The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback ...The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
Objective Grasp quality and health status of drinking water, and provide scientific basis for decision making of health administrative de- partment. Method According to the Standards for Drinking Water Quality （ GB...Objective Grasp quality and health status of drinking water, and provide scientific basis for decision making of health administrative de- partment. Method According to the Standards for Drinking Water Quality （ GB 5749 -2006）, monitoring results of Tianjin urban and rural drinking water health in 2013 were evaluated, and software SPSS 20.0 and GeoDa was used for temporal-spatial analysis on water quality. Result There were 2 882 copies of monitoring samples in total, in which both finished water and tap water of urban district were qualified, while qualified rates of tap water and secondary water supply from the county were respectively 86.36% and 93.91%, and major exceeding indexes were pH and total number of colonies. Qualified rates of tap water and secondary water supply from the county had difference（x2 = 1 576.875, P 〈0.01 ）. Quality of tap water（ X2 = 5.425, P 〉 0.05） and secondary water supply （X2 = 16.009, P 〉 0.05） was stable at temporal distribution （ January-December）, but spatial distribution of tap water had certain regional difference（x2 = 1 255.802, P 〈0.01 ）. Conclusion General quality situation of Tianjin urban and rural drinking water was better, but qualified rate of water quality in some counties was lower, which had safety risk and threatened the health of residents in the corresponding county. The related departments should enhance the supervision and management of drinking water supply, im- prove supply water quality, strengthen water quality monitoring, and guarantee drinking water safety. Geographic information system can better real- ize visualization of drinking water quality monitoring information.展开更多
This paper proposes an analysis model of frame aggregation in error-free channel with unsaturated traffic and fixed aggregation size. Integrated with model of channel access, calculation of MAC (Media Access Control) ...This paper proposes an analysis model of frame aggregation in error-free channel with unsaturated traffic and fixed aggregation size. Integrated with model of channel access, calculation of MAC (Media Access Control) average service time and queue model of frame aggregation, our model can get the stable result with a recursive algorithm, and it further derive the throughput and latency of frame aggregation in steady state. As the impact of traffic, frame length, collision probability, buffer size, aggregation size and interactive effects are taken into consideration, the effect of every parameter could be evaluated and the major factor which degrades the performance of frame aggregation can be determined in different situation with this model. By the simulation and numerical analysis, this model confirmed its accuracy. The proposed model can be used in the design, optimization and deployment of WLAN (Wireless Local Area Network) and WMN (Wireless Mesh Network) widely.展开更多
The Internet of things(IoT)is a wireless network designed to perform specific tasks and plays a crucial role in various fields such as environmental monitoring,surveillance,and healthcare.To address the limitations im...The Internet of things(IoT)is a wireless network designed to perform specific tasks and plays a crucial role in various fields such as environmental monitoring,surveillance,and healthcare.To address the limitations imposed by inadequate resources,energy,and network scalability,this type of network relies heavily on data aggregation and clustering algorithms.Although various conventional studies have aimed to enhance the lifespan of a network through robust systems,they do not always provide optimal efficiency for real-time applications.This paper presents an approach based on state-of-the-art machine-learning methods.In this study,we employed a novel approach that combines an extended version of principal component analysis(PCA)and a reinforcement learning algorithm to achieve efficient clustering and data reduction.The primary objectives of this study are to enhance the service life of a network,reduce energy usage,and improve data aggregation efficiency.We evaluated the proposed methodology using data collected from sensors deployed in agricultural fields for crop monitoring.Our proposed approach(PQL)was compared to previous studies that utilized adaptive Q-learning(AQL)and regional energy-aware clustering(REAC).Our study outperformed in terms of both network longevity and energy consumption and established a fault-tolerant network.展开更多
Based on related statistical data during 1980-2014,change rule of Guangxi cultivated land pressure level was studied.Taking each municipal administrative division as evaluation unit,temporal-spatial change trend of cu...Based on related statistical data during 1980-2014,change rule of Guangxi cultivated land pressure level was studied.Taking each municipal administrative division as evaluation unit,temporal-spatial change trend of cultivated land pressure level was explored by establishing pressure index model of cultivated land,and principal component analysis was used to explore the driving force of cultivated land pressure.Results showed that from 1980 to 2014 in Guangxi,cultivated land pressure was at level one in 12 years,level two in 19 years and level three in 4 years;mean of cultivated land pressure in each city during 2005-2014 was taken as average level of cultivated land pressure in the city,in which cultivated land pressure values of Chongzuo City,Baise City,Laibin City,Liuzhou City,Fangchenggang City,Nanning City,Hechi City and Guigang City were all lower than average level in Guangxi at the same period.Driving factors of cultivated land pressure index mainly contained urbanization rate,Engel coefficient of rural households(ECRH),per capita cultivated land area,total population and rural per capita net income(RPFI).展开更多
