Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the o...Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the occurrence of Be in BCS is unclear,which seriously hinders the development of pollution control technologies.In order to enhance the understanding of BCS,the occurrence of Be and the microscale interactions with coexisting phases were investigated for the first time.It was found that CaSO_(4)·2H_(2)O and amorphous SiO_(2) are the primary phases of BCS.The simulated experiments of purified materials showed that Be interacted with CaSO_(4)·2H_(2)O and amorphous SiO_(2).Be can enter into the lattice of CaSO_(4)·2H_(2)O mainly as free Be2+.Amorphous SiO_(2) can adsorb Be2+particularly at a pH range of 3–5.The dissolution behavior experiment of BCS shows that about 52%of the Be is readily extracted under acidic conditions,which refers to the Be of independent occurrence.In contrast,the remaining 48%of Be can be extracted only after the CaSO_(4)·2H_(2)O has completely dissolved.Hence,CaSO_(4)·2H_(2)O is identified as the key occurrence phase which determines the highly efficient dissolution of Be.As a result,this study enhances the understanding of BCS and lays the foundation for the development of Be separation technologies.展开更多
In order to effectively predict occurrence quantity of Myzus persicae, BP neural network theory and method was used to establish prediction model for oc- currence quantity of M. persicae. Meanwhile, QPSO algorithm was...In order to effectively predict occurrence quantity of Myzus persicae, BP neural network theory and method was used to establish prediction model for oc- currence quantity of M. persicae. Meanwhile, QPSO algorithm was used to optimize connection weight and threshold value of BP neural network, so as to determine. the optimal connection weight and threshold value. The historical data of M. persica quantity in Hongta County, Yuxi City of Yunnan Province from 2003 to 2006 was adopted as training samples, and the occurrence quantities of M. persicae from 2007 to 2009 were predicted. The prediction accuracy was 99.35%, the mini- mum completion time was 30 s, the average completion time was 34.5 s, and the running times were 19. The prediction effect of the model was obviously superior to other prediction models. The experiment showed that this model was more effective and feasible, with faster convergence rate and stronger stability, and could solve the similar problems in prediction and clustering. The study provides a theoretical basis for comprehensive prevention and control against M. persicae.展开更多
Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pest...Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pests and their natural enemies is required to minimize the pest population and yield losses.In the current study,analysis of the seasonal population trend of pests and natural enemies and their relative occurrence on cultivars of three cotton species in Central India has been carried out.Results A higher number and diversity of sucking pests were observed during the vegetative cotton growth stage(60 days after sowing),declining as the crop matured.With the exception of cotton jassid(Amrasca biguttula biguttula Ishida),which caused significant crop damage mainly from August to September;populations of other sucking insects seldom reached economic threshold levels(ETL)throughout the studied period.The bollworm complex populations were minimal,except for the pink bollworm(Pectinophora gossypiella Saunders),which re-emerged as a menace to cotton crops during the cotton cropping season 2017–2018 due to resistance development against Bt-cotton.A reasonably good number of predatory arthropods,including coccinellids,lacewings,and spiders,were found actively preying on the arthropod pest complex of the cotton crop during the early vegetative growth stage.Linear regression indicates a significant relationship between green boll infestations and pink bollworm moths in pheromone traps.Multiple linear regression analyse showed mean weekly weather at one-or two-week lag periods had a significant impact on sucking pest population(cotton aphid,cotton jassid,cotton whitefly,and onion thrips)fluctuation.Gossypium hirsutum cultivars RCH 2 and DCH 32,and G.barbadense cultivar Suvin were found susceptible to cotton jassid and onion thrips.Phule Dhanvantary,an G.arboreum cotton cultivar,demonstrated the highest tolerance among all evaluated cultivars against all sucking pests.Conclusion These findings have important implications for pest management in cotton crops.Susceptible cultivars warrant more attention for plant protection measures,making them more input-intensive.The choice of appropriate cultivars can help minimize input costs,thereby increasing net returns for cotton farmers.展开更多
Alkaline lacustrine shale is highly heterogeneous,and the complex relationship between the organicinorganic porosity network and hydrocarbon occurrence restricts the effectiveness of shale oil exploration and developm...Alkaline lacustrine shale is highly heterogeneous,and the complex relationship between the organicinorganic porosity network and hydrocarbon occurrence restricts the effectiveness of shale oil exploration and development.Herein,we investigated the Fengcheng Formation(P_(1)f)in Mahu Sag.This study integrated geochemistry,Soxhlet extraction,scanning electron microscopy,gas adsorption,and nuclear magnetic resonance T_(1)-T_(2)spectroscopy to elucidate the microscopic oil occurrence mechanisms in shales.Results indicate the presence of felsic shale,dolomitic shale,lime shale,and mixed shale within the P_(1)f.Matrix pores and microfractures associated with inorganic minerals are the predominant pore types in P_(1)f.Adsorbed oil primarily resides on the surfaces of organic matter and clay minerals,while free oil predominantly occupies inorganic pores and microfractures with larger pore sizes.Variations exist in the quantity and distribution of shale oil accumulation across different scales,where free oil and adsorbed oil are governed by dominant pores with diameters exceeding 10 nm and ineffective pores with diameters below 10 nm,respectively.Shale oil occurrence characteristics are influenced by organic matter,pore structure,and mineral composition.Felsic shale exhibits a high abundance of dominant pores,possesses the highest oil content,predominantly harbors free oil within these dominant pores,and demonstrates good mobility.Fluid occurrence in dolomitic shale and lime shale is intricate,with low oil content and a free oil to adsorbed oil ratio of 1:1.Mixed shale exhibits elevated clay mineral content and a scarcity of dominant pores.Moreover,ineffective pores contain increased bound water,resulting in medium oil content and limited mobility predominantly due to adsorption.Presently,shale oil mainly occurs in the dominant pores with a diameter larger than 10 nm in a free state.During the exploration and development of alkaline lacustrine shale oil resources,emphasis should be placed on identifying sweet spots within the felsic shale characterized by dominant pores.展开更多
