Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments invo...Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.展开更多
The rare earth elements(REEs)extraction by chemical leaching from ion-adsorption type rare earth ores(IAREO)has led to serious ecological and environmental risks.Conversely,demand for bioleaching is on the rise with t...The rare earth elements(REEs)extraction by chemical leaching from ion-adsorption type rare earth ores(IAREO)has led to serious ecological and environmental risks.Conversely,demand for bioleaching is on the rise with the advantage of being environmental-friendly.As one of the organic acids produced by biological metabolism,citric acid was used to leach REEs and explore the performance and process.The results demonstrate that citric acid exhibits higher leaching efficiency(96.00%)for REEs at a relatively low concentration of 0.01 mol/L compared with(NH_(4))_(2)SO_(4)(84.29%,0.1 mol/L)and MgSO_(4)(83.99%,0.1 mol/L).Citric acid shows a preference for leaching heavy rare earth elements,with 99%leaching efficiency in IAREO,which shows higher capacity than(NH_(4))_(2)SO_(4)and MgSO_(4)(as inorganic leaching agents).Kinetic analysis indicates that the leaching process of REEs with citric acid is controlled by both the internal diffusion kinetics and chemical reaction kinetics,which is different from inorganic leaching agents.Visual Minteq calculations confirm that RE-Citrate is the main constituent of the extract solution in the leaching process of the IAREO,thereby enhancing the leaching efficiency of REEs from the IAREO.It suggests that citric acid may be used as a promising organic leaching agent for the environmentalfriendly extraction of REEs from IAREO.展开更多
The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the i...The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the infected person or community is the preferred choice to protect our health.Since humans are the only carriers,it might be possible to control the positive rate if the infected population or host carriers are isolated from each other.Isolation alone may not be a proper solution.These are the resolutions of previous research work carried out on COVID-19 throughout the world.The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well.In this research work,we have pre-sented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems.In the first step,we created a fuzzy Susceptible-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death(SEIAHRD)model for COVID-19,analyzed it using granular differentiability,and reported disease dynamics for time-independent disease control parameters.In the second step,we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader.Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.展开更多
This study investigates the genetic differentiation and gene flow within the Subalpine Warbler(Curruca cantillans)complex using mitochondrial DNA(mtDNA)analysis.We focused on three primary populations based on phyloge...This study investigates the genetic differentiation and gene flow within the Subalpine Warbler(Curruca cantillans)complex using mitochondrial DNA(mtDNA)analysis.We focused on three primary populations based on phylogenetic findings and geographical distributions.Popl:Includes C.c.albistriata(distributed in extreme northeast Italy(Trieste),southern Slovenia,and south along the north Adriatic coast to Albania,as well as east to southern Bulgaria,Greece,Crete,and western Turkey,with non-breeding grounds in the central and eastern Sahel from eastern Mali to northwest Sudan)and C.c.cantillans(occurring in Sicily,central and southern Italy,and locally in north-central Italy,with non-breeding grounds presumably in the western Sahel).Pop2:Represents C.iberiae,found in Spain and western France.Pop3:Comprises C.subalpina,distributed across the Balearic Islands,Corsica,Sardinia,some Tuscan islands,and north and central Italy,with non-breeding grounds extending into the western Sahel,reaching northern Nigeria and Niger.Our genetic analysis indicates that all three populations have expanded recently but maintain unique genetic structures.Despite this recent expansion,the populations exhibit limited genetic diversity.Using AMOVA,we found that most genetic variation is between populations rather than within them,indicating significant genetic differentiation.This study uniquely combines population genetic data with advanced analyses to provide detailed insights into the genetic structure and connectivity of the Subalpine Warbler complex,highlighting the distinct genetic lineages within the Mediterranean biodiversity hotspot.展开更多
This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Op...This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Optimization(SFO)algorithm.The primary objective is to address multi-objective optimization challenges within mechanical engineering,with a specific emphasis on planetary gearbox optimization.The algorithm is equipped with the ability to dynamically select the optimal mutation operator,contingent upon an adaptive normalized population spacing parameter.The efficacy of HMODESFO has been substantiated through rigorous validation against estab-lished industry benchmarks,including a suite of Zitzler-Deb-Thiele(ZDT)and Zeb-Thiele-Laumanns-Zitzler(DTLZ)problems,where it exhibited superior performance.The outcomes underscore the algorithm’s markedly enhanced optimization capabilities relative to existing methods,particularly in tackling highly intricate multi-objective planetary gearbox optimization problems.Additionally,the performance of HMODESFO is evaluated against selected well-known mechanical engineering test problems,further accentuating its adeptness in resolving complex optimization challenges within this domain.展开更多
BACKGROUND Rectal cancer is one of the common digestive system malignant tumors around the world.Its early diagnosis and staging are crucial for rectal cancer treatment and prognosis.In recent years,tumor markers have...BACKGROUND Rectal cancer is one of the common digestive system malignant tumors around the world.Its early diagnosis and staging are crucial for rectal cancer treatment and prognosis.In recent years,tumor markers have gradually received attention in early screening,treatment monitoring and prognostic evaluation of cancer,but their predictive role in rectal cancer staging and differentiation is still unclear.AIM To assess the prognostic value of tumor markers alpha-fetoprotein(AFP)cancer antigen 72-4(CA72-4),carbohydrate antigen 19-9(CA19-9),and carcinoembryonic antigen(CEA),alongside multimodal magnetic resonance imaging(MRI),for staging and differentiating rectal cancer in patients.METHODS This study retrospectively analyzed 167 patients with rectal cancer who were treated at our institution from January 2020 to December 2024.Each patient underwent serological testing and multimodal MRI for diagnosis.Histopathological examination after surgical resection or imaging based on follow-up was used as the gold standard.According to the T stage and differentiation degree,patients were divided into low stage group(T1-T2)and high stage group(T3-T4).In addition,they