First-order Mechanism Research Articles

Fermi acceleration under Lorentz invariance violation

In this paper, the acceleration of particles in astrophysical sources by the Fermi mechanism is revisited under the assumption of Lorentz invariance violation (LIV). We calculate the energy spectrum and the acceleration time of particles leaving the source as a function of the energy beyond which the Lorentz invariance violation becomes relevant. Lorentz invariance violation causes significant changes in the acceleration of particles by the first and second-order Fermi mechanisms. The energy spectrum of particles accelerated by first-order Fermi mechanism under LIV assumption shows a strong suppression for energies above the break. The calculations presented here complete the scenario for LIV searches with astroparticles by showing, for the first time, how the benchmark acceleration mechanisms (Fermi) are modified under LIV assumption.

Multi-perspective patient representation learning for disease prediction on electronic health records

Patient representation learning based on electronic health records (EHR) is a critical task for disease prediction. This task aims to effectively extract useful information on dynamic features. Although various existing works have achieved remarkable progress, the model performance can be further improved by fully extracting the trends, variations, and the correlation between the trends and variations in dynamic features. In addition, sparse visit records limit the performance of deep learning models. To address these issues, we propose the multi-perspective patient representation Extractor (MPRE) for disease prediction. Specifically, we propose frequency transformation module (FTM) to extract the trend and variation information of dynamic features in the time–frequency domain, which can enhance the feature representation. In the 2D multi-extraction network (2D MEN), we form the 2D temporal tensor based on trend and variation. Then, the correlations between trend and variation are captured by the proposed dilated operation. Moreover, we propose the first-order difference attention mechanism (FODAM) to calculate the contributions of differences in adjacent variations to the disease diagnosis adaptively. To evaluate the performance of MPRE and baseline methods, we conduct extensive experiments on two real-world public datasets. The experiment results show that MPRE outperforms state-of-the-art baseline methods in terms of AUROC and AUPRC.

Do geological records correlate with the supercontinent cycle?

Whether the supercontinent cycle (Sc) is the major process driving plate tectonics evolution has not been purposely investigated. If true, it would result in more geological records formed during each supercontinent assembly. In this study, a quantitative statistical approach is used to investigate this question. Six global geological datasets (GGDs) of carbonatite, zircon hafnium, kimberlite, metamorphism, monazite and zircon records are analyzed using Spearman’s correlation (ρs). Ranking the GGDs according to Spearman’s method allows them to be compared. Each GGD shows moderate to very strong correlations (0.5 < ρs < 0.9), with the metamorphism, monazite, zircon and zircon hafnium datasets displaying the most similarities. Each published supercontinent cyclicity (Sc 500 Myr, Sc 600 Myr, Sc 800 Myr and Sc acceleration) is then depicted according to its assembly timing. A second Spearman correlation performed with the four supercontinent cyclicities suggests that the Sc acceleration hypothesis best fits the geological archives (average ρs = 0.45), potentially supporting the supercontinent cycle as the first-order mechanism of plate tectonics evolution. Conversely, constant cyclicities result in weaker correlations (average ρs < 0.26), which could indicate significant decoupling of the geological archives and the supercontinent cycle. Moreover, Sc 600 surprisingly shows no correlation with the six GGDs (average ρs = 0.04). The implications for the supercontinent cycle and the limits of Spearman’s correlation are also discussed.

Catalytic Stability of S-1-(4-Hydroxyphenyl)-Ethanol Dehydrogenase from Aromatoleum aromaticum.

