Search Results (32,163)

This modeling study investigates the impact of the 2023 Canadian wildfire aerosols (primarily black carbon and organic aerosol) on weather forecasts, concluding that incorporating real-time aerosol forcing improves model performance over using climatology. Experiments without real-time data severely underestimated aerosol optical depth (AOD), an error mitigated by including the forcing or using the coupled atmosphere–chemistry model. The aerosols exerted a strong direct radiative effect, reducing surface downward shortwave (SW) flux and generating corresponding surface cooling over the wildfire region. Furthermore, including aerosol–cloud interactions amplified this cooling and led to an increase in the overall cloud fraction and precipitation, illustrating complex indirect effects. While these physical improvements enhanced the representation of the atmosphere, the positive impact on overall medium-range forecasting performance (5–10 days) was modest, suggesting that the benefits of accurately representing wildfire feedback on the coupled Earth system are achieved through relatively slow processes, such as radiation feedback. Full article

Soil moisture (SM) in the mountains is critical for agropastoral productivity, and it is subject to both large-scale climate gradients and fine-scale effects of terrain, vegetation and soil. However, how the climate, topography, soil and vegetation factors impact surface SM spatiotemporal dynamics remains elusive in mountainous terrains, due to their complex interactions. Based on multi-source datasets, this study employs the structural equation model to investigate the impact pathways of climate and vegetation factors on annual surface SM dynamics from the year 2000 to 2022 in the Tianshan Mountains of China (TS). We also utilize the factor and interaction detectors of Geographical Detector to explore the individual and interactive effects of climate, topography, soil and vegetation factors on the spatial pattern of the annual surface SM. Moreover, their integrated impacts on the spatiotemporal dynamics of annual surface SM were investigated based on the explanatory power from the factor detector and total effects from structural equation modeling. The results showed that the multi-year average surface SM was 0.21 m³·m⁻³ for the whole region, with greater values in areas with dense vegetation and high elevation. Annual surface SM exhibited significant increasing trends across different land cover classifications and elevation zones, which was directly influenced by vegetation greenness enhancement. Precipitation (PRE) and relative humidity (RH) also significantly influenced the temporal variations in surface SM through their indirect effect on vegetation greenness, while these indirect effects were much lower than the direct effect of vegetation greenness. RH, PRE and surface net solar radiation (SSR) showed strong individual and interactive effects on the spatial distribution of surface SM, particularly the interactive effects of RH and PRE with wind speed (WS). Surface SM was highly sensitive to RH and PRE in the central TS. Overall, vegetation greenness, PRE and RH were the main drivers of surface SM variations across both temporal and spatial scales, while SSR, total evaporation and WS primarily shaped its spatial distribution. These insights enhance our understanding of land–atmosphere interactions in mountainous areas and provide scientific references for sustainable agropastoral water resource management under global warming. Full article

Cosmological filaments, galaxy clusters, and galaxies are magnetized reservoirs of cosmic rays (CRs). The exchange of CRs across these structures is usually modeled assuming that they remain charged and magnetically confined. At high energies, hadronic interactions can convert CR protons to neutrons. This physics is routinely included in air-shower and ultra-high-energy (UHE) CR propagation Monte Carlo simulations used for composition studies but is rarely treated explicitly in propagation models of CR transport and exchange between magnetized reservoirs. CR neutrons are not affected by magnetic fields and can propagate ballistically over kpc-Mpc distances before decaying back into protons, with relativistic time dilation extending their effective decay length. We show how such charged–neutral switching modifies CR confinement and escape in four representative environments: a Milky Way-like galaxy, a starburst galaxy, a galaxy cluster, and a cosmological filament. By solving the transport of a confined CR proton population in each structure using a diffusion/streaming propagation approach with hadronic pp and p$\gamma$ interactions, and treating neutron production and decay as a stochastic Poisson “jump” process, we find that neutron-mediated steps can allow additional CR escape from large-scale cosmological structures at energies where charged-particle transport alone would predict strong CR confinement and attenuation in ambient radiation fields. These effects imply a qualitative shift in how ultra-high-energy CRs are transferred from embedded sources into filaments and voids once intermediate neutron propagation is considered, with consequences for the partitioning of CRs across the large-scale structure of the Universe. Full article

