentosa caused by PDE6B mutation.Adeno-associated virus(AAV)-mediated gene therapy is a promising strategy for treating retinitis pigmentosa.The aim of this study was to explore the molecular mechanisms by which AAV2-PDE6B rescues retinal function.To do this,we injected retinal degeneration 10(rd10)mice subretinally with AAV2-PDE6B and assessed the therapeutic effects on retinal function and structure using dark-and light-adapted electroretinogram,optical coherence tomography,and immunofluorescence.Data-independent acquisition-mass spectrometry-based proteomic analysis was conducted to investigate protein expression levels and pathway enrichment,and the results from this analysis were verified by real-time polymerase chain reaction and western blotting.AAV2-PDE6B injection significantly upregulated PDE6βexpression,preserved electroretinogram responses,and preserved outer nuclear layer thickness in rd10 mice.Differentially expressed proteins between wild-type and rd10 mice were closely related to visual perception,and treating rd10 mice with AAV2-PDE6B restored differentially expressed protein expression to levels similar to those seen in wild-type mice.Kyoto Encyclopedia of Genes and Genome analysis showed that the differentially expressed proteins whose expression was most significantly altered by AAV2-PDE6B injection were enriched in phototransduction pathways.Furthermore,the phototransductionrelated proteins Pde6α,Rom1,Rho,Aldh1a1,and Rbp1 exhibited opposite expression patterns in rd10 mice with or without AAV2-PDE6B treatment.Finally,Bax/Bcl-2,p-ERK/ERK,and p-c-Fos/c-Fos expression levels decreased in rd10 mice following AAV2-PDE6B treatment.Our data suggest that AAV2-PDE6B-mediated gene therapy promotes phototransduction and inhibits apoptosis by inhibiting the ERK signaling pathway and upregulating Bcl-2/Bax expression in retinitis pigmentosa.

Enhancer of Shoot Regeneration 2(ESR2)regulates pollen maturation and vitality in watermelon(Citrullus lanatus)

Watermelon(Citrullus lanatus)holds global significance as a fruit with high economic and nutritional value.Exploring the regulatory network of watermelon male reproductive development is crucial for developing male sterile materials and facilitating cross-breeding.Despite its importance,there is a lack of research on the regulation mechanism of male reproductive development in watermelon.In this study,we identified that ClESR2,a VIIIb subclass member in the APETALA2/Ethylene Responsive Factor(AP2/ERF)superfamily,was a key factor in pollen development.RNA insitu hybridization confirmed significantClESR2 expression in the tapetum and pollen during the later stage of anther development.The pollens of transgenic plants showed major defects in morphology and vitality at the late development stage.The RNA-seq and protein interaction assay confirmed that ClESR2 regulates pollen morphology and fertility by interacting with key genes involved in pollen development at both transcriptional and protein levels.These suggest that Enhancer of Shoot Regeneration 2(ESR2)plays an important role in pollen maturation and vitality.This study helps understand the male reproductive development of watermelon,providing a theoretical foundation for developing male sterile materials.

Runx2 regulates peripheral nerve regeneration to promote Schwann cell migration and re-myelination

Runx2 is a major regulator of osteoblast differentiation and function;however,the role of Runx2 in peripheral nerve repair is unclea r.Here,we analyzed Runx2expression following injury and found that it was specifically up-regulated in Schwann cells.Furthermore,using Schwann cell-specific Runx2 knocko ut mice,we studied peripheral nerve development and regeneration and found that multiple steps in the regeneration process following sciatic nerve injury were Runx2-dependent.Changes observed in Runx2 knoc kout mice include increased prolife ration of Schwann cells,impaired Schwann cell migration and axonal regrowth,reduced re-myelination of axo ns,and a block in macrophage clearance in the late stage of regeneration.Taken together,our findings indicate that Runx2 is a key regulator of Schwann cell plasticity,and therefore peripheral nerve repair.Thus,our study shows that Runx2 plays a major role in Schwann cell migration,re-myelination,and peripheral nerve functional recovery following injury.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