were divided into low-differentiation groups and high-differentiation groups according to their differentiation degree.We compared the accuracy,sensitivity and specificity of tumor marker levels and MRI in rectal cancer stage and differentiation.RESULTS The study's findings indicate that in the context of rectal cancer T staging,there is substantial concordance between MRI and clinicopathological assessments,with a Kappa coefficient of 0.789(P<0.001).Similarly,for various degrees of tumor differentiation,MRI and clinicopathological evaluations demonstrated substantial agreement,with a Kappa coefficient of 0.651(P<0.001).Notably,the concentrations of tumor markers CA19-9,CA72-4,CEA,and AFP were significantly elevated in the T3-T4 stage compared to the T1-T2 stage.Furthermore,these markers were significantly higher in the low-differentiation group compared to the high-differentiation group(P<0.05).The combined use of tumor markers and MRI for preoperative T staging of rectal cancer yielded a diagnostic sensitivity of 93.7%and a specificity of 94.6%,as evidenced by the receiver operating characteristic analysis,with an area under the curve of 0.947.For tumor differentiation,the diagnostic sensitivity and specificity were 93.6%and 97.1%,respectively,with an area under the curve of 0.978(95%confidence interval:0.946-1.000),surpassing the accuracy of individual detection methods.CONCLUSION The CA19-9,CA72-4,CEA and AFP tumor markers combined with multimodal MRI have high sensitivity and specificity in diagnosing rectal cancer stage and differentiation.Their diagnostic efficacy is significantly better than that of single tests,which can effectively improve the predictive ability of rectal cancer stage and differentiation,provide a more reliable diagnostic reference for clinical practice,and have important clinical significance.展开更多
A-type rocks have drawn considerable attention in the past few decades due to their distinctive mineralogical and geochemical fingerprints and prospective utility for geodynamic reconstruction of the lithosphere.A com...A-type rocks have drawn considerable attention in the past few decades due to their distinctive mineralogical and geochemical fingerprints and prospective utility for geodynamic reconstruction of the lithosphere.A comprehensive study,involving zircon U-Pb geochronology,wholerock elemental and Sr-Nd-Pb isotopic geochemistry,was undertaken to elucidate the origin and evolutionary process for syenites from the Daguiping area in the North Daba mountains,South Qinling belt.The syenites revealed an Ordovician igneous crystallization age of 454.4±17 Ma,coeval with the neighboring mafic rocks.All samples show high SiO_(2),LREEs,and HFSEs(Nb,Ta,Zr and Hf)contents,with negative to slightly positive Eu(Eu/Eu^(*)=0.78-1.08)anomalies.The geochemical characteristics of the Daguiping syenites imply that they are of A_1-type magmatic affinity,which is confirmed by their high total alkali levels(8.57 wt.%-11.94 wt.%),Zr+Nb+Ce+Y contents(738.00 ppm-1734.78 ppm),and 10000×Ga/Al ratios(3.25-4.22),as well as low Y/Nb ratios(0.30-0.40).Our samples exhibit a wide range of initial^(87)Sr/^(86)Sr ratios of 0.701943 to 0.709802 and a narrow range of^(143)Nd/^(144)Nd ratios of 0.512205-0.512246 withε_(Nd)(t)values from+3.0 to+3.8.These rocks display(^(206)Pb/^(204)Pb)_(initial),(^(207)Pb/^(204)Pb)_(initial),and(^(208)Pb/^(204)Pb)_(initial)ratios range from 17.96 to 18.62,15.55 to 15.59,and 36.87 to 38.22,respectively.All of the isotopic data indicate that the syenites were essentially mantle-derived.A cogenetic source for the Daguiping syenites and coeval mafic rocks in the South Qinling belt is supported by their uniform Sr-Nd-Pb isotope data and linear major/trace elemental changes,with prolonged fractional crystallization considered as the essential mechanism for these geochemical discrepancies.Mass-balance and Rayleigh fractionation modeling estimate~85 vol%fractional crystallization involving amphibole,clinopyroxene,plagioclase,Kfeldspar,biotite,Fe-Ti oxide,and quartz,to reproduce the compositional varieties between a coeval mafic rock and the Daguiping syenites.The Daguiping syenites and associated alkaline rocks were likely related to a rifting episode triggered by asthenospheric upwelling,which led to the South Qinling detaching from the South China Block along the Mianlue suture during the Early Paleozoic.展开更多
The numerical calculation method has greatly promoted the process of optimal design of scramjet,but it still needs extremely heavy calculation for the model with complex thermochemical reaction.Data-driven deep learni...The numerical calculation method has greatly promoted the process of optimal design of scramjet,but it still needs extremely heavy calculation for the model with complex thermochemical reaction.Data-driven deep learning relies heavily on a large amount of data in the face of complex nonlinear features.Therefore,combining“data-driven model”and“Navier-Stokes equation”,an intelligent prediction model of supersonic combustion flow process is constructed.This algorithm integrates the theory priors of combustion flow into the neural network model,and uses convolutional grouping and rearrangement to reduce the feature redundancy calculation,so as to achieve high-precision and high-efficiency prediction of velocity,density,pressure and temperature fields.This study makes a comprehensive comparison from two aspects of performance and efficiency.Unsteady scramjet multi-physical field dataset is constructed under different incoming Mach number conditions.The experimental results show that compared with other methods,the proposed algorithm can achieve the maximum Peak Signal-to-Noise Ratio(PSNR)improvement of 38.75%and Learned Perceptual Image Patch Similarity(LPIPS)improvement of 68.13%in predicting the average quality of images,and the computational cost of the model is reduced by 30.36%compared with other models.In addition,the high model can also effectively predict the unknown incoming flow condition.展开更多
The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This pape...The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability.Our results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT environments.Nodes are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient networks.The algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet Delivery Ratio(PDR)of 99% and a robust network throughput of up to 1800 kbps in more compact node configurations.This study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.展开更多
Let X be a real uniformly convex and uniformly smooth Banach space and C a nonempty closed and convex subset of X.Let Π_(C):X→C denote the generalized metric projection operator introduced by Alber in[1].In this pap...Let X be a real uniformly convex and uniformly smooth Banach space and C a nonempty closed and convex subset of X.Let Π_(C):X→C denote the generalized metric projection operator introduced by Alber in[1].In this paper,we define the Gâteaux directional differentiability of Π_(C).We investigate some properties of the Gâteaux directional differentiability of Π_(C).In particular,if C is a closed ball,or a closed and convex cone(including proper closed subspaces),or a closed and convex cylinder,then,we give the exact representations of the directional derivatives of Π_(C).By comparing the results in[12]and this paper,we see the significant difference between the directional derivatives of the generalized metric projection operator Π_(C) and the Gâteaux directional derivatives of the standard metric projection operator PC.展开更多
