Search Results (9,808)

Graphite nozzles remain the dominant choice for small hybrid and solid rocket motors operating on laboratory and university budgets, owing to their low cost, ease of machining, and rapid turnaround during iterative design campaigns. These same programs, however, must contend with the fact that graphite erodes through coupled thermochemical and mechanical mechanisms when exposed to the oxidizing species generated by high-energy propellant combustion, and the resulting throat-area growth fundamentally alters the time histories of chamber pressure, thrust, and delivered specific impulse. This paper presents a nozzle-erosion reconstruction model that extracts the time-resolved throat area from coupled thrust and chamber-pressure measurements using the thrust coefficient relationship, scales the reconstructed area history against pre- and post-test throat measurements, identifies the onset and rate of erosion, and accounts for variable sensor lag between the thrust-stand and pressure-transducer signal chains. The model is exercised on two complementary sets of laboratory-scale GOX/ABS hybrid hot-fire data that together span roughly two orders of magnitude in total throat-area change and peak chamber pressures from 0.5 to 3.4 MPa: a controlled three-operating-point campaign conducted in support of the NASA Plume-Surface Interaction (PSI) program, and a set of higher-pressure firings from the laboratory development series in which the technique was matured. Reconstructed erosion-onset times, erosion rates, and total throat-diameter change are reported for each firing, the reconstruction accuracy is characterized as a function of erosion magnitude. A correlation of graphite erosion with chamber pressure is examined across the combined envelope. The results demonstrate the robustness of the reconstruction technique and provide a reusable framework for post-test reconstruction of transient nozzle geometry in rocket-engine ground testing. Full article

Consumers are looking for plant-based drinks that provide natural colour and bioactive compounds. Microgreens can be used as a source of pigments and phenolics for such beverages. This study developed a beetroot–tarragon microgreen beverage using hydroalcoholic extracts obtained with a green extraction approach and examined its stability during refrigerated storage. The drink was evaluated for proximate composition, water activity, colour parameters (CIE L*a*b*), microbiological quality and antioxidant activity by the ABTS radical cation decolorization assay (ABTS) over 15 days at 4 ± 2 °C. The beverage showed low fat and energy content and water activity values close to 1.00, so microbiological safety relied on pasteurization and cold storage. Escherichia coli and Staphylococcus aureus were not detected, while total aerobic mesophilic counts reached 10⁴–10⁵ colony-forming units per gram (CFU/g), with slightly lower values in samples containing tarragon. Colour measurements indicated betalain loss and colour fading in the beetroot drink, whereas the reduction in E* was more than 80 percentage points lower in the beetroot–tarragon beverage than in the beetroot-only drink, indicating a strong protective effect of tarragon microgreens on colour stability. For the mixed beetroot–tarragon beverage, mean TEAC increased by about 37% between day 1 and day 10 of refrigerated storage. These results indicate that beetroot and tarragon microgreen extracts can be used to formulate refrigerated plant-based beverages with acceptable colour, microbiological safety and antioxidant capacity. Full article

Plant essential oils are widely utilized as natural preservatives, flavoring agents, and nutritional supplements owing to their remarkable antibacterial, antioxidant, and aroma-enhancing properties. However, their low abundance in plant matrices, together with the compositional complexity and thermal sensitivity of volatile constituents, poses significant challenges for efficient extraction and purification. In recent years, membrane separation technology has emerged as a promising green strategy for the extraction, purification, and concentration of plant essential oils. Membrane-based processes, including microfiltration, ultrafiltration, nanofiltration, reverse osmosis, and pervaporation, enable selective separation under mild operating conditions based on differences in molecular size, polarity, and diffusivity. Compared with conventional thermal- and solvent-based methods, membrane processes offer lower energy consumption, reduced solvent usage, and superior retention of thermolabile bioactive compounds and natural aroma profiles. Moreover, recent advances in membrane materials and surface modification strategies have significantly improved membrane selectivity, permeability, and fouling resistance, thereby enhancing process stability and industrial applicability. This review systematically summarizes the theoretical principles, separation mechanisms, membrane classifications, and recent applications of membrane technologies in plant essential oil processing. Based on a comparative analysis of more than 120 published studies, the performance of different membrane processes is evaluated in terms of flux, selectivity, energy consumption, and product quality. Particular attention is given to current challenges, including the lack of standardized performance metrics and comprehensive techno-economic assessments. Recent advances in membrane materials and surface modification strategies, together with future research directions and industrial prospects, are also discussed. This review provides valuable guidance for membrane selection, process optimization, and sustainable industrial implementation in plant essential oil extraction and purification. Full article

