Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and fields.Several metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization problems.Hence novel optimization methodologies are still needed.The Al-Biruni earth radius(BER)search optimization algorithm is proposed in this paper.The proposed algorithm was motivated by the behavior of swarm members in achieving their global goals.The search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization problems.The results show that BER can both explore and avoid local optima.BER has also been tested on an engineering design optimization problem.The results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

Mathematical Modeling and Evaluation of Reliability Parameters Based on Survival Possibilities under Uncertain Environment

In this article,mathematical modeling for the evaluation of reliability is studied using two methods.One of the methods,is developed based on possibility theory.The performance of the reliability of the system is of prime concern.In view of this,the outcomes for the failure are required to evaluate with utmost care.In possibility theory,the reliability information data determined from decision-making experts are subjective.The samemethod is also related to the survival possibilities as against the survival probabilities.The other method is the one that is developed using the concept of approximation of closed interval including the piecewise quadratic fuzzy numbers.In this method,a decision-making expert is not sure of his/her estimates of the reliability parameters.Numerical experiments are performed to illustrate the efficiency of the suggested methods in this research.In the end,the paper is concluded with some future research directions to be explored for the proposed approach.

Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection

The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized.While it is a multi-objective problem,current methods tend to treat feature selection as a single-objective optimization task.This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase(LMuMOGWO)for tackling feature selection problems.The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer(MOGWO):a Lévy flight and a mutation operator.The Lévy flight,a type of random walk with jump size determined by the Lévy distribution,enhances the global search capability of MOGWO,with the objective of maximizing classification accuracy while minimizing the number of selected features.The mutation operator is integrated to add more informative features that can assist in enhancing classification accuracy.As feature selection is a binary problem,the continuous search space is converted into a binary space using the sigmoid function.To evaluate the classification performance of the selected feature subset,the proposed approach employs a wrapper-based Artificial Neural Network(ANN).The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO,BMOGWO-S(based sigmoid),BMOGWO-V(based tanh)as well as Non-dominated Sorting Genetic Algorithm II(NSGA-II)and Multi-objective Particle Swarm Optimization(BMOPSO).The results demonstrate that the proposed LMuMOGWO approach is capable of successfully evolving and improving a set of randomly generated solutions for a given optimization problem.Moreover,the proposed approach outperforms existing approaches in most cases in terms of classification error rate,feature reduction,and computational cost.

热解析GC用的大容量固相萃取器的开发及其基本特性的探讨

开发了一种用于液体和气体样品中微量组分富集的大容量固相萃取装置。在小金属钛管(内径1.2mm外径1.6mm长6～30mm)的外壁键合上一层聚二甲基硅氧烷(厚0.32mm),就能有效地萃取多种有机物,结果可用热解吸-气相色谱-质谱联检。

A scale-integrated exploration model for orogenic gold deposits based on a mineral system approach

Concept-based orogenic gold exploration requires a scale-integrated approach using a robust mineral system model.Most genetic hypotheses for orogenic gold deposits that involve near-surface or magmatic-hydrothermal fluids are now negated in terms of a global mineral system model.Plausible models involve metamorphic fluids,but the fluid source has been equivocal.Crustal metamorphic-fluid models are most widely-accepted but there are serious problems for Archean deposits,and numerous Chinese provinces,including Jiaodong,where the only feasible fluid source is sub-crustal.If all orogenic gold deposits define a coherent mineral system,there are only two realistic sources of fluid and gold,based on their syn-mineralization geodynamic settings.These are from devolatilization of a subducted oceanic slab with its overlying gold-bearing sulfide-rich sedimentary package,or release from mantle lithosphere that was metasomatized and fertilized during a subduction event,particularly adjacent to craton margins.In this model,CO_2 is generated during decarbonation and S and ore-related elements released from transformation of pyrite to pyrrhotite at about 500 ℃.This orogenic gold mineral system can be applied to conceptual exploration by first identifying the required settings at geodynamic to deposit scales.Within these settings,it is then possible to define the critical gold mineralization processes in the system:fertility,architecture,and preservation.The geological parameters that define these processes,and the geological,geophysical and geochemical proxies and responses for these critical parameters can then be identified.At the geodynamic to province scales,critical processes include a tectonic thermal engine and deep,effective,fluid plumbing system driven by seismic swarms up lithosphere-scale faults in an oblique-slip regime during uplift late in the orogenic cycle of a convergent margin.At the district to deposit scale,the important processes are fluid focussing into regions of complex structural geometry adjacent to crustal-scale plumbing systems,with gold deposition in trap sites involving complex conjugations of competent and/or reactive rock sequences and structural or lithological fluid caps.Critical indirect responses to defined parameters change from those generated by geophysics to those generated by geochemistry with reduction in scale of the mineral system-driven conceptual exploration.