This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters wh...This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.展开更多
The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite...The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite,with pearl production displaying notable sexual dimorphism.Consequently,understanding the molecular mechanisms governing sex determination and differentiation is crucial for advancing breeding strategies in the pearl oyster industry.To elucidate these mechanisms,this study conducted integrative transcriptomic analyses of P.maxima gonadal tissues using isoform sequencing(Isoseq)and RNA sequencing(RNA-seq).Comparative analysis of ovarian and testicular tissues identified 2768 differentially expressed genes(DEGs).Gene coexpression network analysis delineated four key modules,including three sex-specific modules and one shared module.Key genes implicated in sex determination and maintenance were identified,including FOXL2,NANOS1,andβ-catenin,important for ovarian maintenance,and DMRT,SOX30,FEM1,and FOXJ1,crucial for testicular maintenance.These genes,widely studied in other taxa,were confirmed as hub genes in the sex-related modules of P.maxima.Interestingly,genes within the shared module were significantly enriched in the spliceosome pathway.Alternative splicing analysis highlighted its extensive role in gonadal tissues,with more pronounced activity observed in the testis compared to the ovary.Nearly half(47.83%,375)of the identified genes undergoing differential alternative splicing(DASGs)also exhibited differential transcript usage(DTUGs),while only 17%of DTUGs overlapped with DEGs.Genes associated with sex differentiation,such as DMRT,β-catenin,and U2AF2,displayed sex-specific and/or sex-biased isoforms.These findings offer novel insights into the molecular basis of sex differentiation in P.maxima,which could inform the development of targeted breeding strategies aimed at sex control,thereby enhancing pearl quality and yield in aquaculture.This study offers a robust molecular foundation for advancing breeding programs and optimizing production in the pearl oyster industry.展开更多
Nicotiana tabacum(2n=4x=48),an economically important non-food crop and a model plant for genetic studies,faces challenges in efficient genotyping of novel germplasm.To address this,we developed the Ta-LD-SC,a 20K SNP...Nicotiana tabacum(2n=4x=48),an economically important non-food crop and a model plant for genetic studies,faces challenges in efficient genotyping of novel germplasm.To address this,we developed the Ta-LD-SC,a 20K SNP Affymetrix Axiom array,based on resequencing data from 150 tobacco accessions.A total of 20,213 unique SNPs were carefully selected,achieving coverage of over 90%of the tobacco genome(Nitab4.5 and NtaSR1)with a uniform probe distribution,limiting density to no more than 5 SNPs per 200 kb.The array underwent extensive validation using 866 tobacco accessions(NP panel)and 288 F2 individuals from a cross between K326 and Oxford 26(GP panel).Performance metrics demonstrated its robustness,with high SNP call rates(93.6%-99.8%),a low technical error rate(<1%),and a superior PolyHighResolution SNP rate(79.79%)compared to other crop SNP arrays.Population structure analysis of the NP panel revealed two major introductions of foreign germplasm that have significantly influenced the genetic diversity of Chinese tobacco resources.Using the array,a genome-wide association study(GWAS)identified 62 genes linked to eight agronomic traits,and a high-density genetic map encompassing 4553 SNPs across 6606.08 cM was constructed.The Ta-LD-SC array provides a valuable tool for rapid,high-quality genotyping offering supporting marker annotations that may benefit genetic research and breeding of tobacco.展开更多
Recent engineering applications increasingly adopt smart materials,whose mechanical responses are sensitive to magnetic and electric fields.In this context,new and computationally efficient modeling strategies are ess...Recent engineering applications increasingly adopt smart materials,whose mechanical responses are sensitive to magnetic and electric fields.In this context,new and computationally efficient modeling strategies are essential to predict the multiphysic behavior of advanced structures accurately.Therefore,the manuscript presents a higher-order formulation for the static analysis of laminated anisotropic magneto-electro-elastic doubly-curved shell structures.The fundamental relations account for the full coupling between the electric field,magnetic field,and mechanical elasticity.The configuration variables are expanded along the thickness direction using a generalized formulation based on the Equivalent Layer-Wise approach.Higher-order polynomials are selected,allowing for the assessment of prescribed values of the configuration variables at the top and bottom sides of solids.In addition,an effective strategy is provided for modeling general surface distributions of mechanical pressures and electromagnetic external fluxes.The model is based on a continuum-based formulation which employs an analytical homogenization of the multifield material properties,based on Mori&Tanaka approach,of a magneto-electro-elastic composite material obtained from a piezoelectric and a piezomagnetic phase,with coupled magneto-electro-elastic effects.A semi-analytical Navier solution is applied to the fundamental equations,and an efficient post-processing equilibrium-based procedure is here used,based on the numerical assessment with the Generalized Differential Quadrature(GDQ)method,to recover the response of three-dimensional shells.The formulation is validated through various examples,investigating the multifield response of panels of different curvatures and lamination schemes.An efficient homogenization procedure,based on the Mori&Tanaka approach,is employed to obtain the three-dimensional constitutive relation of magneto-electro-elastic materials.Each model is validated against three-dimensional finite-element simulations,as developed in commercial codes.Furthermore,the full coupling effect between the electric and magnetic response is evaluated via a parametric investigation,with useful insights for design purposes of many engineering applications.The paper,thus,provides a formulation for the magneto-electro-elastic analysis of laminated structures,with a high computational efficiency,since it provides results with three-dimensional capabilities with a two-dimensional formulation.The adoption of higher-order theories,indeed,allows us to efficiently predict not only the mechanical response of the structure as happens in existing literature,but also the through-the-thickness