Search Results (21,054)

A formal development of the HypoEquilibrium (HE) state concept within the Steepest-Entropy-Ascent Quantum Thermodynamics (SEAQT) framework is presented, emphasizing its rigorous mathematical formulation. Using a general decomposition of the Hilbert space, HE states are defined in operator language and the reduced evolution of the associated intensive parameters for the regime where the dissipative dynamics commutes with the Hamiltonian is derived. It is proved that the M-th-order HE family (where M is the number of spectral sectors) constitutes an invariant manifold under the SEAQT equation of motion, ensuring that states initially representing a “mixture of canonicals” maintain this structure throughout their evolution. Furthermore, a formal connection is established between the HE ansatz and the rate-controlled constrained equilibrium (RCCE) method, identifying HE variables as constraint potentials. Finally, the model is extended to Non-Hamiltonian SEAQT (NH-SEAQT) interactions to describe thermodynamically consistent energy and entropy exchanges between subsystems and heat baths. This work provides the formal foundation for reduced-order modeling of far-from-equilibrium relaxation and transport processes, and supports a methodology previously applied across various physical and chemical systems. Full article

The Vehicle Routing Problem with Time Windows (VRPTW) takes on a structurally distinct form when the goods being routed undergo first-order quality decay during transport. In this setting, distance minimisation alone underestimates the true economic cost. A per-customer minimum-quality acceptance constraint further introduces a non-linear feasibility condition that does not appear in the classical formulation. This paper addresses such a setting in the context of loose-skin citrus fruit (e.g., mandarins) distribution, where stock has already undergone several days of cold storage at the origin warehouse, and remaining shelf life makes retail time windows binding rather than decorative. We formulate a Maturity-Aware Multi-Echelon Dynamic Reallocation Vehicle Routing Problem with Time Windows (MA-MEDR-VRPTW) on a three-echelon network (origin warehouse → distribution centres → stores) over a seven-day rolling horizon. A first contribution shows that the minimum-quality acceptance constraint admits an analytic transformation into a time-window tightening, which removes per-extension exponential evaluations from the subproblem solver. The algorithmic contribution is a proximal alternating direction method of multipliers (ADMM) with NG-route relaxation (padmm-ma) whose quality-loss weight is updated by a residual-balancing rule and is decoupled from the outer reallocation linear program (LP) through approximate dynamic-programming-style marginal costs. On twelve Solomon-derived mandarin instances (72 feasible algorithm–instance combinations), padmm-ma returns a mean seven-day cost of 12,638 CNY against 11,753 CNY for a subgradient baseline ($+7.5\%$) at statistically indistinguishable arrival quality (paired Wilcoxon $p=0.077$ for ${\overline{q}}_{\mathrm{arr}}$), while cutting mean wall-clock time from 350 to 23 seconds (about $15\times$). The method, therefore, reads as a fast operational heuristic for daily re-planning. An ablation, an exact-MIP benchmark on tractable subproblems, and a scale extension to $n=100$ customers round out the validation. Full article

Steam-assisted gravity drainage (SAGD) is constrained in deep heavy-oil reservoirs by wellbore heat losses, delayed steam-chamber development and high steam–oil ratio (SOR). This study develops an experimentally parameterized reduced-order screening framework for thermocable-assisted SAGD, formulated as a digital-twin prototype that couples heat transfer, temperature-dependent viscosity, chamber-growth geometry and energy-efficiency indicators. The formulation is evaluated within an experimentally parameterized screening matrix covering steam temperature, oil viscosity, permeability, depth, cable power and early heating time. The graphical dependencies are presented in a unified publication format and supplemented by heat-balance, chamber-field, sensitivity and operating-window analyses. For the reference experimental case, thermocable support increases oil rate from 84.1 to 96.1 t/day and reduces SOR from 2.70 to 2.30 t/t. The cable heat input is small relative to useful steam heat; therefore, its effect is interpreted through local compensation of downstream heat deficit and longitudinal temperature stabilization rather than through bulk energy addition. The strongest sensitivity is associated with steam rate, oil viscosity and depth, whereas cable power shows a beneficial but saturating effect. The proposed reduced-order digital-twin prototype is intended for feasibility screening, preliminary operating-window selection and prioritization of candidate regimes for detailed thermal-reservoir simulation and subsequent field-scale validation. Full article

