Search Results (3,925)

Recent lattice studies have revealed that the color flux tube between static quark–anti-quark pairs exhibits an excess entanglement entropy (flux-tube entanglement entropy, FTE²) that scales linearly with the quark separation L. In this paper, we demonstrate sim-ilar behavior in a string-net model based on SU(2)_k fusion categories, where the nontriv-ial object j = 1/2 (analogous to color charge) cannot exist in isolation due to the fusion rules, naturally exhibiting “confinement”. We compute the entanglement entropy of the flux tube connecting two j = 1/2 objects using the microcanonical (equal-weight) pre-scription S(R) = ln(dim(Hom(R))) and find an entropy density σ_k = ln d_1/2 = ln(2cos\({\frac{\pi}{k+2}}\)). For 𝑘 = 3, the category reduces to the Fibonacci case, yielding an entropy density σ₃ = ln φ ≈ 0.4812 (φ is the golden ratio), which is qualitatively comparable in magnitude to the scale inferred from lattice studies and the entropy surface mechanism. Under a thermalization assumption for the fusion-channel degrees of freedom, minimiz-ing the free energy F = (𝒥 \({-}\) Tσ_k)L yields a confinement–deconfinement transition at (T_c = 𝒥/σ_k), which is first-order-like (tension sign reversal) rather than a continuous crit-ical transition. The parameter k offers a tunable knob, making the SU(2)_k family a com-putable laboratory for entropic confinement. The predicted entropy-density jump can be directly tested in quantum simulator platforms (e.g., Rydberg arrays or superconducting circuits) that realize Fibonacci anyonic models. Full article

Mare’s milk is recognized for its nutritional value, but information on the relationships of mare age and number of foalings with body conformation, udder morphology, milk yield, and milk composition in the indigenous Kushum breed remains limited. Forty-one clinically healthy lactating Kushum mares were evaluated in June and classified by age (4–7, 8–11, and 12–16 years) and number of foalings (1–3, 4–7, and 8–11). Body traits were measured once; udder morphometry was available for 30 mares. Milk yield was recorded at 08:00, 10:00, 12:00, 14:00, and 16:00 h on two consecutive days. On Day 2, a 100-mL aliquot was collected after each milking, and the five aliquots were pooled into one 500-mL composite sample per mare; physicochemical composition was available for 40 mares. Age and number-of-foalings effects were evaluated in separate models. Continuous morphometric and physicochemical traits were analyzed by one-way ANOVA with Tukey-adjusted comparisons, with Benjamini–Hochberg false discovery rate (FDR) correction across trait families; two-day milk yield was additionally evaluated with a repeated-measures mixed model. After FDR correction, cannon bone circumference, body weight, udder length, and udder width differed among both age and number-of-foalings groups. Teat shape also differed among groups. The two-day mean daily milk yield did not differ by age (p = 0.483) or number of foalings (p = 0.195), although significant group-by-day interactions were detected. In pooled Day-2 milk, SNF, lactose, glucose, freezing point, acidity, lactic acid, density, and urea differed among both classification factors after FDR correction (q < 0.05), whereas fat, protein, total solids, galactose, citric acid, and casein did not. PCA explained 60.9% of the variance in body/udder traits plus mean milk yield and 68.8% of the variance in physicochemical composition. These findings indicate selective associations of age and number of foalings with Kushum mare phenotype and milk composition, while emphasizing the limitations of small udder subgroups and equal-volume pooled sampling. Full article

The increasing generation of plastic waste has intensified the search for sustainable recycling technologies capable of recovering valuable resources while minimizing environmental impacts. Among emerging solutions, thermochemical recycling processes such as pyrolysis, gasification, and hydrothermal liquefaction have gained significant attention. However, the presence of chlorine-containing polymers, particularly poly(vinyl chloride) (PVC), represents a major challenge due to the release of hydrogen chloride (HCl), catalyst deactivation, equipment corrosion, and contamination of valuable products. Consequently, effective dechlorination pretreatments are essential for improving process performance and product quality. This review provides a comprehensive overview of current pretreatment technologies for chlorine management in plastic solid waste. Mechanical sorting, density-based separation, chemical extraction, alkaline treatments, hydrothermal processing, thermal dehydrochlorination, catalytic methods, and emerging photocatalytic approaches are critically analyzed and compared. The mechanisms, operating conditions, chlorine removal efficiencies, technological readiness levels, and industrial applicability of each method are discussed. Moreover, particular attention will be devoted to integrating different pretreatment technologies to achieve an overall enhanced chlorine removal efficiency before thermochemical technologies. Finally, reported techno-economic, environmental, and safety indicators are compared where quantitative data are available, while the principal data gaps and technological barriers to large-scale implementation are identified. Full article

