Search Results (4,656)

For the first time, the hole mobility values for benzo[f]- and naphtho[1,2-f]-annelated [¹,²,⁵]oxadiazolo[3,4-b]thieno[3,2-h]quinoxalines were determined experimentally by using the space-charge-limited current method. Analysis of the X-ray diffraction data for naphtho[1,2-f][¹,²,⁵]oxadiazolo[3,4-b]thieno[3,2-h]quinoxaline revealed significant π–π stacking, which may be attributed to enhanced electron mobility. These findings are further supported by the observed low hole conductivity values, which reached 4.10 × 10⁻⁹ cm²·V⁻¹·s⁻¹. Therefore, polycyclic compounds based on the furazano[3,4-b]pyrazine core can be considered a convenient scaffold for developing both electron and hole transport materials in various organic photovoltaic devices. Full article

The homochirality of biomolecules motivates the search for chiral surfaces capable of enantioselective recognition, yet systematic links between amino acid functional-group geometry and adsorption on chiral inorganic nanocrystals (NCs) remain limited. Here we investigate the enantioselective adsorption of asparagine, serine, and histidine onto intrinsically chiral Λ- and Δ-TbPO₄·H₂O NCs, which crystallize in a monoclinic (pseudo-hexagonal) structure. Individual-enantiomer adsorption isotherms and enantiomeric excess (ee) from racemic mixtures were determined using circular dichroism spectroscopy combined with potentiometric titration. Adsorption of single enantiomers followed the Langmuir model at low coverage, with L-enantiomers preferring Λ-NCs and D-enantiomers preferring Δ-NCs; matched chiral pairs showed roughly twofold higher equilibrium constants than mismatched pairs. At relatively high surface coverage, the adsorption behavior deviated from the Langmuir model and fitted the Frumkin model, which contains lateral attraction between adsorbed molecules. Enantioselectivity was highest at low racemate concentrations and declined with increasing total racemate concentrations, mirroring trends previously found for tartaric acid and aspartic acid on the same NCs. Tb³⁺–Tb³⁺ spacings on the dominant facets closely matched intramolecular functional-group distances in the amino acids, supporting a three-point chiral recognition mechanism. Full article

Urban road networks in Sub-Saharan Africa diverge from the sensor-rich, lane-disciplined environments conventional models assume. This paper establishes an empirical baseline of network efficiency and velocity decay along the 8.0 km Mile 17 to Governor’s Roundabout corridor in Buea, Cameroon, marked by a 25 m/km inbound gradient, unsignalized intersections, and a taxi share of 59.55% inbound and 65.27% outbound. Fifteen-minute PCU counts were recorded at three points across three peak windows over three consecutive weekdays (1–3 April 2026), yielding 18 h of counts and 36 floating-car GPS runs. Volume-to-capacity ratios (v/c), Peak Hour Factors, and space-mean speeds were derived for both directions, with SD, coefficient of variation, and 95% confidence intervals computed to quantify sampling uncertainty. Results show near over-saturation (v/c: 0.98–1.06) at Bonduma, particularly during the afternoon outbound window. However, the 95% confidence intervals span v/c = 1.00, indicating significant uncertainty in Level of Service classifications. Mean Travel Time Ratios ranged from 1.10 to 2.04. At Bonduma in the evening, an elevated Informal Transport Disruption Factor (ITDF = 0.96) co-occurred with only moderate volume (v/c = 0.87), consistent with, though not proof of, informal-transport-related delay. Finally, the paper introduces two new indicators, the Directional Flow Asymmetry Index (DFAI) and Corridor Velocity Decay Rate (CVDR), to quantify directional imbalances that standard v/c analysis misses. Alongside the ITDF, these metrics serve as empirical calibration inputs for a future reinforcement learning traffic control framework (BACATC). Because no AI controller was built or evaluated in this study, the findings establish a quantified field baseline rather than a demonstration of AI-based control. Full article