distribution of electric and magnetic variables.A novel higher-order theory has been proposed in this work for the magneto-electro-elastic analysis of laminated shell structures with varying curvatures.This theory employs a generalized method to model the distribution of the displacement field components,electrostatic,and magneto-static potential,accounting for higher-order polynomials.The thickness functions have been defined to prescribe the arbitrary values of configuration variables at the top and bottom surfaces,even though the model is ESL-based.The fundamental governing equations have been derived in curvilinear principal coordinates,considering all coupling effects among different physical phenomena,including piezoelectric,piezomagnetic,and magneto-electric effects.A homogenization algorithm based on a Mori&Tanaka approach has been adopted to obtain the equivalent magneto-electro-mechanical properties of a two-phase transversely isotropic composite.In addition,an effective method has been adopted involving the external loads in terms of surface tractions,as well as the electric and magnetic fluxes.In the post-processing stage,a GDQ-based procedure provides the actual 3D response of a doubly-curved solid.The model has been validated through significant numerical examples,showing that the results of this semi-analytical theory align well with those obtained from 3D numerical models from commercial codes.In particular,the accuracy of the model has been verified for lamination schemes with soft layers and various curvatures under different loading conditions.Moreover,this formulation has been used to predict the effect of combined electric and magnetic loads on the mechanical response of panels with different curvatures and lamination schemes.As a consequence,this theory can be applied in engineering applications where the combined effect of electric and magnetic loads is crucial,thus facilitating their study and design.An existing limitation of this study is that the solution is that it is derived only for structures with uniform curvature,cross-ply lamination scheme,and simply supported boundary conditions.Furthermore,it requires that each lamina within the stacking sequence exhibits magneto-electro-elastic behavior.Therefore,at the present stage,it cannot be used for multifield analysis of classical composite structures with magneto-electric patches.A further enhancement of the research work could be the derivation of a solution employing a numerical technique,to overcome the limitations of the Navier method.In this way,the same theory may be adopted to predict the multifield response of structures with variable curvatures and thickness,as well as anisotropic materials and more complicated boundary conditions.Acknowledgement:The authors are grateful to the Department of Innovation Engineering of Univer-sity of Salento for the support.展开更多
Epigenetics is the discipline of regulating cellular activity through chemical modification or modulation of noncoding RNAs without altering the nucleotide sequence.Studies on this topic include the exploration of DNA...Epigenetics is the discipline of regulating cellular activity through chemical modification or modulation of noncoding RNAs without altering the nucleotide sequence.Studies on this topic include the exploration of DNA methylation,histone modification,noncoding RNA regulation,and chromatin remodeling.Derived from the apical tissues of young permanent teeth,stem cells from apical papilla are odontogenic adult stem cells with high proliferation,self-renewal capacity,and differentiation potential.These cells play crucial roles in root formation and development.This article focuses on the two epigenetic regulatory mechanisms of histone modifications and non-coding RNA.This review summarizes,generalizes,and evaluates the status of research on the epigenetic regulation of the multidirectional differentiation of stem cells from the apical papilla,aiming to explore the mechanisms underlying the multidirectional differentiation process of these stem cells.展开更多
Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that...Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.展开更多
Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly...Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly on imaging-based technology,which requires complex staining and sophisticated instrumentation.In this work,we develop a label-free method based on artificial intelligence(AI)-assisted impedance-based flow cytometry(IFC)to differentiate between various BC cells and epithelial cells at single-cell resolution.By applying multiple-frequency excitations,the electrical characteristics of cells,including membrane and nuclear opacities,are extracted,allowing distinction to be made between epithelial cells,low-grade,and high-grade BC cells.Through the use of a constriction channel,the electro-mechanical properties associated with active deformation behavior of cells are investigated,and it is demonstrated that BC cells have a greater capability of shape recovery,an observation that further increases differentiation accuracy.With the assistance of a convolutional neural network-based AI algorithm,IFC is able to effectively differentiate various BC and epithelial cells with accuracies of over 95%.In addition,different grades of BC cells are successfully differentiated in both spiked mixed samples and bladder tumor tissues.展开更多
Lycium ruthenicum(black goji)is a medicinal plant native to the Qinghai-Tibet Plateau(Cao et al.,2021),known for its high anthocyanin content(Avula et al.,2023)in fruit.In contrast,the white and purple variants contai...Lycium ruthenicum(black goji)is a medicinal plant native to the Qinghai-Tibet Plateau(Cao et al.,2021),known for its high anthocyanin content(Avula et al.,2023)in fruit.In contrast,the white and purple variants contain little anthocyanin(Zong et al.,2019).The evolutionary relationship of the variants and the genetic basis underlying their color differentiation has rarely been well studied at the whole genome level(Li et al.,2024).In this study,we present a near-complete genome assembly of L.ruthenicum,providing a valuable resource for investigating its evolutionary relationships with other Lycium species and fruit color variants.Through integrated genomic,transcriptomic,and functional analyses,we identify a key structural variation of AN1,a bHLH transcription factor essential for anthocyanin biosynthesis,which underlies the formation of white and purple goji in L.ruthenicum.展开更多
Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study...Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.展开更多
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金supported by the National Key R&D Program of China(Grant No.:2022YFC3501805)the National Natural Science Foundation of China(Grant No.:82374030)+2 种基金the Science and Technology Program of Tianjin in China(Grant No.:23ZYJDSS00030)the Tianjin Outstanding Youth Fund,China(Grant No.:23JCJQJC00030)the China Postdoctoral Science Foundation-Tianjin Joint Support Program(Grant No.:2023T030TJ).
文摘Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.
