Time Scale Research Articles

Investigating the Restricted Dynamical Environment in and Around Aβ Peptide Oligomers in Aqueous Ionic Liquid Solutions.

It is widely believed that the aggregation of amyloid β (Aβ) peptides into soluble oligomers is the root cause behind Alzheimer's disease. In this study, we have performed room-temperature molecular dynamics (MD) simulations of aggregated Aβ oligomers of different sizes (pentamer (O(5)), decamer (O(10)), and hexadecamer (O(16))) in binary aqueous solutions containing 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]) ionic liquid (IL). Investigations have been carried out to obtain a microscopic understanding of the effects of the IL on the dynamic environment around the exterior surfaces and within the confined nanocores of the oligomers. The calculations revealed that in contrast to nearly uniform dynamics near the exterior surface, heterogeneous structural distortions of oligomers of varying sizes and nonuniform distributions of water and IL components within their core volumes modify the core dynamics in a differential manner. It is demonstrated that increasingly restricted mobility of water and IL components is the origin behind the longer time scale of dynamic heterogeneity in and around the oligomers. Importantly, due to the equivalent nondirectional nature of the B-F bonds, BF4- anions are found to reorient on a time scale faster than that of water molecules. Further, the structural relaxation of protein-anion (PA) hydrogen bonds around the oligomers has been found to be correlated with sluggish translational motions of the anions but anticorrelated with their reorientational time scale. In addition, it is quantified that compared to the pure aqueous medium, strengthening of protein-water (PW) hydrogen bonds in the presence of the IL leads to their longer lifetimes.

Spatiotemporal Spectroscopy of Fast Excited-State Diffusion in 2D Covalent Organic Framework Thin Films.

Covalent organic frameworks (COFs), crystalline and porous conjugated structures, are of great interest for sustainable energy applications. Organic building blocks in COFs with suitable electronic properties can feature strong optical absorption, whereas the extended crystalline network can establish a band structure enabling long-range coherent transport. This peculiar combination of both molecular and solid-state materials properties makes COFs an interesting platform to study and ultimately utilize photoexcited charge carrier diffusion. Herein, we investigated the charge carrier diffusion in a two-dimensional COF thin film generated through condensation of the building blocks benzodithiophene-dialdehyde (BDT) and N,N,N',N'-tetra(4-aminophenyl)benzene-1,4-diamine (W). We visualized the spatiotemporal evolution of photogenerated excited states in the 2D WBDT COF thin film using remote-detected time-resolved PL measurements (RDTR PL). Combined with optical pump terahertz probe (OPTP) studies, we identified two diffusive species dominating the process at different time scales. Initially, short-lived free charge carriers diffuse almost temperature-independently before relaxing into bound states at a rate of 0.7 ps-1. Supported by theoretical simulations, these long-lived bound states were identified as excitons. We directly accessed the lateral exciton diffusion within the oriented and crystalline film, revealing remarkably high diffusion coefficients of up to 4 cm2 s-1 (200 K) and diffusion lengths of several hundreds of nanometers and across grain boundaries. Temperature-dependent exciton transport analysis showed contributions from both incoherent hopping and coherent band-like transport. In the transport model developed based on these findings, we discuss the complex impact of order and disorder on charge carrier diffusion within the WBDT COF thin film.

Analysis of the Propagation Characteristics of Meteorological Drought to Hydrological Drought and Their Joint Effects on Low-Flow Drought Variability in the Oum Er Rbia Watershed, Morocco

Analysis of the temporal relationship between meteorological drought and hydrological drought is crucial in monitoring water resource availability. This study examined the linear and lagged relationships of the spread of meteorological drought to hydrological drought and their joint effects on low-flow drought variability in the Oum Er-Rbia (OER) watershed. To this end, random forest (RF) model and statistical methods were used to study the characteristics of the temporal relationships between meteorological and hydrological drought indices at monthly, seasonal, and annual scales. The various analyses revealed that the relationship between hydrological and meteorological drought is mainly a function of the time scale considered, the choice of indices to describe each type of drought and the season considered. The hydrological drought of surface water and snow cover is synchronized with the meteorological drought at the monthly, seasonal, and annual scales. In contrast, the transition from meteorological drought to groundwater drought has a lag time of 1 month and is statistically significant up to t − 5 and t + 5, i.e., 6 months. The linear correlation between the annual rainfall deficit and the monthly groundwater storage index was the lowest (0.15) in December and the highest (0.83) in March. This suggests a seasonal response of groundwater drought to the cumulative effects of precipitation deficits. The RF analysis highlighted the importance of the cumulative characteristics of meteorological drought regarding the severity of low-flow drought. The meteorological drought indices at longer time scales have a greater impact on the severity of low-flow drought, with a contribution of approximately 10% per index. However, the relative contributions of meteorological factors and hydrological indices rarely exceed 5%. Thus, by exploring for the first time the complex interactions among the severity of low-flow regimes, meteorological and hydrological drought indices and meteorological factors, this study provides a new perspective for understanding the characteristics of propagation from meteorological to severe hydrological drought.