This article establishes a strong averaging principle for a class of slow-fast stochastic evolution systems that incorporate both McKean–Vlasov interactions and multivalued operators within a Hilbert-space variational framework. The slow variable $\upsilon$ evolves according to a Caputo fractional differential law of order $\varrho \in (0,1)$ and is driven by fractional Brownian motion (fBm) with Hurst index $H_1\in (1/2,1)$, interpreted as scalar or cylindrical according to the underlying state space, while the fast variable $\nu$ follows a standard Brownian-driven stochastic differential equation. This hybrid formulation preserves the memory effects and long-range dependencies of the slow dynamics while maintaining the Markov property of the fast subsystem, which is essential for the averaging argument. The analysis relies on a weighted Volterra–Young estimate for singular stochastic convolutions. Since $H_1>1/2$, the stochastic integral in the slow equation is interpreted pathwise in the Young sense rather than in the Itô sense. In contrast, the fast equation, driven by standard Brownian motion, is interpreted in the usual Itô sense, preserving its Markovian structure essential for the ergodic averaging argument. Under explicit Hölder, monotonicity, coercivity, compactness, and integrability assumptions, well-posedness is proved via a Hölder-space fixed-point argument combined with variational approximation and maximal-monotone limit identification. A key technical contribution of this work is the rigorous treatment of the multivalued fractional equation: an $L^{q^{\prime }}$-integrable measurable selector $\mathfrak{a}$ for the subdifferential term is constructed by identifying it as the weak limit of the regularized Yosida operators, and its membership in the multivalued graph is established through a Minty argument that requires a limsup inequality rather than merely weak convergence. Subject to the standard ergodicity of the Brownian-driven fast variable, strong convergence of the slow component to the solution of the averaged fractional equation is proved. The averaging principle is established for $\varrho \in (1/2,1)$. This restriction arises from the singular block-integral estimate used in the proof, which requires $\varrho >1/2$; the case $\varrho \le 1/2$ is therefore beyond the scope of the present argument and is left for future work. To demonstrate the broad applicability of the abstract framework, the general results are applied to two important classes of fractional stochastic systems. The first consists of finite-dimensional fractional slow-fast McKean–Vlasov (SF-MV) stochastic variational inequalities (SVIs), including reflected stochastic systems in convex domains as an important special case. The second consists of fractional SF-MV multivalued stochastic partial differential equations (SPDEs). For both classes, explicit averaging rates are obtained under suitable Lipschitz assumptions. Full article

Background: Single-time-point cerebrospinal fluid (CSF) volume proportion (pCSFV) has shown limited prognostic utility after out-of-hospital cardiac arrest (OHCA). We hypothesized that serial within-patient change in pCSFV (ΔpCSFV), rather than absolute values, would reflect progression of neurologic injury. Methods: This retrospective 72–96-h landmark cohort study included comatose adult OHCA survivors who underwent brain computed tomography (CT) within 6 h (early) and at 72–96 h (delayed) after return of spontaneous circulation. pCSFV was quantified using Hounsfield-unit-based volumetry. ΔpCSFV was calculated as delayed pCSFV minus early pCSFV. The primary outcome was poor 6-month neurologic outcome (Cerebral Performance Category 3–5). Results: Among 125 patients, 63 (50.4%) had poor neurologic outcomes. Early and delayed pCSFV did not differ significantly between outcome groups, whereas ΔpCSFV was lower in the poor-outcome group (p < 0.001). In the five-parameter multiple-imputation model, ΔpCSFV was associated with poor outcome (adjusted odds ratio [aOR] 0.684 per 1 percentage-point increase, 95% confidence interval [CI] 0.494–0.947; p = 0.022), with a consistent result in the complete-case sensitivity analysis (aOR 0.648, 95% CI 0.446–0.940; p = 0.022). However, this association was attenuated after additional adjustment for early pCSFV (aOR 0.728, 95% CI 0.462–1.146; p = 0.170). Adding ΔpCSFV to the baseline model did not significantly improve discrimination (area under the curve 0.962 vs. 0.955; p = 0.292). Conclusions: ΔpCSFV may provide complementary information on serial CSF-space changes but should not be interpreted as a baseline-independent marker. These findings apply only to patients who survived and underwent delayed CT at 72–96 h. The observed data-derived cutoff is exploratory and requires external validation before any clinical application. Full article

