Search Results (5,673)

The transportation sector is a major consumer of primary energy and is a significant contributor to greenhouse gas emissions. Sustainable transportation requires identifying and quantifying factors influencing transport-related CO₂ emissions. This research aims to establish an adaptable, precise, and transparent forecasting structure for transport CO₂ emissions of the United States. For this reason, we proposed a multi-stage method that incorporates explainable Machine Learning (ML) and Feature Selection (FS), guaranteeing interpretability in comparison to conventional black-box models. Due to high multicollinearity among 24 initial variables, hierarchical feature clustering and multi-step FS were applied, resulting in five key predictors: Total Primary Energy Imports (TPEI), Total Fossil Fuels Consumed (FFT), Annual Vehicle Miles Traveled (AVMT), Air Passengers-Domestic and International (APDI), and Unemployment Rate (UR). Four ML methods—Support Vector Regression, eXtreme Gradient Boosting, ElasticNet, and Multilayer Perceptron—were employed, with ElasticNet outperforming the others with RMSE = 45.53, MAE = 30.6, and MAPE = 0.016. SHAP analysis revealed AVMT, FFT, and APDI as the top contributors to CO₂ emissions. This framework aids policymakers in making informed decisions and setting precise investments. Full article

Soybean (Glycine max (L.) Merrill) is a major oilseed crop rich in phytosterols and tocopherols, compounds associated with functional and nutritional properties of vegetable oils. This study aimed to apply, for the first time, Independent Component Analysis (ICA) to discriminate the composition of phytosterols (β-sitosterol, campesterol, stigmasterol) and tocopherols (α, β, γ, δ) in 20 soybean genotypes—14 non-transgenic and six transgenic—cultivated in two major producing regions of Paraná state, Brazil (Londrina and Ponta Grossa). Lipophilic compounds were extracted from soybean seeds, quantified via gas chromatography and HPLC, and statistically analyzed using ICA with the JADE algorithm. The extracted independent components successfully differentiated soybean varieties based on phytochemical profiles. Notably, transgenic cultivars from Ponta Grossa exhibited higher levels of total tocopherols, including α- and β-tocopherol, while conventional cultivars from both regions showed elevated phytosterol content, particularly campesterol and stigmasterol. ICA proved to be a powerful unsupervised method for visualizing patterns in complex compositional data. These findings highlight the significant influence of genotype and growing region on the nutraceutical potential of soybean, and support the use of multivariate analysis as a strategic tool for cultivar selection aimed at enhancing functional quality in food applications. Full article

In high energy density physics, the demand for precise detection of nanosecond-level fast physical processes is high. Ga:ZnO (GZO), GaN, and other fast scintillators are widely used in pulsed signal detection. However, many of them, especially wide-bandgap materials, still face issues of low luminous intensity and significant self-absorption. Therefore, an enhanced method was proposed to tune the wavelength of materials via coating perovskite quantum dot (QD) films. Three-layer samples based on GZO were primarily investigated and characterized. Radioluminescence (RL) spectra from each face of the samples, as well as their decay times, were obtained. Lower temperatures further enhanced the luminous intensity of the samples. Its overall luminous intensity increased by 2.7 times at 60 K compared to room temperature. The changes in the RL processes caused by perovskite QD and low temperatures were discussed using the light tuning and transporting model. In addition, an experiment under a pico-second electron beam was conducted to verify their pulse response and decay time. Accordingly, the samples were successfully applied in beam state monitoring of nanosecond pulsed proton beams, which indicates that GZO wafer coating with perovskite QD films has broad application prospects in pulsed radiation detection. Full article

