The growing interest in proton therapy (PT) in recent decades is justified by the evidence that protons dose distribution allows maximal dose release at the tumor depth followed by sharp distal dose fall-off. But, in the holistic management of head and neck cancer (HNC), limiting the potential of PT to a mere dosimetric advantage appears reductive. Indeed, the precise targeting of PT may help evaluate the effectiveness of de-escalation strategies, especially for patients with human papillomavirus associated-oropharyngeal cancer (OPC) and nasopharyngeal cancer (NPC). Furthermore, PT could have potentially greater immunogenic effects than conventional photon therapy, possibly enhancing both the radiotherapy (RT) capability to activate anti-tumor immune response and the effectiveness of immunotherapy drugs. Based on these premises, the aim of the present paper is to conduct a narrative review reporting the safety and efficacy of PT compared to photon RT focusing on NPC and OPC. We also provide a snapshot of ongoing clinical trials comparing PT with photon RT for these two clinical scenarios. Finally, we discuss new insights that may further develop clinical research on PT for HNC. Full article

The distribution of shallow subsurface quality factors (Q) is a crucial indicator for assessing the integrity of subsurface structures and serves as a primary parameter for evaluating the attenuation characteristics of seismic waves propagating through subsurface media. As the complexity of underground spaces increases, regions expand, and testing environments diversify, the survivability of test nodes is compromised, resulting in sparse effective seismic data with a low signal-to-noise ratio (SNR). Within the confined area defined by the source and sensor placement, only the Q factor along the wave propagation path can be estimated with relative accuracy. Estimating the Q factor in other parts of the area is challenging. Additionally, in recent years, deep neural networks have been employed to address the issue of missing values in seismic data; however, these methods typically require large datasets to train networks that can effectively fit the data, making them less applicable to our specific problem. In response to this challenge, we have developed a supervised learning method for the restoration of shallow subsurface Q factor distributions. The process begins with the construction of an incomplete labeled data volume, followed by the application of a block-based data augmentation technique to enrich the training samples and train the network. The uniformly partitioned initial data are then fed into the trained network to obtain output data, which are subsequently combined to form a complete Q factor data volume. We have validated this training approach using various networks, all yielding favorable results. Additionally, we compared our method with a data augmentation approach that involves creating random masks, demonstrating that our method reduces the mean absolute percentage error (MAPE) by 5%. Full article

This research investigates the intersection of paramedicine and environmental sustainability (ES) by using mixed methods (surveys and policy analysis) to analyze organizational policy and professional beliefs. It advocates integrating ES into paramedic training and operations to reflect broader environmental values, and challenges, of a sector providing first response service delivery to climate-induced emergencies. Assessing paramedics’ willingness/interest in environmental education, timing (foundational or continuing professional development/CPD and organizational policy governing accreditation and practice in Australia and New Zealand (ANZ) found growing awareness of paramedics’ role in environmental stewardship. Disparity, however, exists between individual interest in ES training and its systemic exclusion in CPD policy and standards. The relevance of sociological thought, specifically Durkheimian theory, for construing ES interdependently, rather than individualistically (as predominated in the under-researched area) is advanced to promote ES reconceptualization, goal articulation and measurement. Results and practical recommendations are discussed amidst multidisciplinary literature to further emerging ES values exhibited in ANZ policy and paramedic beliefs. The article concludes systemic change is timely. Specifically, embedding ES into foundational and/or CPD training may leverage the professional interest found in the study and, importantly, ensure emergency practices promote the long-term environmental health prerequisite to supporting human health, congruent with the sector’s remit. Full article

