Search Results (13,951)

One-shot devices are products that can only be used once. Typical one-shot devices include airbags, fire extinguishers, inflatable life vests, ammo, and handheld flares. Most of them are life-saving products and should be highly reliable in an emergency. Quality control of those productions and predicting their reliabilities over time is critically important. To assess the reliability of the products, manufacturers usually test them in controlled conditions rather than user conditions. We may rely on public datasets that reflect their reliability in actual use, but the datasets often come with missing observations. The experimenter may lose information on covariate readings due to human errors. Traditional missing-data-handling methods may not work well in handling one-shot device data as they only contain their survival statuses. In this research, we propose Multiple Imputation with Unsupervised Learning (MIUL) to impute the missing data using Hierarchical Clustering, k-prototype, and density-based spatial clustering of applications with noise (DBSCAN). Our simulation study shows that MIUL algorithms have superior performance. We also illustrate the method using datasets from the Crash Report Sampling System (CRSS) of the National Highway Traffic Safety Administration (NHTSA). Full article

This study investigates the tribological properties of graphite foils (GF) with densities of 1.0, 1.3, and 1.6 g/cm³, produced from purified natural graphite of different particle sizes (40–80 μm, 160–200 μm, >500 μm). Surface roughness was measured after cold rolling and friction testing at static (0.001 mm/s) and dynamic conditions (0.1 Hz and 1 Hz). Results showed that static friction tests yielded similar roughness values (S_a ≈ 0.5–0.7 μm, S_q ≈ 0.5–1.0 μm) across all densities and particle sizes. Dynamic friction tests revealed increased roughness (S_a from 0.7 to 3.5 μm, S_q from 1.0 to 6.0–7.0 μm). Friction coefficients (µ) decreased with higher sliding speeds, ranging from 0.22 to 0.13. GF with 40–80 μm particles had the lowest friction coefficient (µ = 0.13–0.15), while 160–200 μm particles had the highest (µ = 0.15–0.22). Density changes had minimal impact on friction for the 40–80 μm fraction but reduced friction for the 160–200 μm fraction. Young’s modulus increased with density and decreased with particle size, showing values from 127–274 MPa for 40–80 μm, 104–212 MPa for 160–200 μm, and 82–184 MPa for >500 μm. The stress–strain state in the graphite foil samples was simulated under normal and tangential loads. This makes it possible to investigate the effect of the anisotropy of the material on the stress concentration inside the sample, as well as to estimate the elasticity modulus under normal compression. Structural analyses indicated greater plastic deformation in GF with 40–80 μm particles, reducing coherent-scattering region size from 28 nm to 24 nm. GF samples from 160–200 μm and >500 μm fractions showed similar changes, expanding with density increase from 18 nm to 22 nm. Misorientation angles of GF nanocrystallites decreased from 30° to 27° along the rolling direction (RD). The coherent scattering regions of GF with 40–80 μm particles increased, but no significant changes in the coherent scattering regions were observed for the 160–200 μm and >500 μm fractions during dynamic friction tests. Microstrains and residual macrostresses in GF increased with density for all fractions, expanding under higher friction-induced loads. Higher values of both stresses indicate a higher level of accumulated deformation, which appears to be an additional factor affecting the samples during friction testing. This is reflected in the correlation of the results with the roughness and friction coefficient data of the tested samples. Full article

Polymer grouting materials are increasingly used in the filling of mine fissures. Unlike conventional inorganic grouting materials, the self-expansion of polymers adds complexity to their diffusion process within the crack. The objective of this research was to examine how polymer grouting material spreads in cracks at ambient temperatures and pressure. The investigation involved conducting grouting tests and performing numerical fluid simulation calculations using the finite-volume method in the computational fluid dynamics software, ANSYS FLUENT 2022 R1. The fluid volume approach was employed to determine the boundary between fluid and air and to ascertain the variation patterns of density in the slurry and the fracture system. This study applied the principles of fluid mechanics to investigate the patterns of variation in the physical characteristics of polymer grouting materials, including their density, pressure, flow velocity, and movement distance, during the diffusion process. The results indicated that the density of the polymer grouting material decreased exponentially over time throughout the diffusion process. With the increase in the grouting’s volume, the grout’s pressure and the permeable distance of the grout increased. The slurry’s pressure near the grouting hole exceeded the other points’ pressure. The physical parameters of the slurry were numerically simulated by ANSYS FLUENT 2022 R1 software, and the results were compared with the experimental data. After comparing the numerical simulation results with the test data, it was clear that the numerical simulation method was superior in accurately predicting the distribution pattern of each parameter of the polymer slurry during diffusion. The grouting volume, pressure distribution, and real-time change in the position of the flow of slurry could be efficiently determined through numerical calculation and simulated grouting tests. This work can offer valuable information for designing polymer grouting materials used in underground mine fissures. Full article