Ancient deep roots for Mesozoic world-class gold deposits in the north China craton:An integrated genetic perspective

The North China Craton(NCC)hosts some of the world-class gold deposits that formed more than 2 billion years after the major orogenic cycles and cratonization.The diverse models for the genesis of these deposits remain equivocal,and mostly focused on the craton margin examples,although synchronous deposits formed in the interior domains.Here we adopt an integrated geological and geophysical perspective to evaluate the possible factors that contributed to the formation of the major gold deposits in the NCC.In the Archean tectonic framework of the NCC,the locations of the major gold deposits fall within or adjacent to greenstone belts or the margins of micro-continents.In the Paleoproterozoic framework,they are markedly aligned along two major collisional sutures-the Trans North China Orogen and the Jiao-Liao-Ji Belt.Since the Mesozoic intrusions hosting these deposits do not carry adequate signals for the source of gold,we explore the deep roots based on available geophysical data.We show that the gold deposits are preferentially distributed above zones of uplifted MOHO and shallow LAB corresponding to thinned crust and eroded sub-lithospheric mantle,and that the mineralization is located above regions of high heat flow representing mantle upwelling.The NCC was at the center of a multi-convergent regime during the Mesozoic which intensely churned the mantle and significantly en riched it.The geophysical data on Moho and LAB upwarp from the centre towards east of the craton is more consistent with paleo-Pacific slab subduction from the east exerting the dominant control on lithospheric thinning.Based on these results,and together with an evaluation of the geochemical and isotopic features of the Mesozoic magmatic intrusions hosting the gold mineralization,we propose a genetic model that invokes reworking of ancient Au archives preserved in the lower crust and metasomatised upper mantle and which were generated through multiple subduction,underplating and cumulation events associated with cratonization of the NCC as well as the subduction-collision of Yangtze Craton with the NCC.The heat and material input along zones of heterogeneously thinned lithosphere from a rising turbulent mantle triggered by Mesozoic convergent margins surrounding the craton aided in reworking the deep roots of the ancient Au reservoirs,leading to the major gold metallogeny along craton margins as well as in the interior of the NCC.

Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance.Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas.Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas.Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today’s technology.The accuracy of the forecast is mostly determined by the model used.The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial Antenna.Support Vector Machines(SVM),Random Forest,K-Neighbors Regressor,and Decision Tree Regressor were utilized as the basic models.The Adaptive Dynamic Polar Rose Guided Whale Optimization method,named AD-PRS-Guided WOA,was used to pick the optimal features from the datasets.The suggested model is compared to models based on five variables and to the average ensemble model.The findings indicate that the presented model using Random Forest results in a Root Mean Squared Error(RMSE)of(0.0102)for bandwidth and RMSE of(0.0891)for gain.This is superior to other models and can accurately predict antenna bandwidth and gain.