Derived from the denitrifying bacterium Aromatoleum aromaticum EbN1 (Azoarcus sp.), the enzyme S-1-(4-hydroxyphenyl)-ethanol dehydrogenase (S-HPED) belongs to the short-chain dehydrogenase/reductase family. Using research techniques like UV-Vis spectroscopy, dynamic light scattering, thermal-shift assay and HPLC, we investigated the catalytic and structural stability of S-HPED over a wide temperature range and within the pH range of 5.5 to 9.0 under storage and reaction conditions. The relationship between aggregation and inactivation of the enzyme in various pH environments was also examined and interpreted. At pH 9.0, where the enzyme exhibited no aggregation, we characterized thermally induced enzyme inactivation. Through isothermal and multitemperature analysis of inactivation data, we identified and confirmed the first-order inactivation mechanism under these pH conditions and determined the kinetic parameters of the inactivation process. Additionally, we report the positive impact of glucose as an enzyme stabilizer, which slows down the dynamics of S-HPED inactivation over a wide range of pH and temperature and limits enzyme aggregation. Besides characterizing the stability of S-HPED, the enzyme's catalytic activity and high stereospecificity for 10 prochiral carbonyl compounds were positively verified, thus expanding the spectrum of substrates reduced by S-HPED. Our research contributes to advancing knowledge about the biocatalytic potential of this catalyst.

Evaluation of ChatGPT and Gemini large language models for pharmacometrics with NONMEM.

To assess ChatGPT 4.0 (ChatGPT) and Gemini Ultra 1.0 (Gemini) large language models on NONMEM coding tasks relevant to pharmacometrics and clinical pharmacology. ChatGPT and Gemini were assessed on tasks mimicking real-world applications of NONMEM. The tasks ranged from providing a curriculum for learning NONMEM, an overview of NONMEM code structure to generating code. Prompts in lay language to elicit NONMEM code for a linear pharmacokinetic (PK) model with oral administration and a more complex model with two parallel first-order absorption mechanisms were investigated. Reproducibility and the impact of "temperature" hyperparameter settings were assessed. The code was reviewed by two NONMEM experts. ChatGPT and Gemini provided NONMEM curriculum structures combining foundational knowledge with advanced concepts (e.g., covariate modeling and Bayesian approaches) and practical skills including NONMEM code structure and syntax. ChatGPT provided an informative summary of the NONMEM control stream structure and outlined the key NONMEM Translator (NM-TRAN) records needed. ChatGPT and Gemini were able to generate code blocks for the NONMEM control stream from the lay language prompts for the two coding tasks. The control streams contained focal structural and syntax errors that required revision before they could be executed without errors and warnings. The code output from ChatGPT and Gemini was not reproducible, and varying the temperature hyperparameter did not reduce the errors and omissions substantively. Large language models may be useful in pharmacometrics for efficiently generating an initial coding template for modeling projects. However, the output can contain errors and omissions that require correction.

Further insights into steady three-dimensional MHD Sakiadis flows of radiating-reacting viscoelastic nanofluids via Wakif’s-Buongiorno and Maxwell’s models

AbstractKeeping in mind the stress relaxation tendency of many viscoelastic multi-phase flows (e.g., polymer solution flows and transport phenomena of red cell suspensions within blood media), the present research investigation intends principally to develop a realistic model for revealing properly the aspects of reacting-radiating Maxwell nanofluids during their laminar boundary layer flows in the steady regime over a horizontal impermeable surface under a transversal magnetic influence. For this purpose, the principal leading differential formulation is derived theoretically by linking Wakif’s-Buongiorno approach with Maxwell’s model. By invoking fundamentally the general boundary layer assumptions and the passive control strategy for the nanoparticles, the governing PDEs’ formulation is simplified accordingly and then stated properly for the case of the convective heating condition at the impermeable bi-stretching surface. By executing a feasible non-dimensionalization technique, the monitoring ODEs’ system is achieved successfully, whose solutions are presented precisely in different illustrative scenarios using Richardson’s extrapolation method. After carrying out successfully several validating tests, it is demonstrated that the weakly viscoelastic feature has generally a slight delaying effect on the nanofluid motion. This dynamical weakening can be reinforced more with the generation of thermal energy by intensifying the external magnetic field source. Additionally, these physical factors show an intensifying influence on the surface drag forces. However, a dropping impression is seen for the local heat transfer at the contact surface. Contrary to the broadening impact of the radiative heat transfer as well as the convective heating and thermophoresis mechanisms on the thermal and mass boundary layer regions, it is witnessed that the first-order chemical reaction mechanism and Brownian’s motion exhibit a shrinking impact on the mass boundary layer region.