We extract some physical and chemical features re-lated to the occurrence of single nucleotide polymorphism （SNP） from three groups of sliding windows around SNP site,and then make the predictions about accuracy by ...We extract some physical and chemical features re-lated to the occurrence of single nucleotide polymorphism （SNP） from three groups of sliding windows around SNP site,and then make the predictions about accuracy by using radial basis function （RBF） networks. The result of the forward sliding windows sug-gests that the accuracies and Matthews correlation coefficient （MCC values） ascend with the increasing of length of sliding windows. The accuracies range from 73.27 % to 80.69 %,and MCC values range from 0.465 to 0.614. The backward sliding windows and the sliding windows with fixed length three are de-signed to find the crucial sites related to SNP. The results imply that the occurrence possibility of SNP relies heavily on the above physical and chemical features of sites which are at a distance around 20 bases from the SNP site. Compared with the support vector machine （SVM）,our RBF network approach has achieved more satisfactory results.展开更多
In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a to...In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.展开更多
Due to the limitations of widely used energy spectrum and spectral analyses for the determination of trace elements in coal,the modes of occurrence of Li still remains unclear.This study investigated the distribution ...Due to the limitations of widely used energy spectrum and spectral analyses for the determination of trace elements in coal,the modes of occurrence of Li still remains unclear.This study investigated the distribution of Li in selected bulk samples and in-situ kaolinite particles in the No.6 Li-rich coals from the Haerwusu Mine of the Jungar Coalfield using ICP-MS and LA-ICP-MS.The results reveal an elevated Li concentration in the lower section of the No.6 coal with high Sr/Ba ratio compared to the upper section with more terrigenous mudstone along the vertical profile.LA-ICP-MS mapping and spot analyses results showed that Li was concentrated in kaolinite but occur in variations in the concentrations of Li among different types of kaolinite.The concentration of Li in kaolinite is ranked as follows:cryptocrystalline kaolinite(2225.83 ppm)>vermicular kaolinite(651.49 ppm)>altered K-bearing kaolinite(593.44 ppm)>clastic kaolinite(478.68 ppm).The in-situ concentration of Li in kaolinite is much higher than that of the bulk samples,indicating that kaolinite is the dominant host mineral for Li as well.The Al2O3/TiO2 and Nb/Yb-Zr/TiO2 ratios indicate that Li in No.6 coal primarily originated from Paleoproterozoic granite in the Yinshan Mountain and felsic volcanic ash.Seawater leaching has a critical influence on the redistribution of Li in the coal from the Haerwusu Mine or even the whole Jungar Coalfield.展开更多
Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the co...Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.展开更多
Rare earth elements(REEs) are associated with phosphorite,which is an important strategic reserve resource.During sorting process of phosphorite,REEs may move with specific host minerals,however,occurrence state and m...Rare earth elements(REEs) are associated with phosphorite,which is an important strategic reserve resource.During sorting process of phosphorite,REEs may move with specific host minerals,however,occurrence state and moving pattern of REEs from rock to products are still unclear,which limits separation and enrichment of REEs from phosphorite.Mappings of scanning electron microscope(SEM) and electron probe X-ray micro-analyzer(EPMA) of REEs are highly consistent with those of calcium and phosphorus,and complementary with that of magnesium,which indicates that fluorapatite(Fap) is the main host mineral of REEs.The results of flotation and leaching experiments further indicate that REEs are enriched along with Fap from phosphorite to products.Occupied sites and occupation number of REEs were obtained by X-ray diffraction(XRD) refinement based on the Rietveld method.La,Ce,Nd,and Y can occupy both Ca1 and Ca2 sites.The ratios of La,Ce,Nd,and Y at Ca2 and Cal sites are 4.20,3.70,3.00,and 1.33,showing a decreasing trend,indicating that La,Ce,and Nd tend to occupy Ca2 sites,while Y tends to occupy Ca1 sites.X-ray absorption fine structure(XAFS) shows that REEs mainly form coordinate structures with oxygen and fluorine,which is a direct evidence that REEs replace calcium(Ⅱ) in phosphorite in an isomorphism form.Coordination structure and polyhedral configuration analysis indicate that substitution degree of La,Ce,Nd,and Y is Y> La> Ce≈Nd from easy to difficult at Cal and Ca2 sites.The research enriches the mineralization theory of REEs-bearing phosphorite and provides certain theoretical guidance for selective enrichment of REEs from phosphorite.展开更多
Understanding the occurrence state of shale oil is crucial for the effective development of shale oil resources.Although the second member of the Kongdian Formation(Ek2)is a key interval for lacustrine shale oil produ...Understanding the occurrence state of shale oil is crucial for the effective development of shale oil resources.Although the second member of the Kongdian Formation(Ek2)is a key interval for lacustrine shale oil production in the Cangdong Sag,Bohai Bay Basin,the occurrence state and controlling factors of shale oil in this formation remain poorly understood.This study established a multi-step programmed pyrolysis,combined with a light hydrocarbon recovery scheme,to quantitatively characterize the shale oil in different occurrence states.An integrated approach utilizing Rock-Eval pyrolysis,pyrolysis-gas chromatography,and crude oil gas chromatography was employed.Factors influencing the shale oil occurrence state were analyzed from petrology and organic geochemistry perspectives.The study revealed significant variations of shale oil occurrence states within the Ek2,attributed to differences in sedimentary organic matter,mineral compositions,sedimentary structures,and thermal maturity.Felsic laminae are the primary reservoir space for oil in laminated shales,and the frequent interbedding of felsic and organic-rich laminae facilitates the retention of free oil.The contents of free and adsorbed oil are primarily influenced by organic matter content and shale storage capacity,both of which exhibit distinct occurrence patterns.Based on the shale reservoir quality classification using the pyrolysis values of S1-1+S1-2 and(S1-1+S1-2)×100/TOC,the Ek2 shale demonstrates significant exploitation potential,with the first-level reservoirs comprising 66%,second-level reservoirs 11%,and third-level reservoirs 23%.These findings provide new insights into the geological accumulation and production of shale oil.展开更多