基金Project supported by the Thousand Talents Program of Jiangxi Province,China(JXSQ2023201003)National Natural Science Foundation of China(42107254)+4 种基金Science and Technology Major Program of Ordos City(2022EEDSKJZDZX014-2)Technological Innovation Guidance Program of Jiangxi Province(20212BDH81029)Rare Earth Industry Fund(IAGM2020DB06)Selfdeployed Projects of Ganjiang Innovation Academy,Chinese Academy of Sciences(E055A01)the Key Research Program of the Chinese Academy of Sciences(ZDRW-CN-2021-3-3)。
文摘The rare earth elements(REEs)extraction by chemical leaching from ion-adsorption type rare earth ores(IAREO)has led to serious ecological and environmental risks.Conversely,demand for bioleaching is on the rise with the advantage of being environmental-friendly.As one of the organic acids produced by biological metabolism,citric acid was used to leach REEs and explore the performance and process.The results demonstrate that citric acid exhibits higher leaching efficiency(96.00%)for REEs at a relatively low concentration of 0.01 mol/L compared with(NH_(4))_(2)SO_(4)(84.29%,0.1 mol/L)and MgSO_(4)(83.99%,0.1 mol/L).Citric acid shows a preference for leaching heavy rare earth elements,with 99%leaching efficiency in IAREO,which shows higher capacity than(NH_(4))_(2)SO_(4)and MgSO_(4)(as inorganic leaching agents).Kinetic analysis indicates that the leaching process of REEs with citric acid is controlled by both the internal diffusion kinetics and chemical reaction kinetics,which is different from inorganic leaching agents.Visual Minteq calculations confirm that RE-Citrate is the main constituent of the extract solution in the leaching process of the IAREO,thereby enhancing the leaching efficiency of REEs from the IAREO.It suggests that citric acid may be used as a promising organic leaching agent for the environmentalfriendly extraction of REEs from IAREO.
文摘The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the infected person or community is the preferred choice to protect our health.Since humans are the only carriers,it might be possible to control the positive rate if the infected population or host carriers are isolated from each other.Isolation alone may not be a proper solution.These are the resolutions of previous research work carried out on COVID-19 throughout the world.The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well.In this research work,we have pre-sented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems.In the first step,we created a fuzzy Susceptible-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death(SEIAHRD)model for COVID-19,analyzed it using granular differentiability,and reported disease dynamics for time-independent disease control parameters.In the second step,we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader.Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.
基金completed while U.P.was at theUniversity of Oxford,supported by TüBITAK BIDEB 2219(Grant Number:1059B192301787)。
文摘This study investigates the genetic differentiation and gene flow within the Subalpine Warbler(Curruca cantillans)complex using mitochondrial DNA(mtDNA)analysis.We focused on three primary populations based on phylogenetic findings and geographical distributions.Popl:Includes C.c.albistriata(distributed in extreme northeast Italy(Trieste),southern Slovenia,and south along the north Adriatic coast to Albania,as well as east to southern Bulgaria,Greece,Crete,and western Turkey,with non-breeding grounds in the central and eastern Sahel from eastern Mali to northwest Sudan)and C.c.cantillans(occurring in Sicily,central and southern Italy,and locally in north-central Italy,with non-breeding grounds presumably in the western Sahel).Pop2:Represents C.iberiae,found in Spain and western France.Pop3:Comprises C.subalpina,distributed across the Balearic Islands,Corsica,Sardinia,some Tuscan islands,and north and central Italy,with non-breeding grounds extending into the western Sahel,reaching northern Nigeria and Niger.Our genetic analysis indicates that all three populations have expanded recently but maintain unique genetic structures.Despite this recent expansion,the populations exhibit limited genetic diversity.Using AMOVA,we found that most genetic variation is between populations rather than within them,indicating significant genetic differentiation.This study uniquely combines population genetic data with advanced analyses to provide detailed insights into the genetic structure and connectivity of the Subalpine Warbler complex,highlighting the distinct genetic lineages within the Mediterranean biodiversity hotspot.
基金supported by the Serbian Ministry of Education and Science under Grant No.TR35006 and COST Action:CA23155—A Pan-European Network of Ocean Tribology(OTC)The research of B.Rosic and M.Rosic was supported by the Serbian Ministry of Education and Science under Grant TR35029.
文摘This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Optimization(SFO)algorithm.The primary objective is to address multi-objective optimization challenges within mechanical engineering,with a specific emphasis on planetary gearbox optimization.The algorithm is equipped with the ability to dynamically select the optimal mutation operator,contingent upon an adaptive normalized population spacing parameter.The efficacy of HMODESFO has been substantiated through rigorous validation against estab-lished industry benchmarks,including a suite of Zitzler-Deb-Thiele(ZDT)and Zeb-Thiele-Laumanns-Zitzler(DTLZ)problems,where it exhibited superior performance.The outcomes underscore the algorithm’s markedly enhanced optimization capabilities relative to existing methods,particularly in tackling highly intricate multi-objective planetary gearbox optimization problems.Additionally,the performance of HMODESFO is evaluated against selected well-known mechanical engineering test problems,further accentuating its adeptness in resolving complex optimization challenges within this domain.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China,No.LTGY24H160006Jiaxing Medical Key Discipline,No.2023-ZC-015.