Sustained-release nitrogen fertilizer delivery systems based on carboxymethyl cellulose-grafted polyacrylamide: Swelling and release kinetics

Sustained or controlled-release delivery systems can enhance functions such as nutrient usage; minimize soil contamination, and reduce the required fertilizer dose. This paper reports the development of a carboxymethyl cellulose-g-polyacrylamide copolymer (CMC-g-PAM) as a sustained and slow-release fertilizer carrier for urea. The developed copolymer was characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and thermo gravimetric analysis (TG). The grafting process increased the activation energy of CMC from 0.1521 to 0.5952 J/mol with a higher loading percentage of 72.140.85% using a 15% urea solution. The swelling ratio is significantly dependent on the pH. The maximum swelling ratio of 1199.58% at pH 9. However, Swelling follows a pseudo-first-order reaction with the maximum swelling ratio in a saline of 349.76%.The CMC-g-PAM copolymer loaded with urea exhibited sustained and slow release, with the maximum cumulative percentage of 69.12% at pH 9 and 38.94% in saline. Urea release from the CMC-g-PAM copolymer followed the first-order, Fickian, and biexponential biphasic release mechanisms. The release of the CMC-g-PAM copolymer loaded with urea is a complicated process governed by diffusion and a biphasic releasing profile.

Indications for an alternative breaking of symmetry in fracture-induced electromagnetic emissions recorded prior to the 2023 Mw7.8 and Mw7.5 Turkey Earthquakes

Several evidence has been reported corroborating the view that the MHz band fracture-induced electromagnetic emissions (FEME), also known as fracture-induced electromagnetic radiation (FEMR), which are detected prior to shallow main earthquakes (EQs) of moment magnitude Mw>5.5 with epicenters on land or near coastline, can be studied in analogy to a Z(2) spin system undergoing a second-order phase transition. Specifically, by analyzing MHz FEME/FEMR time series recorded prior to several earthquakes in the past >20 years, information has been extracted about the organization to critical state, the critical state itself, as well as for the step-by-step development of the spontaneous symmetry breaking (SSB) phenomenon. Using the “method of critical fluctuations” (MCF) and a recently proposed method for the wavelet-based detection of scaling behavior in noisy experimental data, we identified for the first time a different way of breaking the symmetry embedded in the MHz FEME/FEMR time series recorded by the hELlenic Seismo-ElectroMagnetics Network (ELSEM-Net) prior to the devastating (Mw=7.8 and Mw=7.5) EQs that occurred in south-east Turkey on 06/02/2023. Particularly, after the achievement of the critical state, indications were found that, although the underlying system started to break the symmetry according to the second-order phase transition mechanism (through SSB), SSB was not completed. Instead, the system seems to have changed symmetry and presented indications that the break of symmetry was finally achieved according to the first-order phase transition mechanism. Specifically, after the incomplete SSB, it was found to present tricritical behavior, followed by indications of triple degeneration of the order parameter fixed-point. This change of behavior observed in the MHz FEME/FEMR is a puzzling phenomenon for several reasons, which are discussed in detail, whereas suggestions are expressed as a first attempt for the possible explanation of the new findings.