IMPULSIVE EXPONENTIAL SYNCHRONIZATION OF FRACTIONAL-ORDER COMPLEX DYNAMICAL NETWORKS WITH DERIVATIVE COUPLINGS VIA FEEDBACK CONTROL BASED ON DISCRETE TIME STATE OBSERVATIONS

This article aims to address the global exponential synchronization problem for fractional-order complex dynamical networks(FCDNs)with derivative couplings and impulse effects via designing an appropriate feedback control based on discrete time state observations.In contrast to the existing works on integer-order derivative couplings,fractional derivative couplings are introduced into FCDNs.First,a useful lemma with respect to the relationship between the discrete time observations term and a continuous term is developed.Second,by utilizing an inequality technique and auxiliary functions,the rigorous global exponential synchronization analysis is given and synchronization criterions are achieved in terms of linear matrix inequalities(LMIs).Finally,two examples are provided to illustrate the correctness of the obtained results.

O(t^(-β))-SYNCHRONIZATION AND ASYMPTOTIC SYNCHRONIZATION OF DELAYED FRACTIONAL ORDER NEURAL NETWORKS

This article explores the O(t^(-β))synchronization and asymptotic synchronization for fractional order BAM neural networks(FBAMNNs)with discrete delays,distributed delays and non-identical perturbations.By designing a state feedback control law and a new kind of fractional order Lyapunov functional,a new set of algebraic sufficient conditions are derived to guarantee the O(t^(-β))Synchronization and asymptotic synchronization of the considered FBAMNNs model;this can easily be evaluated without using a MATLAB LMI control toolbox.Finally,two numerical examples,along with the simulation results,illustrate the correctness and viability of the exhibited synchronization results.

Flexo-photocatalysis in centrosymmetric semiconductors

The separation of photogenerated electron–hole pairs is vitally important for photocatalysis,which can be effectively promoted by polarization field.However,it only manifests in piezoelectric/pyroelectric/ferroelectric materials that have a non-centrosymmetric structure.Here,we demonstrate that the polarization enhanced photocatalysis(with wide spectra from ultraviolet(UV)light to visible light)can be achieved in centrosymmetric semiconductors,such asδ-MnO_(2) and TiO_(2) nanosheets integrated nanoflowers,by using the strain-gradient-induced flexoelectric polarization that is always overlooked in polarization-enhanced catalysis.Under ultrasonic and illumination excitation,the organic pollutants(methylene blue(MB),etc.)can be effectively degraded within 30 min with excellent stability and repeatability.Compared with photocatalysis,the flexo-photocatalytic performance of above centrosymmetric semiconductors is substantially increased by 85%.Moreover,the factors related to flexo-photocatalysis such as material morphology,mechanical stimuli source,and adsorption are explored to deeply understand the mechanism of flexo-photocatalysis.This work opens up a way for high-performance photocatalysis in centrosymmetric semiconductors.

Paleo-Mesoarchean sedimentary record in the Dharwar Craton,India:Implications for Archean ocean oxygenation