文摘BACKGROUND Rectal cancer is one of the common digestive system malignant tumors around the world.Its early diagnosis and staging are crucial for rectal cancer treatment and prognosis.In recent years,tumor markers have gradually received attention in early screening,treatment monitoring and prognostic evaluation of cancer,but their predictive role in rectal cancer staging and differentiation is still unclear.AIM To assess the prognostic value of tumor markers alpha-fetoprotein(AFP)cancer antigen 72-4(CA72-4),carbohydrate antigen 19-9(CA19-9),and carcinoembryonic antigen(CEA),alongside multimodal magnetic resonance imaging(MRI),for staging and differentiating rectal cancer in patients.METHODS This study retrospectively analyzed 167 patients with rectal cancer who were treated at our institution from January 2020 to December 2024.Each patient underwent serological testing and multimodal MRI for diagnosis.Histopathological examination after surgical resection or imaging based on follow-up was used as the gold standard.According to the T stage and differentiation degree,patients were divided into low stage group(T1-T2)and high stage group(T3-T4).In addition,they were divided into low-differentiation groups and high-differentiation groups according to their differentiation degree.We compared the accuracy,sensitivity and specificity of tumor marker levels and MRI in rectal cancer stage and differentiation.RESULTS The study's findings indicate that in the context of rectal cancer T staging,there is substantial concordance between MRI and clinicopathological assessments,with a Kappa coefficient of 0.789(P<0.001).Similarly,for various degrees of tumor differentiation,MRI and clinicopathological evaluations demonstrated substantial agreement,with a Kappa coefficient of 0.651(P<0.001).Notably,the concentrations of tumor markers CA19-9,CA72-4,CEA,and AFP were significantly elevated in the T3-T4 stage compared to the T1-T2 stage.Furthermore,these markers were significantly higher in the low-differentiation group compared to the high-differentiation group(P<0.05).The combined use of tumor markers and MRI for preoperative T staging of rectal cancer yielded a diagnostic sensitivity of 93.7%and a specificity of 94.6%,as evidenced by the receiver operating characteristic analysis,with an area under the curve of 0.947.For tumor differentiation,the diagnostic sensitivity and specificity were 93.6%and 97.1%,respectively,with an area under the curve of 0.978(95%confidence interval:0.946-1.000),surpassing the accuracy of individual detection methods.CONCLUSION The CA19-9,CA72-4,CEA and AFP tumor markers combined with multimodal MRI have high sensitivity and specificity in diagnosing rectal cancer stage and differentiation.Their diagnostic efficacy is significantly better than that of single tests,which can effectively improve the predictive ability of rectal cancer stage and differentiation,provide a more reliable diagnostic reference for clinical practice,and have important clinical significance.
基金jointly supported by the Natural Science Foundation of China(Nos.42172056,41772052)。
文摘A-type rocks have drawn considerable attention in the past few decades due to their distinctive mineralogical and geochemical fingerprints and prospective utility for geodynamic reconstruction of the lithosphere.A comprehensive study,involving zircon U-Pb geochronology,wholerock elemental and Sr-Nd-Pb isotopic geochemistry,was undertaken to elucidate the origin and evolutionary process for syenites from the Daguiping area in the North Daba mountains,South Qinling belt.The syenites revealed an Ordovician igneous crystallization age of 454.4±17 Ma,coeval with the neighboring mafic rocks.All samples show high SiO_(2),LREEs,and HFSEs(Nb,Ta,Zr and Hf)contents,with negative to slightly positive Eu(Eu/Eu^(*)=0.78-1.08)anomalies.The geochemical characteristics of the Daguiping syenites imply that they are of A_1-type magmatic affinity,which is confirmed by their high total alkali levels(8.57 wt.%-11.94 wt.%),Zr+Nb+Ce+Y contents(738.00 ppm-1734.78 ppm),and 10000×Ga/Al ratios(3.25-4.22),as well as low Y/Nb ratios(0.30-0.40).Our samples exhibit a wide range of initial^(87)Sr/^(86)Sr ratios of 0.701943 to 0.709802 and a narrow range of^(143)Nd/^(144)Nd ratios of 0.512205-0.512246 withε_(Nd)(t)values from+3.0 to+3.8.These rocks display(^(206)Pb/^(204)Pb)_(initial),(^(207)Pb/^(204)Pb)_(initial),and(^(208)Pb/^(204)Pb)_(initial)ratios range from 17.96 to 18.62,15.55 to 15.59,and 36.87 to 38.22,respectively.All of the isotopic data indicate that the syenites were essentially mantle-derived.A cogenetic source for the Daguiping syenites and coeval mafic rocks in the South Qinling belt is supported by their uniform Sr-Nd-Pb isotope data and linear major/trace elemental changes,with prolonged fractional crystallization considered as the essential mechanism for these geochemical discrepancies.Mass-balance and Rayleigh fractionation modeling estimate~85 vol%fractional crystallization involving amphibole,clinopyroxene,plagioclase,Kfeldspar,biotite,Fe-Ti oxide,and quartz,to reproduce the compositional varieties between a coeval mafic rock and the Daguiping syenites.The Daguiping syenites and associated alkaline rocks were likely related to a rifting episode triggered by asthenospheric upwelling,which led to the South Qinling detaching from the South China Block along the Mianlue suture during the Early Paleozoic.
基金supported by the Program of Key Projects of Foundation Strengthening Plan,China(No.2022-JCJQ-ZD114-12-03)the Graduate Student Innovation Fund Lighthouse Program of Southwest University of Science and Technology,China(No.24ycx3009)。
文摘The numerical calculation method has greatly promoted the process of optimal design of scramjet,but it still needs extremely heavy calculation for the model with complex thermochemical reaction.Data-driven deep learning relies heavily on a large amount of data in the face of complex nonlinear features.Therefore,combining“data-driven model”and“Navier-Stokes equation”,an intelligent prediction model of supersonic combustion flow process is constructed.This algorithm integrates the theory priors of combustion flow into the neural network model,and uses convolutional grouping and rearrangement to reduce the feature redundancy calculation,so as to achieve high-precision and high-efficiency prediction of velocity,density,pressure and temperature fields.This study makes a comprehensive comparison from two aspects of performance and efficiency.Unsteady scramjet multi-physical field dataset is constructed under different incoming Mach number conditions.The experimental results show that compared with other methods,the proposed algorithm can achieve the maximum Peak Signal-to-Noise Ratio(PSNR)improvement of 38.75%and Learned Perceptual Image Patch Similarity(LPIPS)improvement of 68.13%in predicting the average quality of images,and the computational cost of the model is reduced by 30.36%compared with other models.In addition,the high model can also effectively predict the unknown incoming flow condition.
文摘The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices.This paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability.Our results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT environments.Nodes are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient networks.The algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet Delivery Ratio(PDR)of 99% and a robust network throughput of up to 1800 kbps in more compact node configurations.This study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.