Exploring novel mechanical metamaterials: Unravelling deformation mode coupling and size effects through second-order computational homogenisation

Architected materials and mechanical metamaterials are known for their unique macroscopic properties and complex behaviour that often defy conventional continuum mechanics. Therefore, in this contribution, a recent multi-scale second-order computational homogenisation method (Dos Santos et al., 2023) is employed to explore these materials under finite strains. The approach combines a second gradient continuum theory at the macro-scale and a representative volume element (RVE) with classical first-order continuum mechanics at the micro-scale. The Method of Multi-scale Virtual Power ensures a consistent scale transition. The predictive capability and applicability of the second-order computational strategy are evaluated through coupled multi-scale numerical simulations. These simulations involve two- and three-dimensional problems, with a strong focus on the development of novel metamaterials, while also accounting for diverse loading conditions, such as tension/compression-induced undulation, bending, and compression-induced torsion. Comparisons with first-order homogenisation and Direct Numerical Simulations validate the approach. Analysis of homogenised consistent tangents reveals valuable insights into macroscopic properties. Overall, the results highlight the capability of the second-order strategy to capture significant phenomena, including second-order deformation modes, coupling deformation mechanisms, and size effects.

Anthropogenic carbon pathways towards the North Atlantic interior revealed by Argo-O2, neural networks and back-calculations

The subpolar North Atlantic (SPNA) is a region of high anthropogenic CO2 (Cant) storage per unit area. Although the average Cant distribution is well documented in this region, the Cant pathways towards the ocean interior remain largely unresolved. We used observations from three Argo-O2 floats spanning 2013-2018 within the SPNA, combined with existing neural networks and back-calculations, to determine the Cant evolution along the float pathways from a quasi-lagrangian perspective. Our results show that Cant follows a stepwise deepening along its way through the SPNA. The upper subtropical waters have a stratified Cant distribution that homogenizes within the winter mixed layer by Subpolar Mode Water formation in the Iceland Basin. In the Irminger and Labrador Basins, the high-Cant footprint (> 55 μmol kg−1) is mixed down to 1400 and 1800 dbar, respectively, by deep winter convection. As a result, the maximum Cant concentration is diluted (<45 μmol kg−1). Our study highlights the role of water mass transformation as a first-order mechanism for Cant penetration into the ocean. It also demonstrates the potential of Argo-O2 observations, combined with existing methods, to obtain reliable Cant estimates, opening ways to study the oceanic Cant content at high spatio-temporal resolution.

Long-term X-Ray Outburst in the TeV-detected Blazar Mrk 501 in 2021–2022: Further Clues for the Emission and Unstable Processes

This paper presents the results of a detailed X-ray timing and spectral analysis of Mrk 501, which are based mainly on the Swift data obtained during 2021 February–2022 December. The source showed strongly enhanced X-ray activity, characterized by a long-term increase in the baseline 0.3–10 keV flux level superimposed by shorter-term flares on timescales of a few weeks to about 2 months. During some time intervals, Mrk 501 was the brightest blazar in the X-ray sky and, moreover, showed an intense intraday variability, which was sometimes detected within the exposures lasting a few hundred seconds. These instances were characterized by fractional variability amplitudes of 4%–18% and were mostly observed during short-term X-ray flares. The source exhibited extreme spectral properties with dominance of the spectral curvature, frequent occurrence of hard photon indices in the 0.3–10 keV and 0.3–300 GeV bands, and the peak of a synchrotron spectral energy distribution in the hard X-ray range. These properties demonstrate the importance of relativistic magnetic reconnection, first-order Fermi mechanism within the magnetic field of different confinement efficiencies, stochastic acceleration, and hadronic processes. The X-ray and γ-ray fluxes showed a log-normal distribution, which hints at the imprint of accretion disk instabilities on the blazar jet, as well as the possible presence of hadronic cascades and random fluctuations in the particle acceleration rate. The optical–UV and γ-ray variabilities showed a weak or absent correlation with the X-ray flaring activity, which is not consistent with simple leptonic models and requires more complex particle acceleration, emission, and variability scenarios.

