Turbulence of the bureaucratic environment as a result of the efficiency of the public sector budget in the Regional Secretariat of South Buton Regency. The importance of this research lies in the fact that budget efficiency is not just a fiscal instrument, but also a source of environmental turbulence that has direct implications for the stability and performance of regional bureaucracies. To answer these problems, this study uses a qualitative approach based on the theory of bureaucratic environmental turbulence. Data was collected through in-depth interviews, observations, and documentation, then analyzed qualitatively through the process of reduction, presentation, and a conclusion drawn. The results of the study show that the turbulence of the bureaucratic environment is driven by budget efficiency, which is characterized by increasing economic policy uncertainty, political pressure, public and media demands, and regional fiscal limitations. This turbulence forces the bureaucracy to make rapid adaptations that are not always followed by structural readiness and organizational capacity

Abstract Understanding thermalization dynamics is a fundamental goal of statistical physics. Recently, the wave turbulence (WT) theory has been applied widely to predict the scaling of thermalization times in ideal nonlinear lattices, yet its relevance to real materials is unclear. In this work, we investigate the thermalization dynamics of out-of-plane flexural modes in monolayer graphene with periodic boundary condition, assessing the applicability of the WT theory to this realistic lattice with complex interatomic interactions. The WT theory predicts that, within the weakly nonlinear regime, the thermalization time T eq scales with the specfic energy ε as T eq ∝ ε -2 in the thermodynamic limit, governed by four-wave resonances. Simulations of large graphene sheets confirm this scaling and show data collapse when the time is rescaled by ε -2 . For small systems, the sparsity of discrete wave vectors in the Brillouin zone suppress low-order resonances, leading to steeper scaling consistent with higher-order multi-wave processes. In the strong nonlinear regime, when frequency broadening exceeds the spacing between neighboring modes, the Chirikov resonance mechanism sets in, and an alternative scaling law for thermalization emerges. The critical energy for Chirikov overlap decreases with increasing system size, exhibiting a power-law trend. These results extend the WT theory to a structurally complex, experimentally relevant material and clarify how the order of resonant wave-wave interaction, finite-size constraints, and the effects of strong nonlinearity control thermalization dynamics.

The intensification of regulations on greenhouse gas emissions and pollutants has underscored the necessity for advanced injector concepts that ensure fuel flexibility and scalability, addressing critical demands within the thermochemical energy conversion sector. An additively manufactured µ-slit injector is proposed and evaluated across a wide range of operating conditions, including variations in jet velocity, fuel loading, air preheating temperature, and fuel type. Detached fuel film dynamics are analysed using machine learning-based object detection, revealing reduced film length with increasing jet velocity and decreasing mass flow rate, ensuring uniform radial distribution. Phase Doppler interferometry confirms the production of fine droplets, with an average diameter of 20 µm, inherently generated by the µ-scale fuel outlet design while maintaining a low pressure drop. Combustion performance, assessed via OH * -chemiluminescence for H 2 , CH 4 , ethanol, and Jet A1, shows excellent stability for H 2 across both low- and high-momentum jet regimes, attributed to enhanced turbulent mixing driven by the high density ratio. In contrast, CH 4 and Jet A1 exhibit similar lift-off trends. Ethanol and Jet A1 display significant pressure drop increases at high preheating condition, highlighting pre-vapourisation effects. Additionally, a correlation for gaseous fuels between the pressure drop and fluid property ratios is established, consistent with turbulent flow theory, and further extended by incorporating the injector discharge coefficient and compressibility effects. These results demonstrate that the µ-slit injector seamlessly accommodates both gaseous and liquid fuels, delivering exceptional fuel flexibility and scalability, and positioning it as a promising candidate for industrial burners, micro-gas turbines, and hybrid aero-engine systems.