Carbon dots offer excellent physico-chemical properties and biocompatibility for cancer theranostics systems, either as therapeutic agents themselves, or as potential drug carriers. It is, however, postulated that the drug carrier affects the mechanism of action and intracellular target molecules of a drug. Therefore, in the present study, we systematically evaluated protein alterations in HeLa cervical cancer cells after treatment with sulfur-doped carbon dots (S-CDs). Synchrotron Radiation μFTIR spectroscopy and label-free LC–MS/MS proteomics integrated with bioinformatics were used to assess molecular changes. μFTIR revealed a shift and increased intensity of α-helices, indicating structural changes in proteins as a result of the interaction between S-CDs and cells. Proteomic analysis identified 122 statistically significant (p ≤ 0.05) proteins with increased abundance and 61 with decreased abundance following S-CD exposure, many of which possess high α-helix content, consistent with μFTIR findings. Functional analyses showed that up-regulated proteins were enriched in molecular adaptor, transporter, and transcription regulator activities, particularly those involved in RNA metabolism and translation. Down-regulated proteins were dominated by protein-modifying enzymes and cytoskeletal components. Pathway enrichment analysis indicated alterations in mRNA processing, ribosomal pathways, translation factors, aminoacyl-tRNA biosynthesis, and proteasome degradation. Key hub proteins included ribosomal proteins and translation initiation factors. S-CD treatment led to opposite regulation of many proteins compared to their regulation in untreated HeLa cells including down-regulation of ribosomal proteins (RPS27L, RPS19, and RPS5), aminoacyl-tRNA biosynthesis proteins (IARS1, LARS1, and MARS1), and proteasome degradation proteins (PSMD2, PSMD3, and PSMD11), which aligns with the observed cytotoxic effect of S-CDs on cervical cancer cells. Overall, these results highlight significant proteomic and structural protein changes induced by S-CDs and support their potential for cervical cancer treatment, warranting further investigation of this nanomaterial’s biological applications. Full article

To reduce the time and computational cost of vibro-acoustic simulations in gear reducer noise evaluation, this study develops a simulation-driven surrogate modeling framework for a three-stage helical gear reducer. A high-fidelity “vibration–acoustic radiation” simulation chain is established, where the housing vibration responses computed in Romax Designer are mapped into ACTRAN to obtain the radiated noise. Using Optimal Latin Hypercube Sampling, 300 designs are generated by varying the first-stage pinion micro-modification parameters (tooth drum, tooth slope, and tooth profile), and the average RMS sound pressure level over six field points is adopted as the noise metric. A BP neural network (BPNN) surrogate is then constructed, in which Bayesian Optimization (BOA) is used to tune hidden layer nodes and learning rate, and an improved Sparrow Search Algorithm (ISSA) is employed to optimize the initial weights and biases, forming the proposed BOA-ISSA-BPNN model. On the test set, the proposed model achieves R² = 0.97499, RMSE = 0.91385, and MAE = 0.6547, with an average prediction time of 32.35s. Meanwhile, comparisons with SVM, BPNN, BOA-BPNN, SSA-BPNN, and ISSA-BPNN demonstrate superior prediction accuracy; moreover, relative to the hour-level computational cost of high-fidelity simulations, the proposed surrogate enables rapid noise evaluation on the order of tens of seconds, enabling fast micro-modification design iteration and practical engineering decision-making. Full article

Thoracoabdominal aortic aneurysms (TAAAs) are uncommon and usually silent until rupture, causing a substantial burden to the health care system. Aneurysm growth and rupture prediction is mainly based on aneurysm diameter measurement by imaging modalities, meaning that the biology of aneurysm growth is not part of a potentially more adequate surveillance of aortic aneurysm patients. Alternatives or complementary options for aortic aneurysm surveillance are an ongoing, non-addressed open issue of vascular medicine. The application of different biomarkers has been discussed, yet so far, an adequate candidate for aortic aneurysm surveillance, if it comes to the thoracic or thoracoabdominal aorta, preferably without radiation exposure, has not been named. Elastin breakdown, as a component of aortic wall degeneration primarily driven by matrix metalloproteinases (MMPs), is a core element of aneurysm development. Desmosine is an elastin-specific cross-link increasingly studied as a circulating or urinary biomarker of compromised aortic wall integrity and disease activity. Accordingly, this review investigated whether plasma desmosine (pDES), a highly specific marker of elastin degradation, could be used as a non-invasive biomarker for detecting aortic aneurysms and assessing their risk profile. The existing literature of desmosine in fields of aortic pathologies in the acute and chronic setting will be assessed based on the current literature; furthermore, future perspectives of desmosine as a biomarker of aortic pathologies, such as aortic aneurysm dynamics, will be discussed. Full article