文摘Let X be a real uniformly convex and uniformly smooth Banach space and C a nonempty closed and convex subset of X.Let Π_(C):X→C denote the generalized metric projection operator introduced by Alber in[1].In this paper,we define the Gâteaux directional differentiability of Π_(C).We investigate some properties of the Gâteaux directional differentiability of Π_(C).In particular,if C is a closed ball,or a closed and convex cone(including proper closed subspaces),or a closed and convex cylinder,then,we give the exact representations of the directional derivatives of Π_(C).By comparing the results in[12]and this paper,we see the significant difference between the directional derivatives of the generalized metric projection operator Π_(C) and the Gâteaux directional derivatives of the standard metric projection operator PC.
文摘This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.
基金supported by the Hainan Province Science and Technology Talent Innovation Project(KJRC2023A02)Project of Sanya Yazhouwan Science and Technology City Management Foundation(SKJC-KJ-2019KY01)Sanya Science and Technology Special Fund(2022KJCX91)。
文摘The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite,with pearl production displaying notable sexual dimorphism.Consequently,understanding the molecular mechanisms governing sex determination and differentiation is crucial for advancing breeding strategies in the pearl oyster industry.To elucidate these mechanisms,this study conducted integrative transcriptomic analyses of P.maxima gonadal tissues using isoform sequencing(Isoseq)and RNA sequencing(RNA-seq).Comparative analysis of ovarian and testicular tissues identified 2768 differentially expressed genes(DEGs).Gene coexpression network analysis delineated four key modules,including three sex-specific modules and one shared module.Key genes implicated in sex determination and maintenance were identified,including FOXL2,NANOS1,andβ-catenin,important for ovarian maintenance,and DMRT,SOX30,FEM1,and FOXJ1,crucial for testicular maintenance.These genes,widely studied in other taxa,were confirmed as hub genes in the sex-related modules of P.maxima.Interestingly,genes within the shared module were significantly enriched in the spliceosome pathway.Alternative splicing analysis highlighted its extensive role in gonadal tissues,with more pronounced activity observed in the testis compared to the ovary.Nearly half(47.83%,375)of the identified genes undergoing differential alternative splicing(DASGs)also exhibited differential transcript usage(DTUGs),while only 17%of DTUGs overlapped with DEGs.Genes associated with sex differentiation,such as DMRT,β-catenin,and U2AF2,displayed sex-specific and/or sex-biased isoforms.These findings offer novel insights into the molecular basis of sex differentiation in P.maxima,which could inform the development of targeted breeding strategies aimed at sex control,thereby enhancing pearl quality and yield in aquaculture.This study offers a robust molecular foundation for advancing breeding programs and optimizing production in the pearl oyster industry.
基金supported by the Guizhou Provincial Basic Research Program(Natural Science)[(2024)648]the Program of China National Tobacco Corporation(110202101032(JY-09),110202201003(JY-03))the Program of Guizhou Branch of China National Tobacco Corporation(2023XM02,2021XM05,2022XM05,2024XM01).
文摘Nicotiana tabacum(2n=4x=48),an economically important non-food crop and a model plant for genetic studies,faces challenges in efficient genotyping of novel germplasm.To address this,we developed the Ta-LD-SC,a 20K SNP Affymetrix Axiom array,based on resequencing data from 150 tobacco accessions.A total of 20,213 unique SNPs were carefully selected,achieving coverage of over 90%of the tobacco genome(Nitab4.5 and NtaSR1)with a uniform probe distribution,limiting density to no more than 5 SNPs per 200 kb.The array underwent extensive validation using 866 tobacco accessions(NP panel)and 288 F2 individuals from a cross between K326 and Oxford 26(GP panel).Performance metrics demonstrated its robustness,with high SNP call rates(93.6%-99.8%),a low technical error rate(<1%),and a superior PolyHighResolution SNP rate(79.79%)compared to other crop SNP arrays.Population structure analysis of the NP panel revealed two major introductions of foreign germplasm that have significantly influenced the genetic diversity of Chinese tobacco resources.Using the array,a genome-wide association study(GWAS)identified 62 genes linked to eight agronomic traits,and a high-density genetic map encompassing 4553 SNPs across 6606.08 cM was constructed.The Ta-LD-SC array provides a valuable tool for rapid,high-quality genotyping offering supporting marker annotations that may benefit genetic research and breeding of tobacco.
基金funded by the Project PNRR M4C2—Innovation Grant DIRECT:Digital twIns foR EmergenCy supporT—CUP F83C22000740001.