Damage to conductors inside suspension clamps is extremely concealed, and failure to detect it effectively may lead to conductor breakage accidents. However, the engineering field still lacks reliable and efficient inspection methods. To address this, this paper proposes a strand-breakage damage detection method based on modal parameter identification under hammer impact excitation. A full-scale wire experiment is conducted to validate the detection method and investigate its influencing factors. The experiment shows that as the damage to the conductor inside the suspension clamp intensifies, the modal frequency of the conductor decreases, with a more pronounced decline in higher-order modes. Tension is positively correlated with the modal frequency of conductor vibration, and fluctuations in operating tension can cause drastic changes in modal frequency. Such variations can even exceed the modal frequency shift caused by structural damage. During the detection process, it is necessary to consider the impact of tension fluctuations on the detection results. The modal frequency of the conductor decreases slightly as the temperature rises. Specifically, for every 10 °C increase in temperature, the modal frequency of the conductor changes by less than 1%. The small fluctuations in modal frequency caused by temperature are much smaller than the frequency differences corresponding to adjacent degrees of damage. Therefore, there is no need to consider the influence of temperature during the actual detection process. This study verifies the feasibility of using modal identification under impact excitation for detecting strand breakage inside suspension clamps through experiments and analyzes the influencing factors of modal frequency, providing experimental support for the application of detection technology. Full article

PFAS form a class of synthetic chemicals that has become an area of increasing concern because of its impact on the environment and the threat it poses to human health. The structure of PFAS makes them highly resistant to degradation. As a result, they are highly effective at bioaccumulation. Certain water treatment technologies have been proven to remove PFAS from contaminated water sources. This study reviews the most promising treatment technologies used for the treatment of PFAS-contaminated waters. Well-established treatment technologies, such as granular activated carbon, ion exchange resin, reverse osmosis, and nanofiltration, were quantitatively compared. The removal efficiency was assessed by collecting the data of individual PFAS species from the literature and grouping them into five groups: PFAS (all species), PFSA, PFCA, long chain, and short chain. The results identified that, for all PFAS groups, the most effective treatment technologies were in the following order: reverse osmosis, nanofiltration, ion exchange resin, and granular activated carbon. The performance of reverse osmosis and nanofiltration did not appear to significantly differ between the different PFAS groups, as opposed to ion exchange resin and granular activated carbon, where there was a greater degree of variation in performance between different PFAS groups. Overall, it was identified that membrane technologies outperformed adsorbent technologies. However, the cost associated with membrane technologies may limit its economic viability when compared with adsorbent technologies, which are typically a more viable option except under specific circumstances. For example, contaminated water with high concentrations of other contaminants that need to be treated simultaneously. Lack of standardised experimental and operational conditions limited the available data. While this work provides guidance on which treatment is more likely to be appropriate based on the concentration and composition of different species of PFAS, more data are needed to conduct a more accurate statistical analysis and enable accurate modelling of treatment performance. Full article

Hydrogen supplementation in compression-ignition diesel engines is increasingly investigated as a practical retrofit approach for reducing the environmental impact of existing marine and stationary diesel power systems. This study examines the effects of hydrogen enrichment on combustion stability, pressure behavior, harmonic response, fuel consumption, and exhaust emissions in a 1966 Deutz A12L 714 marine auxiliary generator-set. The engine was operated at 900, 1200, and 1500 rpm with hydrogen supplied through the intake-air stream at flow rates up to 130.15 L/min. Results indicate that hydrogen enrichment improved fuel consumption and combustion-related dynamic behavior without increasing peak cylinder pressure or exhaust-gas temperature. Low-order vibration harmonics, particularly the 1X and 3X components associated with torque ripple and cyclic combustion variability, decreased with hydrogen addition. COV(Pmax) remained below 0.27% across all operating conditions, indicating preserved combustion stability, while hydrocarbon emissions and fuel consumption decreased by approximately 30% and 13%, respectively, at the highest hydrogen enrichment conditions. Phase-averaged pressure traces obtained showed virtually unchanged combustion-cycle structure and periodicity under maximum hydrogen enrichment. The findings indicate that hydrogen enrichment improves combustion stability and overall engine performance without increasing combustion severity, supporting its potential application as a retrofit solution for marine auxiliary engines, distributed generators, and other legacy diesel-engine systems. Full article