The early Archean oceans were marked by significant redox changes which have subsequently shaped the Earth’s biosphere.Archean chemical sediments of banded Iron and Manganese formations provide important geochemical proxies for these historical shifts in the redox conditions and to trace the ancient sedimentation patterns and protoliths.In this study,we investigate the proto-ore of the Archean Mn-formations of the Sandur,Chitradurga and Shimoga greenstone belts of Dharwar Craton of southern Peninsular India,which is geochemically characterised as quartz arenites,Mn-arenites,Fe-arenites,Mn-argillites and Fe-argillites.The geochemical systematics suggest their deposition in shallow to deeper shelf in the Archean proto-ocean.The detrital zircon U-Pb systematics of Mn arenites and argillites indicate their maximum depositional age of 3230±52 Ma representing the oldest onset of sedimentation during the Paleo-Mesoarchean timeframe in the Chitradurga Group of Dharwar Supergroup.The detrital influx proxies suggest variations in sedimentation rates associated with the Archean transgressive-regressive cycles and fluctuating hydrodynamic conditions,together reflecting an increasing trend in the contributions of recycled sediment from Sandur to Chitradurga and Shimoga greenstone belts.The available detrital zircon ages of the Mn arenites and argillites from these greenstone belts indicate a~600 Ma prolonged period of Mn deposition for which high-T hydrothermal fluids from Archean mid-oceanic ridges supplied the manganese.The trace element compositions of the concordant detrital zircons suggest 3.3-3.1 Ga Dharwar basement TTG/granitoid source which is corroborated by the zircon crystallization temperatures of 690-820℃.The source-normalisedα-dose rates of the detrital zircons signify greater degrees of sediment transport and multi-cycle nature which correspond to the earliest episode of crustal growth in the Indian sub-continent associated with the Mesoarchean Ur supercontinent.The clastic-chemogenic sedimentation attained through concomitant detrital sediment-seawater-metalliferous hydrothermal fluid mixing at an epicontinental passive margin resulted in the deposition of Mn-arenites and argillites closer to the higher Eh shore,while the Fe-rich sediments formed at a relatively deeper shelf characterised by comparatively lower Eh and more alkaline conditions.The comprehensive geochemical and geochronological data of the Archean Mn arenite-argillite sequences reveal the significance of regional episodes of ocean oxygenation at the shallow shelves of Archean oceans prior to great oxygenation event(GOE)that was mediated by the prolific growth of ancient microbiota which transformed the Earth to a more habitable planet.

Triboelectric nanogenerator integrated with a simple controlled switch for regularized water wave energy harvesting

Ocean is full of low-frequency,irregular,and widely distributed wave energy,which is suitable as the energy source for maritime Internet of Things(IoTs).Utilizing triboelectric nanogenerators(TENGs)to harvest ocean wave energy and power sensors is proven to be an effective scheme.However,in random ocean waves,the irregular electrical energy output by general TENGs restricts the applications.At present,achieving regularized water wave energy harvesting relies on rather complex mechanical structure designs,which is not conducive to industrialization.In this work,we proposed a novel mechanical controlled TENG(MCTENG)with a simple controlled switch to realize the regularization function.The structural parameters of the MC-TENG are optimized,and the optimal output voltage,output current,and transferred charge respectively reach 1684.2 V,85.4μA,and 389.9 nC,generating a peak power density of 38.46 W·m^(−3)·Hz^(−1).Under real water wave environment,the output of the MC-TENG is regularized and keeps stable regardless of any wave conditions.Moreover,the potential applications of the MC-TENG are demonstrated in powering environmental temperature,humidity,and wind speed sensors.This work renders a simple approach to achieve effective regularized ocean wave energy harvesting,promoting the TENG industrialization toward practical application of maritime IoTs.

Contrasting sources and enrichment mechanisms in lithium-rich salt lakes:A Li-H-O isotopic and geochemical study from northern Tibetan Plateau