High-temperature proton-exchange membrane fuel cells (HT-PEMFCs) generate useful thermal energy that can be recovered for additional power production. This study investigates an integrated HT-PEMFC–organic Rankine cycle (ORC) system by combining response surface methodology (RSM) with thermodynamic energy analysis. A 17-run response-surface design was used to quantify the effects of pressure, temperature, and current density on polarization voltage. Power density was derived directly from the RSM-predicted voltage using P_d = iE to preserve physical consistency. The electrochemical model was benchmarked against published phosphoric-acid-doped polybenzimidazole HT-PEMFC polarization data under comparable conditions. The constrained optimization identified an operating condition of 400 kPa, 443 K, and approximately 1.198 A cm⁻², giving a predicted voltage of 0.5395 V and a power density of approximately 0.6462 W cm⁻². This represents a 12.9% increase in power density relative to the adopted reference condition. Separately, the reference thermodynamic case produced 13.08 kW of gross HT-PEMFC stack electrical power and 15.45 kW of thermal output assumed available to the ORC. The available legacy R409A reference case was evaluated at an evaporator pressure of 2 MPa, yielding approximately 1.24 kW of ORC net power and a net thermal efficiency of about 8.02%. The resulting combined modeled electrical output was approximately 14.32 kW before unmodeled balance-of-plant auxiliary power consumption, with the ORC contribution corresponding to about 9.5% of the gross HT-PEMFC stack output. The results demonstrate the complementary potential of physically consistent HT-PEMFC operating-condition optimization and waste-heat recovery, while the ORC results remain specific to the retained R409A reference dataset. Full article

This narrative review summarizes current data on the role of desialylation of low-density lipoproteins (LDL) as a key initiating mechanism of atherogenesis that precedes oxidative modification. The structural and functional significance of sialic acid in apolipoprotein B-100 is considered, and the enzymes of the sialidase (neuraminidase) family responsible for its cleavage are characterized. The pathogenic role of increased sialidase activity in atherosclerosis, type 2 diabetes mellitus, and other diseases is discussed. The advantages of using dietary supplements based on natural sialidase inhibitors for long-term prevention compared with synthetic drugs are shown. Examples of already existing dietary supplements with antiatherosclerotic effects are described. A separate section is devoted to computer methods (molecular docking) for searching for new sialidase inhibitors among flavonoids; according to virtual screening data, gallated catechins were identified as the most promising candidates. The feasibility of further experimental and clinical studies to create effective and safe nutraceuticals that affect the early stages of atherogenesis is substantiated. Full article

HERA-GM separates an offline learned tactical proposal from the authority to execute it. A Dueling Double DQN trained with Conservative Q-Learning proposes one of five tactical actions. The runtime process then uses the action-value margin, semantic feature availability, annotation density, a Mahalanobis diagnostic, and fixed hard-rule conditions to assign ACCEPT, DEFER, or RECOVER. The study separately examined proposer agreement, authority changes, closed-loop outcomes, and held-out-family discrimination. The original frozen evaluation used 113 nuPlan Mini scenarios from 39 logs and 1970 closed-loop runs. An additional exploratory behavior-cloning block added 339 runs. Behavior cloning had slightly higher offline macro-F1 than CQL, whereas DDQN without CQL had much lower agreement under the tested configurations. The main comparison between M1 and the simpler B3 gate showed no supported primary safety difference, indicating limited added endpoint effect from Mahalanobis and hard-rule evidence in this cohort. M1 also showed lower safety-failure and drivable-area violation rates than behavior cloning, but with lower conditional progress; the primary result did not remain below 0.05 after pooled Holm adjustment across the five clean comparisons. The Mahalanobis score did not distinguish held-out semantic families reliably. The findings describe the operating trade-offs and limits of conditional execution authority rather than a safety guarantee. Full article