Complexities in post-wildfire governance: lessons from Colorado’s 2020 wildfires

BackgroundThe increasing size and severity of western U.S. wildfires in recent years has generated greater attention towards post-wildfire response and recovery. Post-fire governance requires coordinating response and recovery capacities across jurisdictions, landscapes, and time scales. The presence of wildfire on federal public lands necessitates federal agency involvement in both suppression and recovery efforts, and program coordination with lower levels of government and non-governmental organizations. Using semi-structured interviews, we investigated experiences of leaders across the governance system with federal post-fire policies and programs following the record-breaking Cameron Peak and East Troublesome wildfires in the state of Colorado.ResultsOur research found that persistent administrative and coordination challenges exist within and among federal agencies in the post-fire response and recovery space. Challenges included cross-jurisdictional coordination of key emergency response programs, program rules that affect post-fire project timing and effectiveness, the absence of a formal federal post-fire response strategy, and program funding issues. These factors revealed and exacerbated scale mismatches between existing agency capacities and the post-fire landscapes that result from unprecedentedly longer, larger, and more severe wildfires occurring in the western USA. Non-federal and non-governmental organizations were instrumental in overcoming these challenges through coordinating response and recovery efforts across both federal and private lands. To improve the federal post-fire response capacity, study participants stressed the importance of broader cross-jurisdictional use of federal resources, longer timeframes for recovery activities, and reforming the federal funding process.ConclusionsOur findings revealed a persistence of post-fire coordination and funding issues within federal land management agencies, and current agency capacities remain insensitive to the scale of twenty-first-century post-wildfire settings. Addressing the mismatches between existing agency resources and the spatial and temporal scale complexities of post-fire environments will require broader federal support for existing programs along with re-envisioning the overall approach to the post-fire response and recovery process.

Revisiting the Inconsistent Influence of El Niño–Southern Oscillation on the Equatorial Atlantic

Abstract The impact of El Niño–Southern Oscillation (ENSO) on the equatorial Atlantic zonal mode (AZM) is investigated using two atmospheric reanalysis products and 44 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). While the impact of ENSO on equatorial Atlantic SST is inconsistent, as previously reported, there is a very robust influence of decaying ENSO events in boreal spring on the contemporaneous surface zonal winds over the equatorial Atlantic, with El Niño events associated with anomalous easterlies that cool the equatorial Atlantic. This dynamic impact is counteracted by a thermodynamic impact, in which El Niño events cause changes in surface heat fluxes that lead to warming over the tropical Atlantic. The thermodynamic influence is active throughout the life cycle of the ENSO event, but the dynamic influence is highly seasonal with a pronounced peak in boreal spring. Thus, a quickly decaying El Niño event will lead to warming, while a slowly decaying event will lead to cooling in the equatorial Atlantic. The ENSO–AZM relation is further complicated by partially independent Atlantic variability, in particular that associated with the South Atlantic subtropical dipole (SASD). Prediction experiments with a simple linear regression model support the role of the SASD as an AZM precursor. Many CMIP6 models show skillful predictions of the June–August AZM based on SST indices in the preceding December–February, with correlations above 0.5. When predictions are restricted to ENSO years, even more models exceed this threshold, but skill in the reanalyses remains relatively low, possibly due to insufficient training data. Significance Statement El Niño is the strongest climate signal on interannual time scales. Its influence on the equatorial Atlantic, however, is surprisingly inconsistent. Here, we show, using an ensemble of climate models and observation-based data, that El Niño has a very robust influence on equatorial Atlantic surface winds, but only in boreal spring. This leads to a large difference in how El Niño events influence the equatorial Atlantic, based on how quickly they decay in boreal spring. We also find that variability in the South Atlantic, which is partly independent of El Niño, has a strong influence on the equatorial Atlantic, supporting the result of previous studies. These findings suggest that the predictability of equatorial Atlantic temperature anomalies may be higher than previously thought.

