Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters.A neural network(NN)-based approach is investigated that facilitates such a process.Both multilayer perceptron(MLP)-based NN and convolutional neural network(CNN)models are trained to map the q-profile to the plasma current density J-profile,and vice versa,while satisfying the Grad–Shafranov radial force balance constraint.When the initial target models are trained,using a database of semianalytically constructed numerical equilibria,an initial CNN with one convolutional layer is found to perform better than an initial MLP model.In particular,a trained initial CNN model can also predict the q-or J-profile for experimental tokamak equilibria.The performance of both initial target models is further improved by fine-tuning the training database,i.e.by adding realistic experimental equilibria with Gaussian noise.The fine-tuned target models,referred to as fine-tuned MLP and fine-tuned CNN,well reproduce the target q-or J-profile across multiple tokamak devices.As an important application,these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers,where the desired input quantity is the safety factor instead of the plasma current density.

Baseline design of the KunLun Turbulence Profiler instrument

Adaptive optics systems are the most powerful tools to counteract the image blurring caused by atmospheric turbulence,allowing ground-based telescopes to capture high-resolution images.A critical parameter influencing adaptive optics system performance is the atmospheric refractive index structure constant,C_(n)^(2),which characterizes the intensity of atmospheric optical turbulence as a function of altitude.Given its simplicity,the lunar scintillometer is the preferred method for detecting atmospheric turbulence in challenging environments like Dome A in Antarctica,where sites are still in the developmental stages and local environmental conditions are extremely harsh.However,optimizing the performance of such instruments requires carefully determining the baseline configuration of photon sensors according to each site's specific optical turbulence profile characteristics.This study uses a Monte Carlo method to identify the optimal configuration for the KunLun Turbulence Profiler(KLTP),an instrument comparable to the lunar scintillometer,developed for use at Dome A.Simulations conducted using the obtained optimal baseline configuration recovered three different model optical turbulence profiles,demonstrating the effectiveness of our method in obtaining an optimal baseline configuration.Our approach can be easily applied to baseline design for similar turbulence profilers at other sites.

三维薛定谔方程组的线性Profile分解

为了研究线性薛定谔方程组解Strichartz估计的紧性缺失问题,针对H•^(1)(R^(3))×H•^(1)(R^(3))中的三维线性薛定谔方程组的有界解向量序列,使用解序列的Profile分解方法,构造为解向量子列的(1/√h_(n))U(t-t_(n))/h_(n)^(2),(x-x_(n))/h_(n)类型的Profile分解和.其中,U是线性薛定谔方程组的解向量,在Strichartz范数估计下具有一个很小的余项.首先确定伸缩变换参数序列族,利用傅里叶变换和迭代的思想确定Profile分解族.其次验证了Profile分解和的收敛性,说明了Strichartz范数下余项的收敛性.最后证明了当线性薛定谔方程组的解序列有界时,都可以分解为解向量子列和的形式.

Morphological,phylogenetic and metabolite profile of Prorocentrum clipeus,a newly recorded epiphytic dinoflagellate in the northern Yellow Sea

More than 30 species of benthic Prorocentrum have been identified,some of which produce okadaic acid(OA)and its derivatives,dinophysistoxins(DTXs),which cause diarrhetic shellfish poisoning(DSP).Increasing numbers of benthic Prorocentrum species have been reported in tropical and subtropical waters of China.In contrast,only a few benthic Prorocentrum species have been reported in temperate waters.In this study,morphological descriptions obtained using light microscopy,scanning electron microscopy and molecular characterization of one Prorocentrum clipeus strain isolated from the Yellow Sea are presented.Prorocentrum clipeus cells were nearly circular in shape,with a collar,ridge,and one protrusion.The periflagellar area was wide U-shaped,with two curved projections on platelet 1a.Nine periflagellar platelets of different sizes were observed.The morphology closely fits that of the species isolated from other locations.Phylogenetic analysis based on the molecular sequences of the small subunit(SSU)rDNA,internal transcribed spacer(ITS),and large subunit(LSU)rDNA was performed.A comprehensive metabolomic analysis incorporating target,suspect and non-target screenings was first applied to investigate the intracellular and extracellular metabolite profiles of the current isolate of P.clipeus.According to the results of the target and suspect screenings,179 metabolites or toxins produced by DSP-related algal species,including OA,dinophysistoxin-1(DTX1),dinophysistoxin-2(DTX2)and pectenotoxin-2(PTX2),were not detected.Non-target screening involving feature-based molecular networking(FBMN)provided a global view of major metabolites produced by the P.clipeus DF128 strain and revealed 23 clusters belonging to at least 13 compound classes,with organometallic compounds,lipids and lipid-like molecules,phenylpropanoids and polyketides,and benzenoids as major types.To date,this is the first record of the characterization of P.clipeus in samples from Chinese waters.Our results support the wide distribution of epibenthic Prorocentrum species.