The microscopic occurrence characteristics primarily constrain the enrichment and mobility of shale oil.This study collected the lacustrine shales from the Palaeogene Funing Formation in the Gaoyou Sag, Subei Basin. C...The microscopic occurrence characteristics primarily constrain the enrichment and mobility of shale oil.This study collected the lacustrine shales from the Palaeogene Funing Formation in the Gaoyou Sag, Subei Basin. Conventional and multistage Rock-Eval, scanning electron microscopy, and nuclear magnetic resonance(NMR) T1-T2were performed to analyze the contents and occurrence characteristics of shale oil. Low-temperature nitrogen adsorption-desorption(LTNA/D) experiments were conducted on the shales before and after extraction. The relationships between shale oil occurrence with organic matter and pore structures were then discussed. Predominantly, the shale oil in the Funing Formation is found within fractures, with secondary occurrences in interparticle pores linked to brittle minerals and sizeable intraparticle pores associated with clay minerals. The selected shales can be categorized into two types based on the nitrogen isotherms. Type A shales are characterized by high contents of felsic and calcareous minerals but low clay minerals, with larger TOC and shale oil values. Conversely, Type B shales are marked by abundant clay minerals but diminished TOC and shale oil contents. The lower BET specific surface area(SSA), larger average pore diameter, and simpler pore surfaces and pore structures lead to the Type A shales being more conducive to shale oil enrichment and mobility. Shale oil content is predominantly governed by the abundance of organic matter, while an overabundance of organic matter typically equates to a reduced ratio of free oil and diminished fluidity. The BET SSA, volumes of pores less than 25 and 100 nm at extracted state all correlate negatively with total and adsorbed oil contents but display no correlation with free oil, while they have positive relationships with capillary-bound water.Consequently, pore water is mainly saturated in micropores(<25 nm) and minipores(25-100 nm), as well as adsorbed oil, while free oil, i.e., bound and movable oil, primarily exists in mesopores(100-1000 nm) and macropores(>1000 nm). These findings may enhance the understanding of the microscopic occurrence characteristics of shale oil and will contribute to guide resource estimation and shale oil sweet spot exploitation in the Gaoyou Sag, Subei Basin.展开更多
Pore structure characteristics,gas content,and micro-scale gas occurrence mechanisms were investigated in the Shan_(2)^(3)sub-member marine-continental transitional shale of the southeastern margin of the Ordos Basin ...Pore structure characteristics,gas content,and micro-scale gas occurrence mechanisms were investigated in the Shan_(2)^(3)sub-member marine-continental transitional shale of the southeastern margin of the Ordos Basin using scanning electron microscope images,lowtemperature N_(2)/CO_(2)adsorption and high-pressure mercury intrusion,methane isothermal adsorption experiments,and CH4-saturated nuclear magnetic resonance(NMR).Two distinct shale types were identified:organic pore-rich shale(Type OP)and microfracture-rich shale(Type M).The Type OP shale exhibited relatively well-developed organic matter pores,while the Type M shale was primarily characterized by a high degree of microfracture development.An experimental method combining methane isothermal adsorption on crushed samples and CH4-saturated NMR of plug samples was proposed to determine the adsorbed gas,free gas,and total gas content under high temperature and pressure conditions.There were four main research findings.(1)Marine-continental transitional shale exhibited substantial total gas content in situ,ranging from 2.58 to 5.73 cm^(3)/g,with an average of 4.35 cm^(3)/g.The adsorbed gas primarily resided in organic matter pores through micropore filling and multilayer adsorption,followed by multilayer adsorption in clay pores.(2)The changes in adsorbed and free pore volumes can be divided into four stages.Pores of<5 nm exclusively contain adsorbed gas,while those of 5-20 nm have a high proportion of adsorbed gas alongside free gas.Pores ranging from 20 to 100 nm have a high proportion of free gas and few adsorbed gas,while pores of>100 nm and microfractures are almost predominantly free gas.(3)The proportion of adsorbed gas in Type OP shale exceeds that in Type M,reaching 66%.(4)Methane adsorbed in Type OP shale demonstrates greater desorption capability,suggesting a potential for enhanced stable production,which finds support in existing production well data.However,it must be emphasized that high-gas-bearing intervals in both types present valuable opportunities for exploration and development.These data may support future model validations and enhance confidence in exploring and developing marine-continental transitional shale gas.展开更多
0 INTRODUCTION The Andean orogenic belt,a globally significant active continental margin(Lamb et al.,1997),extends in a north-south direction along the western coast of South America.The Colombian Andes,located in the...0 INTRODUCTION The Andean orogenic belt,a globally significant active continental margin(Lamb et al.,1997),extends in a north-south direction along the western coast of South America.The Colombian Andes,located in the northern segment of this orogen,constitute a vital component and host abundant Au-Cu resources.Three principal Au-Cu metallogenic belts(Chocó,Middle Cauca,and Antioquia)are developed from west to east across Colombia(Lesage et al.,2013;Sillitoe,2008;Figure 1a).展开更多
The occurrence types and controlling factors of organic matter in the sepiolite-containing successions of the first member of Mid-Permian Maokou Formation(Mao-1 Member for short)in the Eastern Sichuan Basin,SW China,h...The occurrence types and controlling factors of organic matter in the sepiolite-containing successions of the first member of Mid-Permian Maokou Formation(Mao-1 Member for short)in the Eastern Sichuan Basin,SW China,have been investigated through outcrop section measurement,core observation,thin section identification,argon ion polishing-field scanning electron microscopy,energy spectrum analysis,X-ray diffraction,total organic carbon content(TOC),major and trace element analysis.Finally,the symbiotic adsorption model of sepiolite for organic matter enrichment has been established.The results show that the sepiolite-containing successions of the Mao-1 Member are composed of the rhythmite of mudstone,argillaceous limestone and limestone,with five depositional intervals vertically and the organic matter mostly developed in the mudstone and argillaceous limestone layers within the lower three intervals.The organic matter occurrence types are mostly layered or nodular in macro to meso-scale,blocky-vein-like under a microscope,but scattered,interstitial or adsorbed at a mesoscopic scale.It underwent transition processes from lower to higher salinity,from oxygen-poor and anoxic reduction to oxygen-poor and localized oxygen enrichment on the palaeo-environment of the Mao-1 Member.The first two intervals of the early depositional phase of Mao-1 Member