The present paper demonstrates that the weak turbulence closure theory of kinetic plasma turbulence is equivalent to the quasi-normal Markovian (QNM) closure theory developed in the fluid turbulence context. While the plasma weak turbulence theory, largely formulated in the former Soviet plasma physics community, adopted the description “weak” to mark the distinction from a phenomenological theory of Langmuir wave collapse, which is known as the “strong” turbulence theory, it was nevertheless recognized in the fluid turbulence literature that the plasma weak turbulence theory and the QNM closure theory are conceptually equivalent. In spite of this, however, the actual demonstration of the equivalence between the two approaches has not been carried out in the literature. The present paper achieves such a concrete demonstration on the basis of a framework in which the plasma is considered unmagnetized and primarily interacting through the electrostatic force. This is done for the sake of simplicity, but the general methodology is applicable to more general situations, such as electromagnetic plasma turbulence or turbulence in magnetized plasmas.

Flow separation from a continuous surface under adverse pressure gradient remains one of the most challenging problems for turbulence modeling within the Reynolds-Averaged Navier–Stokes (RANS) framework. Although the Shear Stress Transport (SST) model performs well for a wide range of flows, its predictive capability deteriorates in wake regions dominated by complex turbulent structures. To enhance its accuracy, a modified SST model incorporating the Renormalization Group (RNG) theory of turbulence is proposed. The RNG correction is introduced as an additional source term in the dissipation equation and is limited to the reattachment region through a blending function to ensure computational efficiency and numerical stability. The model is validated using several canonical problems, including the curved backward-facing step, vertical and inclined backward-facing steps, and the periodic hills case at various Reynolds numbers. The effects of the inflow boundary condition are carefully examined to isolate the intrinsic performance of the modified model. For this purpose, an experimental campaign is performed. Comparisons with benchmark Large Eddy Simulation studies and experimental data show that the RNG-enhanced SST model substantially improves the prediction of mean velocity, turbulence kinetic energy, and wall quantities such as pressure coefficient, wall shear stress, and boundary-layer parameters. In particular, the prediction of the reattachment position is improved, yielding reduced relative errors that are nearly half of the SST model. These findings demonstrate that integrating RNG theory provides a computationally cost-effective, numerically robust, and physically consistent improvement to the SST model for separated flows from a continuous surface.

ABSTRACT While several studies point to decreased relationship quality among caregiving couples, few studies have examined the mechanisms through which providing care can shape or reshape the characteristics of romantic relationships. To shed light on this issue, we engage the frameworks of relational turbulence theory (RTT) and transition processing communication (TPC) to identify both (1) the ways caregiving for an aging adult influences marital relationships and (2) the maintenance strategies these couples engage in to sustain a healthy relationship. Using both quantitative and qualitative data, we identified eight everyday relationship experiences specific to caregiving, examined associations between TPC and relationship parameters described by RTT, and utilized rich description to illuminate caregivers’ experiences employing the four forms of TPC. Engaging in TPC was associated with improved relationship parameters, while cohabiting with an aging adult was associated with worsened relationship experiences. Results point to TPC as a potential communicative intervention for married caregivers.

ABSTRACT The spectral behavior of the wet refractivity in the troposphere has not yet been studied, contrary to air temperature, specific humidity, and wind field. As wet refractivity is directly linked to air moisture, it causes highly variable tropospheric delays in geodetic observations using radio wave signals. Knowing the spectral behavior of the wet refractivity thus provides scientists with an important constraint or source of data for both tropospheric delays modeling and numerical weather/climate modeling. To fill this gap, in this work, we present a new toolset to analyze the spectral properties of the tropospheric wet refractivity field. As an example, using fifth-generation European center for medium-range weather forecasts re-analysis (ERA5) hourly products, the three-dimensional (3D) wet refractivity fields overhead Tahiti Island during 2019–2020 are derived as a case study, where the perturbations of the wet refractivity field are modeled with 3D Zernike functions and a corresponding power spectrum w.r.t a radial index n and a space index l is derived. Results show that the power spectrum w.r.t the power index n×l is almost flat at low n×l but progressively transitions to a power-law decline with an index of −2.9 (approximately −3) at higher n×l. The flat pattern indicates large-scale atmospheric processes considered in ERA5, and the −3-scaling law conforms to the two-dimensional (2D) atmospheric turbulence theory as found in other atmospheric variables. This −3-scaling law is also similar to the well-known Kaula’s rule in geodesy works, allowing us to derive a Kaula-like rule as an additional a priori information for modeling the wet refractivity field with 3D Zernike functions.