The classical Neumann–Kelvin (NK) theory of potential flow around a free-surface-piercing ship that steadily advances in calm water or through regular waves is considered. Specifically, this study presents an elementary ‘no-equation interpretation’ of the rigid-waterplane linear flow model and the related modification of the NK theory recently presented by the authors and complements the detailed mathematical analysis given in that earlier study. Specifically, the NN (Neumann–Noblesse) integral equation obtained in that previous study by applying Green’s fundamental identity to an alternative linear flow model called the rigid-waterplane flow model, in which an open free-surface-piercing ship hull is closed by a rigid waterplane slightly submerged under the free surface, is interpreted in light of Saint-Venant’s principle. Briefly, the present study argues that the NK integral equation obtained in the classical NK theory of potential flow around a ship contains a singularity at the ship waterline and that this singularity is removed—in the spirit of the classical Saint-Venant principle—in the rigid-waterplane flow model and the related weakly-singular NN integral equation, which can then be viewed as a ‘regularization’ of the NK integral equation. This study also presents variants of the NN integral equation in which a function defined in terms of the ship hull surface geometry by an integral over the ship waterplane or an integral around the ship waterline is expressed as equivalent integrals over the ship hull surface. Like the NN integral equation given previously, the equivalent variants of the weakly-singular NN integral equation obtained in this study do not involve a waterline integral and hold for a ship that steadily advances in calm water or through regular waves, as well as for an offshore structure or a moored ship in regular waves. Full article

Radiation-responsive promoters represent a functionally distinct class of transcriptional regulatory elements that translate genotoxic stress signals into quantifiable gene expression outputs. These promoters occupy a unique mechanistic position within the broader radiation biomarker landscape: rather than directly measuring molecular damage products, they report the cellular interpretation of radiation-induced stress through coordinated gene regulatory networks. This review provides a systematic analysis of five major classes of radiation-responsive promoters—microRNA (miRNA) promoters, tRNA-derived small RNA (tsRNA) promoters, acute-phase protein gene promoters, DNA repair gene promoters, and long non-coding RNA (lncRNA) promoters—with emphasis on their regulatory logic, dose-response characteristics, and current evidence for clinical deployment. We further describe four complementary screening strategies: homology-based conservation analysis, functional genomics and transcriptomics, epigenetic modification profiling, and synthetic biology promoter engineering. Applications spanning biosensor development, biological dosimetry, treatment response prediction, and radiation-guided gene therapy are evaluated within a two-track framework that distinguishes biomarker-oriented applications (Track A) from tool-oriented reporter gene systems (Track B). Critical appraisal of current limitations—including insufficient clinical-grade validation, absence of standardized dose-response curves, and reproducibility deficits—is integrated throughout. Future priorities include multi-center prospective validation studies, FAIR-compliant data infrastructure, AI-driven multi-omics integration, and point-of-care detection platforms. Radiation-responsive promoter biology holds significant potential for advancing precision radiotherapy and nuclear emergency medical response, contingent upon systematic closure of the current evidence gap relative to established gold-standard cytogenetic methods. Full article

Background: Radiotherapy (RT) is a core modality for cancer treatment, yet it is plagued by inter-observer variability in target delineation, inefficient manual workflows, and challenges in fusing multi-type clinical data. Large language models (LLMs), with their superior semantic understanding and cross-modal fusion capabilities present novel solutions to these challenges. Scope: This narrative review provided a comprehensive overview of the current landscape and emerging trends of LLM applications across the entire RT workflow. Findings: LLMs demonstrated substantial clinical utility in key RT domains, including automated target volume delineation (e.g., Medformer, Radformer), dose prediction (e.g., DoseGNN), treatment planning automation (e.g., GPT-Plan), patient education, clinical decision support, medical information extraction, and prognosis assessment. These applications not only have the potential to enhance the accuracy and efficiency of RT but also facilitate the standardization of clinical pathways. However, widespread clinical adoption was impeded by critical limitations, including model hallucinations, insufficient generalizability, and unresolved issues regarding data privacy and ethical governance. Conclusions: LLMs possessed transformative potential to revolutionize radiation oncology. Future endeavors should prioritize technical refinements to mitigate model deficiencies, establish standardized evaluation benchmarks, and develop robust ethical frameworks. These concerted efforts are crucial for translating LLM research into clinical practice and advancing the era of intelligent, precision RT. Full article