constitute the cyclothems of mudstone,argillaceous limestone and limestone and quantities of fibrous-feathered sepiolite settle down within the Tongjiang-Changshou sag with continuous patchy organic matter from adsorption of alginate by sepiolite in intercrystalline,bedding surfaces and interlayer pores.The third and fourth intervals in the mid-depositional phase are mostly composed of the mudstone and argillaceous limestone alternations with the continuous patchy or banded organic matter in the surface and inter-crystalline pores of fibrous,feathered and flaky sepiolite.And the fifth interval in the late depositional phase of the Mao-1 Member comprises the cyclothems of extremely thin layered argillaceous limestone and thick-layered limestone with the fibrous sepiolite depositing in the argillaceous limestone and irregular organic matter dispersing around the sepiolite.Therefore,the symbiotic adsorption between organic matter and sepiolite effectively enhances the preservation efficiency of organic matter and improves the source rock quality of the Mao-1 Member,which enhances our understanding on the enrichment model of the depositional organic matter.展开更多
Neonicotinoid insecticides(NEOs)have become an integral part of the global insecticide market due to their high efficiency and low toxicity.However,their environmental persistence has raised significant ecological con...Neonicotinoid insecticides(NEOs)have become an integral part of the global insecticide market due to their high efficiency and low toxicity.However,their environmental persistence has raised significant ecological concerns.Dongting Lake represents a vital freshwater lake in China,and its ecosystem health directly affects regional ecological balance and people’s livelihoods.This study systematically investigated the occurrence characteristics and ecological risks of NEOs in water bodies and sediments across the Dongting Lake basin.Based on surface water and sediment samples collected from 26 representative sampling sites,this study quantified nine NEOs using liquid chromatography triple quadrupole mass spectrometry.Furthermore,it assessed ecological risks posed by the NEOs using the risk quotient(RQ)method and fugacity modeling.The results revealed the presence of six NEOs in the water bodies:imidacloprid(IMI),acetamiprid(ACE),clothianidin(CLO),thiamethoxam(THIA),flonicamid(FLO),and dinotefuran(DIN).The total concentrations of these six NEOs averaged 275.11 ng/L.Five predominant NEOs(i.e.,IMI,THIA,ACE,CLO,and DIN)were identified in the sediments,with a mean concentration of 0.31 ng/g.The NEO concentrations in the water bodies across the Dongting Lake basin increased in the order of the Xiangjiang,Zishui,Yuanjiang,and Lishui rivers(collectively referred to as the Four Rivers),the mainstream of Dongting Lake,the Xinqiang River,the Miluo River,and the Hudu,Ouchi,and Songzi rivers(collectively referred to as the Three Outlets).Sediments from tributaries progressively accumulate in the lake.The ecological risk assessment identified IMI and DIN as the highest-risk compounds(RQ>1),with high-risk areas concentrated in the mainstream of Dongting Lake and the Ouchi,Miluo,and Hudu rivers.The fugacity model showed that IMI,ACE,and THIA are prone to diffuse from sediments to water bodies in most areas,with fugacity fractions(ff)values of greater than 0.5.In contrast,the mainstream of Dongting Lake acts as a sink of CLO and DIN(ff values:<0.5).Sediments at the lake’s outlet emerge as an important sink of NEOs.Based on the results of this study,it is advisable to strengthen the supervision of NEO applications in agricultural areas and to implement zonal control strategies.These measures will help reduce ecological risks and protect the safety of water ecosystems in the Dongting Lake region.展开更多
Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemical...Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemicals”and“PTSD,”and relevant literature was compiled.Network clustering co-occurrence analysis and qualitative narrative review were conducted.Results:Three hundred and one articles were included in the analysis of published research,which has surged since 2015 with nearly half of all relevant articles coming from North America.The category is dominated by neuroscience and neurology,with two journals,Addictive Behaviors and Drug and Alcohol Dependence,publishing the greatest number of papers on these topics.Most studies focused on psychedelic intervention for PTSD.Three timelines show an“ebb and flow”phenomenon between“substance use/marijuana abuse”and“psychedelic medicine/medicinal cannabis.”Other phytochemicals account for a small proportion of the research and focus on topics like neurosteroid turnover,serotonin levels,and brain-derived neurotrophic factor expression.Conclusion:Research on phytochemicals and PTSD is unevenly distributed across countries/regions,disciplines,and journals.Since 2015,the research paradigm shifted to constitute the mainstream of psychedelic research thus far,leading to the exploration of botanical active ingredients and molecular mechanisms.Other studies focus on anti-oxidative stress and anti-inflammation.展开更多
Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,for...Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,forest land and fallow land were investigated in six regions of northern China.Generic richness,diversity,abundance and biomass of soil nematodes was the lowest in crop land.The richness and diversity of soil nematodes were 28.8and 15.1%higher in fallow land than in crop land,respectively.No significant differences in soil nematode indices were found between forest land and fallow land,but their network keystone genera composition was different.Among the keystone genera,50%of forest land genera were omnivores-predators and 36%of fallow land genera were bacterivores.The proportion of fungivores in forest land was 20.8%lower than in fallow land.The network complexity and the stability were lower in crop land than forest land and fallow land.Soil pH,NH_(4)^(+)-N and NO_(3)^(–)-N were the major factors influencing the soil nematode community in crop land while soil organic carbon and moisture were the major factors in forest land.Soil nematode communities in crop land influenced by artificial management practices were more dependent on the soil environment than communities in forest land and fallow land.Land use induced soil environment variation and altered network relationships by influencing trophic group proportions among keystone nematode genera.展开更多
Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of...Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a n...The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.展开更多
基金supported by the National Natural Science Foundation of China(No.22276219)the foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.52121004)+1 种基金the major program Natural Science Foundation of Hunan Province of China(No.2021JC0001)the Fundamental Research Funds for the Central Universities of Central South University(No.2024ZZTS0063).