An analysis was carried out on the thermal dissociation of selected inorganic salts according to Transition-State Theory (TST). For this purpose, two possibilities were compared in the context of rate constants: in the first case using the Arrhenius constant directly from TST, and in the second, using the thermodynamic equilibrium constant of the reaction/process of active state formation. The determined relationships are presented in the form of temperature profiles. It was established that TST applies to reactions for which there is a formally and experimentally reversible reaction, in the literal sense or catalytic process. The importance of the isoequilibrium temperature, which results from the intersection of the thermodynamic temperature profile and the Gibbs free energy of activation, was demonstrated. Its values close to the equilibrium temperature are indicative of more dynamic kinetic qualities. As part of the discussion, the Kinetic Compensation Effect (KCE) was used to observe changes in the entropy of activation by comparing two kinetic characteristics of the same reaction. Enthalpy–Entropy Compensation (EEC) was shown to be the same law as KCE, just expressed differently. This was made possible by TST, specifically the entropy of activation at isokinetic temperature, by which the perspective of the relationship of energy effects changes. Full article

For flood discharge structures with high water heads, aeration facilities are usually installed in engineering to promote water flow aeration and prevent cavitation damage to the overflow surface. Actual engineering has shown that as the slope of the discharge channel bottom decreases or water level changes lead to a decrease in the Froude number, the cavity morphology after conventional aeration facilities or allotype aerators is poor. This article proposes a curved aeration facility scheme based on the idea of locally increasing the bottom slope to reduce the impact angle, which is formed by the convex parabolic bottom plate and concave parabolic bottom plate. The convex parabolic bottom plate is tangent to a flat bottom plate behind the offset, and the concave parabolic bottom plate is tangent to the downstream. The jet landing point is controlled at the junction of the convex parabolic bottom plate and the concave parabolic bottom plate, and the lower jet trajectory is in line with the parabolic bottom plate. The corresponding parabolic bottom plate calculation formulas were theoretically derived, and the design method of the shape parameters of the aeration facility was provided. Through specific engineering case studies, it was found that: (1) As the Z_AC/Z_AG value increases, point C becomes closer to point G, the slope of the water tongue landing point C becomes steeper, and the cavity is less likely to return water. (2) When the position of the water tongue landing point is 0.5–0.8 times the height of the water tongue impact point, there is almost no water accumulation in the calculated cavity. At this time, the platform length L_AB = 0.5L_AF, the convex parabolic section length L_BC = (0.45–0.6) L_AG, the concave parabolic section length L_CD = (0.43–0.11) L_AG, the convex parabolic section calculation formula is z (x) = −A₁x₂ (A₁ = 0.0059–0.00564), and the concave parabolic section calculation formula is A₂x₂ − B₂x₂ (A₂ = 0.003347–0.01927).This solved the problem of aeration and corrosion reduction under small bottom slope, large-unit discharge, and low Froude number engineering conditions. Full article

In this paper, a multi-frequency MIMO antenna for 5G and Wi-Fi 6E is presented. The antenna uses a cosine-shape monopole and split-ring resonator (SRR) structure for tri-band radiation, and frequency band expansion is achieved through SRR, folded split-ring resonators (FSRR) and Archimedean spiral metasurfaces for decoupling, with which a combination of surface wave and space wave decoupling is achieved. The Archimedean spiral metasurface unit can achieve space wave decoupling in the tri-band. By adopting the method of combining space wave decoupling and surface wave decoupling, the miniature antenna is achieved. The measured results closely align with the simulated results. Specifically, maintaining a reflection coefficient of −10 dB, the measured results indicate an increase in isolation of 3.5 dB, 36.47 dB, and 6.42 dB for the frequency bands of 3.45–3.55 GHz, 5.7–5.9 GHz, and 6.75–7 GHz, respectively. Additionally, the MIMO antenna demonstrates an average efficiency of approximately 89%, with an average envelope correlation coefficient (ECC) of 0.0025. Furthermore, the antenna’s peak gain increases by 4.3 dB at 3.5 GHz, 3.8 dB at 5.8 GHz, and 1.9 dB at 6.9 GHz upon integrating the metasurface. The proposed method and structure are anticipated to contribute significantly to decoupling in multi-frequency MIMO antennas. Full article