Caffeine is an alkaloid with a purine structure and has been well known for centuries due to its presence in popular drinks—tea and coffee. However, the structural and spectroscopic parameters of this compound, as well as its chemical and biological activities, are still not fully known. In this study, for the first time, we report on the measured oxygen-17 NMR spectra of this stimulant. To support the assignment of our experimental NMR data, extensive quantum chemical calculations of NMR parameters, including nuclear magnetic shielding constants and indirect spin–spin coupling constants, were performed. In a theoretical study, using nine efficient density functionals (B3LYP, BLYP, BP86, CAM-B3LYP, LC-BLYP, M06, PBE0, TPSSh, wB97x), and in combination with a large and flexible correlation-consistent aug-cc-pVTZ basis set, the structure and NMR parameters were predicted for a free molecule of caffeine and in chloroform, DMSO and water. A polarized continuum model (PCM) was used to include a solvent effect. As a result, an optimal methodology was developed for predicting reliable NMR data, suitable for studies of known, as well as newly discovered, purines and similar alkaloids. The results of the current work could be used in future basic and applied studies, including NMR identification and intermolecular interactions of caffeine in various raw materials, like plants and food, as well as in the structural and spectroscopic characterization of new compounds with similar structures. Full article

A disruptive Electric Propulsion system is proposed for next-generation Low-Earth-Orbit (LEO) small satellite constellations, utilizing an RF-powered Helicon Plasma Thruster (HPT). This system is built around a Magnetically Enhanced Inductively Coupled Plasma (MEICP) reactor, which enables acceleration of quasi-neutral plasma through a magnetic nozzle. The MEICP reactor features an innovative design with a multi-dipole magnetic confinement system, generated by neodymium iron boron (NdFeB) permanent magnets, combined with an azimuthally asymmetric half-wavelength right (HWRH) antenna and a variable-section ionization chamber. The plasma reactor is followed by a solenoid-free magnetic nozzle (MN), which facilitates the formation of an ambipolar potential drop, enabling the conversion of electron thermal energy into ion beam energy. This study explores the impact of an inhomogeneous magnetic field on the heating mechanism of the HPT and highlights its multi-mode operation within a pulsed power range of 200 to 500 W of RF. The discharge state, characterized by high-energy electron-excited ions and low-energy excited neutral particles in the plasma plume, was analyzed using optical emission spectroscopy (OES). The experimental testing campaign, conducted under pulsed power excitation, reveals that, as RF input power increases, the MEICP reactor transitions from inductive (H-mode) to wave coupling (W-mode) discharge modes. Spectrograms, electron temperature, and plasma density measurements were obtained for the Helicon Plasma Thruster within its operational envelope. Based on OES data, the ideal specific impulse was estimated to exceed 1000 s, highlighting the significant potential of this technology for future LEO/VLEO space missions. Full article

The use of deep eutectic solvents (DESs) for the preparation of polymer membranes for environmental separation technologies is comprehensively reviewed. DESs have been divided into five categories based on the hydrogen bond donor (HBD) and acceptor (HBA) that are involved in the production of the DESs, and a wide range of DESs’ physicochemical characteristics, such as density, surface tension, viscosity, and melting temperature, are initially gathered. Furthermore, the most popular techniques for creating membranes have been demonstrated and discussed, with a focus on the non-solvent induced phase separation (NIPS) method. Additionally, a number of studies have been reported in which DESs were employed as pore formers, solvents, additives, or co-solvents, among other applications. The addition of DESs to the manufacturing process increased the presence of finger-like structures and macrovoids in the cross-section and, on numerous occasions, had a substantial impact on the overall porosity and pore size. Performance data were also gathered for membranes made for various separation technologies, such as ultrafiltration (UF) and nanofiltration (NF). Lastly, DESs provide various options for the functionalization of membranes, such as the creation of various liquid membrane types, with special focus on supported liquid membranes (SLMs) for decarbonization technologies, discussed in terms of permeability and selectivity of several gases, including CO₂, N₂, and CH₄. Full article