Weighted directed networks can exhibit stronger aggregate interactions without becoming more integrated or topologically richer. Using daily prices for 32 stock indices over 2006–2026, we construct effective transfer entropy (ETE) networks from range-based variance states and recompute GLMY path homology over a directed edge-density filtration. In 88 overlapping 120-common-date windows, total ETE is associated with a higher density required for global weak connectivity and with smaller integrated first- and second-dimensional Betti curves. These are dependence-aware descriptive associations: reduced-overlap estimates are imprecise, and controls for edge concentration and mean variance reduce the connectivity association to approximately zero. Direct coverage measures show that high-intensity windows can distribute weight broadly while their strongest edges reach nodes unevenly. Exact circular-shift tests yield empty 5% BH-FDR backbones, so individual channels are not treated as established. Null-model, rank-stability, coefficient-field, and discretization checks delimit the fixed-density result. A common absolute-weight contrast yields positive rather than negative TETE–Betti associations, showing that the negative baseline relation is specific to the fixed-density filtration. The results distinguish interaction intensity, dispersion, strong-edge coverage, and directed path-homology organization as separate network dimensions. Full article

Organic-rich shale contains chemically heterogeneous mineral–organic interfaces that produce strong and spatially variable proton surface relaxation, complicating the identification of clay-bound water and the conversion of NMR relaxation time into pore size. Conventional interpretations commonly treat surface relaxivity as a constant, while the respective contributions of water-retaining surface chemistry, molecular restriction, and paramagnetic centers remain insufficiently separated. In this study, Wufeng–Longmaxi shale samples from the Yongchuan Block were investigated using mineralogical and pore structural characterization, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, cation exchange capacity, zeta potential, electron paramagnetic resonance, controlled hydration, one- and two-dimensional low-field time domain NMR, and molecular dynamics simulations. Under the present fluid and acquisition conditions, strongly surface-associated water was operationally identified mainly at T₂ < 1.6 ms and T₁ < 85 ms, while the effective transverse surface relaxivity ranged from 3.6 to 9.1 μm/s. Water retention was more closely associated with cation exchange capacity and surface –OH/O–C environments, whereas relaxation efficiency was controlled more directly by EPR-detectable paramagnetic centers and restricted molecular motion of interfacial water. Simulations of Na-smectite, chlorite, illite, and kerogen-covered illite revealed systematic differences in water density layering, adsorption strength, hydrogen bond persistence, molecular residence, translational diffusion, rotational reorientation, and proton–proton dipolar correlation. A chemistry-informed model combining the EPR-derived paramagnetic center density with a surface area-weighted molecular restriction index explained 86% of the measured relaxivity variation, with an adjusted R² of 0.83 and leave-one-out cross-validation RMSE and MAE values of 0.71 and 0.57 μm/s, respectively. At the core scale, the variable relaxivity interpretation reduced the mean absolute percentage error of characteristic pore diameter from 21.9% to 4.5% and the RMSE of the clay-bound water fraction from 3.4 to 0.4 percentage points relative to the fixed relaxivity method. Transfer to NMR logging further reduced lithology-dependent biases in pore size conversion and clay-bound water partitioning. These results define shale surface relaxivity as an emergent interfacial property arising from coupled magnetic and molecular controls and provide a mechanistic basis for NMR analysis of chemically heterogeneous shale materials. Full article