A sensitivity analysis is performed to analyze the effects of the nanoparticle(NP)aggregation and thermal radiation on heat transport of the nanoliquids(titania based on ethylene glycol)over a vertical cylinder.The op...A sensitivity analysis is performed to analyze the effects of the nanoparticle(NP)aggregation and thermal radiation on heat transport of the nanoliquids(titania based on ethylene glycol)over a vertical cylinder.The optimization of heat transfer rate and friction factor is performed for NP volume fraction(1%≤φ≤3%),radiation parameter(1≤R_(t)≤3),and mixed convection parameter(1.5≤λ≤2.5)via the facecentered central composite design(CCD)and the response surface methodology(RSM).The modified Krieger and Dougherty model(MKDM)for dynamic viscosity and the Bruggeman model(BM)for thermal conductivity are utilized to simulate nanoliquids with the NP aggregation aspect.The complicated nonlinear problem is treated numerically.It is found that the temperature of nanoliquid is enhanced due to the aggregation of NPs.The friction factor is more sensitive to the volume fraction of NPs than the thermal radiation and the mixed convection parameter.Furthermore,the heat transport rate is more sensitive to the effect of radiative heat compared with the NP volume fraction and mixed convection parameter.展开更多
Individual participant data (IPD) meta-analysis was developed to overcome several meta-analytical pitfalls of classical meta-analysis. One advantage of classical psychometric meta-analysis over IPD meta-analysis is th...Individual participant data (IPD) meta-analysis was developed to overcome several meta-analytical pitfalls of classical meta-analysis. One advantage of classical psychometric meta-analysis over IPD meta-analysis is the corrections of the aggregated unit of studies, namely study differences, i.e., artifacts, such as measurement error. Without these corrections on a study level, meta-analysts may assume moderator variables instead of artifacts between studies. The psychometric correction of the aggregation unit of individuals in IPD meta-analysis has been neglected by IPD meta-analysts thus far. In this paper, we present the adaptation of a psychometric approach for IPD meta-analysis to account for the differences in the aggregation unit of individuals to overcome differences between individuals. We introduce the reader to this approach using the aggregation of lens model studies on individual data as an example, and lay out different application possibilities for the future (e.g., big data analysis). Our suggested psychometric IPD meta-analysis supplements the meta-analysis approaches within the field and is a suitable alternative for future analysis.展开更多
This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day a...This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons.Road Traffic Accident(RTA)data in 3 years(2015-2017)in Hanoi,Vietnam were used to analyze and test this approach.Firstly,the RTA data were divided into four seasons in accordance with Hanoi's weather conditions and the time intervals such as the daytime,nighttime,or peak hours.Then,the Kernel Density Estimation(KDE)method was applied to analyze hotspots according to the time intervals and seasons.Finally,the results were presented by using the comap technique.This study considered both analyses with and without SI.The accident SI measures the seriousness of an accident.The approach method is to give higher weights to the more serious accidents,but not with the extremely high values calculated on a direct rate to the accident expenditures.The results showed that both analyses determined the relatively similar hotspots,but the rankings of some hotspots were quite different due to the integration of SI.It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate.From there,the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately.This is also the first study about this issue in Vietnam,so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities.展开更多
Citrate-reduced silver nanoparticles (Ag-NPs) are used extensively for surface-enhanced Raman scattering (SERS) studies, but are typically found to aggregate using an aggregation agent. This study is aimed at developi...Citrate-reduced silver nanoparticles (Ag-NPs) are used extensively for surface-enhanced Raman scattering (SERS) studies, but are typically found to aggregate using an aggregation agent. This study is aimed at developing a simple, stable, and reproducible aggregated method for Ag-NPs without any aggregation agents in aqueous solutions. The aggregation is induced by the process of centrifugation, water washing and ultrasonication. A mechanism based on the nonuniform distribution of capping ligands is proposed to account for the aggregated structure formation. UV-Vis-NIR extinction spectra and TEM allowed us to identify the existence of Ag-NPs aggregation. Further, due to the polydisperse mixture of Ag-NPs (20~65 nm) used in the present work, Ag-NPs are aggregated closely, which contribute to the observation of low-concentration SERS from the residual citrate layer or even the single-molecule SERS of R6Gon aggregation. After the evaporation of droplet of Ag-NPs aggregation on the Si substrate, citrate or R6Gcould also be detected but with marked redor blue-shifts.展开更多
Empirical orthogonal function(EOF)analysis was applied to a 50-year long time series of monthly mean positions of the Kuroshio path south of Japan from a regional reanalysis.Three leading EOF modes characterize the co...Empirical orthogonal function(EOF)analysis was applied to a 50-year long time series of monthly mean positions of the Kuroshio path south of Japan from a regional reanalysis.Three leading EOF modes characterize the contributions from three typical paths of the Kuroshio meander:the typical large meander path,the offshore nonlarge meander path,and the nearshore non-large meander path,respectively.Accordingly,the spatial variation characteristics of oceanic anomaly fields can be depicted by their regression fields upon the associated three leading principal components(PCs),which are well-matched with the results of composite analysis corresponding to each period of the three typical Kuroshio paths.A new index for the typical large meander is defined by using the second leading PC,which is highly correlated with the Kushimoto-Uragami index.Spectral analysis of this new index series shows variability of the Kuroshio path south of Japan at time scales of about 7–8 years and 20 years.展开更多
Data aggregation technology reduces traffic overhead of wireless sensor network and extends effective working time of the network,yet continued operation of wireless sensor networks increases the probability of aggreg...Data aggregation technology reduces traffic overhead of wireless sensor network and extends effective working time of the network,yet continued operation of wireless sensor networks increases the probability of aggregation nodes being captured and probability of aggregated data being tampered.Thus it will seriously affect the security performance of the network. For network security issues,a stateful public key based SDAM( secure data aggregation model) is proposed for wireless sensor networks( WSNs),which employs a new stateful public key encryption to provide efficient end-to-end security. Moreover,the security aggregation model will not impose any bound on the aggregation function property,so as to realize the low cost and high security level at the same time.展开更多