Background: Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but severe complication following vaccination with adenovirus vector-based COVID-19 vaccines. Antibodies directed against platelet factor 4 (PF4) are thought to be responsible for platelet activation and subsequent thromboembolic events in these patients. Since a single vaccination does not lead to sufficient immunization, subsequent vaccinations against COVID-19 have been recommended. However, concerns exist regarding the possible development of a new thromboembolic episode after subsequent vaccinations in VITT patients. Methods: We prospectively analyzed follow-up data from four VITT patients (three women and one man; median age, 44 years [range, 22 to 62 years]) who subsequently received additional COVID-19 vaccines. Platelet counts, anti-PF4/heparin antibody level measurements, and a functional platelet activation assay were performed at each follow-up visit. Additionally, we conducted a literature review and summarized similar reports on the outcome of subsequent vaccinations in patients with VITT. Results: The patients had developed thrombocytopenia and thrombosis 4 to 17 days after the first vaccination with ChAdOx1 nCoV-19. The optical densities (ODs) of anti-PF4/heparin antibodies decreased with time, and three out of four patients tested negative within 4 months. One patient remained positive even after 10 months post first vaccination. All four patients received an mRNA-based vaccine as a second vaccination against SARS-CoV-2. No significant drop in platelet count or new thromboembolic complications were observed during follow-up. We identified seven publications reporting subsequent COVID-19 vaccination in VITT patients. None of the patients developed thrombocytopenia or thrombosis after the subsequent vaccination. Conclusion: Subsequent vaccination with an mRNA vaccine appears to be safe in VITT patients. Full article

Nailfold capillaroscopy is a non-invasive investigation, which allows for the study of the microvasculature (anatomical and functional). Rheumatoid arthritis (RA) is associated with a high risk of cardiovascular atherosclerotic diseases, with endothelial dysfunction (macrovascular and microvascular) representing the first step in atherosclerosis development. The aim of this study is represented by the assessment of microvascular endothelial dysfunction in RA patients by means of nailfold capillaroscopy and to assess its evolution after a period of 12 months of anti TNF-alpha treatment. The study included 70 consecutive patients with RA and 70 healthy subjects, matched for age and gender, as the control group. Rheumatoid factor, anti-cyclic citrullinated peptide antibodies, serum TNF-α, C reactive protein, and erythrocytes sedimentation rate were evaluated in all patients, but in controls, only rheumatoid factor, serum TNF-α, C reactive protein, and erythrocytes sedimentation rate were measured. The RA activity was measured by DAS28. Nailfold capillaroscopy was carried out in all patients and controls, determining the baseline nailfold capillary density (Db), nailfold capillary density during reactive hyperemia (Dh), and nailfold capillary density after venous congestion (Dc). Data were presented as mean ± standard deviation. Statistical analysis was performed using ANOVA and Pearson’s correlation, with p < 0.05 being statistically significant. Db, Dh, and Dc were lower in RA patients than in controls (p < 0.0001), correlating with RA activity and TNF-α (p < 0.05). After 12 months of anti TNF-α treatment, microvascular endothelial dysfunction improved (p < 0.0001). Microvascular endothelial dysfunction can be assessed by nailfold capillaroscopy, with anti TNF-α medication contributing to its improvement. Full article