HgCdSe has recently been proposed as a potential alternative material to HgCdTe for fabricating high-performance infrared detectors. This work presents a study on the growth of high-crystalline-quality HgCdSe materials on GaSb (211)B substrates via molecular beam epitaxy and demonstration of the first prototype HgCdSe-based mid-wave infrared detectors. By optimizing the MBE growth parameters, and especially the thermal cleaning process of the GaSb substrate surface prior to epitaxial growth, high-quality HgCdSe material was achieved with a record XRD full width at half maximum of ~65 arcsec. At a temperature of 77 K, the mid-wave infrared HgCdSe n-type material demonstrated a minority carrier lifetime of ~1.19 µs, background electron concentration of ~2.2 × 10¹⁷ cm⁻³, and electron mobility of ~1.6 × 10⁴ cm²/Vs. The fabricated mid-wave infrared HgCdSe photoconductor presented a cut-off wavelength of 4.2 µm, a peak responsivity of ~40 V/W, and a peak detectivity of ~1.2 × 10⁹ cmHz^1/2/W at 77 K. Due to the relatively high background electron concentration, the detector performance is lower than that of state-of-the-art low-doped HgCdTe counterparts. However, these preliminary results indicate the great potential of HgCdSe materials for achieving next-generation IR detectors on large-area substrates with features of lower cost and larger array format size. Full article

It has long been accepted that breathing gases that are physiologically inert include helium (He), neon (Ne), nitrogen (N₂), argon (Ar), krypton (Kr), xenon (Xe), and hydrogen (H₂). The term “inert gas” has been used to describe them due to their unusually high chemical stability. However, as investigations have advanced, many have shown that inert gas can have specific biological impacts when exposed to high pressure or atmospheric pressure. Additionally, different inert gases have different effects on intracellular signal transduction, ion channels, and cell membrane receptors, which are linked to their anesthetic and cell protection effects in normal or pathological processes. Through a selective analysis of the representative literature, this study offers a concise overview of the state of research on the biological impacts of inert gas and their molecular mechanisms. Full article

As urbanization accelerates and climate change intensifies, the ecological integrity of urban riparian forests faces growing threats, underscoring the need for a systematic framework to guide their sustainable management. To address this gap, we developed a causal framework by applying text mining and sentence classification to 1001 abstracts from previous studies, structured within the DPSIR (Driver–Pressure–State–Impact–Response) model. The analysis identified six dominant thematic clusters—water quality, ecosystem services, basin and land use management, climate-related stressors, anthropogenic impacts, and greenhouse gas emissions—which reflect the multifaceted concerns surrounding urban riparian forest research. These themes were synthesized into a structured causal model that illustrates how urbanization, land use, and pollution contribute to ecological degradation, while also suggesting potential restoration pathways. To validate its applicability, the framework was applied to four major urban streams in Seoul, where indicator-based analysis and correlation mapping revealed meaningful linkages among urban drivers, biodiversity, air quality, and civic engagement. Ultimately, by integrating large-scale text mining with causal inference modeling, this study offers a transferable approach to support adaptive planning and evidence-based decision-making under the uncertainties posed by climate change. Full article

The impact mechanism of long-term creep in gas-containing coal on coal and gas outbursts has not been fully elucidated and remains insufficiently understood for the purpose of disaster engineering control. This investigation conducted triaxial creep experiments on raw coal specimens under controlled confining pressures, axial stresses, and gas pressures. Through systematic analysis of coal’s physical responses across different loading conditions, we developed and validated a novel creep damage constitutive model for gas-saturated coal through laboratory data calibration. The key findings reveal three characteristic creep regimes: (1) a decelerating phase dominates under low stress conditions, (2) progressive transitions to combined decelerating–steady-state creep with increasing stress, and (3) triphasic decelerating–steady–accelerating behavior at critical stress levels. Comparative analysis shows that gas-free specimens exhibit lower cumulative strain than the 0.5 MPa gas-saturated counterparts, with gas presence accelerating creep progression and reducing the time to failure. Measured creep rates demonstrate stress-dependent behavior: primary creep progresses at 0.002–0.011%/min, decaying exponentially to secondary creep rates below 0.001%/min. Steady-state creep rates follow a power law relationship when subject to deviatoric stress (R² = 0.96). Through the integration of Burgers viscoelastic model with the effective stress principle for porous media, we propose an enhanced constitutive model, incorporating gas adsorption-induced dilatational stresses. This advancement provides a theoretical foundation for predicting time-dependent deformation in deep coal reservoirs and informs monitoring strategies concerning gas-bearing strata stability. This study contributes to the theoretical understanding and engineering monitoring of creep behavior in deep coal rocks. Full article