A physics-informed neural network is employed to reconstruct near-wall flow fields from particle image velocimetry (PIV) data in regions where direct measurements are inaccessible. Experiments were conducted in a vertical square duct, and four datasets were prepared with mean velocity components and Reynolds stresses measured at the duct's center plane for Reynolds numbers in the range Re=2.1×104 to 3.2×104. The Reynolds-averaged Navier–Stokes equations were incorporated in the training as physical constraints, and a two-step training strategy was introduced to address closure limitations in near-wall region with insufficient prior knowledge. In the first stage, the model was trained within the PIV domain to denoise the flow data and reconstruct pressure field through data assimilation, producing results consistent with Darcy friction coefficients at each Re. The second stage incorporated additional physical constraints, including force balance and a simplified turbulence-closure approximation, to recover the near-wall flow behavior. The final model produced velocity profiles consistent with turbulent boundary layer theory, capturing the linear viscous sublayer and the onset of the logarithmic region. The reconstructed Reynolds stresses effectively captured the strong near-wall anisotropy reported in previous studies, exhibiting peak approximately eight times larger in the streamwise direction than in the wall-normal direction. Comparisons with models trained without Reynolds stress regularization confirmed that this constraint contributes to improved Reynolds stress prediction.

Abstract This work presents a new theoretical and numerical model describing all possible linear interactions between upper-hybrid wave turbulence and random density fluctuations in a weakly magnetized solar wind plasma. Not only linear processes, such as wave reflection, refraction, scattering, tunneling, trapping, or mode conversion at constant frequency, are taken into account, but so are linear wave coupling, interferences between scattered waves, etc. Compact equations describing the radiation of electromagnetic waves in the O -, X -, and Z -modes by the current resulting from the transformations of upper-hybrid waves on density fluctuations are determined analytically and solved numerically, providing the time variations of electromagnetic energies and the corresponding radiation rates. Jointly, on the basis of these numerical results, which validate the model’s hypotheses, analytical calculations are conducted under the framework of weak turbulence theory extended to randomly inhomogeneous plasmas, which recover the main physical conclusions stated when using the model. The dependencies of radiation rates on plasma parameters, such as magnetization, electron temperature, and average level of random density fluctuations, are determined in the form of scaling laws. This work opens a new way to analyze the efficiency of electromagnetic emissions at plasma frequency by realistic wave and density turbulence spectra interacting in solar wind plasmas.

Abstract The problem above marked as resolved is more than a hundred years known as the closure problem of turbulence. Extending its name follows from below presented knowledge that to be its solution successful it is necessary to find an effective averaging tool enabling one to describe and smooth down any random turbulent field without any phenomenological limitations. To convince of necessity of such tool author in the article previously proved the nondifferentiability of random fields of measurable turbulence characteristics. But the decisive momentum of his solution strategy arose from the idea that randomness is an autonomous factor of physical processes and, therefore, this property can be utilized as a property of independent variables of the governing PDEs. To realize this idea author picked random frequences of turbulent fluctuations. Author then postulated the dual property as well as bifunctionality hypothesis and found suitable constitutive equations enabling him: (i) to express the instantaneous behaving of any random vector and scalar turbulent fields; (ii) to average the non-linear N–S system for the thermally known turbulent flow over the characteristic domains in the 5–D random space; (iii) to close the averaged equations systems with the set of four relationships named the Energy Distribution Equations (EDE) as the key result of the closure process. The energy invariance principle was used to find a closing equation for the energy distribution factor. The resultant EDEs were successfully verified meanwhile by comparing them with data from four independent sources of experiments made in boundary layers of wind tunnel flows of high anisotropy. This closure problem solution was obtained without the use of any auxiliary parameters or assumptions of phenomenological or experimental origin. From the nature of EDEs it follows that all turbulent mean flows are always 3–Dimensional. The use of randomness autonomy as the property of independent variables at describing turbulent flows is not limited upon Newtonian fluids.