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.

Soil resilience assessment using soil profile descriptions and Analytic Hierarchy Process in Mediterranean mountains considering diverse fire occurrences

Wildfires are complex natural phenomena that exert significant impacts on landscapes,societies,and economies.Understanding the concept of resilience is crucial in mitigating its possible negative impacts,as it involves preparing for,responding to,and recovering from wildfires.This research aims to demonstrate the utility of in situ soil profile description in assessing land use resilience using an Analytic Hierarchy Process(AHP)through an expert panel survey.The study examines a catchment located in the Balearic Islands,considering two fire occurrences(once and twice),comparing abandoned agricultural terraces and natural hillslopes.The results demonstrated that the priority ranking of variables to assess soil profile resilience against wildfires,determined by a panel of 10 experts,identified horizon depth(25.1%),slope inclination(21.5%),and hydrological connectivity(16.6%)as the most crucial factors.Other variables,such as number and size of roots,structure of pedal soil material,size class structure,and rock fragments,also contributed to resilience but to a lesser extent,with scores ranging from 5.7%to 9.6%.Analyzing the priorities established by the experts using AHP,the results showed that the least resilient soil horizon was H1 of the control hillslope,especially under high and low connectivity processes,which aligned with the loss of superficial soil horizons after one and two wildfires.Hillslopes showed greater changes in resilience after occurring wildfires compared to terraces,with the most significant alterations occurring after the second wildfire event.This study addresses a significant knowledge gap in the field by highlighting the interconnectedness of wildfires,resilience,and land use,providing insights into land management strategies for wildfire-prone regions.

Three-Channel Interference Interpretation of Fano Profile

Fano resonance is a ubiquitous phenomenon, and it is commonly interpreted as a two-channel interference of the discrete and continuous channels. The present work investigates the Fano profile from a perspective of the temporal evolution of the wave function. By exciting the atom with a δ pulse and calculating the evolution of the wave function, the Fano formula is deduced. The results clearly show that the Fano resonance is of a three-channel interference, which is different from the traditional understanding. The three channels are revealed as the groundcontinuum, ground-discrete-continuum, and a previously unmentioned third channel, i.e., ground-continuumdiscrete-continuum. The present three-channel interpretation can be easily generalized to other physical systems,contributing to a deeper understanding of the Fano profile.

TP-PROFILE: Monitoring the Thermodynamic Structure of the Troposphere over the Third Pole

Ground-based microwave radiometers(MWRs)operating in the K-and V-bands(20–60 GHz)can help us obtain temperature and humidity profiles in the troposphere.Aside from some soundings from local meteorological observatories,the tropospheric atmosphere over the Tibetan Plateau(TP)has never been continuously observed.As part of the Chinese Second Tibetan Plateau Scientific Expedition and Research Program(STEP),the Tibetan Plateau Atmospheric Profile(TPPROFILE)project aims to construct a comprehensive MWR troposphere observation network to study the synoptic processes and environmental changes on the TP.This initiative has collected three years of data from the MWR network.This paper introduces the data information,the data quality,and data downloading.Some applications of the data obtained from these MWRs were also demonstrated.Our comparisons of MWR against the nearest radiosonde observation demonstrate that the TP-PROFILE MWR system is adequate for monitoring the thermal and moisture variability of the troposphere over the TP.The continuous temperature and moisture profiles derived from the MWR data provide a unique perspective on the evolution of the thermodynamic structure associated with the heating of the TP.The TP-PROFILE project reveals that the low-temporal resolution instruments are prone to large uncertainties in their vapor estimation in the mountain valleys on the TP.