CO₂-enhanced coalbed methane recovery (CO₂-ECBM) has been demonstrated as an effective enhanced oil recovery (EOR) technique that enhances the production of coalbed methane (CBM) while achieving the goal of CO₂ sequestration. In this paper, the grand canonical Monte Carlo simulation is used to investigate the dynamic mechanism of CO₂-ECBM in anthracite pores. First, an anthracite pore containing both organic and inorganic matter was constructed, and the adsorption and diffusion characteristics of CO₂ and CH₄ in the coal pores under different temperature and pressure conditions were studied by molecular dynamics (MD) simulations. The results indicate that the interaction energy of coal molecules with CO₂ and CH₄ is positively associated with pressure but negatively associated with temperature. At 307.15 K and 101.35 kPa, the interaction energies of coal adsorption of single-component CO₂ and CH₄ are −1273.92 kJ·mol⁻¹ and −761.53 kJ·mol⁻¹, respectively. The interaction energy between anthracite molecules and CO₂ is significantly higher compared to CH₄, indicating that coal has a greater adsorption capacity for CO₂ than for CH₄. Furthermore, the distribution characteristics of gas in the pores before and after injection indicate that CO₂ mainly adsorbs and displaces CH₄ by occupying adsorption sites. Under identical conditions, the diffusion coefficient of CH₄ surpasses that of CO₂. Additionally, the growth rate of the CH₄ diffusion coefficient as the temperature increases is higher than that of CO₂, which indicates that CO₂-ECBM is applicable to high-temperature coal seams. The presence of oxygen functional groups in anthracite molecules greatly influences the distribution of gas molecules within the pores of coal. The hydroxyl group significantly influences the adsorption of both CH₄ and CO₂, while the ether group has a propensity to impact CH₄ adsorption, and the carbonyl group is inclined to influence CO₂ adsorption. The research findings are expected to provide technical support for the effective promotion of CO₂-ECBM technology. Full article

Objective: This study aims to develop and validate the Futile Recanalization Prediction Score (FRPS), a novel tool designed to predict the severity risk of FR and aid in pre- and post-EVT risk assessments. Methods: The FRPS was developed using a rigorous process involving the selection of predictor variables based on clinical relevance and potential impact. Initial equations were derived from previous meta-analyses and refined using various statistical techniques. We employed machine learning algorithms, specifically random forest regression, to capture nonlinear relationships and enhance model performance. Cross-validation with five folds was used to assess generalizability and model fit. Results: The final FRPS model included variables such as age, sex, atrial fibrillation (AF), hypertension (HTN), diabetes mellitus (DM), hyperlipidemia, cognitive impairment, pre-stroke modified Rankin Scale (mRS), systolic blood pressure (SBP), onset-to-puncture time, sICH, and NIHSS score. The random forest model achieved a mean R-squared value of approximately 0.992. Severity ranges for FRPS scores were defined as mild (FRPS < 66), moderate (FRPS 66–80), and severe (FRPS > 80). Conclusions: The FRPS provides valuable insights for treatment planning and patient management by predicting the severity risk of FR. This tool may improve the identification of candidates most likely to benefit from EVT and enhance prognostic accuracy post-EVT. Further clinical validation in diverse settings is warranted to assess its effectiveness and reliability. Full article

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms—the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)—were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρ_t), Rayleigh-corrected reflectances (ρ_s), and remote sensing reflectances (R_rs). MCI slightly outperformed NDCI across all reflectance products. MCI using ρ_t showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales. Full article