This study investigates the highly selective synthesis of ethanol from methanol, CO₂, and H₂ over a Ru-Co bimetallic catalyst, focusing on reaction condition optimization, kinetics, scale-up feasibility, and catalyst stability. The optimal reaction conditions were identified as 170 °C, a (CO + CO₂)/H₂ initial pressure ratio of 1:13.33, a CO/CO₂ initial pressure ratio of 1:3, a methanol/catalyst solution mass ratio of 1:18.96, and a reaction time of 1~4 h, at which the space–time yield (STY) of ethanol exceeded 2 g·L⁻¹·h⁻¹ while the ethanol selectivity remained above 93%. Kinetic analysis confirmed the methanol–CO hydrogenation pathway (E_a = 43.42 kJ·mol⁻¹) as the dominant route for ethanol formation, with the reverse water–gas shift (RWGS) reaction serving as the temperature-sensitive key step for in situ CO generation. Scale-up from a 20 mL to 3 L reactor showed similar catalytic performance. Notably, the catalyst showed excellent long-term stability over 30 recycling runs (150 cumulative hours). This work provides a mild, efficient, and scalable route for ethanol production from CO₂ and methanol, aligned with carbon neutrality strategies. Full article

Wind power expansion in the Brazilian Northeast faces two mutually reinforcing difficulties: the best-resource areas are progressively being occupied by operating projects, and the grid-connection cost has become comparable to the cost of the turbines themselves. Treating site selection and layout optimization as separate problems, which is the dominant practice in the literature, leads to suboptimal solutions under these conditions. This paper proposes Wind Farm Swarm Optimization (WFSO), a bi-level formulation based on Particle Swarm Optimization that unifies both problems in a single search loop: the outer level moves the centroids of candidate farms in continuous space, while the inner level optimizes the turbine layout of each candidate. Both levels share the levelized cost of energy (LCOE), which endogenously incorporates the connection cost, automatically selecting from among the available scenarios, and the interference zones of existing wind turbines. The methodology was validated on a benchmark case with a known optimum and applied to a 3500 km² region in Rio Grande do Norte, Brazil, using real resource, constraint, and infrastructure data. Four outer-PSO settings, spanning 1300 to 20,200 objective-function evaluations, converged to the same region and connection point, with a reference LCOE of 249.64 R$/MWh under a common seed. Repeated runs with independent seeds reveal a bimodal objective landscape whose success rate is governed by the evaluation budget: from about 11,400 evaluations, every seed reaches the best basin, and a configuration that is executable in 3.6 h stays within 0.27% of the 38.6 h reference. A sequential siting-then-layout baseline built with the same inner optimizer reaches an LCOE 9.4% higher, and on a reduced benchmark the method matches the optimum verified by exhaustive enumeration in 10 out of 10 seeds, which makes the tool practical for prospecting campaigns covering multiple areas. Full article

Though many food systems on Earth offer benefits to space travelers, their ability to meet the demands of spaceflight remains unestablished. This study examines the application of magnesium oxide-coated halloysite nanotubes (MgO-HNTs), synthesized via electrodeposition, to enhance seed germination and early plant development under Earth, lunar, and Martian soil conditions. Successful surface modification was confirmed by scanning electron microscopy. Growth experiments with Heirloom Cherry Tomato and Golden Tomato seeds were conducted under hydroponic and soil-based conditions and subsequently extended to lunar and Martian regolith simulants. A Response Surface Methodology approach, based on a Box-Behnken Design, evaluated the effects of temperature, MgO-HNT concentration, and light duration on multiple growth responses, identifying seedling length and the root length stress tolerance index (RLSI) as the most responsive indicators of treatment. Optimal conditions (25 °C, 12 h photoperiod, 100 mg/mL MgO-HNTs) produced the greatest increases in root and shoot length in Earth soil. In lunar regolith, optimal root development occurred at 100 mg/mL (root length: 17.7 mm, shoot length: 5.08 mm, RLSI: 141.1%, germination: 80%), whereas Martian regolith peaked at 10 mg/mL (root length: 12.3 mm, shoot length: 4.28 mm, RLSI: 167.9%, germination: 100%), which may be associated with differences in the physicochemical properties of the two substrates. These findings offer preliminary evidence that MgO-HNTs can enhance early plant development across terrestrial and extraterrestrial substrates. As this study was limited to a single crop species under short-term, controlled laboratory conditions without direct physiological or biochemical biomarker measurements, further validation will be required to support broader agricultural or in-situ resource utilization (ISRU) applications. Full article