Based on the official criminal data released by the Tokyo Metropolitan Police Department in 2019,this paper discusses the temporal-spatial distribution of various types of crimes in the special wards of Tokyo.The resu...Based on the official criminal data released by the Tokyo Metropolitan Police Department in 2019,this paper discusses the temporal-spatial distribution of various types of crimes in the special wards of Tokyo.The results show that:(1)The times of high and low incidence of different types of crime differ significantly.Although vicious crime and violent crime present no obvious monthly distribution,property crime clearly differs between the first and second half of a calendar year.(2)The month before the new year sees a surge in most types of crime.(3)Vicious crime peaks in the hours between night and early morning.Violent crime and property crime correlate positively with the frequency of human interaction and peak in the morning and evening commuting hours.(4)The spatial distribution of crime resembles the concentric circles of the three rings of the special wards of Tokyo,with a central high-incidence area,a center-peripheral low-incidence area,and a marginal high-incidence area.In addition,the center sees more personal crime than the periphery,whereas property crimes show the opposite trend.(5)A spatial autocorrelation analysis shows that the special wards of Tokyo may be grouped into the“high-high”and“low-low”agglomeration modes of different types of crime,with marked differences between the various types of crime.The crime can be divided into three types:central agglomeration,double central agglomeration,and decentralized agglomeration.展开更多
Petrographic, physical, and mechanical assessment investigation of NikanaiGhar limestone aggregate exposed in the Lower Dir area of Malakand Division, Pakistan, were conducted to evaluate and investigate its potential...Petrographic, physical, and mechanical assessment investigation of NikanaiGhar limestone aggregate exposed in the Lower Dir area of Malakand Division, Pakistan, were conducted to evaluate and investigate its potential for use as a construction material for engineering projects. Different geotechnical tests and petrographic analyses were performed to evaluate its potential for construction purposes. Geotechnical tests include unconfined compressive strength, ultimate tensile strength test, specific gravity, share strength, porosity, and water absorption. The evaluated physical attributes were compared to standard specifications to determine their suitability as a construction material. Petrographic investigation indicates mainly two types of stones. Stylolitic spar stone and Spar stone are metamorphosed equivalent limestones and are not prone to alkali-silica reactivity. Mutual relationships between physical parameters have been described by simple regression analysis. Significant direct correlation of specific gravity with ultimate tensile strength and uniaxial compressive strength was noted. However, negative trends of Porosity with ultimate tensile strength and uniaxial compressive strength were observed which is in accordance with standard. The analysis revealed that the limestones of NikanaiGhar Formation fall within the standard specification limits and can be used as aggregates for the indigenous construction industry.展开更多
[ Objective] The research aimed to analyze temporal-spatial variation characteristics of the extreme precipitation days over South China from 1961 to 2010. [ Method] Based on the daily precipitation data in meteorolog...[ Objective] The research aimed to analyze temporal-spatial variation characteristics of the extreme precipitation days over South China from 1961 to 2010. [ Method] Based on the daily precipitation data in meteorological stations over South China, extreme precipitation thresholds were determined according to the percentiles distribution for different stations. Temporal-spatial variation characteristics of the extreme precipitation days over South China were studied by the methods of fuzzy clustering, trend coefficient, wavelet analysis and cross spectrum analysis, etc. [ Re- suit] Four sub-regions were identified over South China. They were respectively Nanling area, west Guangxi area, Coast area and Hainan area. Occurrence seasons of the extreme precipitations in each sub-region were significantly different. Extreme precipitation clays in four sub-regions all had increase trends, and those of Nanling area and Coast area were significant. From wavelet analysis and cress spectrum analysis, there were significant periodic variation characteristics. Extreme precipitation days in each sub-region all had significant same-phase evolution trends at the peri- od of 2 -5 years, but backward time length was different. [ Conclusion] The research provided background materials for forecast and influence as- sessment of the extremely heavy precipitation over South China.展开更多
A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and cli...A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and climbing up to the plateaus of the patterns pre-lithographed on the indium tin oxide glass as the frequency of the alternating electrical field increased. Two critical frequencies fcritl ≈ 15 kHz and fcrit2 ≈ 40 kHz, corresponding to the transitions of the colloid behaviour were observed. When f 〈 15 kHz, the particles were forced to aggregate along the grooves of the negative photoresist patterned template. When 15 kHz 〈 f 〈 40 kHz, the particle clusters became unstable and most particles started to disperse and were blocked by the fringes of the negative photoresist patterns. As the frequency increased to above 40 kHz, the majority of particles started to climb up to the plateaus of the patterns. Furthermore, the dynamics analysis for the behaviour of the colloids was given and we found out that positive or negative dielectrophoresis force, electrohydrodynamic force, particle-particle interactions and Brownian motion change with the frequency of the alternating electric field. Thus, changes of the related forces affect or control the behaviour of the colloids.展开更多