Metabolic profiles and morphological characteristics of leaf tips among different sweet potato(Ipomoea batatas Lam.)varieties

Sweet potato leaf tips have high nutritional value,and exploring the differences in the metabolic profiles of leaf tips among different sweet potato varieties can provide information to improve their qualities.In this study,a UPLC-Q-Exactive Orbitrap/MS-based untargeted metabolomics method was used to evaluate the metabolites in leaf tips of 32 sweet potato varieties.Three varieties with distinct overall metabolic profiles(A01,A02,and A03),two varieties with distinct profiles of phenolic acids(A20 and A18),and three varieties with distinct profiles of flavonoids(A05,A12,and A16)were identified.In addition,a total of 163 and 29 differentially expressed metabolites correlated with the color and leaf shape of sweet potato leaf tips,respectively,were identified through morphological characterization.Group comparison analysis of the phenotypic traits and a metabolite-phenotypic trait correlation analysis indicated that the color differences of sweet potato leaf tips were markedly associated with flavonoids.Also,the level of polyphenols was correlated with the leaf shape of sweet potato leaf tips,with lobed leaf types having higher levels of polyphenols than the entire leaf types.The findings on the metabolic profiles and differentially expressed metabolites associated with the morphology of sweet potato leaf tips can provide useful information for breeding sweet potato varieties with higher nutritional value.

Optimizing profile line interval for enhanced accuracy in rock joint morphology and shear strength assessments

2D profile lines play a critical role in cost-effectively evaluating rock joint properties and shear strength.However, the interval(ΔI_(L)) between these lines significantly impacts roughness and shear strength assessments. A detailed study of 45 joint samples using four statistical measures across 500 different ΔI_(L)values identified a clear line interval effect with two stages: stable and fluctuation-discrete.Further statistical analysis showed a linear relationship between the error bounds of four parameters,shear strength evaluation, and their corresponding maximum ΔI_(L)values, where the gradient k of this linear relationship was influenced by the basic friction angle and normal stress. Accounting for these factors,lower-limit linear models were employed to determine the optimal ΔI_(L)values that met error tolerances(1%–10%) for all metrics and shear strength. The study also explored the consistent size effect on joints regardless of ΔI_(L)changes, revealing three types of size effects based on morphological heterogeneity.Notably, larger joints required generally higher ΔI_(L)to maintain the predefined error limits, suggesting an increased interval for large joint analyses. Consequently, this research provides a basis for determining the optimal ΔI_(L), improving accuracy in 2D profile line assessments of joint characteristics.

Kinetic equilibrium reconstruction with internal safety factor profile constraints on EAST tokamak

Reconstruction of plasma equilibrium plays an important role in the analysis and simulation of plasma experiments. The kinetic equilibrium reconstruction with pressure and edge current constraints has been employed on EAST tokamak. However, the internal safety factor(q) profile is not accurate. This paper proposes a new way of incorporating q profile constraints into kinetic equilibrium reconstruction. The q profile is yielded from the Polarimeter Interferometer(POINT)reconstruction. Virtual probes containing information on q profile constraints are added to inputs of the kinetic equilibrium reconstruction program to obtain the final equilibrium. The new equilibrium produces a more accurate internal q profile. This improved method would help analyze EAST experiments.

Multi-circular formation control with reinforced transient profiles for nonholonomic vehicles:A path-following framework

This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.