With the development of the social economy and the improvement of electrification, cables and wires play an important role in people’s lives and industrial development. Meanwhile, the large-scale laying of cables has also made them a fire hazard that cannot be ignored in land construction such as residential buildings, utility tunnels, nuclear power plants, refineries, marine systems such as submarines and ships, and airborne systems such as spacecrafts and aircrafts. In this work, studies on fire the characteristics of cables and wires over the last decades have been reviewed. Based on different experimental forms and objects (laboratory wires and commercial cables), this paper summarizes the theories of the fire dynamics in wire combustion, including the models of ignition and flame propagation, the criteria for blowing off and quenching, and the critical conditions for dripping behavior. The effects of materials, layouts, and environments on wire combustion phenomena such as airflow, ambient pressure, oxygen, gravity, and orientation angle have been discussed in detail according to the theories of heat transfer and combustion. In addition, test standards and studies on the fire behavior and release of toxic gases of commercial cables have also been fully described. Through the summary of the above content, it is expected to build a preliminary theoretical framework and future research directions for researchers in the field of cable fires. Full article

Aiming at the cooperative localization problem for the dynamic UAV swarm in an anchor-limited environment, an adaptive Wasserstein filter (AWF) with distance-constrained bare bones self-recovery particles (CBBP) is proposed. Firstly, to suppress the cumulative error from the inertial navigation system (INS), a position-prediction strategy based on transition particles is designed instead of using inertial measurements directly, which ensures that the generated prior particles can better cover the ground truth and provide the uncertainties of nonlinear estimation. Then, to effectively quantify the difference between the observed and the prior data, the Wasserstein measure based on slice segmentation is introduced to update the posterior weights of the particles, which makes the proposed algorithm robust against distance-measurement noise variance under the strongly nonlinear model. In addition, to solve the problem of particle impoverishment caused by traditional resampling, a diversity threshold based on Gini purity is designed, and a fast bare bones particle self-recovery algorithm with distance constraint is proposed to guide the outlier particles to the high-likelihood region, which effectively improves the accuracy and stability of the estimation. Finally, the simulation results show that the proposed algorithm is robust against cumulative error in an anchor-limited environment and achieves more competitive accuracy with fewer particles. Full article

Using Uncrewed Aerial Vehicles (UAVs) to monitor the condition of nodal transportation assets—airports, seaports, heliports, vertiports, and cargo terminals—presents a transformative approach to traditional inspection methods. The focus on nodal assets rather than linear assets like roads, railways, bridges, and waterways fills a gap in addressing the dynamic challenges specific to transportation hubs. This study reviews scholarly literature on applying UAV-based remote sensing (URS) techniques to assess the condition of various transportation hubs, which are critical junctures in global logistics networks. Utilizing a systematic literature review framework, this study reviewed 486 publications from 2015 to 2023 to extract insights from the evolving discourse on URS applications. The findings suggest that these emerging methods resulted in substantial enhancements in time saving, cost efficiency, safety, and reliability. Specifically, this study presents evidence on how URS approaches can overcome the constraints of conventional inspection methods by enabling rapid, high-precision mapping and surveillance in complex and constrained environments. The findings highlight the role of UAVs in enhancing operational workflows and decision making in transportation planning and maintenance. By bridging the gap between traditional practices and innovative technology, this research offers significant implications for stakeholders in the field, advocating for a shift towards more dynamic, cost-effective, and precise asset management strategies. Full article

Landing a multi-rotor uncrewed aerial vehicle (UAV) on a moving target in the presence of partial observability, due to factors such as sensor failure or noise, represents an outstanding challenge that requires integrative techniques in robotics and machine learning. In this paper, we propose embedding a long short-term memory (LSTM) network into a variation of proximal policy optimization (PPO) architecture, termed robust policy optimization (RPO), to address this issue. The proposed algorithm is a deep reinforcement learning approach that utilizes recurrent neural networks (RNNs) as a memory component. Leveraging the end-to-end learning capability of deep reinforcement learning, the RPO-LSTM algorithm learns the optimal control policy without the need for feature engineering. Through a series of simulation-based studies, we demonstrate the superior effectiveness and practicality of our approach compared to the state-of-the-art proximal policy optimization (PPO) and the classical control method Lee-EKF, particularly in scenarios with partial observability. The empirical results reveal that RPO-LSTM significantly outperforms competing reinforcement learning algorithms, achieving up to 74% more successful landings than Lee-EKF and 50% more than PPO in flicker scenarios, maintaining robust performance in noisy environments and in the most challenging conditions that combine flicker and noise. These findings underscore the potential of RPO-LSTM in solving the problem of UAV landing on moving targets amid various degrees of sensor impairment and environmental interference. Full article