α-synuclein, a member of the synuclein family, is predominately expressed in brain tissues, where it is the major component of Lewy bodies, the major hallmark of Parkinson＇s disease. We analyzed the phylogenetics, g...α-synuclein, a member of the synuclein family, is predominately expressed in brain tissues, where it is the major component of Lewy bodies, the major hallmark of Parkinson＇s disease. We analyzed the phylogenetics, gene structure, and effects of different forms of α-synuclein on in vitro protein aggregation. The synuclein phylogenetic tree showed that sequences could be classified into α, β, and y protein groups. The orthologous gene α-, β- and y-synuclein showed similar evolutionary distance to the paralogous gene α-, β- and y-synuclein. Bioinformatics analysis suggests that the amino-acid sequence of human a-synuclein can be divided into three regions： N-terminal amphipathic region （1-60）, central hydrophobic non-amyloid beta component segment （61-95）, and the C-terminal acidic part （96-140）. The mutant site of A30P is at the second exon of α-synuclein, whereas E46K is located at the third exon of α-synuclein. α-synuclein alternative splicing results in four isomers, and five exons, all of which participate in protein coding, comprising 140 amino acids to produce the major α-synuclein in vivo. The three α-synuclein isoforms are products of alternative splicing, α-synuclein 126, 112 and 98. We also review the genetic and cellular factors that affect the aggregation of α-synuclein and compounds that inhibit aggregation. A better understanding of α-synuclein sequences, structure, and function may allow better targeted therapy and diagnosis of α-synuclein in Parkinson＇s disease and other neurodegenerative diseases.展开更多
The rapid growth of IP traffic has contributed to wide deployment of optical devices in elastic optical network.However,the passband shape of wavelength selective switches(WSSs)that are used in reconfigurable optical ...The rapid growth of IP traffic has contributed to wide deployment of optical devices in elastic optical network.However,the passband shape of wavelength selective switches(WSSs)that are used in reconfigurable optical add-drop multiplexer(ROADM)/optical cross connect(OXC)is not ideal,causing the narrowing of spectrum.Spectral narrowing will lead to signal impairment.Therefore,guard-bands need to be inserted between adjacent paths which will cause the waste of resources.In this paper,we propose a service-based intelligent aggregation node selection and area division(ANS-AD)algorithm.For the rationality of the aggregation node selection,the ANS-AD algorithm chooses the aggregation nodes according to historical traffic information based on big data analysis.Then the ANS-AD algorithm divides the topology into areas according to the result of the aggregation node selection.Based on the ANS-AD algorithm,we propose a time-domain and spectral-domain flow aggregation(TS-FA)algorithm.For the purpose of reducing resources'waste,the TS-FA algorithm attempts to reduce the insertion of guard-bands by time-domain and spectral-domain flow aggregation.Moreover,we design a time-domain and spectral-domain flow aggregation module on software defined optical network(SDON)architecture.Finally,a simulation is designed to evaluate the performance of the proposed algorithms and the results show that our proposed algorithms can effectively reduce the resource waste.展开更多
A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linea...A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.展开更多
Soil organic matter (SOM) is a complex heterogeneous mixture formed through decomposition and organo-mineral interactions, and characterization of its composition and biogeochemical stability is challenging. From this...Soil organic matter (SOM) is a complex heterogeneous mixture formed through decomposition and organo-mineral interactions, and characterization of its composition and biogeochemical stability is challenging. From this perspective, Rock-Eval® is a rapid and efficient thermal analytical method that combines the quantitative and qualitative information of SOM, including several parameters related to thermal stability. This approach has already been used to monitor changes in organic matter (OM) properties at the landscape, cropland, and soil profile scales. This study was aimed to assess the stability of SOM pools by characterizing the grain size fractions from forest litters and topsoils using Rock-Eval® thermal analysis. Litter (organic) and topsoil samples were collected from a beech forest in Normandy (France), whose management in the last 200 years has been documented. Fractionation by wet sieving was used to separate large debris (> 2 000 μm) and coarse (200–2 000 μm) and fine particulate OM (POM) (50–200 μm) in the organic samples as well as coarse (200–2 000 μm), medium (50–200 μm), and fine (< 50 μm) fractions of the topsoil samples. Rock-Eval® was able to provide thermal parameters sensitive enough to study fine-scale soil processes. In the organic layers, quantitative and qualitative changes were explained by the progressive decomposition of labile organic compounds from plant debris to the finest organic particles. Meanwhile, the grain size fractions of topsoils presented different characteristics. The coarse organo-mineral fractions showed higher C contents, albeit with a different composition, higher thermal stability, and greater decomposition degree than the plant debris forming the organic layer. These results are consistent with those of previous studies that microbial activity is more effective in this fraction. The finest fractions of topsoils showed low C contents, the highest thermal stability, and low decomposition degree, which can be explained by the stronger interactions with the mineral matrix. Therefore, it is suggested that the dynamics of OM in the different size fractions be interpreted in the light of a plant-microbe-soil continuum. Finally, three distinct thermostable C pools were highlighted through the grain size heterogeneity of SOM: free coarse OM (large debris and coarse and fine particles), weakly protected OM in (bio)aggregates (coarse fraction of topsoil), and stabilized OM in the fine fractions of topsoil, which resulted from the interactions within organo-mineral complexes. Therefore, Rock-Eval® thermal parameters can be used to empirically illustrate the conceptual models emphasizing the roles of drivers played by the gradual decomposition and protection of the most thermally labile organic constituents.展开更多
基金funded by the National Natural Science Foundation of China(NSFC)(No.62066024)funded by Basic Scientific Research Projects of Higher Education Institutions in Liaoning Province(LJ212411632063)the National Undergraduate Training Program for Innovation and Entrepreneurship(S202511632045).