文摘Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the occurrence of Be in BCS is unclear,which seriously hinders the development of pollution control technologies.In order to enhance the understanding of BCS,the occurrence of Be and the microscale interactions with coexisting phases were investigated for the first time.It was found that CaSO_(4)·2H_(2)O and amorphous SiO_(2) are the primary phases of BCS.The simulated experiments of purified materials showed that Be interacted with CaSO_(4)·2H_(2)O and amorphous SiO_(2).Be can enter into the lattice of CaSO_(4)·2H_(2)O mainly as free Be2+.Amorphous SiO_(2) can adsorb Be2+particularly at a pH range of 3–5.The dissolution behavior experiment of BCS shows that about 52%of the Be is readily extracted under acidic conditions,which refers to the Be of independent occurrence.In contrast,the remaining 48%of Be can be extracted only after the CaSO_(4)·2H_(2)O has completely dissolved.Hence,CaSO_(4)·2H_(2)O is identified as the key occurrence phase which determines the highly efficient dissolution of Be.As a result,this study enhances the understanding of BCS and lays the foundation for the development of Be separation technologies.
基金Supported by Science and Technology Project of China National Tobacco Corporation(2009YN005&2010YN18&2010YN19)
文摘In order to effectively predict occurrence quantity of Myzus persicae, BP neural network theory and method was used to establish prediction model for oc- currence quantity of M. persicae. Meanwhile, QPSO algorithm was used to optimize connection weight and threshold value of BP neural network, so as to determine. the optimal connection weight and threshold value. The historical data of M. persica quantity in Hongta County, Yuxi City of Yunnan Province from 2003 to 2006 was adopted as training samples, and the occurrence quantities of M. persicae from 2007 to 2009 were predicted. The prediction accuracy was 99.35%, the mini- mum completion time was 30 s, the average completion time was 34.5 s, and the running times were 19. The prediction effect of the model was obviously superior to other prediction models. The experiment showed that this model was more effective and feasible, with faster convergence rate and stronger stability, and could solve the similar problems in prediction and clustering. The study provides a theoretical basis for comprehensive prevention and control against M. persicae.
基金Funding support for the Crop Pest Surveillance and Advisory Project(CROPSAP)。
文摘Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pests and their natural enemies is required to minimize the pest population and yield losses.In the current study,analysis of the seasonal population trend of pests and natural enemies and their relative occurrence on cultivars of three cotton species in Central India has been carried out.Results A higher number and diversity of sucking pests were observed during the vegetative cotton growth stage(60 days after sowing),declining as the crop matured.With the exception of cotton jassid(Amrasca biguttula biguttula Ishida),which caused significant crop damage mainly from August to September;populations of other sucking insects seldom reached economic threshold levels(ETL)throughout the studied period.The bollworm complex populations were minimal,except for the pink bollworm(Pectinophora gossypiella Saunders),which re-emerged as a menace to cotton crops during the cotton cropping season 2017–2018 due to resistance development against Bt-cotton.A reasonably good number of predatory arthropods,including coccinellids,lacewings,and spiders,were found actively preying on the arthropod pest complex of the cotton crop during the early vegetative growth stage.Linear regression indicates a significant relationship between green boll infestations and pink bollworm moths in pheromone traps.Multiple linear regression analyse showed mean weekly weather at one-or two-week lag periods had a significant impact on sucking pest population(cotton aphid,cotton jassid,cotton whitefly,and onion thrips)fluctuation.Gossypium hirsutum cultivars RCH 2 and DCH 32,and G.barbadense cultivar Suvin were found susceptible to cotton jassid and onion thrips.Phule Dhanvantary,an G.arboreum cotton cultivar,demonstrated the highest tolerance among all evaluated cultivars against all sucking pests.Conclusion These findings have important implications for pest management in cotton crops.Susceptible cultivars warrant more attention for plant protection measures,making them more input-intensive.The choice of appropriate cultivars can help minimize input costs,thereby increasing net returns for cotton farmers.
基金financially supported by the State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Efficient Development(33550000-22-ZC0613-0006)National Natural Science Foundation of China(42202133)+2 种基金CNPC Innovation Fund(2022DQ02-0106)Strategic Cooperation Technology Projects of the CNPC and CUPB(ZLZX2020-01-05)Key Laboratory of Tectonics and Petroleum Resources(China University of Geosciences),Ministry of Education,China(TPR-2023-05)。
文摘Alkaline lacustrine shale is highly heterogeneous,and the complex relationship between the organicinorganic porosity network and hydrocarbon occurrence restricts the effectiveness of shale oil exploration and development.Herein,we investigated the Fengcheng Formation(P_(1)f)in Mahu Sag.This study integrated geochemistry,Soxhlet extraction,scanning electron microscopy,gas adsorption,and nuclear magnetic resonance T_(1)-T_(2)spectroscopy to elucidate the microscopic oil occurrence mechanisms in shales.Results indicate the presence of felsic shale,dolomitic shale,lime shale,and mixed shale within the P_(1)f.Matrix pores and microfractures associated with inorganic minerals are the predominant pore types in P_(1)f.Adsorbed oil primarily resides on the surfaces of organic matter and clay minerals,while free oil predominantly occupies inorganic pores and microfractures with larger pore sizes.Variations exist in the quantity and distribution of shale oil accumulation across different scales,where free oil and adsorbed oil are governed by dominant pores with diameters exceeding 10 nm and ineffective pores with diameters below 10 nm,respectively.Shale oil occurrence characteristics are influenced by organic matter,pore structure,and mineral composition.Felsic shale exhibits a high abundance of dominant pores,possesses the highest oil content,predominantly harbors free oil within these dominant pores,and demonstrates good mobility.Fluid occurrence in dolomitic shale and lime shale is intricate,with low oil content and a free oil to adsorbed oil ratio of 1:1.Mixed shale exhibits elevated clay mineral content and a scarcity of dominant pores.Moreover,ineffective pores contain increased bound water,resulting in medium oil content and limited mobility predominantly due to adsorption.Presently,shale oil mainly occurs in the dominant pores with a diameter larger than 10 nm in a free state.During the exploration and development of alkaline lacustrine shale oil resources,emphasis should be placed on identifying sweet spots within the felsic shale characterized by dominant pores.