The development of high-performance solid electrolytes is critical to advancing solid-state lithium-ion batteries (SSBs), with lithium lanthanum zirconium oxide (LLZO) emerging as a leading candidate due to its chemical stability and wide electrochemical window. In this study, we systematically investigated the effects of cation dopants, including aluminum (Al³⁺), tantalum (Ta⁵⁺), gallium (Ga³⁺), and rubidium (Rb⁺), on the structural, electronic, and ionic transport properties of LLZO using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. It appeared that, among all simulated results, Al-LLZO exhibits the highest ionic conductivity of 1.439 × 10⁻² S/cm with reduced activation energy of 0.138 eV, driven by enhanced lithium vacancy concentrations and preserved cubic-phase stability. Ta-LLZO follows, with a conductivity of 7.12 × 10⁻³ S/cm, while Ga-LLZO and Rb-LLZO provide moderate conductivity of 3.73 × 10⁻³ S/cm and 3.32 × 10⁻³ S/cm, respectively. Charge density analysis reveals that Al and Ta dopants facilitate smoother lithium-ion migration by minimizing electrostatic barriers. Furthermore, Al-LLZO demonstrates low electronic conductivity (1.72 × 10⁻⁸ S/cm) and favorable binding energy, mitigating dendrite formation risks. Comparative evaluations of radial distribution functions (RDFs) and XRD patterns confirm the structural integrity of doped systems. Overall, Al emerges as the most effective and economically viable dopant, optimizing LLZO for scalable, durable, and high-conductivity solid-state batteries. Full article

Background and Objectives: A correct diagnosis of beta-hemolytic group A streptococcus (GAS)-pharyngitis allows the prevention of complications and unnecessary use of antibiotics. The aim of this study was to assess the management of pediatric GAS-pharyngitis in Romanian general practitioners (GPs)’ practice. Material and Methods: a cross-sectional study was conducted using a questionnaire distributed to Romanian GPs. Results: In total, 56 GPs completed the questionnaire, mostly females (83.9%, n = 47) from an urban area (60.7%, n = 34). They treated 5–10 (35.7%) or more than 10 (32.1%) cases of GAS monthly and considered white exudate on tonsils (92.9%, n = 52) to be the most suggestive clinical sign. Of the GPs, 25% (n = 14) used the Centor Criteria, 10.7% (n = 6) performed a rapid antigen detection test, and 42.9% (n = 24) requested throat culture for diagnosis. The younger GPs used the Centor Criteria significantly more often (p = 0.027) than the older ones. Most GPs (69.6%, n = 39) preferred targeted antibiotic therapy. Amoxicillin-clavulanate was the most commonly used antibiotic (55.4%, n = 31). Most GPs preferred oral antibiotics (89%, n = 50) for 10 days (55.4%, n = 31). Conclusions: Antibiotic treatment was initiated mostly based on clinical symptoms and in a short-course therapy. GPs stated that they prefer targeted antibiotic therapy, but they did not use proper diagnostic tools. Full article

Biochar, a carbon-rich material derived from biomass, presents a sustainable solution to several pressing challenges in U.S. agriculture, including soil degradation, carbon emissions, and waste management. Despite global advancements, the U.S. biochar market remains underexplored in terms of economic viability, adoption potential, and sector-specific applications. This narrative review synthesizes two decades of literature to examine biochar’s applications, production methods, and market dynamics, with a focus on its economic and environmental role within the United States. The review identifies biochar’s multifunctional benefits: enhancing soil fertility and crop productivity, sequestering carbon, reducing greenhouse gas emissions, and improving water quality. Recent empirical studies also highlight biochar’s economic feasibility across global contexts, with yield increases of up to 294% and net returns exceeding USD 5000 per hectare in optimized systems. Economically, the global biochar market grew from USD 156.4 million in 2021 to USD 610.3 million in 2023, with U.S. production reaching ~50,000 metric tons annually and a market value of USD 203.4 million in 2022. Forecasts project U.S. market growth at a CAGR of 11.3%, reaching USD 478.5 million by 2030. California leads domestic adoption due to favorable policy and biomass availability. However, barriers such as inconsistent quality standards, limited awareness, high costs, and policy gaps constrain growth. This study goes beyond the existing literature by integrating market analysis, SWOT assessment, cost–benefit findings, and production technologies to highlight strategies for scaling biochar adoption. It concludes that with supportive legislation, investment in research, and enhanced supply chain transparency, biochar could become a pivotal tool for sustainable development in the U.S. agricultural and environmental sectors. Full article