This paper presents a highly linear second-order, tunable bandpass filter (BPF) based on low-Gm operational transconductance amplifiers (OTAs) to be used in a single-frequency bioimpedance analysis (SFBIA) system. The center frequency of the proposed BPF can be set at the target center frequency $f_c$ = 1 kHz through a tuning current $I_C$, thus compensating for process variations and temperature changes after fabrication. A low quality factor is established to let the input signal pass through without significant phase shift or gain fluctuation, while reducing the out-of-band noise contribution to the readout circuit. The proposed BPF was implemented in a 0.18 $\mathsf{\mu }$m CMOS process and consumes 2.6 $\mathsf{\mu }$W from a 1.8 V supply. The Gm reduction technique enables precise control of the OTA’s transconductance, and therefore of the center frequency of the BPF. For $I_C$ ranging from 28 nA to 138 nA, the measured $f_c$ varies from 690 Hz to 3 kHz, with a constant Q factor of approximately 0.4. The proposed BPF can handle input signals as high as 132 mV_pp with a maximum 1% total harmonic distortion. Full article

Programmable electromagnetic environments, including reconfigurable intelligent surface (RIS)-assisted systems, are often described in terms of physical or controllable degrees of freedom. Such counts, however, do not determine which channel or operator directions can actually be distinguished by a finite measurement architecture. This paper develops an operator-space formulation of observable degrees of freedom for programmable propagation systems. We distinguish three nested layers: the physical operator space generated by the family of physically admissible propagation operators, the effective operator space selected by architectural constraints, and the observable subspace induced by a finite probing architecture. Once the effective space is fixed, observability is characterized by the spectrum of the associated measurement Gram operator. To remove arbitrary amplitude scaling, we introduce a common probe-energy normalization and define the resolution-dependent observable dimension $N_{\mathrm{obs}}\left(\eta \right)$ from the normalized Gram spectrum. The same spectrum also yields an observability condition number, which quantifies the stability of the visible subspace. We then extend the construction to symmetry-resolved operator spaces, showing how invariant probing can create sectorial blind subspaces and how controlled symmetry breaking produces second-order restricted visibility inside the original blind subspace. The mathematical ingredients are standard finite-dimensional tools from operator theory, frame theory, representation theory, and matrix concentration; the contribution is their integration into a measurement-oriented degrees-of-freedom framework for programmable electromagnetic environments. Numerical experiments with normalized probing families, sectorial decompositions, controlled symmetry breaking, and a canonical narrowband RIS-inspired model illustrate that architectures with the same effective dimension and probing budget can exhibit substantially different observable dimensions and conditioning. The results support the view that practical electromagnetic design should optimize not only the number of accessible modes or control states, but also the Gram geometry through which those directions are measured. Full article

This paper discusses the development of a fully nonlinear flight dynamics model of a hover-capable Air-Launched Uncrewed Aerial System (ALUAS) in order to (1) understand the dynamics, controllability, and airloads during complicated maneuvers and (2) gain insights from simulation to inform the design and operation of future ALUASs. Prior studies conducted wind tunnel tests on full-scale models to measure the airloads on the propeller, isolated fuselage, and full aircraft. The flight dynamics model, once corrected with the test data, was used to simulate maneuvers including hover-to-cruise transition, cruise-to-hover transition, ground launch, air launch from a moving helicopter, and air launch with asymmetric wing unfolding. These simulations demonstrate the capability of the vehicle to perform complicated maneuvers to meet various mission objectives in challenging environments. Full article