We introduce a method for describing eigenvalue distributions of correlation matrices from multidimensional time series. Using our newly developed matrix H theory, we improve the description of eigenvalue spectra for empirical correlation matrices in multivariate financial data by considering an informational cascade modeled as a hierarchical structure akin to the Kolmogorov statistical theory of turbulence. Our approach extends the Marchenko-Pastur distribution to account for distinct characteristic scales, capturing a larger fraction of data variance, and challenging the traditional view of noise-dressed financial markets. We conjecture that the effectiveness of our method stems from the increased complexity in financial markets, reflected by new characteristic scales and the growth of computational trading. These findings not only support the turbulent market hypothesis as a source of noise but also provide a practical framework for noise reduction in empirical correlation matrices, enhancing the inference of true market correlations between assets.

Abstract Observations of ocean surface currents from the JPL Doppler Scatterometer (DopplerScatt) during the S-MODE campaigns reveal unexpectedly shallow second-order velocity structure function (SF) slopes at submesoscale separation scales ( r < 10 km), deviating from classical turbulence theory and prior modeling results. This discrepancy suggests missing physics in current submesoscale-resolving numerical ocean models or an incomplete interpretation of the DopplerScatt observations. To investigate this, we analyze high-resolution Regional Ocean Modeling System (ROMS) simulations across a range of configurations that isolate the influence of model resolution, season, high-frequency forcings, and surface gravity wave effects on currents. We find that high-frequency motions associated with near-inertial waves reduce the transverse SF amplitude, driving the ratio of longitudinal to transverse SFs close to unity at submesoscales independently of the season. Additionally, the inclusion of wave-current interactions, often omitted in standard submesoscale-resolving models, can produce energetic small-scale motions, leading to broadband shallow structure function slopes. These results reveal a broader mechanism by which shallow structure function slopes can emerge: any process that injects kinetic energy at small scales over a narrow range of wavenumbers will appear broadband in structure function space and produce shallow scalings. Wave effects are one such candidate and offer a plausible interpretation of the DopplerScatt observations under energetic wave conditions. However, under low wave conditions, other processes with similar spectral characteristics are required to account for the observed shallowness. Finally, the relatively large transverse-to-longitudinal SF ratio in DopplerScatt may reflect its lateral averaging over part of an inertial period, a sampling strategy not replicated in models and warranting further study.

This study applied relational turbulence theory to examine how relationship characteristics in the form of relational uncertainty and partner interdependence during the transition to parenthood are associated with more severe appraisals of irritations, features of communication during couple conflict, and perceptions of increased turbulence in the relationship. We conducted a longitudinal study of 78 couples who were surveyed three times during the transition to parenthood from pregnancy to six months after birth. Data were analyzed using multilevel modeling and examined both actor and partner effects. Results point to between-person and within-person actor effects, with actors’ relational uncertainty and facets of interdependence predicting perceived severity of irritations and features of conflict episodes. In addition, actors’ severity of irritations predicted conflict features and perceived relational turbulence. Partner effects emerged for relational uncertainty predicting communicative openness, conflict management, and relational turbulence, and facets of interdependence predicting most outcomes. The results are discussed in terms of their theoretical contributions and practical implications for first-time parents.