Deep marine shale is the primary carrier of shale gas resources in Southwestern China. Because the occurrence and gas content of methane vary with burial conditions, understanding the microscopic mechanism of methane occurrence in deep marine shale is critical for effective shale gas exploitation. The temperature and pressure conditions in deep shale exceed the operating limits of experimental equipment; thus, few studies have discussed the microscopic occurrence mechanism of shale gas in deep marine shale. This study applies molecular simulation technology to reveal the methane’s microscopic occurrence mechanism, particularly the main controlling factor of adsorbed methane in deep marine shale. Two types of simulation models are also proposed. The Grand Canonical Monte Carlo (GCMC) method is used to simulate the adsorption behavior of methane molecules in these two models. The results indicate that the isosteric adsorption heat of methane in both models is below 42 kJ/mol, suggesting that methane adsorption in deep shale is physical adsorption. Adsorbed methane concentrates on the pore wall surface and forms a double-layer adsorption. Furthermore, adsorbed methane can transition to single-layer adsorption if the pore size is less than 1.6 nm. The total adsorption capacity increases with rising pressure, although the growth rate decreases. Excess adsorption capacity is highly sensitive to pressure and can become negative at high pressures. Methane adsorption capacity is determined by pore size and adsorption potential, while accommodation space and adsorption potential are influenced by pore size and mineral type. Under deep marine shale reservoir burial conditions, with burial depth deepening, the effect of temperature on shale gas occurrence is weaker than pressure. Higher temperatures inhibit shale gas occurrence, and high pressure enhances shale gas preservation. Smaller pores facilitate the occurrence of adsorbed methane, and larger pores have larger total methane adsorption capacity. Deep marine shale with high formation pressure and high clay mineral content is conducive to the microscopic accumulation of shale gas in deep marine shale reservoirs. This study discusses the microscopic occurrence state of deep marine shale gas and provides a reference for the exploration and development of deep shale gas. Full article

The production of iron and steel plays a significant role in the anthropogenic carbon footprint, accounting for 7% of global GHG emissions. In the context of CO₂ mitigation, the steelmaking industry is looking to potentially replace traditional carbon-based ironmaking processes with hydrogen-based direct reduction of iron ore in shaft furnaces. Before industrialization, detailed modeling and parametric studies were needed to determine the proper operating parameters of this promising technology. The modeling approach selected here was to complement REDUCTOR, a detailed finite-volume model of the shaft furnace, which can simulate the gas and solid flows, heat transfers and reaction kinetics throughout the reactor, with an extension that describes the whole gas circuit of the direct reduction plant, including the top gas recycling set up and the fresh hydrogen production. Innovative strategies (such as the redirection of part of the bustle gas to a cooling inlet, the use of high nitrogen content in the gas, and the introduction of a hot solid burden) were investigated, and their effects on furnace operation (gas utilization degree and total energy consumption) were studied with a constant metallization target of 94%. It has also been demonstrated that complete metallization can be achieved at little expense. These strategies can improve the thermochemical state of the furnace and lead to different energy requirements. Full article