Second-order multi-scale modelling of natural and architected materials in the presence of voids: Formulation and numerical implementation

This contribution proposes a second-order computational homogenisation formulation for natural and architected materials in the presence of voids. The macro-scale is described by a second gradient continuum theory in the finite strain regime, and the micro-scale is modelled by the concept of representative volume element (RVE) within the classical first-order continuum mechanics. The Method of Multi-scale Virtual Power is employed to link the two scales, ensuring a variationally consistent scale transition. Unlike the multi-scale model proposed by Rodrigues Lopes and Andrade Pires (2022), the developed formulation allows the consideration of voids in the RVE domain and boundary, which is critical for modelling cellular materials, lattice structures, and metamaterials, among others. This is achieved by defining the kinematical quantities only in the solid domain of the RVE and postulating a new homogenisation relation for the second-order gradient. The kinematic constraints are imposed on the RVE by the Lagrange multiplier method and particularised for minimal (lower bound), periodic and direct (upper bound) conditions. It is demonstrated that the homogenised macroscopic stress tensors can be expressed in terms of the Lagrange multipliers. The finite element method is adopted for the numerical solution of the micro and macro equilibrium. The Newton–Raphson scheme is employed to solve the non-linear systems of equations at both scales and the consistent macroscopic tangents required for the FE2 framework are derived. Several numerical examples of porous solids, lattice structures and metamaterials illustrate the consistency and applicability of the formulation for two and three-dimensional problems.

Temporal and Spatial Characteristics of Hard X-Ray Sources in a Flare Model with a Vertical Current Sheet

Abstract We analyzed changes in the height of the coronal hard X-ray (HXR) source for flares SOL2013-05-13T01:50 and SOL2013-05-13T15:51. Analysis of the Reuven Ramaty High Energy Solar Spectroscopic Imager data revealed the downward motion of the HXR source and the separation of the sources by energy and height. In the early stages of the flares, a negative correlation was found between the HXR source area in the corona and HXR flux. For the SOL2013-05-13T15:51 event, an increasing trend in the time delay spectra at the footpoints was obtained. For both events, the spectra of the time delays in the coronal HXR source showed a decreasing trend with energy in certain flare phases. To interpret the observed phenomena, we considered a flare model of collapsing traps and calculated the distribution functions of accelerated electrons along the magnetic loop using a nonstationary relativistic kinetic equation. This approach considers betatron and Fermi first-order acceleration mechanisms. The increasing trend of the time delay spectra at the footpoints was explained by the high mirror ratio in the magnetic loop and betatron acceleration mechanism. The observed features in the spatial and temporal behavior of the HXR sources, such as the negative correlation between the HXR source area and HXR flux, can be interpreted by the collapsing trap model.

Decolorization by Catalytic Ozonation USING Mn(II) Fe(II) and Fe(III)

The textile industry holds significant importance in Thailand. It has been estimated that 10-20% of dyes are lost during the dyeing process and subsequently released into wastewater. The high concentration of non-biodegradable substances in these wastewaters makes them challenging to treat using conventional methods. Therefore, this study aimed to assess the effectiveness of a catalytic ozonation process employing Mn(II), Fe(II), and Fe(III) for treating synthetic dye wastewater. The study also sought to optimize operational parameters such as pH and contact time. Both with and without catalytic ozonation, experiments were conducted in a batch reactor with a consistent ozone flow rate of 6 g/hr. Under the non-catalytic ozonation conditions, it was observed that more than 90% of decolorization occurred within 15 minutes at a pH of 9. The ozonation of the dye followed a first-order reaction mechanism at room temperature, with a rate constant (k) of 0.18 min-1. The catalytic ozonation used a concentration of 1.2 mM of Mn(II) was showed color removal of 90% in 8 min. For catalytic ozonation used Fe(II) and Fe(III) with concentrations of 0.6 mM showed color removal of 90% in 10 min. The highest rate constant (k) showed 0.29 min-1 for Mn(II) and 0.21 min-1 for Fe(II) and Fe(III). In conclusion, the study found that the inclusion of a catalyst substantially enhanced the degradation efficiency of the dye compared to ozonation without a catalyst.