Zoonotic diseases represent an increasing health, economic, and social risk in the context of intensified movement of people, animals, and goods, which creates conditions for their rapid spread and the emergence of pandemics. The One Health approach provides an integrated framework that brings together human, animal, and environmental health in order to enable more effective risk management. This study aims to examine the role of insurance and financial mechanisms in zoonotic risk management in the context of One Health. The review identifies four main categories of mechanisms relevant to zoonotic risk management: human health insurance, animal insurance and compensation schemes for livestock producers, public emergency financing mechanisms, and integrated risk-sharing models. The analysis shows that these mechanisms often operate within separate sectors, which may limit their effectiveness in managing complex health threats. These findings suggest that the effectiveness of zoonotic risk management depends not only on the availability of financial resources, but also on how these mechanisms are integrated across sectors. In this context, insurance mechanisms are considered tools for both cost compensation and risk management. They support prevention, early detection, and disease control. The need for their integration within the One Health framework is emphasized. It is also necessary to develop models that ensure a more equitable distribution of risk and financial sustainability for the population as a whole. Full article

The dust extraction impeller is a core component of the vehicle engine auxiliary system that filters dust from the intake air to ensure stable engine operation; its reliability directly affects the performance and operational safety of the vehicle. Critically, the dust extraction impeller can exhibit severe erosion wear in extreme environments, but conventional degradation testing methods are costly and require considerable time to complete. Therefore, this study conducted accelerated degradation testing using the change in impeller blade thickness as the degradation indicator and the dust concentration and impeller rotational speed as dual elevated stress factors to obtain time-series degradation data from 48 blade samples. Linear, exponential, power-law, natural logarithmic, and Gompertz models were subsequently fit to the data for a single sample, and then the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was employed to select the optimal degradation trajectory model. The accuracy of the selected linear model was verified using the data from all samples, confirming that it can be applied to predict the degradation of the dust extraction impeller over time. The contribution of this study comprises the establishment of a degradation assessment framework combining accelerated degradation testing with TOPSIS-based model selection to provide a practical basis for the reliability design and maintenance planning of vehicle dust extraction impellers operating in extreme environments. Full article

We propose and empirically evaluate a two-stage approximation to a Generalized Multivariate Functional Additive Mixed Model (GMFAMM) for the joint bias correction of five NASA POWER reanalysis variables: minimum and maximum temperature ($T_{\min }$, $T_{\max }$), relative humidity (RH), solar radiation (Rad), and precipitation occurrence ($P_{\mathrm{bin}}$). Our primary contribution is the first operational-scale evaluation of such a framework (≈200,000 station–day observations, two orders of magnitude beyond previous studies) together with its deployment in an open-access web application. A systematic grid of more than 200 marginal configurations is evaluated on a strict chronological 70/30 hold-out (training 2016–2022; testing 2023–2025) to identify the optimal marginal specification per variable. Against a correctly specified marginal baseline, station-level linear calibration combined with the marginal GAMM removes the bulk of the systematic bias (RMSE reductions of ≈80%, 82% and 30% for $T_{\min }$, $T_{\max }$ and RH). A shared latent step, using the first principal component of the marginal residual matrix as a scalar proxy for ${\Lambda }_0\left(t\right)$, yields additional but conditional out-of-sample reductions (≈17% $T_{\max }$, 10% RH, 9% Rad; negligible for $T_{\min }$, with precipitation occurrence retained in the shared representation but its joint gain treated as exploratory); because it requires co-located donor observations, at ungauged locations the deployed pipeline applies the marginal correction only, whose spatial transfer is confirmed by leave-one-station-out cross-validation. The residual cross-correlation structure is consistent with, though not in itself proof of, Clausius–Clapeyron coupling. The trained artefacts are deployed in ColClim, an open-access R Shiny application that queries the NASA POWER API and the Open-Meteo forecast service for any location in Colombia and delivers historical bias-corrected series and short-range (1–16 day) forecasts. Full article