基金Supported by Discipline-Crossing Research Foundation of Huazhong Agricultural University(2008XKJC006)the Fundamental Research Funds for the Central Universities of China
文摘We extract some physical and chemical features re-lated to the occurrence of single nucleotide polymorphism （SNP） from three groups of sliding windows around SNP site,and then make the predictions about accuracy by using radial basis function （RBF） networks. The result of the forward sliding windows sug-gests that the accuracies and Matthews correlation coefficient （MCC values） ascend with the increasing of length of sliding windows. The accuracies range from 73.27 % to 80.69 %,and MCC values range from 0.465 to 0.614. The backward sliding windows and the sliding windows with fixed length three are de-signed to find the crucial sites related to SNP. The results imply that the occurrence possibility of SNP relies heavily on the above physical and chemical features of sites which are at a distance around 20 bases from the SNP site. Compared with the support vector machine （SVM）,our RBF network approach has achieved more satisfactory results.
文摘In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.
基金supported by the National Key R&D Program of China(No.2021YFC2902003)National Natural Science Foundation of China(No.42302193No.42272201).
文摘Due to the limitations of widely used energy spectrum and spectral analyses for the determination of trace elements in coal,the modes of occurrence of Li still remains unclear.This study investigated the distribution of Li in selected bulk samples and in-situ kaolinite particles in the No.6 Li-rich coals from the Haerwusu Mine of the Jungar Coalfield using ICP-MS and LA-ICP-MS.The results reveal an elevated Li concentration in the lower section of the No.6 coal with high Sr/Ba ratio compared to the upper section with more terrigenous mudstone along the vertical profile.LA-ICP-MS mapping and spot analyses results showed that Li was concentrated in kaolinite but occur in variations in the concentrations of Li among different types of kaolinite.The concentration of Li in kaolinite is ranked as follows:cryptocrystalline kaolinite(2225.83 ppm)>vermicular kaolinite(651.49 ppm)>altered K-bearing kaolinite(593.44 ppm)>clastic kaolinite(478.68 ppm).The in-situ concentration of Li in kaolinite is much higher than that of the bulk samples,indicating that kaolinite is the dominant host mineral for Li as well.The Al2O3/TiO2 and Nb/Yb-Zr/TiO2 ratios indicate that Li in No.6 coal primarily originated from Paleoproterozoic granite in the Yinshan Mountain and felsic volcanic ash.Seawater leaching has a critical influence on the redistribution of Li in the coal from the Haerwusu Mine or even the whole Jungar Coalfield.
基金financially supported by the Natural Science Foundation of Hunan Province,China(No.2024JJ2074)the National Natural Science Foundation of China(No.22376221)the Young Elite Scientists Sponsorship Program by CAST,China(No.2023QNRC001).
文摘Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.
基金Project supported by Guizhou Provincial Basic Research Program (Natural Science)(Qian Ke He Basic-ZK 2024 General 626)National Natural Science Foundation of China (52164018)Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (13210025)。
文摘Rare earth elements(REEs) are associated with phosphorite,which is an important strategic reserve resource.During sorting process of phosphorite,REEs may move with specific host minerals,however,occurrence state and moving pattern of REEs from rock to products are still unclear,which limits separation and enrichment of REEs from phosphorite.Mappings of scanning electron microscope(SEM) and electron probe X-ray micro-analyzer(EPMA) of REEs are highly consistent with those of calcium and phosphorus,and complementary with that of magnesium,which indicates that fluorapatite(Fap) is the main host mineral of REEs.The results of flotation and leaching experiments further indicate that REEs are enriched along with Fap from phosphorite to products.Occupied sites and occupation number of REEs were obtained by X-ray diffraction(XRD) refinement based on the Rietveld method.La,Ce,Nd,and Y can occupy both Ca1 and Ca2 sites.The ratios of La,Ce,Nd,and Y at Ca2 and Cal sites are 4.20,3.70,3.00,and 1.33,showing a decreasing trend,indicating that La,Ce,and Nd tend to occupy Ca2 sites,while Y tends to occupy Ca1 sites.X-ray absorption fine structure(XAFS) shows that REEs mainly form coordinate structures with oxygen and fluorine,which is a direct evidence that REEs replace calcium(Ⅱ) in phosphorite in an isomorphism form.Coordination structure and polyhedral configuration analysis indicate that substitution degree of La,Ce,Nd,and Y is Y> La> Ce≈Nd from easy to difficult at Cal and Ca2 sites.The research enriches the mineralization theory of REEs-bearing phosphorite and provides certain theoretical guidance for selective enrichment of REEs from phosphorite.
基金supported by the National Natural Science Foundation of China(No.41830431)the Shandong Provincial Key Research and Development Program(No.2020ZLYS08).
文摘Understanding the occurrence state of shale oil is crucial for the effective development of shale oil resources.Although the second member of the Kongdian Formation(Ek2)is a key interval for lacustrine shale oil production in the Cangdong Sag,Bohai Bay Basin,the occurrence state and controlling factors of shale oil in this formation remain poorly understood.This study established a multi-step programmed pyrolysis,combined with a light hydrocarbon recovery scheme,to quantitatively characterize the shale oil in different occurrence states.An integrated approach utilizing Rock-Eval pyrolysis,pyrolysis-gas chromatography,and crude oil gas chromatography was employed.Factors influencing the shale oil occurrence state were analyzed from petrology and organic geochemistry perspectives.The study revealed significant variations of shale oil occurrence states within the Ek2,attributed to differences in sedimentary organic matter,mineral compositions,sedimentary structures,and thermal maturity.Felsic laminae are the primary reservoir space for oil in laminated shales,and the frequent interbedding of felsic and organic-rich laminae facilitates the retention of free oil.The contents of free and adsorbed oil are primarily influenced by organic matter content and shale storage capacity,both of which exhibit distinct occurrence patterns.Based on the shale reservoir quality classification using the pyrolysis values of S1-1+S1-2 and(S1-1+S1-2)×100/TOC,the Ek2 shale demonstrates significant exploitation potential,with the first-level reservoirs comprising 66%,second-level reservoirs 11%,and third-level reservoirs 23%.These findings provide new insights into the geological accumulation and production of shale oil.
基金supported by the National Natural Science Foundation of China(42302160)the Sanya City Science and Technology Innovation Project(2022KJCX51)the Support Plan for Outstanding Youth Innovation Team in Shandong Higher Education Institutions(2022KJ060).