Real-time, non-contact velocity measurement of hot-rolled bars is critical for metallurgical process control, but conventional laser Doppler velocimetry (LDV) systems often fail in these environments. The intense broadband thermal radiation from targets up to 1000 °C, coupled with severe surface depolarization, overwhelms weak scattered signals in high-speed (up to 40 m/s) rolling zones. To address this issue, we developed a fully integrated, thermal-radiation-resistant LDV sensing system. Hardware optimization was achieved by eliminating polarized-light transmission and adopting a parallel-beam design, which significantly enlarges the laser overlap area and increases detection depth. Furthermore, a 1550 nm laser (100 mW) was coaxially combined with a 10 nm narrow-band filter to isolate the thermal background and boost signal strength. A customized workflow utilizing continuous Fourier transform (CFT) spectral refinement and energy centroid estimation was implemented to precisely extract the true Doppler shift. Performance evaluations show the system achieves an excellent signal-to-noise ratio (SNR) of 29,532. Allan variance analysis confirms a stable detection sensitivity of 0.003 m/s (0.1 s integration time), a local short-to-medium-term optimal limit of 1.6 × 10⁻⁴ m/s, and a statistical accuracy of 0.005 m/s. Finally, the system was successfully deployed on an industrial rolling mill production line. It provided reliable velocity feedback for mill speed adjustment, achieving a near-zero-tension rolling process and fundamentally resolving workpiece dragging, squeezing, and steel pile-up. Full article

Background: Inborn errors of metabolism (IEMs) represent a diverse group of genetic disorders affecting biochemical pathways. Despite advances in diagnostic technologies, comprehensive understanding of their historical evolution, classification systems, and diagnostic approaches remains fragmented. Objectives: This systematic review and meta-analysis aimed to synthesize evidence on the historical development, classification frameworks, and diagnostic modalities for IEMs, diagnostic accuracy, and prevalence estimates, providing a comprehensive resource for clinicians and researchers. Methods: Following PRISMA 2020 guidelines, we conducted a systematic search of seven electronic databases (PubMed/MEDLINE, Embase, Scopus, Web of Science, Google Scholar, SciSpace and ArXiv) from January 2000 to March 2026. Studies addressing historical perspectives, classification systems, or diagnostic approaches for IEMs were included. Two independent reviewers performed screening, data extraction, and quality assessment. Meta-analyses were conducted using random-effects models for diagnostic accuracy and prevalence estimates. Results: From 1342 identified records, 54 studies met the inclusion criteria, encompassing 8,234,567 individuals across 35 countries. Historical analysis revealed 16 major milestones from Garrod’s 1902 “chemical individuality” concept to the current AI-powered diagnostics. Four major classification systems were identified: pathophysiological (intoxication, energy deficiency, complex molecule disorders), biochemical pathway (amino acid, organic acid, urea cycle, carbohydrate, fatty acid oxidation, mitochondrial, peroxisomal, lysosomal disorders), organelle-based, and the integrated Society for the Study of Inborn Errors of Metabolism (SSIEM) nosology. Meta-analysis demonstrated high diagnostic performance of tandem mass spectrometry (MS/MS) with a pooled sensitivity of 99.1% (95% CI: 98.6–99.5) and specificity of 99.8% (95% CI: 99.7–99.9%). The pooled global prevalence of IEMs was 50.9 per 100,000 live births (95% CI 45.2–56.8). Next-generation sequencing achieved a diagnostic yield of 42.8% (95% CI: 38.2–47.5%) in suspected cases. Emerging AI-powered diagnostic tools demonstrated high discrimination performance with area under the curve (AUC) values exceeding 0.95 for specific IEM, though external validation remains limited. Newborn screening expanded from single-disease to comprehensive panels detecting over 50 disorders. Conclusions: This comprehensive review demonstrates that IEMs have evolved from rare curiosities to systematically diagnosable conditions through technological advances. Integration of metabolomics, genomics, proteomics and artificial intelligence promises further diagnostic improvements. Standardized classification systems and evidence-based diagnostic algorithms are essential for optimal patient care. Future directions include artificial intelligence-enhanced diagnostics, expanded screening, and personalized medicine approaches. Full article