Small gases pose an unusual problem for studies of molecular transport in proteins. O₂, CO, H₂, and NO can cross short-lived internal spaces opened by protein fluctuations, often faster than experiments can follow continuous migration. Time-resolved crystallography can localize sufficiently populated intermediates, whereas spectroscopy, isotope exchange, and kinetic measurements report molecular exchange over their respective timescales without resolving the complete route. Pressurized noble-gas structures expose internal accommodation sites but rely on surrogate molecules whose size and interactions differ from those of physiological gases. Geometry-based tunnel searches identify available space, while molecular dynamics follows explicit movement through a fluctuating protein. Free-energy and enhanced-sampling approaches can access states or transitions that remain undersampled in direct trajectories. These techniques resolve different quantities rather than progressively more accurate estimates of gas transport. In this Perspective, we argue that gas-migration pathways should be evaluated by the physical consistency of independent observables, with each method interpreted according to the quantity it resolves. This distinction explains why a cavity visible crystallographically may not carry substantial flux, why a rapidly crossed route can remain structurally inconspicuous, and why static narrowing can alter diffusion without predicting its magnitude. Agreement among methods can support a transport assignment when the quantities they resolve are physically consistent with the same mechanism; apparent disagreement may instead reflect differences among occupancy, accessibility, residence, energetic preference, and molecular traffic. Full article

Background/Objectives: Transdermal delivery of hydrophilic drugs remains limited by poor partitioning into the lipid-rich stratum corneum (SC). This study systematically investigated how ternary nanoemulsion composition and surfactant architecture jointly influence the transdermal delivery of salbutamol and whether the resulting composition–performance relationships are preserved across different skin models. Methods: Salbutamol-loaded nanoemulsions were prepared by the phase inversion temperature (PIT) method across a predefined ternary design space using two non-ionic surfactant systems: polyoxyl castor oil and polyoxyl hydroxystearate. Physicochemical characterization, ternary compositional mapping, in vitro permeation testing, generalized additive modeling (GAM), and attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy were combined to evaluate formulation-dependent transport across pig and mouse skin models, complemented by exploratory human-skin experiments. Results: Among the nanoemulsion formulations, pig skin showed the highest salbutamol permeation, with flux values reaching approximately 390 µg/cm²·h. Within the PHS-based system, mouse skin showed lower permeation and a stronger dependence on formulation composition than pig skin, while the simple aqueous vehicle also produced comparatively low permeation in the murine model. The aqueous-vehicle control produced substantially higher permeation than the nanoemulsions in pig skin but lower permeation in mouse skin, while receptor-phase salbutamol concentrations remained below the limit of quantification in human skin. Across both surfactant systems, the most favorable nanoemulsion-mediated permeation was generally associated with water-rich formulations containing comparatively low surfactant levels, whereas highly surfactant-rich regions showed reduced flux despite marked lipid- or protein-associated spectral changes in the descriptive ATR-FTIR analysis. Regression analyses suggested that droplet size and viscosity alone could not consistently explain permeation behavior, whereas compositional modeling revealed pronounced non-linear effects of the water–surfactant–oil balance. Conclusions: Overall, this study demonstrates that nanoemulsion-mediated delivery of hydrophilic drugs is governed primarily by ternary composition, with formulation effects varying across skin models. These findings highlight the importance of composition-based formulation design and appropriate skin-model selection during the development of transdermal systems for hydrophilic drugs. Full article