Lithium(Li),a crucial mineral resource for modern high-tech industries,is notably abundant in the northern Tibetan Plateau,primarily within lithium-rich salt lakes.However,the exploration and development of these resources are hindered due to an incomplete understanding of their nature and origin.Here we present results from a comprehensive study on the hydrochemical parameters,whole-rock geochemistry,H-O isotopes,and Li concentrations in surface brine,river water,geothermal springs,and associated rocks from two representative lithium-enriched salt lakes,the Laguo Co(LGC)and Cangmu Co(CMC)in Tibet to understand the genetic mechanisms.Our water-salt balance calculations and H-O isotopic analysis reveal that Li in LGC and CMC primarily originates from the Suomei Zangbo(SMZB,~91%)and Donglong Zangbo(DLZB,~75%)rivers,respectively.It is estimated that the LGC and CMC took a minimum of 6.0 ka and 3.0 ka to accumulate their current lithium resources,respectively.The distinct geological characteristics reflect evolutionary differences between the two lakes,suggesting diverse lithium sources and enrichment processes.The high lithium ion concentration and light lithium isotope composition in the SMZB river waters indicate the genetic relationship with lithium-enriched geothermal springs in the Tibetan Plateau.Our results suggest that lithium in the LGC originates from lithium-enriched geothermal springs and is primarily supplied through the small-scale SMZB river.In contrast,the formation and evolution of CMC are influenced by the northern Lunggar rifts,receiving a prolonged and stable input from the DLZB,resulting in high lithium concentrations and isotopic values.The absence of lithium-enriched geothermal springs and the prevalence of silicate rocks in the CMC catchment suggest that lithium may be sourced from the weathering of silicate rocks,such as granitic pegmatite veins containing lithium-rich beryl,widely distributed in the upstream area of DLZB.The forward modeling approach,quantifying the contribution fractions of different reservoirs(atmospheric precipitation,silicate,carbonate,and evaporite),indicates that the distinct lithium concentrations in the mainstream(>1 mg/L)and tributaries(<0.1 mg/L)are positively correlated with the ratio of silicate contributions to carbonate contributions,suggesting that dissolved lithium in river waters primarily originates from the weathering and dissolution of silicate rocks.The distinct sources and enrichment mechanisms of lithium in these two salt lakes are attributed to various evolutionary processes,topographical features,hydrological factors,fundamental geological settings,and tectonic histories,despite their spatial proximity.Furthermore,our study highlights the significant role of rivers in the formation of young salt lakes,in addition to geothermal springs.

The Early-Middle Triassic Supervolcano in the Yangtze Block,South China and associated obstacles to biotic recovery

The end-Permian mass extinction was one of the major global crises spanning the entire Early Triassic or longer.Eruptions of volcanos were one of the factors that delayed the biotic recovery after this event.Supervolcano eruptions can cause catastrophic effects on global environment,climate,and life.Here we investigate the tuff layers from Early-Middle Triassic boundary in the Yangtze Block and identify a supervolcano eruption event.The zircon U-Pb ages of the section-Langdai,section-Daijiagou and section-Longmendong tuff samples are 247.1±1.9 Ma,247.6±2.0 Ma and 247.7±1.7 Ma,respectively.These ages mark the Olenekian-Anisian boundary.The zircon grains from the tuff layers have negativeεHf(t)(-15.3 to-0.8),two-stage Hf model(TDM2)ages(1.7 to 2.2 Ga)and display high-δ18O values(mostly>10‰).Clay minerals and quartz dominate the rock composition.The whole rock compositions show that the tuff layers were derived from magma of intermediate to felsic composition,which formed by the remelting of Paleoproterozoic materials of continental crust.The volcanic eruption site is located in the Jinshajiang-Ailaoshan-Song Ma suture zone in the southwestern margin of the Yangtze Block.A combination of the closure of the Paleo-Tethys Ocean Basin and the collision of the Indochina Block and South China contributed to the eruption,which was a supervolcano eruption under the active continental margin arc settings.We speculate that this supervolcano eruption might have contributed to the delayed biotic recovery after the end-Permian mass extinction.

Paleozoic tectonic evolution of the proto-Korean Peninsula along the East Asian continental margin from detrital zircon U-Pb geochronology and Hf isotope geochemistry