Ethyl cellulose-based microcapsules of Citrus aurantifolia (Christm.) Swingle essential oil with an optimized emulsifier for antibacterial cosmetotextiles

Antibacterial microcapsules of Citrus aurantifolia (Christm.) Swingle essential oil (LOs) covered by ethyl cellulose biopolymer were prepared and applied to cotton fabric. The microencapsulation of the LOs was accomplished through a simple coacervation process, whereas the immobilization onto the cotton fabric was based on the pad dry method with citric acid as a binder. Optimization of the type and weight of the emulsifier was considered to result in the best properties of the microcapsules. Employing 1 g of tween-80, the best LO microcapsules were successfully obtained up to 46.7 ± 3.8% yield, with spherical morphology and a well-distributed size range of 0.5–2 μm. The oil content (OC) and encapsulation efficiency (EE) of the microcapsules were achieved at 95.4 ± 0.8% and 77.9 ± 6.6% correspondingly. According to Avrami's kinetic model, the release performance of the LOs microcapsules in 2 h was ruled by the first-order kinetic mechanism with the remaining LOs of 37.7%. The LO microcapsules were successfully immobilized onto cotton fabric with a % add-on of 20.1%. Upon a standard washing test, the attached LOs microcapsules demonstrated 5 cycles of resistance against normal washing, with a mass reduction of the microcapsules up to 52.2%. Further antibacterial assays showed that the cotton fabrics immobilized by the LOs microcapsules exhibited a high inhibition, especially towards Gram-negative bacteria E. coli and K. pneumoniae. Thus, it can be potentially developed for antibacterial functional textile.

Thermal Oxidative Degradation of Pure Cu2S and Industrial White Metal

The kinetics of the thermal oxidation of white metal and Cu2S have been studied by thermogravimetric analysis (TG), which was carried out under atmospheric oxidative conditions (O2 100%) with heating rates of 5, 10, 15 and 20 °C min−1. Each experiment was performed three times, the indicated values being the average of the three experiments. The experimental data were evaluated using isoconversional models based on the Arrhenius equation. The models are constructed using first-order mechanisms in the reactions and therefore, since most of them present adequate regression coefficients, it can be verified that order 1 is the most predominant order among the reactions found. In addition, the Kissinger–Akahira–Sunose model, which has the highest regression coefficient, is considered to be the most optimal. Similar behavior was recorded between Cu2S and white metal, as well as a similar regular increase in the apparent activation energy (Ea) of 10–30 kJ mol−1 for both materials. The reactions that took place during the oxidation of white metal and Cu2S were determined using a computational model based on thermodynamics developed in this work. The identified phases include CuSO4, Cu2SO4, Cu2O, CuO, CuO·CuSO4.

Kinetics of free fatty acids esterification in waste frying oil using novel carbon-based acid heterogeneous catalyst derived from Amazonian Açaí seeds – Role of experimental conditions on a simpler pseudo first-order reaction mechanism

This study reports the kinetics of free fatty acids esterification in waste frying oil, based on a simpler non-conventional pseudo first-order homogeneous reaction mechanism using a highly-efficient acid heterogeneous catalyst derived from seeds of Açaí (Euterpe oleracea Mart.), subjected to changes in temperature, catalyst dosage, MeOH:Oil ratio, and stirring speed. Statistical analyses revealed significant effects all four conditions (p < .05) on the reaction's apparent rate constant (k1) over their different pre-defined levels. Reaction mechanism was inferred to be fundamentally acid ionic exchanges with the oil/water film on catalyst's surface, neglecting kinetically controlled liquid-to-liquid splitting and autocatalyzed esterification.