Insights into Cloud Albedo Biases from a Cloud-Controlling Factor Framework

Abstract A long-standing and pervasive problem in climate modeling is the proper representation of cloud albedo over the Southern Ocean (SO). In this study, we investigate the causes of SO cloud albedo biases using phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations and a cloud-controlling factor approach on daily time scales. Cloud albedo, computed from upwelling and downwelling shortwave radiation at the surface and top of the atmosphere, is averaged into bins of vertical velocity, surface wind, and sea surface temperature. The performance of 15 models in both atmosphere-only and ocean-coupled configurations is evaluated against Clouds and the Earth’s Radiant Energy System (CERES) satellite retrievals in combination with ERA5 reanalysis for the 2000–14 period. We find that the SO cloud biases maximize in the 50°–65° oceanic band and that models tend to underestimate SO cloud reflectivity for cold conditions and weak surface winds. In turn, descent (ascent) conditions are consistently underestimated (overestimated) across models for both hemispheres in the same latitude band. With a very similar approach, we evaluate how models represent the observed cloud albedo hemispheric asymmetry over oceans, which also maximizes in the 50°–65° band. The sign of the asymmetry is consistently predicted by all models, many of which also predict a similar magnitude to observations. However, this is also a consequence of compensating global biases as individually most models tend to either overpredict or underpredict cloud albedo in both hemispheres. We propose that surface temperatures less than 4°C are important in explaining SO bias in cloud albedo and that they also partly explain the observed hemispheric asymmetry. Further, we hypothesize that the 4°C threshold sets a hemispheric asymmetry in cloud phase.

WeTICA: A directed search weighted ensemble based enhanced sampling method to estimate rare event kinetics in a reduced dimensional space.

Estimating rare event kinetics from molecular dynamics simulations is a non-trivial task despite the great advances in enhanced sampling methods. Weighted Ensemble (WE) simulation, a special class of enhanced sampling techniques, offers a way to directly calculate kinetic rate constants from biased trajectories without the need to modify the underlying energy landscape using bias potentials. Conventional WE algorithms use different binning schemes to partition the collective variable (CV) space separating the two metastable states of interest. In this work, we have developed a new "binless" WE simulation algorithm to bypass the hurdles of optimizing binning procedures. Our proposed protocol (WeTICA) uses a low-dimensional CV space to drive the WE simulation toward the specified target state. We have applied this new algorithm to recover the unfolding kinetics of three proteins: (A) TC5b Trp-cage mutant, (B) TC10b Trp-cage mutant, and (C) Protein G, with unfolding times spanning the range between 3and40μs using projections along predefined fixed Time-lagged Independent Component Analysis (TICA) eigenvectors as CVs. Calculated unfolding times converge to the reported values with good accuracy with more than one order of magnitude less cumulative WE simulation time than the unfolding time scales with or without a priori knowledge of the CVs that can capture unfolding. Our algorithm can be used with other linear CVs, not limited to TICA. Moreover, the new walker selection criteria for resampling employed in this algorithm can be used on more sophisticated nonlinear CV space for further improvements of binless WE methods.

Evaluation of Nanomagnetite–Biochar Composite for BTA Removal

In this study, the removal of benzotriazole (BTA), a pervasive aquatic contaminant widely used for its anti-corrosion, UV-stabilizing, and antioxidant properties, by nanomagnetite, biochar, and nanomagnetite–biochar composite is investigated. Nanomagnetite and nanomagnetite–biochar composite were synthesized under anoxic conditions and tested for BTA removal efficiency at neutral pH under both oxic and anoxic conditions at different time scales. Within the short time scale (up to 8 h), the removal of BTA by nanomagnetite–biochar composite was shown to be due to BTA deprotonation by the nanomagnetite surface. Through proton liberation, Fe²⁺ is released in accordance with the reaction Fe₃O₄ + 2H⁺ → Fe₂O₃ + Fe²⁺ + H₂O, which likely influences BTA complexation and its possible redox degradation. On the longer time scale, biochar achieved higher removal efficiency: 50% BTA removed within 48 h, due to formation of a ternary complex with surface Ca2+ ions, or 75% BTA removed after HCl biochar acid wash followed by Ca2+ surface saturation. As BTA presents significant environmental risks due to its extensive industrial applications, the present study offers critical insights into the mechanisms of BTA removal by nanomagnetite–biochar composite, and highlights the potential of such materials for water treatment applications.