Abstract This paper presents a robust computational technique to tackle the intricate nonlinear partial differential equations (PDEs) encountered in mathematical physics. The method is applied to the time-fractional Burgers-Huxley equation, where the time derivative is considered in the Liouville-Caputo sense. This equation, which combines the well-known Burgers and Huxley equations, describes the interplay of reaction, convection, and diffusion in transport phenomena and finds application in acoustics, turbulence theory, traffic flow, and hydrodynamics. The proposed method transforms this complex non-linear fractional PDE into a simple algebraic system. Its ability to handle the non-linear terms without perturbation, discretization, or the calculation of extraneous terms is a major advantage over available analytical approaches. Five different cases of the equation with diverse initial and boundary conditions are discussed. To demonstrate the accuracy and reliability of the semi-analytic approach, the obtained outcomes are compared with existing exact and analytical solutions in the literature, showing a strong level of agreement. Error analysis and the convergence criterion are also discussed.

The turbulent skin-friction theory of van Driest II (involving transformation to incompressible flow) is employed to calculate the local and mean friction coefficients. A wall-wake velocity profile is proposed and employed in the numerical evaluation of the displacement and boundary-layer thicknesses. The proposed velocity profile is shown to be successful in a realistic representation of a compressible boundary layer for given Mach and Reynolds numbers. Values of the calculated variables are compared with existing correlations and experimental/computational data reported in the literature. A two-stage regression analysis is applied to the predicted data to obtain expressions for the streamwise variations of the mean flow properties as functions of the Reynolds and Mach numbers. Explicit correlations for the local and mean friction coefficients, displacement, momentum, and boundary-layer thicknesses are presented for air flow in the Mach number range from 2 to 7 and the Reynolds number range from 7×105 to 7×109. In contrast to the laminar flow case, the thickness of the turbulent boundary layer depends weakly on the Mach number.

Abstract The Surface Water and Ocean Topography (SWOT) mission, equipped with a Ka‐band Radar Interferometer (KaRIn), provides unprecedented sea surface height anomaly (SSHA) observations at kilometer‐scale resolution over a wide swath. Although regional studies have showcased SWOT's capabilities, its SSHA wavenumber spectra at wavelengths below 70 km exhibit shallower slopes (, where is the along‐track wavenumber) than predicted by geostrophic turbulence theory. We analyzed SWOT SSHA data alongside in situ measurements collected by the mission oceanographic campaign from the California Current System during the April–July 2023 calibration and validation (Cal/Val) period. We analyzed steric height from hourly CTD measurements on 11 moorings and 2 gliders and SWOT SSHA using structure functions, revealing that the shallow SWOT SSHA spectra at sub‐70 km scales primarily result from KaRIn instrument noise, with a notable cross‐track dependence (shallowest at the swath edges). Additionally, high‐frequency internal gravity waves also contribute to the shallow spectral slope. Because of limitations in in situ and SWOT observations, we could not quantitatively partition each individual process's contribution. Nevertheless, our results revealed, for the first time, the impact of instrument noise and high‐frequency internal waves on the SSHA spectrum at sub‐70 km that was previously unknown from conventional nadir altimeters, highlighting the complexity of small‐scale SSHA signals and the need for further research.

It is experimentally well-established that non-equilibrium long-range correlations of concentration fluctuations appear in free diffusion of a solute in a solvent, but it remains unknown how such correlations are established dynamically. We address this problem in a model of Donev, Fai, and Vanden-Eijnden (DFV), obtained from the high-Schmidt limit of the Landau-Lifshitz fluctuating hydrodynamic equations for a binary mixture. We consider an initial planar interface of the mean concentration field in an infinite space domain, idealizing prior experiments. Using methods borrowed from turbulence theory, we show both analytically and numerically that a quasi-steady regime with self-similar time decay of concentration correlations appears at long time. In addition to the expected "giant concentration fluctuations" with correlations ∝r for r ≲ L(t) = (Dt)1/2, with diffusivity D, a new regime with spatial decay ∝1/r appears for r ≳ L(t). The quasi-steady regime arises from an initial stage of transient growth ∝t, confirming the prediction of DFV for r ≳ L(t) and discovering an analogous result for r ≲ L(t). Our results give new insight into the emergence of non-equilibrium long-range correlations and provide novel predictions that may be investigated experimentally.