Introduction: As diabetes care becomes increasingly digitalized, stratified, and differentiated, psychosocial vulnerability risks becoming less visible within routine care and documentation. To ensure that differentiated care pathways meaningfully incorporate psychosocial stratification, vulnerability must be identifiable, documented, and revisited as part of routine clinical practice. Aim: The aim of this study is to explore how healthcare professionals identify psychosocial vulnerability in routine diabetes care and how such vulnerability is documented and followed up in the electronic medical record (EMR). Methods: This quality improvement audit with a descriptive analysis component was conducted at Steno Diabetes Center Copenhagen as part of the development of a new differentiated outpatient pathway. Healthcare professionals across disciplines submitted cases of persons with diabetes whom they considered psychosocially vulnerable. Documentation from the preceding six months was reviewed descriptively in order to find patterns of identification, documentation, care planning, and follow-up. Results: A total of 334 referrals representing 275 unique persons with diabetes were submitted. Psychosocial vulnerability extended beyond predefined high-risk categories, as 37% of identified cases did not align with any of the six vulnerability groups described in the Danish VIVE framework. Vulnerability often reflected cumulative everyday-life strain rather than formal diagnoses. While healthcare professionals demonstrated substantial relational attentiveness to psychosocial concerns, this knowledge was not consistently evident in formal documentation. Explicit care plans and longitudinal follow-up were uncommon, and psychosocial concerns were frequently documented as isolated observations rather than as part of structured ongoing care. Conclusions: Psychosocial vulnerability was frequently identified through clinical dialogue and professional judgement and often extended beyond predefined vulnerability categories. The findings highlight the importance of developing shared approaches and a shared understanding of psychosocial vulnerability across professional groups. If psychosocial stratification is to become an operational component of differentiated diabetes care, information about what burdens matter to the person must be identifiable, documented, and carried forward across encounters alongside biomedical information. Full article

This paper investigates a class of Hadamard variable-order fractional differential equations in which the fractional order is determined by the cumulative distribution function (CDF) of a continuous random variable. The proposed framework establishes a novel connection between probability theory and variable-order fractional calculus by allowing the memory index of the fractional operator to evolve according to a prescribed distribution law. To facilitate the analysis, the CDF-based variable order is considered through a piecewise-constant representation on a finite partition of the interval, which transforms the original problem into a family of Hadamard fractional differential equations of constant order on successive subintervals. Existence and uniqueness results are established by converting the differential problem into an equivalent fractional integral equation and applying the Banach contraction principle in suitable Banach spaces. Sufficient conditions ensuring the well-posedness of the problem are derived in terms of explicit bounds involving the fractional order and the nonlinear term. In addition, the Ulam–Hyers stability of the proposed model is investigated, and stability criteria are obtained under the same analytical framework. To illustrate the applicability of the theoretical results, a numerical example involving a CDF-generated variable-order function is presented. The example verifies the assumptions of the existence, uniqueness, and stability theorems and demonstrates the effect of piecewise-constant approximations of the cumulative distribution function on the resulting numerical solutions. The obtained results show that the proposed CDF-based Hadamard variable-order framework provides a mathematically consistent setting for studying fractional differential equations whose memory characteristics depend on probabilistic distributions. Full article

Low-frequency mobile bands remain essential for wide-area and penetration-limited wireless coverage, but their limited channel bandwidth constrains the achievable capacity. This paper presents a measurement-supported extrapolation framework for assessing how lowband MIMO and future AAS-assisted operation can enhance coverage and single-user throughput-oriented capacity in wireless networks. The motivation is to evaluate whether such deployments can strengthen the lower-frequency layer as a robust coverage-and-capacity support layer for general traffic and reduce the load on midband and higher-frequency resources. Controlled radiated SISO and $2\times 2$ MIMO measurements were performed with a base-station simulator and commercial user equipment in representative lowband and midband frequency bands. Measured RSRP, CQI, BLER, MAC-layer throughput, and IP-layer throughput thresholds for a 25 Mbit/s downlink target were used for coverage estimation and conditional extrapolation. Under the Extended Hata model, the measured $2\times 2$ MIMO thresholds yielded a 43% larger estimated radius at 800 MHz than at 1800 MHz, while the same model indicated a 93% radius increase for a representative 10 dB AAS-related beamforming gain scenario. Conditional $4\times 4$ MIMO extrapolations indicated data rates above 100 Mbit/s in 10 MHz and above 200 Mbit/s with 10 MHz two-component-carrier aggregation under ideal high-CQI conditions. The results support the potential of future lowband AAS deployments. The AAS and higher-order MIMO results are scenario-based estimates rather than direct field validation. Full article