Reaction control systems (RCSs) provide rapid and effective attitude-control capabilities for high-speed vehicles operating in high-altitude, low-density environments, where conventional aerodynamic control surfaces become inefficient. However, interactions between lateral jets and high-speed crossflows generate complex shock, separation, and vortex structures, which may significantly alter RCS control effectiveness. In this study, the nonlinear coupled constitutive relations (NCCR) model is employed to investigate dual lateral jet interactions over a cone–cylinder vehicle at an altitude of 80 km and a freestream Mach number of 10. The effects of the jet pressure ratio on the normal force coefficient, force amplification factor, moment amplification factor, wall pressure distribution, and flowfield structure are systematically analyzed. The results show that the absolute value of the normal force coefficient increases with increasing jet pressure ratios, whereas both the force and moment amplification factors decrease. At high-pressure ratios, the direct jet thrust becomes dominant and the relative contribution of jet-induced surface aerodynamic forces decreases. A second small-scale high-pressure region is observed between the two jet orifices, which is attributed to the expanded region of influence of the horseshoe vortex. In addition, the enhanced wrapping effect at high-pressure ratios adversely affects the aerodynamic contribution to RCS control efficiency. As the jet pressure ratio decreases from 750–1500 to 25–50, the relative deviations between Navier–Stokes- and NCCR-predicted force and moment amplification factors decrease from 0.019% to 0.262% and from 0.015% to 0.228%, indicating more pronounced rarefaction and non-equilibrium effects at low jet pressure ratios. Full article

Rubber compounds intended for Mars exploration missions must remain elastic at extremely low temperatures while being manufactured in a reliable and energy-efficient manner. In this study, the effect of vulcanization temperature (100–160 °C) on the network structure and properties of butadiene/silicone rubber (BR/VMQ) blends was investigated, comparing a conventional sulfur curing system (REF) with the same system activated by fluoride anion obtained from tetra-n-butylammonium fluoride (TBAF). The fluoride anion acts as an in situ activator of elemental sulfur, through the opening of the S₈ ring, facilitating the crosslinking process at significantly lower temperatures. Fluoride enabled rapid vulcanization at 100–120 °C, shortening the optimum cure time from 129.1 min to 61.4 min at 100 °C and from 36.7 min to 16.9 min at 120 °C. Equilibrium swelling and thiol-amine analysis revealed opposite structural responses to lowered curing temperature: the crosslink density of the reference compounds increased (from 1.25 × 10⁻⁴ to 1.56 × 10⁻⁴ mol/cm³ between 160 °C and 120 °C), whereas that of the TBAF-containing compounds decreased (from 1.32 × 10⁻⁴ to 0.60 × 10⁻⁴ mol/cm³ between 160 °C and 100 °C), yielding networks dominated by elastic polysulfidic crosslinks (up to 97.2%). We attribute this to a suppressed crosslink maturation under conditions of reduced thermal energy and shortened curing time. Low-temperature curing also suppressed the crystallization of the VMQ phase (melting enthalpy decreasing from 1.23 J/g to 0.21 J/g for TBAF compounds), which we hypothesize results from insufficient energy for phase separation and regular chain packing in this strongly immiscible blend. TBAF-cured compounds exhibited lower tanδ peaks, a stable tanδ plateau between approximately −60 °C and +20 °C, a tanδ-peak shift towards lower temperatures with decreasing curing temperature, and higher elongation at break and tensile strength at −40 °C. The results show that low-temperature, fluoride-activated vulcanization is a promising route for tailoring BR/VMQ networks towards stable dynamic performance across the Martian daily temperature range. Full article

A recurrent challenge in scaling ultra-wideband (UWB) motion-capture systems is interference management when many ranging transactions coexist in time and space. To address this, we study a two-layer localization architecture that separates field-level player localization from local on-body pose tracking, allowing the two tasks to operate with different communication regimes and spatial-reuse policies. A stochastic-geometry framework is used to map sport-dependent parameters, including player density, field size, tag count, anchor count, update rates, and ranging airtime, to reliability and update-rate tradeoffs. The analytical model is parameterized using controlled experiments that characterize ranging success under temporal overlap, player distance, and variable-delay scheduling. These measurements inform the design of a proximity-aware local coordination strategy. We apply our proposed approach to soccer, volleyball, and ice hockey as representative use cases. Our results show that proximity-aware coordination can provide a scalable and lightweight interference management mechanism. Coordination is activated only where local player clustering creates strong interference, while spatially separated players continue to share resources without coordination. For the highest-density scenario tested, this increases the local-layer ranging success from below $50\%$ without coordination to over $80\%$ in four- and eight-player congestion clusters, while avoiding network-wide coordination overhead. Full article