文摘The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
基金Supported by Science and Technology Foundation of Tianjin Municipal Health Bureau(2013KY18,2013KY19)Science and Technology Foundation of Tianjin Center for Disease Control and Prevention(CDCKY1301)Tianjin Natural Science Fund(14JCQNJC11900)
文摘Objective Grasp quality and health status of drinking water, and provide scientific basis for decision making of health administrative de- partment. Method According to the Standards for Drinking Water Quality （ GB 5749 -2006）, monitoring results of Tianjin urban and rural drinking water health in 2013 were evaluated, and software SPSS 20.0 and GeoDa was used for temporal-spatial analysis on water quality. Result There were 2 882 copies of monitoring samples in total, in which both finished water and tap water of urban district were qualified, while qualified rates of tap water and secondary water supply from the county were respectively 86.36% and 93.91%, and major exceeding indexes were pH and total number of colonies. Qualified rates of tap water and secondary water supply from the county had difference（x2 = 1 576.875, P 〈0.01 ）. Quality of tap water（ X2 = 5.425, P 〉 0.05） and secondary water supply （X2 = 16.009, P 〉 0.05） was stable at temporal distribution （ January-December）, but spatial distribution of tap water had certain regional difference（x2 = 1 255.802, P 〈0.01 ）. Conclusion General quality situation of Tianjin urban and rural drinking water was better, but qualified rate of water quality in some counties was lower, which had safety risk and threatened the health of residents in the corresponding county. The related departments should enhance the supervision and management of drinking water supply, im- prove supply water quality, strengthen water quality monitoring, and guarantee drinking water safety. Geographic information system can better real- ize visualization of drinking water quality monitoring information.
基金supported by National Natural Science Foundation of China under Grant No.60772085, 61071108Sino-Finland Joint Project under Grant No.2010DFB10570China Fundamental Research Funds for the Central Universities under Grant No.SWJTU 09ZT14
文摘This paper proposes an analysis model of frame aggregation in error-free channel with unsaturated traffic and fixed aggregation size. Integrated with model of channel access, calculation of MAC (Media Access Control) average service time and queue model of frame aggregation, our model can get the stable result with a recursive algorithm, and it further derive the throughput and latency of frame aggregation in steady state. As the impact of traffic, frame length, collision probability, buffer size, aggregation size and interactive effects are taken into consideration, the effect of every parameter could be evaluated and the major factor which degrades the performance of frame aggregation can be determined in different situation with this model. By the simulation and numerical analysis, this model confirmed its accuracy. The proposed model can be used in the design, optimization and deployment of WLAN (Wireless Local Area Network) and WMN (Wireless Mesh Network) widely.
文摘The Internet of things(IoT)is a wireless network designed to perform specific tasks and plays a crucial role in various fields such as environmental monitoring,surveillance,and healthcare.To address the limitations imposed by inadequate resources,energy,and network scalability,this type of network relies heavily on data aggregation and clustering algorithms.Although various conventional studies have aimed to enhance the lifespan of a network through robust systems,they do not always provide optimal efficiency for real-time applications.This paper presents an approach based on state-of-the-art machine-learning methods.In this study,we employed a novel approach that combines an extended version of principal component analysis(PCA)and a reinforcement learning algorithm to achieve efficient clustering and data reduction.The primary objectives of this study are to enhance the service life of a network,reduce energy usage,and improve data aggregation efficiency.We evaluated the proposed methodology using data collected from sensors deployed in agricultural fields for crop monitoring.Our proposed approach(PQL)was compared to previous studies that utilized adaptive Q-learning(AQL)and regional energy-aware clustering(REAC).Our study outperformed in terms of both network longevity and energy consumption and established a fault-tolerant network.
基金Supported by Public Bidding Project of the Guangxi Department of Land and Resources(GXZC2015-G3-0576-GTZB)
文摘Based on related statistical data during 1980-2014,change rule of Guangxi cultivated land pressure level was studied.Taking each municipal administrative division as evaluation unit,temporal-spatial change trend of cultivated land pressure level was explored by establishing pressure index model of cultivated land,and principal component analysis was used to explore the driving force of cultivated land pressure.Results showed that from 1980 to 2014 in Guangxi,cultivated land pressure was at level one in 12 years,level two in 19 years and level three in 4 years;mean of cultivated land pressure in each city during 2005-2014 was taken as average level of cultivated land pressure in the city,in which cultivated land pressure values of Chongzuo City,Baise City,Laibin City,Liuzhou City,Fangchenggang City,Nanning City,Hechi City and Guigang City were all lower than average level in Guangxi at the same period.Driving factors of cultivated land pressure index mainly contained urbanization rate,Engel coefficient of rural households(ECRH),per capita cultivated land area,total population and rural per capita net income(RPFI).