Regulatory factors of Nrf2 in age-related macular degeneration pathogenesis

Age-related macular degeneration(AMD)is a complicated disease that causes irreversible visual impairment.Increasing evidences pointed retinal pigment epithelia(RPE)cells as the decisive cell involved in the progress of AMD,and the function of anti-oxidant capacity of PRE plays a fundamental physiological role.Nuclear factor erythroid 2 related factor 2(Nrf2)is a significant transcription factor in the cellular anti-oxidant system as it regulates the expression of multiple anti-oxidative genes.Its functions of protecting RPE cells against oxidative stress(OS)and ensuing physiological changes,including inflammation,mitochondrial damage and autophagy dysregulation,have already been elucidated.Understanding the roles of upstream regulators of Nrf2 could provide further insight to the OS-mediated AMD pathogenesis.For the first time,this review summarized the reported upstream regulators of Nrf2 in AMD pathogenesis,including proteins and miRNAs,and their underlying molecular mechanisms,which may help to find potential targets via regulating the Nrf2 pathway in the future research and further discuss the existing Nrf2 regulators proved to be beneficial in preventing AMD.

Demonstration of a small‐scale power generator using supercritical CO_(2)

The supercritical CO_(2)(sCO_(2))power cycle could improve efficiencies for a wide range of thermal power plants.The sCO_(2)turbine generator plays an important role in the sCO_(2)power cycle by directly converting thermal energy into mechanical work and electric power.The operation of the generator encounters challenges,including high temperature,high pressure,high rotational speed,and other engineering problems,such as leakage.Experimental studies of sCO_(2)turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction.Unlike most experimental investigations that primarily focus on 100 kW‐or MW‐scale power generation systems,we consider,for the first time,a small‐scale power generator using sCO_(2).A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm,and a CO_(2)transcritical power cycle test loop was constructed to validate the performance of our manufactured generator.A resistant gas was proposed in the constructed turbine expander to solve the leakage issue.Both dynamic and steady performances were investigated.The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm.The maximum total efficiency of the turbo‐generator was 58.98%,which was affected by both the turbine rotational speed and pressure ratio,according to the proposed performance map.

Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and sensing.Here,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical response.Exploiting the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the meta-atoms.Next,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is observed.To gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the meta-atoms.Our work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Quantitative effect of kerogen type on the hydrocarbon generation potential of Paleogene lacustrine source rocks,Liaohe Western Depression,China

Kerogen types exert a decisive effect on the onset and capacity of hydrocarbon generation of source rocks.Lacustrine source rocks in the Liaohe Western Depression are characterized by thick deposition,high total organic carbon(TOC)content,various kerogen types,and a wide range of thermal maturity.Consequently,their hydrocarbon generation potential and resource estimation can be misinterpreted.In this study,geochemical tests,numerical analysis,hydrocarbon generation kinetics,and basin modeling were integrated to investigate the differential effects of kerogen types on the hydrocarbon generation potential of lacustrine source rocks.Optimized hydrocarbon generation and expulsion(HGE)models of different kerogen types were established quantitatively upon abundant Rock-Eval/TOC/vitrinite reflectance(R_(o))datasets.Three sets of good-excellent source rocks deposited in the fourth(Es4),third(Es3),and first(Es1)members of Paleogene Shahejie Formation,are predominantly types I-II_(1),II_(1)-II_(2),and II-III,respectively.The activation energy of types I-II_(2)kerogen is concentrated(180-230 kcal/mol),whereas that of type III kerogen is widely distributed(150-280 kcal/mol).The original hydrocarbon generation potentials of types I,II_(1),II_(2),and III kerogens are 790,510,270,and 85 mg/g TOC,respectively.The Ro values of the hydrocarbon generation threshold for type I-III source rocks gradually increase from 0.42%to 0.74%,and Ro values of the hydrocarbon expulsion threshold increase from 0.49%to 0.87%.Types I and II_(1)source rocks are characterized by earlier hydrocarbon generation,more rapid hydrocarbon expulsion,and narrower hydrocarbon generation windows than types II_(2)and III source rocks.The kerogen types also affect the HGE history and resource potential.Three types(conventional,tight,and shale oil/gas)and three levels(realistic,expected,and prospective)of hydrocarbon resources of different members in the Liaohe Western Depression are evaluated.Findings suggest that the Es3 member has considerable conventional and unconventional hydrocarbon resources.This study can quantitatively characterize the hydrocarbon generation potential of source rocks with different kerogen types,and facilitate a quick and accurate assessment of hydrocarbon resources,providing strategies for future oil and gas exploration.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Single-neuron neurodegeneration as a degenerative model for Parkinson’s disease