Application of SWAT Model in Assessing Impacts of FMNR on Water Conservation in Ndabibi Central Rift, Kenya

The Ndabibi watershed is predominantly agricultural that impacts its hydrological functions and water balance. This manifest through reduced watershed sponge effect, increased surface runoff during wet season and decreased surface runoff during the dry season, a situation that can be reversed by Farmer Managed Natural Regeneration (FMNR). FMNR is a conservation technique where trees/shrubs/ and other woody plants are allowed to grow naturally with minimal management by a farmer. Its application increases vegetation cover thereby reducing surface runoff. This study sought to establish the impact of FMNR on water conservation. The impact of this technique on surface runoff was quantified using SWAT (Soil and Water Assessment Tools) model. The watershed is ungauged and relied on regionalization with an assumed adoption of 20% FMNR in the watershed. The SWAT model under FMNR was calibrated with coefficient of variation (R2) of 0.95 for 20% and Nash-Sutcliffe of 0.88 on monthly time scale. The monthly streamflow analysis showed that there is a significant change in surface runoff ranging from -21.2% to 24.07% during the wet and dry seasons respectively. The study concludes that there is significant benefit of FMNR in regulating water balance in a given watershed and recommends its widespread adoption.

Tracking Cholesterol Flip-Flop in Mammalian Plasma Membrane through Coarse-Grained Molecular Dynamics Simulations.

Plasma membrane (PM) simulations at longer length and time scales at nearly atomistic resolution can provide invaluable insights into cell signaling, apoptosis, lipid trafficking, and lipid raft formation. We propose a coarse-grained (CG) model of a mammalian PM considering major lipid head groups distributed asymmetrically across the membrane bilayer and validate the model against bilayer structural properties from atomistic simulation. Using the proposed CG model, we identify a recurring pattern in the passive collective cholesterol transbilayer motion and study the individual cholesterol flip-flop events and associated pathways along with lateral ordering in the bilayer during a flip-flop event. We identify two discrete cholesterol flip-flop pathways: (i) a systematic rototranslational pathway and (ii) intraleaflet inversion followed by interleaflet translation (or reverse). We observe a periodic cholesterol enrichment in the exoplasmic leaflet of the PM bilayer and examine the underlying cholesterol-lipid affinities. We observe closer association between cholesterol and palmitoylsphingomyelin (PSM) lipid, relative to other lipids, and conclude that the cholesterol enrichment in the exoplasmic leaflet can be attributed to higher PSM content in that leaflet, together leading to formation of short-lived PSM-cholesterol-rich domains.

Existence of Solutions for a Class of Volterra Integral Equations on Time Scales

ABSTRACTIn this paper, we investigate a class of Volterra integral equations for existence of global classical solutions. We give conditions under which the considered equations have at least one and at least two classical solutions. To prove our main results, we propose a new approach based upon recent theoretical results. More precisely, we give a suitable integral representation of the solutions of the considered Volterra integral equation. Then, we construct two operators for which any fixed point of their sum is a solution of the considered Volterra integral equation.

Exceptionally large fluctuations in orientational order: The lessons of large-deviation theory for liquid crystalline systems.

How condensed-matter simulations depend on the number of molecules being simulated (N) is sometimes itself a valuable piece of information. Liquid crystals provide a case in point. Light scattering and 2d-IR experiments on isotropic-phase samples display increasingly large orientational fluctuations ("pseudo-nematic domains") as the samples approach their nematic phase. The growing length scale of those locally ordered domains is readily seen in simulation as an ever-slower convergence of the distribution of orientational order parameters with N. But the rare-event character and exceptionally slow time scales of the largest fluctuations make them difficult to sample accurately. We show in this paper how taking a large-deviation-theory perspective enables us to leverage simulation-derived information more effectively. A key insight of the theory is that finding quantities such as orientational order parameters (extensive variables) is completely equivalent to deducing the conjugate (intensive) thermodynamic field required to equilibrate that amount of order-and that knowing the relationship between the two (the "equation of state") can easily be turned into knowing the relative free energy of that degree of order. A variety of well-known thermodynamic integration strategies are already founded on this idea, but instead of applying an artificially imposed external field, we use a priori statistical mechanical insights into the small and large-field limits to construct a simulation-guided, interpolated, equation of state. The free energies that result mostly need information from the most probable configurations, making the simulation process far more efficient than waiting for (or artificially generating) large fluctuations.