Free Electron Dynamics and Intrinsic Mobility in Ga2O3 Revealed by Transient Terahertz Conductivity

Here, we investigate the photoconductivity of gallium oxide thin films at different temperatures using time-resolved terahertz spectroscopy. The photogenerated electrons in the conduction band show a monoexponential decay, implying a first-order electron depopulation mechanism. The electron lifetime increases with rising temperature, and this trend coincides with the temperature dependence of the electron mobility rather than diffusion coefficient, suggesting that electron-hole recombination is determined by directional electron drift instead of random diffusion. The electron mobilities extracted from the transient terahertz conductivity are substantially greater than the previously reported Hall mobilities over a wide temperature range, and this is probably because the electron drift in response to the terahertz field is immune from scattering with macroscopic defects. Thus, the mobilities measured here may represent the intrinsic limit of the electron mobility in gallium oxide crystals. Our finding suggests that the current Hall mobility in this wide bandgap semiconductor is still far below the limit, and the long-range electron transport can be further increased by improving the crystalline quality.

Graph context-attention network via low and high order aggregation

Graph attention networks (GATs) have been shown effectively for representation learning. However, existing GATs only employ the first-order attention mechanism and thus fail to fully exploit and learn node’s contextual feature representations. To address this issue, we propose a novel Graph Context-Attention Network (GCAN) via low and high order aggregation for representation learning. The proposed model fully exploits both low-order and high-order information of nodes for representation learning by employing high-order attention mechanism and adversary regularization constraints. The main benefit of the proposed method is that it can effectively capture the discriminative feature differences among node representations while enhancing the diversity and richness of node features. Thus it can alleviate the issue of over-smoothing in the network learning. We perform extensive experiments on nine datasets and the experimental results demonstrate the effectiveness and better performance of our approach.

The metabolic processes of selected pesticides and their influence on plant metabolism. A case study of two field-cultivated wheat varieties

Pesticides that are absorbed by plants undergo biotransformation and might affect plant metabolic processes. The metabolisms of two cultivated wheat varieties, Fidelius and Tobak, treated with commercially available fungicides (fluodioxonil, fluxapyroxad, and triticonazole) and herbicides (diflufenican, florasulam, and penoxsulam) were studied under field conditions. The results provide novel insights regarding the effects of these pesticides on plant metabolic processes. Plants (roots and shoots) were sampled six times during the six-week experiment. Pesticides and pesticide metabolites were identified using GC–MS/MS, LC–MS/MS, and LC–HRMS, while root and shoot metabolic fingerprints were determined using non-targeted analysis. Fungicide dissipation kinetics were analyzed according to the quadratic mechanism (R2: 0.8522–0.9164) for Fidelius roots, and zero-order for Tobak roots (R2: 0.8455–0.9194); shoot dissipation kinetics were analyzed according to first-order (R2: 0.9593–0.9807) and quadratic (R2: 0.8415–0.9487) mechanisms for Fidelius and Tobak, respectively. The fungicide degradation kinetics were different compared to reported literature values, most likely due to differences in pesticide application methods. The following metabolites were respectively identified in shoot extracts of both wheat varieties for fluxapyroxad, triticonazole, and penoxsulam: 3-(difluoromethyl)-N-(3',4',5'-trifluorobiphenyl-2-yl)-1H pyrazole-4-carboxamide, 2-chloro-5-{(E)-[2-hydroxy-3,3-dimethyl-2-(1H-1,2,4-triazol-1-ylmethyl)-cyclopentylidene]-methyl}phenol, and N-(5,8-dimethoxy[1,2,4]triazolo[1,5-c]pyrimidin-2-yl)-2,4-dihydroxy-6 (trifluoromethyl)benzene sulfonamide. Metabolite dissipation kinetics varied depending on the wheat variety. These compounds were more persistent than parent compounds. Despite having the same cultivation conditions, the two wheat varieties varied in their metabolic fingerprints. The study revealed that pesticide metabolism has a greater dependence on plant variety and method of administration compared to the physicochemical properties of the active substance. This highlights the necessity of conducting research on pesticide metabolism under field conditions.