The positive effect of levodopa in the treatment of Parkinson’s disease,although it is limited in time and has severe side effects,has encouraged the scientific community to look for new drugs that can stop the neurodegenerative process or even regenerate the neuromelanin-containing dopaminergic nigrostriatal neurons.Successful preclinical studies with coenzyme Q10,mitoquinone,isradipine,nilotinib,TCH346,neurturin,zonisamide,deferiprone,prasinezumab,and cinpanemab prompted clinical trials.However,these failed and after more than 50 years levodopa continues to be the key drug in the treatment of the disease,despite its severe side effects after 4–6 years of chronic treatment.The lack of translated successful results obtained in preclinical investigations based on the use of neurotoxins that do not exist in the human body as new drugs for Parkinson’s disease treatment is a big problem.In our opinion,the cause of these failures lies in the experimental animal models involving neurotoxins that do not exist in the human body,such as 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and 6-hydroxydopamine,that induce a very fast,massive and expansive neurodegenerative process,which contrasts with the extremely slow one of neuromelanin-containing dopaminergic neurons.The exceedingly slow progress of the neurodegenerative process of the nigrostriatal neurons in idiopathic Parkinson’s patients is due to(i)a degenerative model in which the neurotoxic effect of an endogenous neurotoxin affects a single neuron,(ii)a neurotoxic event that is not expansive and(iii)the fact that the neurotoxin that triggers the neurodegenerative process is produced inside the neuromelanin-containing dopaminergic neurons.The endogenous neurotoxin that fits this degenerative model involving one single neuron at a time is aminochrome,since it(i)is generated within neuromelanin-containing dopaminergic neurons,(ii)does not cause an expansive neurotoxic effect and(iii)triggers all the mechanisms involved in the neurodegenerative process of the nigrostriatal neurons in idiopathic Parkinson’s disease.In conclusion,based on the hypothesis that the neurodegenerative process of idiopathic Parkinson’s disease corresponds to a single-neuron neurodegeneration model,we must search for molecules that increase the expression of the neuroprotective enzymes DT-diaphorase and glutathione transferase M2-2.It has been observed that the activation of the Kelch-like ECH-associated protein 1/nuclear factor(erythroid-derived 2)-like 2 pathway is associated with the transcriptional activation of the DT-diaphorase and glutathione transferase genes.

Identifying multidisciplinary problems from scientific publications based on a text generation method

Purpose:A text generation based multidisciplinary problem identification method is proposed,which does not rely on a large amount of data annotation.Design/methodology/approach:The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique;second,it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model;third,it extracts problem phrases from generated titles according to regular expression rules;fourth,it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm;finally,it identifies multidisciplinary problems based on the disciplinary labels of papers.Findings:Experiments in the“Carbon Peaking and Carbon Neutrality”field show that the proposed method can effectively identify multidisciplinary research problems.The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field.Research limitations:It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness.Practical implications:Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments,fund valuable multidisciplinary problems for research management authorities,and borrow ideas from other disciplines for researchers.Originality/value:This approach proposes a novel multidisciplinary problem identification method based on text generation,which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques.