We present a theoretical study focused on the photoelectron spectrum of near-infrared (NIR) laser-driven ionization of hydrogen atoms by attosecond pulse trains composed of several HHs of the former. We analyze the effects of increasing the intensity of the NIR probe laser to account for the interference of multiple quantum pathways arising from mainbands formed in ionization by the attosecond pulse train within the strong-field approximation (SFA) beyond the commonly used first-order perturbative (in the NIR laser intensity) reconstruction of attosecond beating by interference of two-photon transitions (RABBIT). The structure of the energy bands formed in the photoelectron spectrum is governed by quantum interferences of the photoelectron wave packet released within one optical cycle of the NIR probe laser field—intracycle interference—and by the number of active high harmonic components, leading to higher-order Fourier contributions as a function of the NIR–XUV relative phase delay. We show that Fourier terms can be interpreted in terms of well-defined semiclassical trajectories. Our results demonstrate a significant departure from the standard two-path quantum-interference RABBIT picture, showing that both the phase-dependent oscillations of mainbands and sidebands and the extracted phase delays depend strongly on the probing laser intensity. The predictions of the SFA reveal that the above-threshold ionization bands exhibit systematic splitting and oscillation patterns as a function of the NIR intensity. SFA predictions are compared with results obtained within ab initio solutions of the time-dependent Schrödinger equation (TDSE), showing an excellent agreement, which evidences the minor effect of the Coulomb potential of the remaining ion on the escaping photoelectron for high energy above-threshold ionization. The precise study of the SFA reference phases is essential for the determination of the effect of the Coulomb potential on the escaping photoelectron for what these findings provide new insights into attosecond chronoscopy in the strong-field regime. Full article

Community multi-building energy management is a key approach for reducing carbon emissions from the building sector and alleviating peak grid pressure. However, load coupling among buildings and coordinated energy-storage operation make control-policy design highly challenging. To address the limitation of the standard multi-agent proximal policy optimization (MAPPO) algorithm, in which the centralized critic simply concatenates building observations and therefore struggles to model inter-building interactions, this paper proposes an improved MAPPO algorithm with a multi-head-attention-enhanced centralized critic, referred to as a multi-head-attention MAPPO (MHA-MAPPO). Without changing the decentralized execution framework, the proposed method improves the critic network in three aspects. First, a dual-branch gated embedding module is designed to adaptively fuse local building observations and global interaction information. Second, an interaction-attention path is constructed to explicitly capture pairwise dependencies among buildings through multi-head attention. Third, a context-attention path is introduced to extract high-level community-level global features by means of learnable query vectors. These improvements enable the critic to estimate the joint-state value more accurately and provide more reliable advantage estimates for all agents. Experiments in the CityLearn environment show that, compared with the original MAPPO, MHA-MAPPO improves the mean evaluation reward by approximately 19.2%, reduces the reward standard deviation by one order of magnitude, and decreases peak net load and total net load by approximately 15.4% and 35.5%, respectively. The results verify the effectiveness of multi-head attention for coordinated multi-building scheduling. The proposed method provides a useful reference for improving multi-agent reinforcement learning algorithms in community energy management. Full article