Detrital zircon geochronology and Hf isotope analysis can be used for inferring provenance characteristics,and to evaluate the tectonic evolution of sedimentary basins and their link with regional orogenesis.The Paleozoic sequences of the Okcheon Belt consist of the Lower Paleozoic Joseon and the Upper Paleozoic Pyeongan supergroups with Middle Paleozoic hiatus locally on top of the Neoproterozoic bimodal volcanic rocks,reflecting an intracontinental rift setting between the two basements(viz.Gyeonggi and Yeongnam massifs)at southern part of the Korean Peninsula.Our detrital zircon U-Pb ages and Lu-Hf isotope results show that all these Paleozoic strata commonly have Paleoproterozoic and Paleozoic zircon ages with rare Meso-to Neoproterozoic ages.The individual zircon populations display following features,allowing estimation of their sedimentary provenances:(i)The Paleoproterozoic zircons(ca.1.85 Ga and 2.50 Ga)with similar ranges ofεHf(t)values are most common in the basement rocks of the Korean Peninsula,and were sourced from both the Gyeonggi and Yeongnam massifs.(ii)The Meso-to Neoproterozoic zircons,preserved only in the Middle to Late Cambrian clastic sedimentary rocks within the carbonate sequences probably reflect proximal provenance.(iii)The youngest Paleozoic zircons of each formation,almost coincident with their deposition ages,suggest presence of syndepositional magmatism,indicating proximal magmatic sources during their deposition.(iv)The Cambrian-Ordovician zircons,from the Lower Paleozoic sequences,but rare in the successive Upper Paleozoic sequences,suggest a provenance change after the hiatus between the two sedimentary successions.(v)The Permian zircons showing differentεHf(t)values indicate that detrital sources were varied at that time.The integrated results in our study suggest provenance variability linked to diverse tectonic environments,reflecting prolonged subduction-related crustal evolution of the proto-Korean Peninsula during the Paleozoic.

A Global Best-guided Firefly Algorithm for Engineering Problems

The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when mating.This article proposes a method based on Differential Evolution(DE)/current-to-best/1 for enhancing the FA's movement process.The proposed modification increases the global search ability and the convergence rates while maintaining a balance between exploration and exploitation by deploying the global best solution.However,employing the best solution can lead to premature algorithm convergence,but this study handles this issue using a loop adjacent to the algorithm's main loop.Additionally,the suggested algorithm’s sensitivity to the alpha parameter is reduced compared to the original FA.The GbFA surpasses both the original and five-version of enhanced FAs in finding the optimal solution to 30 CEC2014 real parameter benchmark problems with all selected alpha values.Additionally,the CEC 2017 benchmark functions and the eight engineering optimization challenges are also utilized to evaluate GbFA’s efficacy and robustness on real-world problems against several enhanced algorithms.In all cases,GbFA provides the optimal result compared to other methods.Note that the source code of the GbFA algorithm is publicly available at https://www.optim-app.com/projects/gbfa.

Bipartite quasi-synchronization of multiple neural networks with generalized cooperative-competitive topology

This study examines the bipartite quasi-synchronization(B-Q synchronization)issue of coupled networks with general cooperative-competitive topology and the event-triggered communications between nodes to curb the communication cost.In the existing literature concerning bipartite synchronization,the network topology is required to be structurally balanced,which necessitates that competitive interactions exist only between two distinct subgroups.In this study,we aim to lengthen the network’s topology to a more general signed network in which antagonistic interactions can exist in the same or different subgroups.According to signed graph theory and the markovian stochastic event-triggering mechanism,the dynamical model of multiple neural networks(MNNs)with structurally unbalanced and markovian event-triggered communication is established.By utilizing the stochastic Lyapunov stability analysis,some adequate criteria for B-Q synchronization of MNNs with the structurally unbalanced graph are obtained;also,a bound for the B-Q synchronization error is provided.As a special case,the bipartite synchronization criteria for MNNs with the structurally balanced graph are also obtained.Finally,two simulations are performed to verify the theoretical result.