Rotating compressors are foundational in various industrial processes, particularly in the oil-and-gas sector, where reliable fault detection is crucial for maintaining operational continuity. While Graph Attention Network (GAT) frameworks are widely available, this study advances the state of the art by introducing a Bayesian GAT method specifically tailored for vibration-based compressor fault diagnosis. The approach integrates domain-specific digital-twin simulations built with Rotordynamic software (1.3.0), and constructs dual adjacency matrices to encode both physically informed and data-driven sensor relationships. Additionally, a hybrid forecasting-and-reconstruction objective enables the model to capture short-term deviations as well as long-term waveform fidelity. Monte Carlo dropout further decomposes prediction uncertainty into aleatoric and epistemic components, providing a more robust and interpretable model. Comparative evaluations against conventional Long Short-Term Memory (LSTM)-based autoencoder and forecasting methods demonstrate that the proposed framework achieves superior fault-detection performance across multiple fault types, including misalignment, bearing failure, and unbalance. Moreover, uncertainty analyses confirm that fault severity correlates with increasing levels of both aleatoric and epistemic uncertainty, reflecting heightened noise and reduced model confidence under more severe conditions. By enhancing GAT fundamentals with a domain-tailored dual-graph strategy, specialized Bayesian inference, and digital-twin data generation, this research delivers a comprehensive and interpretable solution for compressor fault diagnosis, paving the way for more reliable and risk-aware predictive maintenance in complex rotating machinery. Full article

Using density functional theory (M06-2X-D3/def2-TZVP), we investigated the 1,2-addition reactions of NH₃ with a series of heavy imine analogues, G13=P-Rea (where G13 denotes a Group 13 element; Rea = reactant), featuring a mixed G13–P–Ga backbone. Theoretical analyses revealed that the bonding nature of the G13=P moiety in G13=P-Rea molecules varies with the identity of the Group 13 center. For G13=B, Al, Ga, and In, the bonding is best described as a donor–acceptor (singlet–singlet) interaction, whereas for G13=Tl, it is characterized by an electron-sharing (triplet–triplet) interaction. According to our theoretical studies, all G13=P-Rea species—except the Tl=P analogue—undergo 1,2-addition with NH₃ under favorable energetic conditions. Energy decomposition analysis combined with natural orbitals for chemical valence (EDA–NOCV), along with frontier molecular orbital (FMO) theory, reveals that the primary bonding interaction in these reactions originates from electron donation by the lone pair on the nitrogen atom of NH₃ into the vacant p-π* orbital on the G13 center. In contrast, a secondary, weaker interaction involves electron donation from the phosphorus lone pair of the G13=P-Rea species into the empty σ* orbital of the N–H bond in NH₃. The calculated activation barriers are primarily governed by the deformation energy of ammonia. Specifically, as the atomic weight of the G13 element increases, the atomic radius and G13–P bond length also increase, requiring a greater distortion of the H₂N–H bond to reach the transition state. This leads to a higher geometrical deformation energy of NH₃, thereby increasing the activation barrier for the 1,2-addition reaction involving these Lewis base-stabilized, heavy imine-like G13=P-Rea molecules and ammonia. Full article

Efficient plastic waste end-of-life management is a serious worldwide environmental issue motivated by growing waste production and negative effects of wrongful disposal. This study presents a comparative overview of plastic waste management regimes within the European Union (EU), the United States of America (USA), and Romania, ranked with circular economy goals. By using the United States Environmental Protection Agency (US EPA) Waste Reduction Model (WARM), version 16, the study provides a quantified score to greenhouse gas (GHG) emissions within three large options of management: recycling, energy recovery through combustion, and landfilling. The model setup utilizes region-specific information on legislation, base technology, and recycling efficiency. The outcomes show that recycling always entails net GHG emissions reductions, i.e., −4.49 kg CO_2e/capita/year for EU plastic waste and −20 kg CO_2e/capita/year for USA plastic waste. Combustion and landfilling have positive net emissions from 1.76 to 14.24 kg CO_2e/capita/year. Economic indicators derived from the model also show significant variation: salaries for PET management amounted to USD 2.87 billion in the EU and USD 377 million in the USA, and tax collection was USD 506 million and USD 2.01 billion, respectively. The conclusions highlight the wider environmental and socioeconomic benefits of recycling and reinforce its status as a cornerstone of circular-economy sustainable plastic waste management and a strategic element of national development agendas, with special reference to Romania’s national agenda. Full article