Accurate characterization of wind-speed distributions is essential for preliminary wind-resource assessment, vertical wind-profile evaluation, and energy-yield estimation. This study presents a CFD-assisted reconstruction and validation framework that integrates two-parameter Weibull statistics with class-conditioned OpenFOAM v13 simulations to reconstruct wind-speed distributions at different measurement heights. Hourly wind-speed records measured at 10 m and 30 m at the Sakarya–Esentepe station during the period of 2009–2010 were used. The 2009 dataset was employed to estimate the Weibull shape and scale parameters by maximum likelihood estimation, while the 2010 dataset was reserved for independent validation. To ensure methodological consistency between statistical wind characterization and steady CFD modeling, the fitted Weibull distribution was discretized into representative wind-speed classes. For each class, a steady Reynolds-averaged Navier–Stokes simulation was performed in OpenFOAM under neutral atmospheric boundary-layer assumptions using the standard k–ε turbulence model, a logarithmic inlet velocity profile, and rough-wall boundary treatment. The class-wise CFD velocity responses extracted at 10 m and 30 m were then weighted by the corresponding Weibull class probabilities to reconstruct height-specific wind-speed probability distributions. The reconstructed distributions showed good agreement with the measured and fitted Weibull references. The RMSE values obtained by CFD for measurements at heights of 10 m and 30 m on the measurement mast were 0.45 m s⁻¹ and 0.52 m s⁻¹, respectively, and the Pearson correlation coefficients were 0.97 and 0.96, respectively; these values indicate that the CFD analyses are reliable. For the Lilliefors-adjusted Kolmogorov–Smirnov statistics, there is no value higher than 0.06. The differences between the reference and CFD-reconstructed AEP estimates were +0.40% at 10 m and −1.97% at 30 m. These findings indicate that the proposed Weibull–OpenFOAM framework provides a reproducible engineering approach for CFD-assisted wind-speed distribution reconstruction and height-specific consistency assessment. However, the method should be interpreted as a class-conditioned reconstruction framework rather than a stand-alone transient atmospheric wind prediction model. Full article

The snapshot proper orthogonal decomposition (POD) method relies on synchronously sampled datasets, significantly limiting its utility for analyzing asynchronous measurements in unsteady flow studies. This paper proposes a frequency-domain proper orthogonal decomposition (FDPOD) method tailored for mode extraction and flow field reconstruction from asynchronously sampled data. The FDPOD framework integrates three key components: frequency-domain transformation to decouple phase discrepancies inherent in asynchronous sampling, power spectral density (PSD) analysis combined with segmented ensemble averaging to suppress spectral leakage errors, and eigenvalue decomposition of energy-ranked frequency components to identify dominant coherent structures. Validated through numerical simulations of a subsonic jet and experimental measurements from a low-speed mixed-flow fan, the method demonstrates exceptional performance under asynchronous conditions: cumulative energy errors are reduced to 0.3% across the first 50 modes, while flow field reconstruction achieves 99.5% accuracy. Dominant mode structures exhibit remarkable consistency with those derived from synchronous conditions, with hot-wire measurement errors remaining below 0.03% for both asynchronous and temporally shuffled datasets. These results position FDPOD as a robust and practical tool for analyzing complex unsteady flows where synchronous data acquisition proves impractical, particularly in large-scale or spatially distributed measurement systems. Full article

Background: Urban planning documents at metropolitan scale typically demand large, cloud-hosted language models that limit their adoption in Global South contexts. This study deploys Moondream, a 1.7-billion-parameter vision-language model (VLM) runnable locally via Ollama, for extracting geographic knowledge from Planes Reguladores Comunales (PRCs) across 29 processed Gran Santiago municipalities. The pipeline combines native PDF text extraction, keyword-based multi-label classification across six thematic axes, and VLM-based optical character recognition and cartographic interpretation. Results: The pipeline processes 2289 PRC articles in 4.3 min at an estimated energy cost of 0.000866 kWh and zero marginal monetary cost. Zoning (53.3%) and land use (43.1%) dominate PRC content, while social housing provisions appear in only 4.0% of articles; normative gap analysis identifies five municipalities where social housing is entirely absent from regulatory text. A comparative evaluation of Moondream against keyword baseline on an 88-article validation sample yields macro-F1 = 0.355 and mean Cohen’s κ = 0.004, confirming that generalist VLMs require domain fine-tuning for specialized legal text. It is argued that the cost asymmetry between industrial-scale and small-model approaches constitutes an epistemic asymmetry with direct consequences for the geographic distribution of urban data infrastructure. Full article