文摘The microscopic occurrence characteristics primarily constrain the enrichment and mobility of shale oil.This study collected the lacustrine shales from the Palaeogene Funing Formation in the Gaoyou Sag, Subei Basin. Conventional and multistage Rock-Eval, scanning electron microscopy, and nuclear magnetic resonance(NMR) T1-T2were performed to analyze the contents and occurrence characteristics of shale oil. Low-temperature nitrogen adsorption-desorption(LTNA/D) experiments were conducted on the shales before and after extraction. The relationships between shale oil occurrence with organic matter and pore structures were then discussed. Predominantly, the shale oil in the Funing Formation is found within fractures, with secondary occurrences in interparticle pores linked to brittle minerals and sizeable intraparticle pores associated with clay minerals. The selected shales can be categorized into two types based on the nitrogen isotherms. Type A shales are characterized by high contents of felsic and calcareous minerals but low clay minerals, with larger TOC and shale oil values. Conversely, Type B shales are marked by abundant clay minerals but diminished TOC and shale oil contents. The lower BET specific surface area(SSA), larger average pore diameter, and simpler pore surfaces and pore structures lead to the Type A shales being more conducive to shale oil enrichment and mobility. Shale oil content is predominantly governed by the abundance of organic matter, while an overabundance of organic matter typically equates to a reduced ratio of free oil and diminished fluidity. The BET SSA, volumes of pores less than 25 and 100 nm at extracted state all correlate negatively with total and adsorbed oil contents but display no correlation with free oil, while they have positive relationships with capillary-bound water.Consequently, pore water is mainly saturated in micropores(<25 nm) and minipores(25-100 nm), as well as adsorbed oil, while free oil, i.e., bound and movable oil, primarily exists in mesopores(100-1000 nm) and macropores(>1000 nm). These findings may enhance the understanding of the microscopic occurrence characteristics of shale oil and will contribute to guide resource estimation and shale oil sweet spot exploitation in the Gaoyou Sag, Subei Basin.
基金the Science and Technology Cooperation Project of the CNPC-SWPU Innovation Alliance,China(No.2020CX030101)the National Natural Science Foundation of China(No.42222209)the Scientific Research and Technological Development Program of CNPC,China(No.2023ZZ0801).
文摘Pore structure characteristics,gas content,and micro-scale gas occurrence mechanisms were investigated in the Shan_(2)^(3)sub-member marine-continental transitional shale of the southeastern margin of the Ordos Basin using scanning electron microscope images,lowtemperature N_(2)/CO_(2)adsorption and high-pressure mercury intrusion,methane isothermal adsorption experiments,and CH4-saturated nuclear magnetic resonance(NMR).Two distinct shale types were identified:organic pore-rich shale(Type OP)and microfracture-rich shale(Type M).The Type OP shale exhibited relatively well-developed organic matter pores,while the Type M shale was primarily characterized by a high degree of microfracture development.An experimental method combining methane isothermal adsorption on crushed samples and CH4-saturated NMR of plug samples was proposed to determine the adsorbed gas,free gas,and total gas content under high temperature and pressure conditions.There were four main research findings.(1)Marine-continental transitional shale exhibited substantial total gas content in situ,ranging from 2.58 to 5.73 cm^(3)/g,with an average of 4.35 cm^(3)/g.The adsorbed gas primarily resided in organic matter pores through micropore filling and multilayer adsorption,followed by multilayer adsorption in clay pores.(2)The changes in adsorbed and free pore volumes can be divided into four stages.Pores of<5 nm exclusively contain adsorbed gas,while those of 5-20 nm have a high proportion of adsorbed gas alongside free gas.Pores ranging from 20 to 100 nm have a high proportion of free gas and few adsorbed gas,while pores of>100 nm and microfractures are almost predominantly free gas.(3)The proportion of adsorbed gas in Type OP shale exceeds that in Type M,reaching 66%.(4)Methane adsorbed in Type OP shale demonstrates greater desorption capability,suggesting a potential for enhanced stable production,which finds support in existing production well data.However,it must be emphasized that high-gas-bearing intervals in both types present valuable opportunities for exploration and development.These data may support future model validations and enhance confidence in exploring and developing marine-continental transitional shale gas.
基金supported by the National Natural Science Foundation of China(No.42572076)the Continental Gold Ltd.,Colombian Branch(No.CG-EXP-041-23).
文摘0 INTRODUCTION The Andean orogenic belt,a globally significant active continental margin(Lamb et al.,1997),extends in a north-south direction along the western coast of South America.The Colombian Andes,located in the northern segment of this orogen,constitute a vital component and host abundant Au-Cu resources.Three principal Au-Cu metallogenic belts(Chocó,Middle Cauca,and Antioquia)are developed from west to east across Colombia(Lesage et al.,2013;Sillitoe,2008;Figure 1a).
基金Supported by National Natural Science Foundation of China(42572132,U24B6001,41872150,42230310,U2344209).
文摘The occurrence types and controlling factors of organic matter in the sepiolite-containing successions of the first member of Mid-Permian Maokou Formation(Mao-1 Member for short)in the Eastern Sichuan Basin,SW China,have been investigated through outcrop section measurement,core observation,thin section identification,argon ion polishing-field scanning electron microscopy,energy spectrum analysis,X-ray diffraction,total organic carbon content(TOC),major and trace element analysis.Finally,the symbiotic adsorption model of sepiolite for organic matter enrichment has been established.The results show that the sepiolite-containing successions of the Mao-1 Member are composed of the rhythmite of mudstone,argillaceous limestone and limestone,with five depositional intervals vertically and the organic matter mostly developed in the mudstone and argillaceous limestone layers within the lower three intervals.The organic matter occurrence types are mostly layered or nodular in macro to meso-scale,blocky-vein-like under a microscope,but scattered,interstitial or adsorbed at a mesoscopic scale.It underwent transition processes from lower to higher salinity,from oxygen-poor and anoxic reduction to oxygen-poor and localized oxygen enrichment on the palaeo-environment of the Mao-1 Member.The first two intervals of the early depositional phase of Mao-1 Member constitute the cyclothems of mudstone,argillaceous limestone and limestone and quantities of fibrous-feathered sepiolite settle down within the Tongjiang-Changshou sag with continuous patchy organic matter from adsorption of alginate by sepiolite in intercrystalline,bedding surfaces and interlayer pores.The third and fourth intervals in the mid-depositional phase are mostly composed of the mudstone and argillaceous limestone alternations with the continuous patchy or banded organic matter in the surface and inter-crystalline pores of fibrous,feathered and flaky sepiolite.And the fifth interval in the late depositional phase of the Mao-1 Member comprises the cyclothems of extremely thin layered argillaceous limestone and thick-layered limestone with the fibrous sepiolite depositing in the argillaceous limestone and irregular organic matter dispersing around the sepiolite.Therefore,the symbiotic adsorption between organic matter and sepiolite effectively enhances the preservation efficiency of organic matter and improves the source rock quality of the Mao-1 Member,which enhances our understanding on the enrichment model of the depositional organic matter.