Enhanced Efficiency of Anionic Guerbet-Type Amino Acid Surfactants.

This study investigates the surfactant properties and efficiency of linear and Guerbet-type amino acid surfactants. Utilizing a Wilhelmy plate method, we assessed the colloidal efficiency of these surfactants, with the lowest observed critical micelle concentration at 0.046 mmol L-1, significantly reducing surface tension to as low as 25.1 mN·m-1. Furthermore, the self-diffusion coefficients of the various surfactants have been determined through 1H pulsed-field gradient nuclear magnetic resonance diffusion-ordered spectroscopy. The self-diffusion coefficients are linked to the surface tension reduction as a function of concentration to determine the characteristic time scale of diffusion. In this work, the characteristic time scale of diffusion of a series of surfactants was calculated to investigate the interfacial coverage efficiency. Our findings indicate an inverse relationship between the characteristic time scale of diffusion and critical micelle concentrations across surfactants with hydrocarbon tail lengths of 8-22 carbons. Shorter tails correspond to lower colloidal efficiencies, but rapid surface tension reduction, resulting in the characteristic time scale of diffusion values ranging from 120 ns to 2.15 s. This property is crucial for applications requiring rapid action, such as enhancing aerosol efficiency, improving dispersion, and wetting materials in products.

Temporal trends of community and climate changes in the anthropocene: 21-year dynamics of four major functional groups in a rocky intertidal habitat along the Pacific coast of Japan

The influence of climate change on marine organism abundance has rarely been assessed (1) at the functional-group level; (2) simultaneously in major functional groups within the same ecosystem; (3) for >10 years; and (4) at metapopulation/community scales. A study simultaneously addressing these gaps would greatly enhance our understanding of the influence of climate change on marine ecosystems. Here, we analyzed 21 years of abundance data at the functional-group and species levels on a regional scale for four major functional groups (benthic algae, sessile animals, herbivorous benthos, and carnivorous benthos) in a rocky intertidal habitat along the northeastern Pacific coast of Japan. We aimed to examine the 21-year trends in regional abundance at both functional-group and species levels, plus their driving mechanisms and their dependence on species properties (thermal niche, calcification status, and vertical niche). Significant temporal trends in abundance were detected at functional-group levels for benthic algae (increasing) and herbivores and carnivores (both decreasing); they followed the temporal population trends of the dominant species. At species level, the metapopulation size of 12 of 31 species were increasing and 4 of those were decreasing, depending on the thermal niche and species calcification status. At both functional-group and species levels, temporal trends in abundance are caused by the direct or indirect influence of warming and ocean acidification. Comparing these results with community responses to marine heat waves in the same study area offered two implications: (1) long-term ecosystem changes associated with global warming will be unpredictable from the community response to marine heat waves, possibly owing to a lack of knowledge of the influence of calcifying status on species’ responses to climate change; and (2) thermal niches contribute greatly to predictions of the influence of warming on population size, regardless of the time scale.

Generalization of some inequalities using Lidstone interpolation via diamond integrals

In present paper, several inequalities involving Csisz´ar divergence are established by utilizing diamond integrals and Lidstone interpolation polynomials. Consequently, new and generalized inequalities are yields. The functions involved in these inequalities are higher order convex functions. Inequalities involving Shannon entropy, Kullback-Leibler discrimination, triangle distance and Jeffrey’s distance, are studied as particular instances with the help of specially chosen convex functions. The main findings are also discussed for some special time scales (both discrete and continuous). Many existing results are also obtained which established the link with existing literature.

Past hydro‐pedological events and trend reflected in the Mid–Late Holocene alluvial record of the Middle Rhône Valley and tributaries: A new reference for South East France