Caring for an aging adult can harm an individual’s mental, physical, and relational well-being. Couples providing eldercare often report increased tension and conflict, decreased time for intimacy, and lowered marital adjustment. Nonetheless, few studies have attempted to explain the mechanisms through which caregiving experiences impact relationship evaluations. This study engages the frameworks of relational turbulence theory and transition processing communication to examine how stress, partner communication, and relationship parameters intersect for married caregivers. The study employs dyadic data to consider four forms of relationship-focused communication that may help married caregivers preserve or elevate their partnership. Results of the study provide evidence that partner engagement in transition processing communication is associated with less relational uncertainty and improved interdependence. However, caregiving stress was associated with decreased engagement in transition processing communication. Results shed light on gender differences in the extent to which stress, communication, and relationship parameters may be connected in the context of caregiving. The study adds to our theoretical and practical understanding of how relationship turmoil develops and is attenuated within RTT and among caregiving couples.

Accurate prediction of bedload transport in vegetated riverbeds is critical for wetland protection and ecological restoration. This study develops a novel turbulence-based theoretical model for bedload transport in vegetated flows. The near-bed turbulent kinetic energy (TKE) is derived from the phenomenological theory of turbulence through quantitative analysis of multiscale turbulent eddy structures. For rigid vegetation, the proposed model provides a unified framework for estimating near-bed TKE across diverse configurations, including uniform distribution, patchy clusters, random arrangements with variable diameters, and vertically heterogeneous morphologies, improving upon previous empirical superposition approaches. The predicted near-bed TKE exhibits a robust correlation with measured bedload transport rates compiled from 358 experimental datasets, supporting its validity as a physically meaningful predictor. Following the operators of formulas developed for unvegetated beds, a refined TKE-based bedload transport formulation for vegetated flow is derived using symbolic regression, calibrated on datasets with uniformly distributed cylindrical vegetation. Validation demonstrates that the proposed transport model maintains high accuracy while effectively generalizing to more complex rigid vegetation scenarios. Compared to existing literature models, our formulation shows improved predictive precision and broader applicability.

Abstract The cross-scale energy transfer among oceanic mesoscale eddies is crucial to shape their equilibrium state with important climate and ecological implications. The classical two- and three-dimensional turbulence theories predict an upscale and downscale energy transfer locally in spectral space (i.e., a cascade-like process), respectively. However, using unprecedented high-resolution measurements of sea level anomalies from the Surface Water and Ocean Topography (SWOT) mission combined with a high-resolution oceanic simulation, we demonstrate the coexistence of downscale and upscale transfers for surface mesoscale eddy kinetic energy (EKE) in the Southern Ocean. The latter dominates the former, leading to a net upscale surface EKE transfer. The downscale surface EKE transfer is generally local in the spectral space, achieved primarily via interactions of mesoscale eddies with horizontal scales differing by less than a factor of 2. In contrast, the upscale surface EKE transfer is less local, involving mesoscale eddies with larger horizontal-scale separation. Accordingly, the upscale surface EKE transfer is severely underestimated in measurements from the last generation of satellite altimeters even at their well-resolved scales of O(100) km. Our findings uncover the crucial contribution of EKE transfer by interactions among mesoscale eddies with evident scale differences, which is overlooked in the existing oceanography literature. Significance Statement By analyzing the unprecedented high-resolution measurements of sea level anomalies from the Surface Water and Ocean Topography (SWOT) mission, this study reveals that the cross-scale eddy kinetic energy transfer involves mesoscale eddies with an evident scale separation.