Predicting stock trends in financial markets is of significant importance to investors and portfolio managers. In addition to a stock’s historical price information, the correlation between that stock and others can also provide valuable information for forecasting future returns. Existing methods often fall short of straightforward and effective capture of the intricate interdependencies between stocks. In this research, we introduce the concept of a Laplacian correlation graph (LOG), designed to explicitly model the correlations in stock price changes as the edges of a graph. After constructing the LOG, we will build a machine learning model, such as a graph attention network (GAT), and incorporate the LOG into the loss term. This innovative loss term is designed to empower the neural network to learn and leverage price correlations among different stocks in a straightforward but effective manner. The advantage of a Laplacian matrix is that matrix operation form is more suitable for current machine learning frameworks, thus achieving high computational efficiency and simpler model representation. Experimental results demonstrate improvements across multiple evaluation metrics using our LOG. Incorporating our LOG into five base machine learning models consistently enhances their predictive performance. Furthermore, backtesting results reveal superior returns and information ratios, underscoring the practical implications of our approach for real-world investment decisions. Our study addresses the limitations of existing methods that miss the correlation between stocks or fail to model correlation in a simple and effective way, and the proposed LOG emerges as a promising tool for stock returns prediction, offering enhanced predictive accuracy and improved investment outcomes. Full article

The growing applicability of functionally graded materials is justified by their ability to contribute to the development of advanced solutions characterized by the material customization, through the selection of the best parameters that will confer the best mechanical behaviour for a given structure under specific operating conditions. The present work aims to attain the optimal design solutions for a set of illustrative 2D and 3D discrete structures built from functionally graded materials using the Red Fox Optimization Algorithm, where the design variables are material parameters. From the results achieved one concludes that the optimal selection and distribution of the different materials’ mixture and the different exponents associated with the volume fraction law significantly influence the optimal responses found. To note additionally the good performance of the coupling between this optimization technique and the finite element method used for the linear static and free vibration analyses. Full article

Irradiation with ultraviolet A (UVA) plays an important role in the pathogenesis of skin photoaging since it increases oxidative stress and inflammation in the epidermis. There is an urgent need to screen, investigate, and apply the potential anti-photoaging active ingredients. Agaricus blazei Murill (ABM) polysaccharides have a wide range of promising pharmacological applications. Previous studies have confirmed their antioxidant effect, but whether it has an anti-photoaging effect is unclear. In this study, two ABM polysaccharides (AB-J and AB-K) were obtained to discuss the potential photodamage-protective capacity. The free radical scavenging abilities in vitro, the safety assessment, and their protective effects and mechanisms on UVA-induced human fibroblasts (HSFs) were evaluated. The intracellular antioxidant enzyme levels and extracellular matrix proteins, such as COL-I and ELN, were significantly accelerated, and metalloproteinases (MMP-1, and MMP-9) were decreased by AB-J and AB-K. The Keap-1-Nrf2/ARE signaling pathway was activated, thus inducing the upregulated expression of downstream genes (Ho-1 and Nqo-1). The suppression of P38 and Jnk1 by AB-J and AB-K was speculated to be the inducer of the activation of the Keap-1-Nrf2/ARE signaling pathway. Owing to the excellent exhibition of AB-J, its safety assessment and the structural characterization are discussed further. Full article