Ionic liquids (ILs) are salts that are liquid at or below 100 °C. They are composed entirely of ions and have unique properties like negligible vapor pressure, high thermal stability, and tunable structures. These characteristics make them a promising alternative to traditional, often volatile and toxic organic solvents in the petrochemical industry. They have broad applications in chemical and petrochemical industry processes. Ionic liquids may be applied in the following processes: desulfurization, benzene toluene xylene (BTX) separation, alkylation, and carbon capture units. Two different ionic liquid-based process configurations have been evaluated for BTX separation. It has been found that the process configuration working with 1-ethyl-3methylimidazolium tricyanomethanide ([emim][TCM]) reduces the energy costs and capital expenditures associated with the Morphylane process by 67 and 63%, respectively. It also reduces solvent costs, confirming it as a cleaner alternative. The hydrodesulfurization (HDS) process is operated under harsh conditions, such as high temperature and high pressure and the requirement of a noble catalyst and hydrogen. High-Temperature Hydrogen Attack (HTHA) failure occurs at high temperatures between the gaseous molecular hydrogen contained inside the steel pressure vessel and the carbon atoms located in the steel matrix or in carbides. Methane molecules are produced during this reaction. This phenomenon can consequently lead to a loss of mechanical properties due to surface decarburization and to the formation of defects caused by methane bubbles mainly located at grain boundaries. The application of ionic liquids (ILs) in oil refineries offers significant advantages, such as safety, environmental sustainability, and process efficiency, primarily by serving as versatile alternatives to hazardous traditional solvents and catalysts. Across BTX extraction, carbon capture, and desulfurization/HDS-adjacent service, the recurring barriers are high viscosity, difficult regeneration, solvent cost/inventory and uncertain long-term stability. Full article

Electric bicycles are popular due to their environmental benefits and convenience. However, electric bicycle fires caused by series arc faults remain a serious safety concern. This study focuses on series arc fault identification for electric bicycles under complex operating conditions, covering state of charge (SoC), torque, and speed variations, and simultaneously considers normal state, DC-side series arc fault, and AC-side series arc fault conditions. Five time-domain features, namely root mean square (RMS), standard deviation (STD), skewness (SK), kurtosis (KUR), and current amplitude (CA), and three frequency-domain features, namely amplitude–frequency energy (AFE), amplitude–frequency mean (AFM), and amplitude–frequency kurtosis (AFK), are extracted. An improved principal component analysis (PCA)-based feature fusion method transforms the eight original time–frequency features into a five-dimensional PCA-fused feature representation consisting of PC1, PC2, PC3, fused PC4–PC7, and PC8. The fused features are classified using a radial basis function (RBF)-support vector machine (SVM) model. The proposed method achieves 98.68% test accuracy, 0.9869 Macro-F1, and 0.9931 Macro-AUC. A classifier comparison and feature-level latency analysis are also provided to clarify the accuracy–cost tradeoff and deployment feasibility. The results indicate that the proposed method can provide an interpretable and lightweight solution for electric bicycle controllers, battery management systems (BMSs), and onboard safety-monitoring applications. Full article

Lithium has become one of the key raw materials for the energy transition due to the central role of lithium-ion batteries in electromobility, energy storage, and the integration of renewable energy sources. However, the rapid increase in demand reveals growing environmental, social, geopolitical, and market tensions. The aim of the paper is a critical synthesis of global lithium utilization from the perspective of challenges, technological innovations, and integrative strategies supporting a more sustainable material–energy system. A broad, systematic literature review covering the entire value chain was applied: resources, extraction, processing, end-use applications, second life of batteries, recycling, and governance. The analysis shows that the strategic importance of lithium arises from the increasing demand pressure from electric vehicles and stationary storage, while the sustainability of the current model is constrained by supply concentration, uneven control over downstream stages, the water–carbon footprint of extraction and processing, social conflicts, and incomplete integration of secondary loops. At the same time, innovations such as direct lithium extraction (DLE), recovery from geothermal brines, design for recycling, second life, and battery passports can partially alleviate these tensions, but they do not eliminate the need for primary supply in the short term. The conclusion of the work is that sustainable global lithium utilization requires simultaneous diversification of sources, development of circular value chains, and multi-level governance integrating resource security, environmental efficiency, and social legitimacy. Full article