ABSTRACTThis paper proposes a new approach to quantitative geomorphology and paleopedology in the mid‐Rhône valley (MRV) based on a compilation of geomorphological metadata from 25 tributaries of the Rhône river and subordinate floodbasins, including 51 geomorphological and paleopedological sites. This study compares two types of hydrogeomorphological data formalization: a temporal similarities analysis between paleosols and fluvial aggradation of sub‐basins, and a quantitative analysis by summed probability distributions comparing floodplain stability and activity phases in cumulative density functions of categorized 14C and chronocultural dates. Alluvial chronologies at centennial to millennial time scales, coinciding with a modification in sedimentation rate, or river style, demonstrate temporal and spatial patterning of MRV alluviation, pedogenesis and erosion across the western Prealpine region, with detection of 24 main Holocene alternative periods (activity versus stability). To explore possible large‐scale hydroclimatic teleconnections, the Holocene MRV results are aligned, and correlations are made, with those of a range of paleohydrological proxy studies from all Rhône drainage basins, Western Europe and the Mediterranean. The MRV rivers respond to the majority of Holocene rapid climatic changes and from 4000/3000 cal a bp to an accelerated sediment delivery and torrentiality from slopes and headwaters, which results in the development of sedimentary cascades from upstream to downstream in the Rhône valley to the delta (the main drivers are discussed in detail in in a companion paper to follow).

Open-boundary molecular dynamics of ultrasound using supramolecular water models.

Ultrasound can be used to manipulate protein function and activity, as well as for targeted drug delivery, making it a powerful diagnostic and therapeutic modality with wide applications in sonochemistry, nanotechnology, and engineering. However, a general particle-based approach to ultrasound modeling remains challenging due to the significant disparity between characteristic time scales governing ultrasound propagation. In this study, we use open-boundary molecular dynamics to simulate ultrasound waves in liquid water under ambient conditions by employing supramolecular water models, i.e., the Martini 3, dissipative particle dynamics, and many-body dissipative particle dynamics models. We demonstrate that our approach successfully reproduces the solution of the traveling wave equation and captures the velocity dispersion characteristic of high-frequency ultrasound waves.

Investigating Oscillations in Higher-Order Half-Linear Dynamic Equations on Time Scales

This study presents novel and generalizable sufficient conditions for determining the oscillatory behavior of solutions to higher-order half-linear neutral delay dynamic equations on time scales. Utilizing the Riccati transformation technique in combination with Taylor monomials, we derive new and comprehensive oscillation criteria that cover a wide range of cases, including super-linear, half-linear, and sublinear equations. These results extend and improve upon existing oscillation criteria found in the literature by introducing more general conditions and providing a broader applicability to different types of dynamic equations. Furthermore, the study highlights the role of symmetry in the underlying equations, demonstrating how symmetry properties can be leveraged to simplify the analysis and provide additional insights into oscillatory behavior. To demonstrate the practical relevance of our findings, we include illustrative examples that show how these new criteria, along with symmetry-based perspectives, can be effectively applied to various time scales.

Nanoscale Magnetic Ordering Dynamics in a High Curie Temperature Ferromagnet.

Thermally driven transitions between ferromagnetic and paramagnetic phases are characterized by critical behavior with divergent susceptibilities, long-range correlations, and spin dynamics that can span kHz to GHz scales as the material approaches the critical temperature Tc, but it has proven technically challenging to probe the relevant length and time scales with most conventional measurement techniques. In this study, we employ scanning nitrogen-vacancy center based magnetometry and relaxometry to reveal the critical behavior of a high-Tc ferromagnetic oxide near its Curie temperature. Cluster analysis of the measured temperature-dependent nanoscale magnetic textures points to a 3D universality class with a correlation length that diverges near Tc. Meanwhile, the temperature-dependent spin dynamics, measured through all optical relaxometry suggest that the phase transition is in the XY universality class. Our results capture both static and dynamic aspects of critical behavior, providing insights into universal properties that govern phase transitions in magnetic materials.

A Vegetable-Price Forecasting Method Based on Mixture of Experts

The accurate forecasting of vegetable prices is crucial for policy formulation, market decisions, and agricultural market stability. Traditional time-series models often require manual parameter tuning and struggle to effectively handle the complex non-linear characteristics of vegetable price data, limiting their predictive accuracy. This study conducts a comprehensive analysis of the performance of traditional methods, deep learning approaches, and cutting-edge large language models in vegetable-price forecasting using multiple predictive performance metrics. Experimental results demonstrate that large language models generally outperform other methods, but do not have consistent performance for all kinds of vegetables across different time scales. As a result, we propose a novel vegetable-price forecasting method based on mixture of expert models (VPF-MoE), which combines the strengths of large language models and deep learning methods. Different from the traditional single model prediction method, VPF-MoE can dynamically adapt to the characteristics of different vegetable types, dynamically select the best prediction method, and significantly improve the accuracy and robustness of the prediction. In addition, we optimized the application of large language models in vegetable-price forecasting, offering a new technological pathway for vegetable-price prediction.