Selecting three-way catalysts (TWCs) solely from precious-metal loading or a single light-off metric may not reflect the broad operating domain encountered by plug-in hybrid electric vehicles (PHEVs). This study linked bench-scale conversion characteristics of three aged, Pt-free Pd-Rh formulations to cycle-level emissions. The formulations represented a low-loading baseline (TWC-1), a proportional increase in Pd and Rh (TWC-2), and a higher-loading Pd-rich strategy (TWC-3). Light-off, temperature–space-velocity, and λ-sweep data were incorporated into coupled vehicle, engine-out emission, catalyst thermal, and aftertreatment models for Worldwide Harmonized Light Vehicle Test Cycle (WLTC) and Real-driving Emission (RDE) evaluation. The formulation ranking varied with the test boundary. At 30,000 h⁻¹, TWC-3 exhibited the lowest CO light-off temperatures, whereas TWC-2 achieved the lowest T50 values for C₃H₆ and NO. At 50,000 h⁻¹ with its corresponding inlet composition, TWC-2 produced the lowest T50 and T90 values for all three species. Across the broader operating domain, TWC-1 deteriorated most when lower temperature coincided with higher space velocity, while the higher-loading Pd-rich strategy provided no consistent advantage for C₃H₆ or NO conversion. The WLTC emphasized light-off and intermediate-temperature activity, whereas the predominantly hot RDE profile included space velocities above 200,000 h⁻¹. Relative to TWC-3, TWC-2 reduced predicted TWC-out CO and NO_x emissions by 10.0% and 4.1% over the WLTC and by 36.4% and 18.8% over the RDE profile, respectively, while producing the lowest cycle-integrated THC emissions. These results demonstrate that the highest precious-metal loading does not necessarily provide the best cycle-level emission control. Linking formulation-specific conversion characteristics with cycle-dependent operating-domain distributions provides a more representative basis for TWC selection than a single light-off metric. Full article

This study investigates the optimization of airflow distribution and pressure drops in H14 HEPA minipleat filters through the introduction of the hot-melt cell as the fundamental hydraulic unit governing local flow behavior. A coupled analytical framework integrating Falkner–Skan boundary-layer theory, Darcy–Weisbach channel friction, and Darcy porous-medium flow was developed and experimentally tested using velocity measurements obtained in a 600 m³/h test bench operating at a frontal velocity of 0.45 m/s under laminar-flow conditions. Ten primary geometric configurations and 21 hot-melt distribution scenarios (totaling 31 cases plus an optimized design case) were systematically evaluated by varying cell width (W), inlet height (H_i), and pleat length (L). Experimental and analytical results reveal significant velocity heterogeneity in the vicinity of the filter surface, which progressively decreases with distance from the filter, while localized velocity amplification is observed near the hot-melt separators. The analysis demonstrates that hydraulic diameter, pleat angle, and hot-melt spacing are the dominant parameters governing pressure drop generation and flow redistribution. Among the configurations investigated, a model-predicted optimized design (W = 46.25 mm, L = 55.00 mm, 230 pleats) yields a theoretical pressure drop reduction of up to 29.23% without significantly compromising the effective filtration area. These results provide an analytical framework for pre-prototyping optimization, although experimental verification of physical prototype validation for mechanical integrity and the preservation of initial efficiency, among other governing physical quantities, remains essential. The results demonstrate that the proposed hot-melt cell concept provides a practical engineering framework for the aerodynamic optimization of minipleat HEPA filters, enabling improved flow uniformity and reduced energy consumption in cleanroom applications. Full article

In an agrivoltaic plot, the hourly panel tracking angle governs electricity, on-site economics, avoided carbon dioxide, irrigation demand and crop yield. Operating for photovoltaic output alone discards that space, and does so when a midday kilowatt-hour has lost its value: 715 h of the studied season carried a non-positive export price, 517 of them at midday. This work formalizes the electrical operating layer of a mechanistic hourly simulator as nine panel-orientation modes, each a constrained program solved deterministically by sequential quadratic programming, a dense angular scan, or both. Two modes keep an energy-proportional objective non-degenerate through an adaptive clean-grid switch and an economics–carbon weighting anchored on the crop. The catalog is a framework, demonstrated over a 153-day season on a 66 kWp single-axis sage (Salvia officinalis) plot near Valencia, Spain. Seasonal photovoltaic energy ranged from 57.0 to 31.9 MWh, plot-mean relative yield from 95% to 109%, and worst-plant protection from 61% to 94%. Energy maximization sits at a flat extreme of the frontier: the Pareto mode gained 11.4 yield points and 31 worst-plant points for 1.1% less energy. Avoided carbon dioxide varied by 2.1% across the nine modes, so a carbon objective is degenerate with energy without an interior term. Full article