An issue of concern in landscape and urban planning, articulated in the United Nation’s (UN’s) Sustainable Development Goals (SDGs), is the increase in urban land consumption over time. Indicator 11.3.1 of the SDGs is dedicated to measuring it, underlining the importance of decreasing urban land consumption per person, a strategy that is understood to contribute positively to climate mitigation and to a host of other social, economic, and environmental objectives. This article aims to explore the practical implications of the official methods for measuring Indicator 11.3.1, as well as two alternatives, and to calculate and compare the global and regional trends of these indicators for the 2000–2020 period for a universe of 3470 cities and metropolitan areas that had 100,000 people or more in the year 2020. Built-up area and population data for this universe were obtained from the Global Human Settlements Layer (GHS-BUILT-S and GHS-POP) published by the European Commission. We applied methods adapted from New York University’s Atlas of Urban Expansion to map the urban extents of all cities in 2000 and 2020, and then we used these urban extents, the built-up areas, and population estimates within them to calculate values for Indicator 11.3.1 and for two alternative indicators for the 2000–2020 period. We found that the current definition of Indicator 11.3.1 of the SDGs—“Ratio of land consumption rate to population growth rate”—has significant limitations in conveying meaningful information and interpretability for practical applications. We suggest two alternative indicators that address these shortcomings: the rate of change of land consumption per person and the rate of density change. Our analysis found that, for the world at large, urban densities declined at an annual rate of 0.5–0.7% between 2000 and 2020, with significant variation in the direction and magnitude of density trends by world region. Additionally, we found density declines to be faster in smaller cities than in larger ones and faster in cities with slower population growth or population declines compared to those with more rapid population growth. Full article

This study aims to scientifically justify the identification of suitable urban properties for urban green infrastructure (UGI) interventions to optimize its natural regulating functions for long-term pollution mitigation and secondary dust reduction. This study adheres to the perception that planning urban transformations to improve ambient air quality (AQ) requires a thorough understanding of urban structural heterogeneity and its interrelationship with the local microclimate. We apply an approach in which UGI and its potential multifunctionality are explored as a structural–functional element of urban local climatic zones. The same (100 × 100 m) spatial framework is used to develop place-based adapted solutions for intervention in UGI. A complex geospatial analysis of Burgas City, the second largest city (by area) in Bulgaria, was conducted by integrating 12 indicators to reveal the spatial disbalance of AQ regulation’ demand and UGI’s potential to supply ecosystem services. A total of 174 municipally owned properties have been identified, of which 79 are of priority importance, including for transport landscaping, inner-quarter spaces, and social infrastructure. Indicators of population density and location of social facilities were applied with the highest weight in the process of prioritizing sites. The study relies on public data and information from the integrated city platform of Burgas, in cooperation with the city’s government. The results have been discussed with stakeholders and implemented by the Municipality of Burgas in immediate greening measures in support of an ongoing program for Burgas Municipality AQ improvement. Full article

The variability of food resources considerably affects the habitat preferences of animals. In mast years, the availability of highly nutritive food increases significantly. We tested whether changes in the distribution of the areas of wisents, Bison bonasus L. concentration, in the Bieszczady Mountains, Poland, were connected with the availability of beechnuts. In the two beech masting years of 2013 and 2022, we considered the months with the highest availability of beechnuts, namely September and October. The beechnut crop varied significantly between as little as 2.4 g dry matter/m², recorded within the Baligród herd’s home range in 2013, and up to 238.8 g dry matter/m² within the Tworylne herd’s range, also in 2013. The analysis of the spatial distribution of beech stands within various parts of the wisents’ home range showed that within the 95% kernel area, their share was mostly high, varying between 25.7% and 42.8%. Meanwhile, within the 50% kernel area, it was generally much lower, except for the year 2022 in the case of the Baligród herd. The densities of wisents varied significantly between the kernel areas of 95% and 50%, ranging between 0.04 and 0.08 animals/ha and 0.17 and 0.48 animals/ha, respectively. However, there was no statistical difference between the figures for all plots tested within the home range of the wisent population and plots dominated by beech. Based on the data obtained in this study, habitat selection patterns of wisents in the Bieszczady Mountains cannot be explained by the availability of beech stands and the phenomenon of mast years. Full article