文摘A sensitivity analysis is performed to analyze the effects of the nanoparticle(NP)aggregation and thermal radiation on heat transport of the nanoliquids(titania based on ethylene glycol)over a vertical cylinder.The optimization of heat transfer rate and friction factor is performed for NP volume fraction(1%≤φ≤3%),radiation parameter(1≤R_(t)≤3),and mixed convection parameter(1.5≤λ≤2.5)via the facecentered central composite design(CCD)and the response surface methodology(RSM).The modified Krieger and Dougherty model(MKDM)for dynamic viscosity and the Bruggeman model(BM)for thermal conductivity are utilized to simulate nanoliquids with the NP aggregation aspect.The complicated nonlinear problem is treated numerically.It is found that the temperature of nanoliquid is enhanced due to the aggregation of NPs.The friction factor is more sensitive to the volume fraction of NPs than the thermal radiation and the mixed convection parameter.Furthermore,the heat transport rate is more sensitive to the effect of radiative heat compared with the NP volume fraction and mixed convection parameter.
文摘Individual participant data (IPD) meta-analysis was developed to overcome several meta-analytical pitfalls of classical meta-analysis. One advantage of classical psychometric meta-analysis over IPD meta-analysis is the corrections of the aggregated unit of studies, namely study differences, i.e., artifacts, such as measurement error. Without these corrections on a study level, meta-analysts may assume moderator variables instead of artifacts between studies. The psychometric correction of the aggregation unit of individuals in IPD meta-analysis has been neglected by IPD meta-analysts thus far. In this paper, we present the adaptation of a psychometric approach for IPD meta-analysis to account for the differences in the aggregation unit of individuals to overcome differences between individuals. We introduce the reader to this approach using the aggregation of lens model studies on individual data as an example, and lay out different application possibilities for the future (e.g., big data analysis). Our suggested psychometric IPD meta-analysis supplements the meta-analysis approaches within the field and is a suitable alternative for future analysis.
文摘This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons.Road Traffic Accident(RTA)data in 3 years(2015-2017)in Hanoi,Vietnam were used to analyze and test this approach.Firstly,the RTA data were divided into four seasons in accordance with Hanoi's weather conditions and the time intervals such as the daytime,nighttime,or peak hours.Then,the Kernel Density Estimation(KDE)method was applied to analyze hotspots according to the time intervals and seasons.Finally,the results were presented by using the comap technique.This study considered both analyses with and without SI.The accident SI measures the seriousness of an accident.The approach method is to give higher weights to the more serious accidents,but not with the extremely high values calculated on a direct rate to the accident expenditures.The results showed that both analyses determined the relatively similar hotspots,but the rankings of some hotspots were quite different due to the integration of SI.It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate.From there,the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately.This is also the first study about this issue in Vietnam,so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities.
文摘Citrate-reduced silver nanoparticles (Ag-NPs) are used extensively for surface-enhanced Raman scattering (SERS) studies, but are typically found to aggregate using an aggregation agent. This study is aimed at developing a simple, stable, and reproducible aggregated method for Ag-NPs without any aggregation agents in aqueous solutions. The aggregation is induced by the process of centrifugation, water washing and ultrasonication. A mechanism based on the nonuniform distribution of capping ligands is proposed to account for the aggregated structure formation. UV-Vis-NIR extinction spectra and TEM allowed us to identify the existence of Ag-NPs aggregation. Further, due to the polydisperse mixture of Ag-NPs (20~65 nm) used in the present work, Ag-NPs are aggregated closely, which contribute to the observation of low-concentration SERS from the residual citrate layer or even the single-molecule SERS of R6Gon aggregation. After the evaporation of droplet of Ag-NPs aggregation on the Si substrate, citrate or R6Gcould also be detected but with marked redor blue-shifts.
基金The National Natural Science Foundation of China under contract No.41876014.
文摘Empirical orthogonal function(EOF)analysis was applied to a 50-year long time series of monthly mean positions of the Kuroshio path south of Japan from a regional reanalysis.Three leading EOF modes characterize the contributions from three typical paths of the Kuroshio meander:the typical large meander path,the offshore nonlarge meander path,and the nearshore non-large meander path,respectively.Accordingly,the spatial variation characteristics of oceanic anomaly fields can be depicted by their regression fields upon the associated three leading principal components(PCs),which are well-matched with the results of composite analysis corresponding to each period of the three typical Kuroshio paths.A new index for the typical large meander is defined by using the second leading PC,which is highly correlated with the Kushimoto-Uragami index.Spectral analysis of this new index series shows variability of the Kuroshio path south of Japan at time scales of about 7–8 years and 20 years.
基金Support by the National High Technology Research and Development Program of China(No.2012AA120802)the National Natural Science Foundation of China(No.61302074)+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education(No.20122301120004)Natural Science Foundation of Heilongjiang Province(No.QC2013C061)
文摘Data aggregation technology reduces traffic overhead of wireless sensor network and extends effective working time of the network,yet continued operation of wireless sensor networks increases the probability of aggregation nodes being captured and probability of aggregated data being tampered.Thus it will seriously affect the security performance of the network. For network security issues,a stateful public key based SDAM( secure data aggregation model) is proposed for wireless sensor networks( WSNs),which employs a new stateful public key encryption to provide efficient end-to-end security. Moreover,the security aggregation model will not impose any bound on the aggregation function property,so as to realize the low cost and high security level at the same time.