Spatiotemporal prediction of groundwater quality is of great significance for regional water environmental safety assessment, pollution risk identification, and urban groundwater resource management. To address the difficulty of existing methods in simultaneously characterizing multi-indicator coupling relationships, temporal evolution processes, and spatial heterogeneity, this study proposes a spatiotemporal groundwater quality prediction model under multi-indicator coupling constraints. First, indicators including dissolved oxygen, total nitrogen, electrical conductivity, dissolved organic carbon, pH, permanganate index, and total phosphorus are uniformly mapped into a risk space to construct an integrated groundwater quality risk index. Then, based on monthly groundwater monitoring data from Yiyang City during 2000–2023, continuous regional grid sequences are generated. In terms of model design, the Temporal Difference Interaction Module (TDIM) is introduced to enhance multi-scale temporal variation modeling, Region-Guided Feature Modulation (RGFM) is used to strengthen regional heterogeneity representation, and Spatiotemporal Boundary-Aware Loss (STB Loss) is adopted to maintain spatiotemporal boundary consistency. The experimental results show that the proposed method achieves a Structural Similarity Index Measure (SSIM) of $0.9814\pm 0.0085$, a Peak Signal-to-Noise Ratio (PSNR) of $40.47\pm 2.19$, a Mean Absolute Error (MAE) of $2.80\times {10}^{-3}\pm 1.50\times {10}^{-3}$, and a Root Mean Square Error (RMSE) of $9.70\times {10}^{-3}\pm 2.69\times {10}^{-3}$, outperforming comparison models overall and providing effective support for dynamic groundwater quality prediction and water environmental safety assessment. Full article

Consecutive warm nights during heatwaves erode the cooling potential of night ventilation (NV), making its effectiveness strongly dependent on both the event and the building conditions. This study quantified the nonlinear effects of heatwave morphology, building thermal mass (TM), and NV strategies on multidimensional thermal responses and identified the operating conditions associated with ventilation performance. Using a 1991–2020 climatological baseline, 36 heatwaves were characterized by eight morphology indicators. A total of 18,000 EnergyPlus simulations examined combinations of three TM levels, two ventilation configurations, window-to-wall ratios (WWRs) ranging from 0.10 to 0.70, openable fraction, and opening schedules. Six indicators captured daytime peaks, persistent overheating, peak temperature lag, nighttime overheating, thermal recovery, and nighttime cooling rate (NCR). Machine learning models were used to identify the governing mechanisms and delineate ventilation strategy regimes. All models achieved R² values above 0.96 under case-level testing, while event-level performance varied across responses. Increasing TM lowered the median daytime peak temperature by 4.5 °C under cross-ventilation but did not improve every response. Predicted daytime peak risk increased sharply when the mean daily minimum temperature exceeded about 27.0 °C. Ventilation configuration also reversed the effects of opening time, duration, and WWR, precluding a single optimum that is independent of heatwave and building conditions. Effective cooling, operationally defined as positive predicted NCR, was generally associated with earlier opening and longer ventilation. Under single-sided ventilation, achieving stable positive predicted NCR generally required ventilation durations longer than approximately 4 h for buildings with low TM and longer than 6 h for those with medium TM. Under cross-ventilation, the corresponding effective domain in the strategy space contracted markedly, and no stable region with positive predicted NCR emerged for buildings with high TM. These findings support a shift from fixed window opening rules to control strategies tailored to heatwave characteristics and building thermophysical properties. The framework provides a basis for natural ventilation operation informed by forecasts, passive cooling retrofits, and thermally resilient building design. Full article