Wind speed differences between weekdays and holidays at urban sites in Japan were investigated in search of the influence of urban anthropogenic heat on surface wind speed using data from the Automated Meteorological Data Acquisition System (AMeDAS) of the Japan Meteorological Agency (JMA) for 44 years. The wind speed was found to be lower on holidays than on weekdays, not only in large cities but also in areas with medium degrees of urbanization, which is interpreted to be due to the stronger stability of the surface boundary layer under lower temperatures with smaller amounts of anthropogenic heat. The rate of decrease is about −3% in central Tokyo, and about −0.5% for the average over stations with population densities between 1000 and 3000 km⁻². Additionally, an analysis using the spatially dense data on the Air Pollution Monitoring System of Tokyo Metropolis for 28 years showed that negative anomalies in wind speed on holidays were detected at many stations in the Tokyo Wards Area, although negative temperature anomalies were limited to a few stations in the central area or near big roads, suggesting different spatial scales in the response of temperature and wind speed to anthropogenic heat. Full article

The literature and practice have proven the connection between competitiveness at all levels (company, region, national) and its position in international value chains, hence the need to “measure” their economic impact. Traditionally, this has been conducted by using complex quantitative data based on statistical sources translated into input/output tables that are difficult to calculate and interpret and rely on outdated data. While the contribution of clusters as drivers of economic competitiveness has been extensively debated over the last 30 years, it is more recently, after the COVID-19 pandemic, leading to tremendous disruptions in international value chains, that their role of generators and drivers of international value chains has been recognized, proven by the rapid response they have been able to provide in “repairing” the disturbances. The current paper proposes a cluster-based value chain analyses method in which the main measurement unit is the density of the chosen indicator along the value chain links (number of enterprises, turnover, R&D expenditure, exports). The results were checked by classical methods and proven to be congruent. The method allows for a rapid response to sudden disruptions and can be used for both cluster managers as well as economic policymakers at regional and national levels. Full article

This study conducts a comprehensive evaluation of four scenario experiments using the CMA_WSP, WRF, and WRF_FITCH models to enhance forecasts of hub-height wind speeds at multiple wind farms in Northern China, particularly under significant wind speed fluctuations during high wind conditions. The experiments apply various wind speed calculation methods, including the Monin–Obukhov similarity theory (ST) and wind farm parameterization (WFP), within a 9 km resolution framework. Data from four geographically distinct stations were analyzed to assess their forecast accuracy over a 72 h period, focusing on the transitional wind events characterized by substantial fluctuations. The CMA_WSP model with the ST method (CMOST) achieved the highest scores across the evaluation metrics. Meanwhile, the WRF_FITCH model with the WFP method (FETA) demonstrated superior performance to the other WRF models, achieving the lowest RMSE and a greater stability. Nevertheless, all models encountered difficulties in predicting the exact timing of extreme wind events. This study also explores the effects of these methods on the wind power density (WPD) distribution, emphasizing the boundary layer’s influence at the hub-heighthub-height of 85 m. This influence leads to significant variations in the central and coastal regions. In contrast to other methods that account for the comprehensive effects of the entire boundary layer, the ST method primarily relies on the near-surface 10 m wind speed to calculate the hub-height wind speed. These findings provide important insights for enhancing wind speed and WPD forecasts under transitional weather conditions. Full article

Selective laser sintering (SLS) is a bed fusion additive manufacturing technology that facilitates rapid, versatile, intricate, and cost-effective prototype production across various applications. It supports a wide array of thermoplastics, such as polyamides, ABS, polycarbonates, and nylons. However, manufacturing plastic components using SLS poses significant challenges due to issues like low strength, dimensional inaccuracies, and rough surface finishes. The operational principle of SLS involves utilizing a high-power-density laser to fuse polymer or metallic powder surfaces. This paper presents a comprehensive analysis of the SLS process, emphasizing the impact of different processing variables on material properties and the quality of fabricated parts. Additionally, the study explores the application of machine learning (ML) techniques—supervised, unsupervised, and reinforcement learning—in optimizing processes, detecting defects, and ensuring quality control within SLS. The review addresses key challenges associated with integrating ML in SLS, including data availability, model interpretability, and leveraging domain knowledge. It underscores the potential benefits of coupling ML with in situ monitoring systems and closed-loop control strategies to enable real-time adjustments and defect mitigation during manufacturing. Finally, the review outlines future research directions, advocating for collaborative efforts among researchers, industry professionals, and domain experts to unlock ML’s full potential in SLS. This review provides valuable insights and guidance for researchers in regard to 3D printing, highlighting advanced techniques and charting the course for future investigations. Full article