文摘Recent engineering applications increasingly adopt smart materials,whose mechanical responses are sensitive to magnetic and electric fields.In this context,new and computationally efficient modeling strategies are essential to predict the multiphysic behavior of advanced structures accurately.Therefore,the manuscript presents a higher-order formulation for the static analysis of laminated anisotropic magneto-electro-elastic doubly-curved shell structures.The fundamental relations account for the full coupling between the electric field,magnetic field,and mechanical elasticity.The configuration variables are expanded along the thickness direction using a generalized formulation based on the Equivalent Layer-Wise approach.Higher-order polynomials are selected,allowing for the assessment of prescribed values of the configuration variables at the top and bottom sides of solids.In addition,an effective strategy is provided for modeling general surface distributions of mechanical pressures and electromagnetic external fluxes.The model is based on a continuum-based formulation which employs an analytical homogenization of the multifield material properties,based on Mori&Tanaka approach,of a magneto-electro-elastic composite material obtained from a piezoelectric and a piezomagnetic phase,with coupled magneto-electro-elastic effects.A semi-analytical Navier solution is applied to the fundamental equations,and an efficient post-processing equilibrium-based procedure is here used,based on the numerical assessment with the Generalized Differential Quadrature(GDQ)method,to recover the response of three-dimensional shells.The formulation is validated through various examples,investigating the multifield response of panels of different curvatures and lamination schemes.An efficient homogenization procedure,based on the Mori&Tanaka approach,is employed to obtain the three-dimensional constitutive relation of magneto-electro-elastic materials.Each model is validated against three-dimensional finite-element simulations,as developed in commercial codes.Furthermore,the full coupling effect between the electric and magnetic response is evaluated via a parametric investigation,with useful insights for design purposes of many engineering applications.The paper,thus,provides a formulation for the magneto-electro-elastic analysis of laminated structures,with a high computational efficiency,since it provides results with three-dimensional capabilities with a two-dimensional formulation.The adoption of higher-order theories,indeed,allows us to efficiently predict not only the mechanical response of the structure as happens in existing literature,but also the through-the-thickness distribution of electric and magnetic variables.A novel higher-order theory has been proposed in this work for the magneto-electro-elastic analysis of laminated shell structures with varying curvatures.This theory employs a generalized method to model the distribution of the displacement field components,electrostatic,and magneto-static potential,accounting for higher-order polynomials.The thickness functions have been defined to prescribe the arbitrary values of configuration variables at the top and bottom surfaces,even though the model is ESL-based.The fundamental governing equations have been derived in curvilinear principal coordinates,considering all coupling effects among different physical phenomena,including piezoelectric,piezomagnetic,and magneto-electric effects.A homogenization algorithm based on a Mori&Tanaka approach has been adopted to obtain the equivalent magneto-electro-mechanical properties of a two-phase transversely isotropic composite.In addition,an effective method has been adopted involving the external loads in terms of surface tractions,as well as the electric and magnetic fluxes.In the post-processing stage,a GDQ-based procedure provides the actual 3D response of a doubly-curved solid.The model has been validated through significant numerical examples,showing that the results of this semi-analytical theory align well with those obtained from 3D numerical models from commercial codes.In particular,the accuracy of the model has been verified for lamination schemes with soft layers and various curvatures under different loading conditions.Moreover,this formulation has been used to predict the effect of combined electric and magnetic loads on the mechanical response of panels with different curvatures and lamination schemes.As a consequence,this theory can be applied in engineering applications where the combined effect of electric and magnetic loads is crucial,thus facilitating their study and design.An existing limitation of this study is that the solution is that it is derived only for structures with uniform curvature,cross-ply lamination scheme,and simply supported boundary conditions.Furthermore,it requires that each lamina within the stacking sequence exhibits magneto-electro-elastic behavior.Therefore,at the present stage,it cannot be used for multifield analysis of classical composite structures with magneto-electric patches.A further enhancement of the research work could be the derivation of a solution employing a numerical technique,to overcome the limitations of the Navier method.In this way,the same theory may be adopted to predict the multifield response of structures with variable curvatures and thickness,as well as anisotropic materials and more complicated boundary conditions.Acknowledgement:The authors are grateful to the Department of Innovation Engineering of Univer-sity of Salento for the support.
文摘Epigenetics is the discipline of regulating cellular activity through chemical modification or modulation of noncoding RNAs without altering the nucleotide sequence.Studies on this topic include the exploration of DNA methylation,histone modification,noncoding RNA regulation,and chromatin remodeling.Derived from the apical tissues of young permanent teeth,stem cells from apical papilla are odontogenic adult stem cells with high proliferation,self-renewal capacity,and differentiation potential.These cells play crucial roles in root formation and development.This article focuses on the two epigenetic regulatory mechanisms of histone modifications and non-coding RNA.This review summarizes,generalizes,and evaluates the status of research on the epigenetic regulation of the multidirectional differentiation of stem cells from the apical papilla,aiming to explore the mechanisms underlying the multidirectional differentiation process of these stem cells.
基金supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI under Grant JP22H03643Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)under Grant JPMJSP2145JST through the Establishment of University Fellowships towards the Creation of Science Technology Innovation under Grant JPMJFS2115.
文摘Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.
基金financial support from the National Natural Science Foundation of China(NSFC Grant No.22076138)the National Natural Science Foundation of China(NSFC Grant No.62174119).
文摘Bladder cancer(BC)is a common malignancy and among the leading causes of cancer death worldwide.Analysis of BC cells is of great significance for clinical diagnosis and disease treatment.Current approaches rely mainly on imaging-based technology,which requires complex staining and sophisticated instrumentation.In this work,we develop a label-free method based on artificial intelligence(AI)-assisted impedance-based flow cytometry(IFC)to differentiate between various BC cells and epithelial cells at single-cell resolution.By applying multiple-frequency excitations,the electrical characteristics of cells,including membrane and nuclear opacities,are extracted,allowing distinction to be made between epithelial cells,low-grade,and high-grade BC cells.Through the use of a constriction channel,the electro-mechanical properties associated with active deformation behavior of cells are investigated,and it is demonstrated that BC cells have a greater capability of shape recovery,an observation that further increases differentiation accuracy.With the assistance of a convolutional neural network-based AI algorithm,IFC is able to effectively differentiate various BC and epithelial cells with accuracies of over 95%.In addition,different grades of BC cells are successfully differentiated in both spiked mixed samples and bladder tumor tissues.
基金supported by the Qinghai Provincial Key Laboratory of Crop Molecular Breeding[2023-1-1].
文摘Lycium ruthenicum(black goji)is a medicinal plant native to the Qinghai-Tibet Plateau(Cao et al.,2021),known for its high anthocyanin content(Avula et al.,2023)in fruit.In contrast,the white and purple variants contain little anthocyanin(Zong et al.,2019).The evolutionary relationship of the variants and the genetic basis underlying their color differentiation has rarely been well studied at the whole genome level(Li et al.,2024).In this study,we present a near-complete genome assembly of L.ruthenicum,providing a valuable resource for investigating its evolutionary relationships with other Lycium species and fruit color variants.Through integrated genomic,transcriptomic,and functional analyses,we identify a key structural variation of AN1,a bHLH transcription factor essential for anthocyanin biosynthesis,which underlies the formation of white and purple goji in L.ruthenicum.
基金financed by the grants from the National Natural Science Foundation of China(No.81803996)Shanghai Key Laboratory of Health Identification and Assessment(No.21DZ2271000)。
文摘Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.