The standard interpretation of quantum measurement on entangled systems holds that measuring one particle nonlocally collapses the wavefunction of its spacelike-separated partner. We argue that this conclusion rests on a false presupposition: that subsystems of entangled systems possess independent ontic states. If the global wavefunction is the sole ontic object ($\psi$-ontic holism), then for entangled systems, there is no “state of B” to be affected by measurement at A. Measurement is a local dynamical process—concretely modeled by continuous spontaneous localization—that destroys one local wavefunction component at the measurement site; the global state factorizes as a consequence, and subsystem ontology emerges for the first time. The transition of the distant particle’s reduced density matrix from mixed to pure reflects this emergence of separability, not a physical change at the distant location. The framework satisfies no-signaling and embraces the contextuality required by the Kochen–Specker and GHZ theorems. We are explicit about its relation to Bell’s theorem: Bell local causality (factorizability) fails, as it must in any empirically adequate theory, but the failure is confined to outcome independence and is identified with the nonseparability of the global ontic state, while parameter independence—and with it the locality of the dynamics—holds exactly. Decoherence provides the mechanism by which the global wavefunction factorizes and classical separability emerges. The apparent nonlocality of quantum mechanics is thus reinterpreted as nonseparability: the fundamental ontology is holistic, but the dynamics are local. Full article

The integration of zeolitic imidazolate framework-8 (ZIF-8) into polymer matrices has created a versatile class of nanocomposites with potential applications in gas separation, water purification, food packaging, sensing, catalysis, energy systems, and environmental remediation. However, their performance is governed by complex and strongly coupled variables, including ZIF-8 particle size, morphology, defect density, surface chemistry, filler loading, polymer compatibility, interfacial adhesion, dispersion state, and processing conditions. To organize this complexity, the review introduces a hierarchical design framework that distinguishes controllable synthesis and processing inputs, experimentally measurable intermediate material states, and condition-dependent performance outputs, thereby providing a structured basis for machine-learning-ready data representation. Conventional trial-and-error approaches are therefore often inefficient and provide limited capacity to identify transferable structure–processing–property relationships. This review examines the emerging role of machine learning (ML) in the rational design and optimization of ZIF-8/polymer nanocomposites for sustainable applications. Particular attention is given to the construction of material descriptors, selection of predictive algorithms, interpretation of feature importance, optimization of synthesis and processing parameters, and prediction of mechanical, thermal, barrier, transport, adsorption, catalytic, and antimicrobial properties. The review further discusses how supervised learning, explainable artificial intelligence, active learning, Bayesian optimization, transfer learning, and physics-informed models can support material screening and multi-objective optimization across performance, cost, energy consumption, environmental impact, and end-of-life considerations. Current limitations, including small and heterogeneous datasets, inconsistent reporting, insufficient negative results, limited model interpretability, and weak experimental validation, are critically evaluated. A future framework is proposed that integrates standardized databases, high-throughput experimentation, multiscale characterization, life-cycle indicators, uncertainty quantification, and closed-loop machine learning. Such an approach could accelerate the transition from empirical formulation toward data-driven, interpretable, and sustainability-oriented design of ZIF-8/polymer nanocomposites. Full article