Generating attosecond pulses with controllable polarization from cyclic H_(3)^(2+) molecules by bichromatic circular fields

We investigate the polarization properties of harmonics from the cyclic H_(3)^(2+) molecular ions in tailored bichromatic counter-rotating circularly polarized(BCCP)fields by solving the time-dependent Schrödinger equation.The allowed harmonics and their helicities are associated with the symmetry compatibility of the field-target systems,and large intensity difference between adjacent harmonics with opposite helicities appears in a wide spectral range when the BCCP field is at certain rotation angles.We try to explain the intensity difference by using a recombination model based on the quantum-orbit theory and by analyzing the ionization pathways.Moreover,to synthesize attosecond pulse trains with tunable polarization,the intensity difference is manipulated by introducing a seed XUV field,and by changing the relative amplitude ratio as well as the helicity of BCCP fields.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Enhanced picosecond terahertz wave generation based on cascade effects in a terahertz parametric generator

Enhanced terahertz wave generation via a Stokes cascade process has been demonstrated using picosecond pulse pumped terahertz parametric generation at 1 kHz repetition rate.Clear cascade saturation of terahertz output was observed,and the corresponding cascade-Stokes spectra were analyzed.The maximum terahertz wave average power was 22μW under a pump power of 30 W,whereas the maximum power conversion efficiency was 8×10^(-7)under a pump power of 21 W.The THz power fluctuation was measured to be about 1%in 20 min.This THz parametric source with a relatively stable output is suitable for a variety of practical applications.

Efficient C-N coupling in electrocatalytic urea generation on copper carbonate hydroxide electrocatalysts

Urea generation through electrochemical CO_(2) and NO_(3)~-co-reduction reaction(CO_(2)NO_(3)RR)is still limited by either the low selectivity or yield rate of urea.Herein,we report copper carbonate hydroxide(Cu_2(OH)_2CO_(3))as an efficient CO_(2)NO_(3)RR electrocatalyst with an impressive urea Faradaic efficiency of45.2%±2.1%and a high yield rate of 1564.5±145.2μg h~(-1)mg_(cat)~(-1).More importantly,H_(2) evolution is fully inhibited on this electrocatalyst over a wide potential range between-0.3 and-0.8 V versus reversible hydrogen electrode.Our thermodynamic simulation reveals that the first C-N coupling follows a unique pathway on Cu_2(OH)_2CO_(3) by combining the two intermediates,~*COOH and~*NHO.This work demonstrates that high selectivity and yield rate of urea can be simultaneously achieved on simple Cu-based electrocatalysts in CO_(2)NO_(3)RR,and provide guidance for rational design of more advanced catalysts.

Automatic Generation of Artificial Space Weather Forecast Product Based on Sequence-to-sequence Model

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.

Impact of volcanism on the formation and hydrocarbon generation of organic-rich shale in the Jiyang Depression, Bohai Bay Basin, China

Globally,most organic-rich shales are deposited with volcanic ash layers.Volcanic ash,a source for many sedimentary basins,can affect the sedimentary water environment,alter the primary productivity,and preserve the organic matter(OM)through physical,chemical,and biological reactions.With an increasing number of breakthroughs in shale oil exploration in the Bohai Bay Basin in recent years,less attention has been paid to the crucial role of volcanic impact especially its influence on the OM enrichment and hydrocarbon formation.Here,we studied the petrology,mineralogy,and geochemical characteristics of the organic-rich shale in the upper submember of the fourth member(Es_(4)^(1))and the lower submember of the third member(Es_(3)^(3))of the Shahejie Formation,aiming to better understand the volcanic impact on organic-rich shale formation.Our results show that total organic carbon is higher in the upper shale intervals rich in volcanic ash with enriched light rare earth elements and moderate Eu anomalies.This indicates that volcanism promoted OM formation before or after the eruption.The positive correlation between Eu/Eu*and Post-Archean Australian Shale indicates hydrothermal activity before the volcanic eruption.The plane graph of the hydrocarbon-generating intensity(S1+S2)suggests that the heat released by volcanism promoted hydrocarbon generation.Meanwhile,the nutrients carried by volcanic ash promoted biological blooms during Es_(4)^(1 )and Es_(3)^(3) deposition,yielding a high primary productivity.Biological blooms consume large amounts of oxygen and form anoxic environments conducive to the burial and preservation of OM.Therefore,this study helps to further understand the organic-inorganic interactions caused by typical geological events and provides a guide for the next step of shale oil exploration and development in other lacustrine basins in China.

Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.