基金National Natural Science Foundation of China(No.U1811464)。
文摘Based on the official criminal data released by the Tokyo Metropolitan Police Department in 2019,this paper discusses the temporal-spatial distribution of various types of crimes in the special wards of Tokyo.The results show that:(1)The times of high and low incidence of different types of crime differ significantly.Although vicious crime and violent crime present no obvious monthly distribution,property crime clearly differs between the first and second half of a calendar year.(2)The month before the new year sees a surge in most types of crime.(3)Vicious crime peaks in the hours between night and early morning.Violent crime and property crime correlate positively with the frequency of human interaction and peak in the morning and evening commuting hours.(4)The spatial distribution of crime resembles the concentric circles of the three rings of the special wards of Tokyo,with a central high-incidence area,a center-peripheral low-incidence area,and a marginal high-incidence area.In addition,the center sees more personal crime than the periphery,whereas property crimes show the opposite trend.(5)A spatial autocorrelation analysis shows that the special wards of Tokyo may be grouped into the“high-high”and“low-low”agglomeration modes of different types of crime,with marked differences between the various types of crime.The crime can be divided into three types:central agglomeration,double central agglomeration,and decentralized agglomeration.
文摘Petrographic, physical, and mechanical assessment investigation of NikanaiGhar limestone aggregate exposed in the Lower Dir area of Malakand Division, Pakistan, were conducted to evaluate and investigate its potential for use as a construction material for engineering projects. Different geotechnical tests and petrographic analyses were performed to evaluate its potential for construction purposes. Geotechnical tests include unconfined compressive strength, ultimate tensile strength test, specific gravity, share strength, porosity, and water absorption. The evaluated physical attributes were compared to standard specifications to determine their suitability as a construction material. Petrographic investigation indicates mainly two types of stones. Stylolitic spar stone and Spar stone are metamorphosed equivalent limestones and are not prone to alkali-silica reactivity. Mutual relationships between physical parameters have been described by simple regression analysis. Significant direct correlation of specific gravity with ultimate tensile strength and uniaxial compressive strength was noted. However, negative trends of Porosity with ultimate tensile strength and uniaxial compressive strength were observed which is in accordance with standard. The analysis revealed that the limestones of NikanaiGhar Formation fall within the standard specification limits and can be used as aggregates for the indigenous construction industry.
文摘[ Objective] The research aimed to analyze temporal-spatial variation characteristics of the extreme precipitation days over South China from 1961 to 2010. [ Method] Based on the daily precipitation data in meteorological stations over South China, extreme precipitation thresholds were determined according to the percentiles distribution for different stations. Temporal-spatial variation characteristics of the extreme precipitation days over South China were studied by the methods of fuzzy clustering, trend coefficient, wavelet analysis and cross spectrum analysis, etc. [ Re- suit] Four sub-regions were identified over South China. They were respectively Nanling area, west Guangxi area, Coast area and Hainan area. Occurrence seasons of the extreme precipitations in each sub-region were significantly different. Extreme precipitation clays in four sub-regions all had increase trends, and those of Nanling area and Coast area were significant. From wavelet analysis and cress spectrum analysis, there were significant periodic variation characteristics. Extreme precipitation days in each sub-region all had significant same-phase evolution trends at the peri- od of 2 -5 years, but backward time length was different. [ Conclusion] The research provided background materials for forecast and influence as- sessment of the extremely heavy precipitation over South China.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.10874153 and 50773003)the Science Foundation of Zhejiang Sci-Tech University of China,and the Innovation Research Project for Graduate Student of Zhejiang Province of China (Grant No.YK 2009051)
文摘A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and climbing up to the plateaus of the patterns pre-lithographed on the indium tin oxide glass as the frequency of the alternating electrical field increased. Two critical frequencies fcritl ≈ 15 kHz and fcrit2 ≈ 40 kHz, corresponding to the transitions of the colloid behaviour were observed. When f 〈 15 kHz, the particles were forced to aggregate along the grooves of the negative photoresist patterned template. When 15 kHz 〈 f 〈 40 kHz, the particle clusters became unstable and most particles started to disperse and were blocked by the fringes of the negative photoresist patterns. As the frequency increased to above 40 kHz, the majority of particles started to climb up to the plateaus of the patterns. Furthermore, the dynamics analysis for the behaviour of the colloids was given and we found out that positive or negative dielectrophoresis force, electrohydrodynamic force, particle-particle interactions and Brownian motion change with the frequency of the alternating electric field. Thus, changes of the related forces affect or control the behaviour of the colloids.