Background/Objectives: Circulating amino acids are not only markers of nutritional status; in experimental and interventional models they have been linked to hepatic lipogenesis, lipoprotein assembly, mitochondrial fatty acid oxidation, and bile acid conjugation, which makes them plausible candidate correlates of obesity-related lipid dysregulation. Despite this, most metabolomic studies of excess adiposity have focused either on a single lipid parameter—typically triglycerides—or only on branched-chain amino acids (BCAAs). This pilot study was designed to generate hypotheses about these associations across the full standard lipid panel using a targeted 19-amino acid liquid chromatography–tandem mass spectrometry (LC-MS/MS) panel in adults spanning the body mass index (BMI) spectrum, with an analytical framework oriented around lipid phenotype variance rather than body weight classification. The design is cross-sectional and the analysis exploratory; no causal or predictive claim is made. Methods: Targeted LC-MS/MS quantification of 19 plasma amino acids was performed in 50 adults grouped as normal weight (n = 20; BMI 22 ± 1.5 kg/m²), overweight (n = 20; BMI 28 ± 1.5 kg/m²), or obese (n = 10; BMI 34 ± 2.0 kg/m²). The analytical framework included: (i) one-way analysis of variance (ANOVA) with Bonferroni correction; (ii) Pearson correlation analysis; (iii) principal component analysis (PCA) performed on the lipid profile itself with amino acid projection vectors; (iv) K-means clustering based on lipid phenotype (K = 3); (v) Ward-linkage hierarchical clustering of the amino acid–lipid correlation matrix; (vi) Random Forest permutation importance for all four lipid outcomes; and (vii) composite lipid risk indices including atherogenic index (TG/HDL-C) and non-HDL cholesterol. Results: A distinct amino acid correlation pattern was observed for each of the four lipid fractions. Triglycerides (TG) correlated most strongly with glutamic acid (r = 0.58) and inversely with glutamine (r = −0.58). High-density lipoprotein cholesterol (HDL-C) correlated most strongly with glutamic acid (r = −0.61) and serine (r = 0.49). The strongest correlates of low-density lipoprotein cholesterol (LDL-C) were phenylalanine (r = 0.56) and leucine (r = 0.56), and those of total cholesterol (TC) were leucine (r = 0.63) and, inversely, glycine (r = −0.54). The atherogenic index (TG/HDL-C) increased 2.9-fold from normal to obese and was most strongly correlated with glutamic acid, isoleucine, and glycine. In the multivariable models the amino acid panel accounted for a modest share of the variance in TG (adjusted R² = 0.43; F(19,30) = 2.97, p = 0.004) and HDL-C (adjusted R² = 0.35; F(19,30) = 2.40, p = 0.016). For LDL-C and TC the adjusted R² values were close to zero (0.06 for both) and the overall models were not statistically significant (both p > 0.33); no interpretable amino acid signal was therefore present for these two fractions, and no predictors are reported for them. Lipid-based K-means clustering identified three lipid-phenotype clusters (Favorable, Intermediate, Adverse lipid profiles) with differences in amino acid z-scores. Conclusions: In this exploratory pilot cohort, lipid dysregulation in abnormal BMI was associated with two partially separable amino acid axes: a glutamic acid–glutamine axis (TG and partially HDL-C), and a glycine–serine putatively protective pattern opposing all atherogenic lipid parameters. These findings extend the established BCAA–insulin-resistance paradigm and suggest that targeted amino acid profiling—particularly for glutamic acid, leucine, glycine, and serine—may serve as a way of discovering candidate biomarkers for further study for dyslipidemia in individuals with abnormal BMI. Full article

Transit-oriented development (TOD) assessment tools were designed largely for dense metropolitan settings and transfer poorly to the dispersed, low-density catchments of intercity railway stations in developing economies, where indicators presupposing high-intensity urban form lose discriminating power and imported criterion weights obscure which dimensions actually drive potential. This study develops an integrated fuzzy multi-criteria framework and applies it to the pre-qualified principal stations of Thailand’s regional railway network. A ten-member expert panel screened a literature-derived indicator pool through a two-round Fuzzy Delphi Method, scoring rules were formalized with a Mamdani-type Fuzzy Logic Method, and importance weights were derived with the Spherical Fuzzy Analytic Hierarchy Process, which preserves expert hesitancy. Density and destination accessibility emerged as the dominant dimensions, with measures of activity concentration carrying the largest global weights. The weighted indicator set was converted into a 100-point assessment guideline and applied network-wide, separating high-, medium-, and low-potential station areas, with regional-center stations ranked highest. Sensitivity analysis shows the ranking is stable under alternative screening thresholds, weighting methods, and panel compositions, so the index is best read as an instrument for screening development readiness rather than a measure of realized TOD performance. Railway operators and local planning authorities can use it to prioritize station-area investment, to sequence interventions by potential level, and to align comprehensive city plans with rail investment programs in regional contexts. Full article