Mitochondria, as the core metabolic organelles, play a crucial role in aerobic respiration/biosynthesis in fungi. Numerous studies have demonstrated a close relationship between mitochondria and Candida albicans virulence and drug resistance. Here, we report an octapeptide-aminopeptidase located in the mitochondrial matrix named Oct1p. Its homolog in the model fungus Saccharomyces cerevisiae is one of the key proteins in maintaining mitochondrial respiration and protein stability. In this study, we utilized evolutionary tree analysis, gene knockout experiments, mitochondrial function detection, and other methods to demonstrate the impact of Oct1p on the mitochondrial function of C. albicans. Furthermore, through transcriptome analysis, real-time quantitative PCR, and morphological observation, we discovered that the absence of Oct1p results in functional abnormalities in C. albicans, affecting hyphal growth, cell adhesion, and biofilm formation. Finally, the in vivo results of the infection of Galleria mellonella larvae and vulvovaginal candidiasis in mice indicate that the loss of Oct1p led to the decreased virulence of C. albicans. In conclusion, this study provides a solid theoretical foundation for treating Candida diseases, developing new targeted drugs, and serves as a valuable reference for investigating the connection between mitochondria and virulence in other pathogenic fungi. Full article

Farm leftovers, particularly crop residues, are a key source of renewable energy in Canada. The nation’s robust agricultural industry provides ample biomass, derived from forestry and agriculture resources, for energy generation. Crop residues, such as straws and husks, play a crucial role in this biomass reservoir, contributing to biofuel production and greenhouse gas mitigation efforts. Focusing on supply chains, waste management, and emission reduction, this study evaluates the sustainability of wheat straw, an agricultural biomass by-product. The environmental issues of various approaches to managing agricultural biomass were explored. Following an evaluation of biomass features, conversion methods, and economic and environmental advantages, the results show anaerobic digestion to be the most sustainable approach. Four metrics were examined in relation to social elements, and numerous aspects were considered as inputs in the evaluation of transportation costs. The use of electric trucks versus fuel-based trucks resulted in an 18% reduction in total operating costs and a 58% reduction in consumption costs. This study examined CO₂ emissions over four different transportation distances. The data indicate that a significant reduction of 36% in kg CO₂ equivalent emissions occurred when the distance was lowered from 100 km to 25 km. These findings offer insights for creating practical plans that should increase the sustainability of agricultural biomass leftovers. Full article

Osteoporosis, a terminal illness, has emerged as a global public health problem in recent years. The long-term use of bone anabolic drugs to treat osteoporosis causes multi-morbidity in elderly patients. Alternative therapies, such as allogenic and autogenic tissue grafts, face important issues, such as a limited source of allogenic grafts and tissue rejection in autogenic grafts. However, stem cell therapy has been shown to increase bone regeneration and decrease osteoporotic bone formation. Stem cell therapy combined with betulin (BET) supplementation might be adequate for bone remodeling and new bone tissue generation. In this study, the effect of BET on the viability and osteogenic differentiation of hFOB 1.19 cells was investigated. The cells were encapsulated in alginate–gelatin (AlGel) microbeads. In vitro tests were conducted during the 12 d of incubation. While BET showed cytotoxic activity (>1 µM) toward non-encapsulated hFOB 1.19 cells, encapsulated cells retained their functionality for up to 12 days, even at 5 µM BET. Moreover, the expression of osteogenic markers indicates an enhanced osteo-inductive effect of betulin on encapsulated hFOB 1.19, compared to the non-encapsulated cell culture. The 3D micro-environment of the AlGel microcapsules successfully protects the hFOB 1.19 cells against BET cytotoxicity, allowing BET to improve the mineralization and differentiation of osteoblast cells. Full article