Discrete Improved Grey Wolf Optimizer for Community Detection

Detecting communities in real and complex networks is a highly contested topic in network analysis.Although many metaheuristic-based algorithms for community detection have been proposed,they still cannot effectively fulfill large-scale and real-world networks.Thus,this paper presents a new discrete version of the Improved Grey Wolf Optimizer(I-GWO)algorithm named DI-GWOCD for effectively detecting communities of different networks.In the proposed DI-GWOCD algorithm,I-GWO is first armed using a local search strategy to discover and improve nodes placed in improper communities and increase its ability to search for a better solution.Then a novel Binary Distance Vector(BDV)is introduced to calculate the wolves’distances and adapt I-GWO for solving the discrete community detection problem.The performance of the proposed DI-GWOCD was evaluated in terms of modularity,NMI,and the number of detected communities conducted by some well-known real-world network datasets.The experimental results were compared with the state-of-the-art algorithms and statistically analyzed using the Friedman and Wilcoxon tests.The comparison and the statistical analysis show that the proposed DI-GWOCD can detect the communities with higher quality than other comparative algorithms.

Effect of chemical composition on zircon radiation damage dating:Implications for low-temperature thermochronology

Zircon radiation damage dating is a low-temperature thermochronological method that can reveal the cooling histories of magmatic intrusions and discriminate sedimentary provenance in combination with other dating methods.This method has broad application prospects because of its advantages of nondestructive,high efficiency,and capable of double(or multiple)dating,involving only multiple measurements by Raman spectrometer and laser ablation-inductively coupled plasma-mass spectrometry.However,several factors,such as zircon chemical composition and the non-uniformity of radiation damage annealing kinetics,can cause poor precision when using this method and thus restricts its wide application.This study examined the effect of chemical composition(P,Ti,Dy,Th,U,and Hf)on Raman spectra using synthetic zircon crystals grown in a lithium-molybdate flux.The results show that the full width at half-maximum(FWHM)of the v_(3)(SiO_(4))band has positive linear correlations with the concentrations of P,Ti,Dy,Th,and U in decreasing order of influence,while the FWHM is unaffected by Hf at concentrations<1 wt.%but increases at concentrations>10 wt.%.Furthermore,the Raman shift is negatively correlated with Th,U,and Dy concentrations,positively correlated with Hf,and shows no obvious correlation with Ti and P.Thus,our study shows that chemical composition is a non-ignorable factor for calculating zircon radiation damage age using Raman spectroscopy,especially for zircon with relatively high concentrations of P,rare earth elements(REEs),Th,U,and Hf.The obtained multiple linear regression equation provides a potential means for estimating the FWHM at zero dose and implication for improving the dating precision of this method.In addition,the observed effects of REEs,Th,U,and Hf on the Raman shift of the v_(3)(SiO_(4))band indicate that chemical composition in zircon might affect the estimation of the P-T conditions of geological processes when using entrapped zircon inclusions in host minerals or the field of zircon as an in situ pressure sensor in hydrothermal experiments.Our study suggests that zircon radiation damage dating,excluding geochemical effects,will be more accurate for addressing lower-temperature geological processes.

Non-dominated Sorting Advanced Butterfly Optimization Algorithm for Multi-objective Problems

This paper uses the Butterfly Optimization Algorithm(BOA)with dominated sorting and crowding distance mechanisms to solve multi-objective optimization problems.There is also an improvement to the original version of BOA to alleviate its drawbacks before extending it into a multi-objective version.Due to better coverage and a well-distributed Pareto front,non-dominant rankings are applied to the modified BOA using the crowding distance strategy.Seven benchmark functions and eight real-world problems have been used to test the performance of multi-objective non-dominated advanced BOA(MONSBOA),including unconstrained,constrained,and real-world design multiple-objective,highly nonlinear constraint problems.Various performance metrics,such as Generational Distance(GD),Inverted Generational Distance(IGD),Maximum Spread(MS),and Spacing(S),have been used for performance comparison.It is demonstrated that the new MONSBOA algorithm is better than the compared algorithms in more than 80%occasions in solving problems with a variety of linear,nonlinear,continuous,and discrete characteristics based on the Pareto front when compared quantitatively.From all the analysis,it may be concluded that the suggested MONSBOA is capable of producing high-quality Pareto fronts with very competitive results with rapid convergence.