基金the Fundamental Research Funds for the Central Universities,No.SWJTU09BR222,SWJTU09BR217the Program of Southwest Jiaotong University Young Teachers Research Fund,No.2009Q057,2009Q051+1 种基金the Program of the Fundamental Research Funds for the Central Universities,No.SWJTU09ZT28the Son Program of Fundamental Platform of Science and Technology Source Condition,the Ministry of Science and Technology of China,No.2005DKA21404
文摘α-synuclein, a member of the synuclein family, is predominately expressed in brain tissues, where it is the major component of Lewy bodies, the major hallmark of Parkinson＇s disease. We analyzed the phylogenetics, gene structure, and effects of different forms of α-synuclein on in vitro protein aggregation. The synuclein phylogenetic tree showed that sequences could be classified into α, β, and y protein groups. The orthologous gene α-, β- and y-synuclein showed similar evolutionary distance to the paralogous gene α-, β- and y-synuclein. Bioinformatics analysis suggests that the amino-acid sequence of human a-synuclein can be divided into three regions： N-terminal amphipathic region （1-60）, central hydrophobic non-amyloid beta component segment （61-95）, and the C-terminal acidic part （96-140）. The mutant site of A30P is at the second exon of α-synuclein, whereas E46K is located at the third exon of α-synuclein. α-synuclein alternative splicing results in four isomers, and five exons, all of which participate in protein coding, comprising 140 amino acids to produce the major α-synuclein in vivo. The three α-synuclein isoforms are products of alternative splicing, α-synuclein 126, 112 and 98. We also review the genetic and cellular factors that affect the aggregation of α-synuclein and compounds that inhibit aggregation. A better understanding of α-synuclein sequences, structure, and function may allow better targeted therapy and diagnosis of α-synuclein in Parkinson＇s disease and other neurodegenerative diseases.
基金funded by ZTE Industry-Academia-Research Cooperation Funds under Grant No.2017110031005226
文摘The rapid growth of IP traffic has contributed to wide deployment of optical devices in elastic optical network.However,the passband shape of wavelength selective switches(WSSs)that are used in reconfigurable optical add-drop multiplexer(ROADM)/optical cross connect(OXC)is not ideal,causing the narrowing of spectrum.Spectral narrowing will lead to signal impairment.Therefore,guard-bands need to be inserted between adjacent paths which will cause the waste of resources.In this paper,we propose a service-based intelligent aggregation node selection and area division(ANS-AD)algorithm.For the rationality of the aggregation node selection,the ANS-AD algorithm chooses the aggregation nodes according to historical traffic information based on big data analysis.Then the ANS-AD algorithm divides the topology into areas according to the result of the aggregation node selection.Based on the ANS-AD algorithm,we propose a time-domain and spectral-domain flow aggregation(TS-FA)algorithm.For the purpose of reducing resources'waste,the TS-FA algorithm attempts to reduce the insertion of guard-bands by time-domain and spectral-domain flow aggregation.Moreover,we design a time-domain and spectral-domain flow aggregation module on software defined optical network(SDON)architecture.Finally,a simulation is designed to evaluate the performance of the proposed algorithms and the results show that our proposed algorithms can effectively reduce the resource waste.
基金Project supported by the National Natural Science Foundation of China (Nos.12072007,12072006,12132001,and 52192632)the Ningbo Natural Science Foundation of Zhejiang Province of China (No.202003N4018)the Defense Industrial Technology Development Program of China (Nos.JCKY2019205A006,JCKY2019203A003,and JCKY2021204A002)。
文摘A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.
文摘Soil organic matter (SOM) is a complex heterogeneous mixture formed through decomposition and organo-mineral interactions, and characterization of its composition and biogeochemical stability is challenging. From this perspective, Rock-Eval® is a rapid and efficient thermal analytical method that combines the quantitative and qualitative information of SOM, including several parameters related to thermal stability. This approach has already been used to monitor changes in organic matter (OM) properties at the landscape, cropland, and soil profile scales. This study was aimed to assess the stability of SOM pools by characterizing the grain size fractions from forest litters and topsoils using Rock-Eval® thermal analysis. Litter (organic) and topsoil samples were collected from a beech forest in Normandy (France), whose management in the last 200 years has been documented. Fractionation by wet sieving was used to separate large debris (> 2 000 μm) and coarse (200–2 000 μm) and fine particulate OM (POM) (50–200 μm) in the organic samples as well as coarse (200–2 000 μm), medium (50–200 μm), and fine (< 50 μm) fractions of the topsoil samples. Rock-Eval® was able to provide thermal parameters sensitive enough to study fine-scale soil processes. In the organic layers, quantitative and qualitative changes were explained by the progressive decomposition of labile organic compounds from plant debris to the finest organic particles. Meanwhile, the grain size fractions of topsoils presented different characteristics. The coarse organo-mineral fractions showed higher C contents, albeit with a different composition, higher thermal stability, and greater decomposition degree than the plant debris forming the organic layer. These results are consistent with those of previous studies that microbial activity is more effective in this fraction. The finest fractions of topsoils showed low C contents, the highest thermal stability, and low decomposition degree, which can be explained by the stronger interactions with the mineral matrix. Therefore, it is suggested that the dynamics of OM in the different size fractions be interpreted in the light of a plant-microbe-soil continuum. Finally, three distinct thermostable C pools were highlighted through the grain size heterogeneity of SOM: free coarse OM (large debris and coarse and fine particles), weakly protected OM in (bio)aggregates (coarse fraction of topsoil), and stabilized OM in the fine fractions of topsoil, which resulted from the interactions within organo-mineral complexes. Therefore, Rock-Eval® thermal parameters can be used to empirically illustrate the conceptual models emphasizing the roles of drivers played by the gradual decomposition and protection of the most thermally labile organic constituents.