Biologics, including monoclonal antibodies (mAb), have proved to be effective and successful therapeutic agents, particularly in the treatment of cancer and immune-inflammatory conditions, as well as allergies and infections. However, their use carries an inherent risk of an immune-mediated adverse drug reaction. In this study, we describe the use of a novel pre-clinical human in vitro skin explant test for predicting skin sensitization and adverse immune reactions. The skin explant test was used to investigate the effects of therapeutic antibodies, which are known to cause a limited reaction in a small number of patients or more severe reactions. Material and Methods: Immune responses were determined by T cell proliferation and multiplex cytokine analysis, as well as histopathological analysis of skin damage (grades I–IV in increasing severity), predicting a negative (grade I) or positive (grade ≥ II) response for an adverse skin sensitization effect. Results: T cell proliferation responses were significantly increased in the positive group (p < 0.004). Multiplex cytokine analysis showed significantly increased levels of IFNγ, TNFα, IL-10, IL-12, IL-13, IL-1β, and IL-4 in the positive response group compared with the negative response group (p < 0.0001, p < 0.0001, p < 0.002, p < 0.01, p < 0.04, p < 0.006, and p < 0.004, respectively). Conclusions: Overall, the skin explant test correctly predicted the clinical outcome of 13 out of 16 therapeutic monoclonal antibodies with a correlation coefficient of 0.770 (p = 0.0001). This assay therefore provides a valuable pre-clinical test for predicting adverse immune reactions, including T cell proliferation and cytokine release, both associated with skin sensitization to monoclonal antibodies. Full article

This study aimed to investigate the efficacy of supercritical CO₂ (SC-CO₂) extraction in enhancing the extraction rate, purity, and antioxidant activity of Indocalamus latifolius (Keng) McClure (Poaceae) leaf terpenoids (ILLTs). Crude extracts obtained from leaves were subjected to qualitative and quantitative analyses, revealing neophytadiene, phytol, β-sitosterol, β-amyrone, squalene, and friedelin as the primary terpenoid constituents, identified through gas chromatography–mass spectrometry (GC-MS). Compared with steam distillation extraction (SD), simultaneous distillation extraction (SDE), ultra-high pressure-assisted n-hexane extraction (UHPE-Hex), ultra-high pressure-assisted ethanol extraction (UHPE-EtOH), ultrasound-assisted n-hexane extraction (UE-Hex), and ultrasound-assisted ethanol extraction (UE-EtOH), SC-CO₂ exhibited a superior ILLT extraction rate, purity, and antioxidant activity. Scanning electron microscopy (SEM) observations of the residues further revealed more severe damage to both the residues and their cell walls after SC-CO₂ extraction. Under optimal parameters (4.5 h, 26 MPa, 39 °C, and 20% ethyl alcohol), the ILLT extraction rate with SC-CO₂ reached 1.44 ± 0.12 mg/g, which was significantly higher than the rates obtained by the other six methods. The subsequent separation and purification using WelFlash C18-l, BUCHI-C18, and Sephadex LH-20 led to an increase in the purity of the six terpenoid components from 12.91% to 93.34%. Furthermore, the ILLTs demonstrated cytotoxicity against HepG2 cells with an IC₅₀ value of 148.93 ± 9.93 μg/mL. Additionally, with increasing concentrations, the ILLTs exhibited an enhanced cellular antioxidant status, as evidenced by reductions in both reactive oxygen species (ROS) and malondialdehyde (MDA) levels. Full article

This paper presents a few-mode fiber (FMF) various fault-detection method for long-reach mode division multiplexing (MDM) based on multi-mode transmission reflection analysis (MM-TRA). By injecting unmodulated continuous light into the FMF, and measuring and quantitatively analyzing the transmitted and reflected or Rayleigh backscattering power of different spatial modes, it is possible to accurately detect and locate reflective and non-reflective fault events. This paper discusses the localization accuracy of fault types such as FMF break, FMF link connector mismatch, and FMF bending. Theoretical analysis and simulation experimental results demonstrate that the proposed MM-TRA can provide an effective characterization of various faults and can achieve high fault localization accuracy. In addition, the influence of mode crosstalk of mode multiplexer/demultiplexer and mode coupling in FMF on the localization accuracy of various faults are considered. The results indicate that when using the combination of LP₀₁ and LP₂₁ modes, the localization errors for the FMF break, connector mismatch, and bending are 3.42 m, 1.97 m, and 3.29 m, respectively, demonstrating good fault localization performance. Full article