Background: Spinopelvic dissociation secondary to sacral fracture–dislocation is a rare but severe injury, most often resulting from high-energy trauma. Management remains challenging, particularly in adolescents, and the optimal choice between open and percutaneous fixation is still debated. Methods: We present two adolescent cases of traumatic sacral fracture–dislocation with spinopelvic dissociation, one treated with percutaneous fixation and one with open lumbopelvic stabilization both with the use of navigation. The systematic literature review included 29 published studies. Together with the present two-patient case series, the overall analysis comprised 30 studies/series and 739 patients. Data on demographics, mechanisms of injury, neurological involvement, treatment strategies, and outcomes were extracted and analyzed. Results: Case 1 (18 years) was managed with closed reduction and percutaneous fixation, achieving complete neurological and functional recovery at 6 months. Case 2 (14 years) underwent open reduction, decompression, and lumbopelvic fixation, with favorable radiological outcomes but residual sphincter dysfunction at follow-up. In the literature, the weighted mean age was 40.6 years (range 5–91), with 48.6% presenting neurological deficits, most frequently cauda equina syndrome. Surgical management was performed in nearly all cases, with mean time to fixation ranging from 3.6 to 8.6 days. Open techniques were predominantly used in patients with severe displacement or neurological compromise, whereas percutaneous fixation was associated with reduced surgical morbidity and satisfactory neurological recovery in selected patients. Permanent bladder and bowel dysfunction persisted in up to 33% of cases. Conclusions: Spinopelvic dissociation following sacral fracture–dislocation remains a rare and highly unstable injury with frequent neurological impairment. Early surgical stabilization may be beneficial when the patient’s clinical condition permits, and the choice between open and percutaneous fixation should be individualized according to fracture morphology, neurological status, and the need for direct decompression. Our adolescent cases highlight both the potential for complete recovery and the risk of residual dysfunction, reflecting the complexity of these injuries. Full article

Onion peel extract (OPE) is rich in polyphenolic compounds with antimicrobial potential. Salmonella Enteritidis (SE) infection in young broiler chicks causes morbidity, reduced growth, and contributes to human gastroenteritis through contaminated poultry products. The spleen is a key secondary lymphoid organ coordinating systemic responses to pathogens in chicken. This study evaluated how dietary OPE influences spleen metabolic profiles during SE infection. Day-old Ross 708 male chicks (n = 128) were assigned to four treatments: CON, CON-SE, OPE (6 g/kg), and OPE-SE. Chicks in CON and OPE received sterile broth, whereas CON-SE and OPE-SE received 2.25 × 10⁸ CFU/mL SE at 2 d of age. At 5 and 12 dpi, spleens from six chicks per treatment were collected for untargeted HPLC-MS metabolomics. A total of 857 metabolites were identified and analyzed using MetaboAnalyst 6.0 (p < 0.05; fold change ≥ 2.0; VIP score > 1.0). In CON-SE chicks, energy generating metabolites (6-phosphogluconic acid, methylmalonic acid, propionic acid) increased, while 13,14-dihydro-15-keto-prostaglandin D2 and kynurenic acid decreased. Dietary OPE elevated several dipeptides (L-Val-Gly, L-Leu-Gly, Gly-Gly-Leu, L-Val-L-Met) and reduced ATP linked metabolites (3,6-di-O-methyl-beta-D-glucose and 3-O-beta-D-galactosyl-sn-glycerol). Enrichment analysis showed that SE infection altered valine, leucine, and isoleucine degradation and aromatic amino acid biosynthesis, whereas OPE enriched galactose and biotin metabolism in uninfected chicks, but enriched tryptophan, taurine and hypotaurine metabolism in SE-infected chicks. Overall, dietary OPE optimized response of metabolic pathways associated with immune activation, unlike corresponding pathways in CON-SE birds. Full article