Changes in the Non-targeted Metabolomic Profile of Three-year-old Toddlers with Elevated Exposure to Polycyclic Aromatic Hydrocarbons

Objective To investigate changes in the urinary metabolite profiles of children exposed to polycyclic aromatic hydrocarbons(PAHs)during critical brain development and explore their potential link with the intestinal microbiota.Methods Liquid chromatography-tandem mass spectrometry was used to determine ten hydroxyl metabolites of PAHs(OH-PAHs)in 36-month-old children.Subsequently,37 children were categorized into low-and high-exposure groups based on the sum of the ten OH-PAHs.Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to identify non-targeted metabolites in the urine samples.Furthermore,fecal flora abundance was assessed by 16S rRNA gene sequencing using Illumina MiSeq.Results The concentrations of 21 metabolites were significantly higher in the high exposure group than in the low exposure group(variable importance for projection>1,P<0.05).Most of these metabolites were positively correlated with the hydroxyl metabolites of naphthalene,fluorine,and phenanthrene(r=0.336–0.531).The identified differential metabolites primarily belonged to pathways associated with inflammation or proinflammatory states,including amino acid,lipid,and nucleotide metabolism.Additionally,these distinct metabolites were significantly associated with specific intestinal flora abundances(r=0.34–0.55),which were mainly involved in neurodevelopment.Conclusion Higher PAH exposure in young children affected metabolic homeostasis,particularly that of certain gut microbiota-derived metabolites.Further investigation is needed to explore the potential influence of PAHs on the gut microbiota and their possible association with neurodevelopmental outcomes.

Calculation and Analysis of TVMS Considering Profile Shifts and Surface Wear Evolution Process of Spur Gear

Profile shift is a highly effective technique for optimizing the performance of spur gear transmission systems.However,tooth surface wear is inevitable during gear meshing due to inadequate lubrication and long-term operation.Both profile shift and tooth surface wear(TSW)can impact the meshing characteristics by altering the involute tooth profile.In this study,a tooth stiffness model of spur gears that incorporates profile shift,TSW,tooth deformation,tooth contact deformation,fillet-foundation deformation,and gear body structure coupling is established.This model efficiently and accurately determines the time-varying mesh stiffness(TVMS).Additionally,an improved wear depth prediction method for spur gears is developed,which takes into consideration the mutually prime teeth numbers and more accurately reflects actual gear meshing conditions.Results show that consideration of the mutual prime of teeth numbers will have a certain impact on the TSW process.Furthermore,the finite element method(FEM)is employed to accurately verify the values of TVMS and load sharing ratio(LSR)of profile-shifted gears and worn gears.This study quantitatively analyzes the effect of profile shift on the surface wear process,which suggests that gear profile shift can partially alleviate the negative effects of TSW.The contribution of this study provides valuable insights into the design and maintenance of spur gear systems.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Cross-section distortion and springback characteristics of double-cavity aluminum profile in force controlled stretch-bending

3D elastic-plastic FE model for simulating the force controlled stretch-bending process of double-cavity aluminum profile was established using hybrid explicit−implicit solvent method.Considering the computational accuracy and efficiency,the optimal choices of numerical parameters and algorithms in FE modelling were determined.The formation mechanisms of cross-section distortion and springback were revealed.The effects of pre-stretching,post-stretching,friction,and the addition of internal fillers on forming quality were investigated.The results show that the stress state of profile in stretch-bending is uniaxial with only a circumferential stress.The stress distribution along the length direction of profile is non-uniform and the maximum tensile stress is located at a certain distance away from the center of profile.As aluminum profile is gradually attached to bending die,the distribution characteristic of cross-section distortion along the length direction of profile changes from V-shape to W-shape.After unloading the forming tools,cross-section distortion decreases obviously due to the stress relaxation,with a maximum distortion difference of 13%before and after unloading.As pre-stretching and post-stretching forces increase,cross-section distortion increases gradually,while springback first decreases and then remains unchanged.With increasing friction between bending die and profile,cross-section distortion slightly decreases,while springback increases.Cross-section distortion decreases by 83%with adding PVC fillers into the cavities of profile,while springback increases by 192.2%.