基金jointly supported by project of the China Geological Survey(DD20243375,DD20230478)the Key Research and Development Program of Hunan Province(2023SK2066)the Natural Science Foundation of Hunan Province(2024JJ7620).
文摘Neonicotinoid insecticides(NEOs)have become an integral part of the global insecticide market due to their high efficiency and low toxicity.However,their environmental persistence has raised significant ecological concerns.Dongting Lake represents a vital freshwater lake in China,and its ecosystem health directly affects regional ecological balance and people’s livelihoods.This study systematically investigated the occurrence characteristics and ecological risks of NEOs in water bodies and sediments across the Dongting Lake basin.Based on surface water and sediment samples collected from 26 representative sampling sites,this study quantified nine NEOs using liquid chromatography triple quadrupole mass spectrometry.Furthermore,it assessed ecological risks posed by the NEOs using the risk quotient(RQ)method and fugacity modeling.The results revealed the presence of six NEOs in the water bodies:imidacloprid(IMI),acetamiprid(ACE),clothianidin(CLO),thiamethoxam(THIA),flonicamid(FLO),and dinotefuran(DIN).The total concentrations of these six NEOs averaged 275.11 ng/L.Five predominant NEOs(i.e.,IMI,THIA,ACE,CLO,and DIN)were identified in the sediments,with a mean concentration of 0.31 ng/g.The NEO concentrations in the water bodies across the Dongting Lake basin increased in the order of the Xiangjiang,Zishui,Yuanjiang,and Lishui rivers(collectively referred to as the Four Rivers),the mainstream of Dongting Lake,the Xinqiang River,the Miluo River,and the Hudu,Ouchi,and Songzi rivers(collectively referred to as the Three Outlets).Sediments from tributaries progressively accumulate in the lake.The ecological risk assessment identified IMI and DIN as the highest-risk compounds(RQ>1),with high-risk areas concentrated in the mainstream of Dongting Lake and the Ouchi,Miluo,and Hudu rivers.The fugacity model showed that IMI,ACE,and THIA are prone to diffuse from sediments to water bodies in most areas,with fugacity fractions(ff)values of greater than 0.5.In contrast,the mainstream of Dongting Lake acts as a sink of CLO and DIN(ff values:<0.5).Sediments at the lake’s outlet emerge as an important sink of NEOs.Based on the results of this study,it is advisable to strengthen the supervision of NEO applications in agricultural areas and to implement zonal control strategies.These measures will help reduce ecological risks and protect the safety of water ecosystems in the Dongting Lake region.
基金the National Natural Science Foundation of China(No.81573150)Military Key Discipline Construction Projects of China(No.HL21JD1206).
文摘Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemicals”and“PTSD,”and relevant literature was compiled.Network clustering co-occurrence analysis and qualitative narrative review were conducted.Results:Three hundred and one articles were included in the analysis of published research,which has surged since 2015 with nearly half of all relevant articles coming from North America.The category is dominated by neuroscience and neurology,with two journals,Addictive Behaviors and Drug and Alcohol Dependence,publishing the greatest number of papers on these topics.Most studies focused on psychedelic intervention for PTSD.Three timelines show an“ebb and flow”phenomenon between“substance use/marijuana abuse”and“psychedelic medicine/medicinal cannabis.”Other phytochemicals account for a small proportion of the research and focus on topics like neurosteroid turnover,serotonin levels,and brain-derived neurotrophic factor expression.Conclusion:Research on phytochemicals and PTSD is unevenly distributed across countries/regions,disciplines,and journals.Since 2015,the research paradigm shifted to constitute the mainstream of psychedelic research thus far,leading to the exploration of botanical active ingredients and molecular mechanisms.Other studies focus on anti-oxidative stress and anti-inflammation.
基金supported by the National Natural Science Foundation of China(U22A20501)the National Key Research and Development Plan of China(2022YFD1500601)+4 种基金the National Science and Technology Fundamental Resources Investigation Program of China(2018FY100304)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA28090200)the Liaoning Province Applied Basic Research Plan Program,China(2022JH2/101300184)the Shenyang Science and Technology Plan Program,China(21-109-305)the Liaoning Outstanding Innovation Team,China(XLYC2008015)。
文摘Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,forest land and fallow land were investigated in six regions of northern China.Generic richness,diversity,abundance and biomass of soil nematodes was the lowest in crop land.The richness and diversity of soil nematodes were 28.8and 15.1%higher in fallow land than in crop land,respectively.No significant differences in soil nematode indices were found between forest land and fallow land,but their network keystone genera composition was different.Among the keystone genera,50%of forest land genera were omnivores-predators and 36%of fallow land genera were bacterivores.The proportion of fungivores in forest land was 20.8%lower than in fallow land.The network complexity and the stability were lower in crop land than forest land and fallow land.Soil pH,NH_(4)^(+)-N and NO_(3)^(–)-N were the major factors influencing the soil nematode community in crop land while soil organic carbon and moisture were the major factors in forest land.Soil nematode communities in crop land influenced by artificial management practices were more dependent on the soil environment than communities in forest land and fallow land.Land use induced soil environment variation and altered network relationships by influencing trophic group proportions among keystone nematode genera.
基金supported by the Chung-Ang University Research Grants in 2023.Alsothe work is supported by the ELLIIT Excellence Center at Linköping–Lund in Information Technology in Sweden.
文摘Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1A6A1A10044950).
文摘The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.