Assessment of spermatogenesis in camels via seminiferous tubule staging and testosterone profiling

Objective:To investigate the successive morphological stages of spermatogenesis,hormonal regulation,and testosterone profile in dromedary camel reproduction.Methods:Testicular tissue samples were obtained from 12 dromedary bull camels aged 7 to 8 at a local abattoir.The histological assessment involved tissue processing,hematoxylin and eosin(H&E)staining,and examination under a microscope.Stereological analysis,germ cell identification,and assessment of seminiferous tubules and maturation were conducted.Testosterone assay was performed by radioimmunoassay using blood samples collected at regular intervals.Results:The study revealed 12 phases of the dromedary camel's seminiferous epithelium cycle,highlighting distinct morphological characteristics and cellular processes.Acrosomal migration,maturation,cap formation,and the Golgi-mediated synthesis of proacrosomal vesicles were also explained in dimension,as were the steps of acrosome biogenesis.Spermatids and mature sperm cells were present when spermatogenesis phases were examined.An analysis of the dimensions of seminiferous tubules revealed specific measures for diameter,area,and epithelial height about luminal characteristics.Moreover,there were noticeable variations in the serum testosterone concentrations during the study period,indicating temporal dynamics.Conclusions:This study outlines the spermatogenesis process in dromedary camels across 12 stages,emphasizing cellular dynamics and acrosomal biogenesis.It also provides seminiferous tubule measurements and observes seasonal testosterone fluctuations,offering insights into reproductive regulation and potential strategies for camel breeding conservation.

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

Experimental study of core MHD behavior and a novel algorithm for rational surface detection based on profile reflectometry in EAST

Microwave reflectometry is a powerful diagnostic that can measure the density profile and localized turbulence with high spatial and temporal resolution and will be used in ITER,so understanding the influence of plasma perturbations on the reflect signal is important.The characteristics of the reflect signal from profile reflectometry,the time-of-flight(TOF)signal associated with the MHD instabilities,are investigated in EAST.Using a 1D full-wave simulation code by the Finite-DifferenceTime-Domain(FDTD)method,it is well validated that the local density flattening could induce the discontinuity of the simulated TOF signal and an obvious change of reflect amplitude.Experimental TOF signals under different types of MHD instabilities(sawtooth,sawtooth precursors and tearing mode)are studied in detail and show agreement with the simulation.Two new improved algorithms for detecting and localizing the radial positions of the low-order rational surface,the cross-correlation and gradient threshold(CGT)method and the 2D convolutional neural network approach(CNN)are presented for the first time.It is concluded that TOF signal analysis from profile reflectometry can provide a straightforward and localized measurement of the plasma perturbation from the edge to the core simultaneously and may be a complement or correction to the q-profile control,which will be beneficial for the advanced tokamak operation.

Profiles of the Headspace Volatile Organic and Essential Oil Compounds from the Tunisian Cardaria draba (L.) Desv. and Its Leaf and Stem Epidermal Micromorphology

In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardariadraba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatileorganic compounds (96.7%–98.9%) were identified;4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones,1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the maingroup, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane(44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in thetwo fractions of EOs, representing 98.8% and 97.2% of the total oil composition, respectively. The principal componentswere hexadecanoic acid (34.6%), 6-methyl-5-hepten-2-one (18.3%), decanal (15.0%), 6,10,14-trimethyl-2-pentadecanone (13.2%), and n-pentacosane (13%). Micromorphological details of the leaf and stem epidermisusing light microscopy revealed polygonal cells with sinuous walls in the adaxial and abaxial leaf surfaces andnearly rectangular and long ones with linear and thick walls for the stem epidermis. The stomata complexes wereanisocytic in the leaf epidermis and mainly anisocytic and rarely paracytic in the stem epidermis. Non-glandulartrichomes were unbranched and long with an acute apex or short with a convex apex. The glandular ones wereidentified for the first time in this species. They were short-stalked with a large secretory head. The highest stomatalindex (17.02%) was recorded in the abaxial leaf surface. The identification of headspace volatiles and essentialoil compounds can be used to characterize this species, and the various epidermis micromorphologicalfeatures are very useful for biosystematics taxonomic studies within Brassicaceae.