Exposure of healthy tissue to ionizing radiation (IR) occurs due to nuclear accidents and terrorism, as well as radiotherapy. The vascular endothelium is a key target of IR, and microvascular endothelial cells (ECs) are particularly vulnerable to radiation. IR induces EC activation leading to endothelial cell injury. Human ghrelin is a stomach-derived peptide with pleiotropic effects, including protection against inflammation. We hypothesize that human ghrelin improves survival in total body irradiation (TBI) and that ghrelin’s protective effect could be mediated by attenuating endothelial cell injury. To test this, mice were exposed to TBI and after 24 h were treated subcutaneously with human ghrelin once daily for 4 days and monitored for 30 days. The survival rate of the human ghrelin-treated group was significantly higher than that of the vehicle group. Subsequently, human ghrelin treatment showed an effective dose modification factor of 1.0681. On day 4 after TBI, human ghrelin significantly attenuated EC permeability in the lungs and improved tight junction protein ZO-1 expression. Human ghrelin also improved ZO-1 and Claudin5 expression in primary mouse lung vascular endothelial cells. Taken together, these results indicate that human ghrelin improves survival after TBI, and its survival benefit is in part due to the attenuation of EC permeability and microvascular barrier dysfunction. Full article

Objectives: While the previous literature has established that meteorological conditions are associated with COVID-19 mortality fluctuations, the relative effect of each of these highly correlated factors remains unclear. This study aims to conduct a comparative analysis to determine which of three main meteorological variables—Ambient Temperature, Ultraviolet (UV) Index, and Sunlight Duration—have the strongest negative association with COVID-19 mortality. The objective is to quantify and rank their impact over a 7-to-21-day biological exposure window. Methods: We conducted retrospective spatiotemporal analyses in the form of panel Poisson Distributed Lag Models (PDLMs) regression using daily data from 21 January 2020 to 10 January 2023, spanning 129 distinct geographical regions worldwide. To ensure a direct and fair comparison of effect sizes, all meteorological and environmental variables were Z-score standardized. We estimated three independent PDLMs—each focusing separately on UV Index, Ambient Temperature, and Sunlight Duration—with lags ranging from 7 to 21 days. These models controlled for overarching time trends and utilized a categorical variable to account for Region Fixed Effects modeling time-invariant regional health and socioeconomic determinants (e.g., obesity, age demographics, healthcare capacity). Furthermore, distributed lags of daily PM2.5 (air pollution) and relative humidity were explicitly included in each model as dynamic confounders. Results: The comparison of PDLM results reveals that the UV Index has the strongest negative association with COVID-19 mortality. A one standard deviation increase in the UV Index corresponds to a massive, highly significant cumulative reduction in deaths observed 1 to 3 weeks later (p < 0.001). Sunlight Duration is the second-strongest protective meteorological factor, whereas Ambient Temperature has the weakest effect. The distributed lags of particulate matter (PM2.5) and relative humidity were found to be statistically insignificant when modeled alongside the meteorological variables. Conclusions: After standardizing variables and controlling for dynamic environmental confounders like air pollution and humidity, the study findings provide robust empirical evidence that meteorological conditions have a strong significant association with COVID-19 mortality fluctuation with a temporal delay, overcoming the confounding effects of merely dry or clear-air conditions. Full article

Traditional villages in the Jiangnan region have experienced significant spatial transformation under rural revitalization, yet thermal environment regulation in public spaces remains insufficiently addressed. This study examines how spatial morphology influences microclimate and outdoor thermal comfort during summer and proposes evidence-based climate-responsive strategies. Three representative provincial-level traditional villages in Wuxi—Yaogeli Village, Zhu Village, and Huangtutang Ancient Village Area—were selected as case studies. Public spaces were classified into open, semi-open, and semi-private types according to spatial openness. Field microclimate measurements and thermal comfort surveys were conducted, and Physiological Equivalent Temperature (PET) was calculated to evaluate thermal conditions. Results show that rural public spaces generally experience significant summer heat stress, with PET exceeding the neutral range during most daytime periods. Spatial openness is significantly positively correlated with PET, identifying solar radiation as the dominant thermal driver. Water bodies provide cooling benefits within limited spatial ranges, constrained by configuration and ventilation conditions. Ecological and composite surfaces reduce heat accumulation compared to single materials. These findings indicate that thermal comfort in rural public spaces is a multi-factor and interaction-driven process, providing empirical support for climate-adaptive rural renewal. Full article

Pinching-antenna systems (PASSs) offer a low-complexity and reconfigurable solution for near-field downlink communications by deploying multiple radiating elements along a single waveguide. Existing studies mainly assume simplified propagation conditions or focus on spectral efficiency, while the impact of environment-dependent interference patterns arising from user-specific blockage conditions on energy-efficient design remains unclear. An energy-efficient downlink design for single-waveguide PASS based on environment-division multiple access (EDMA) is investigated. Under a given propagation environment, EDMA exploits user-dependent blockage and visibility differences through proper pinching-antenna placement, thereby inducing different multi-user interference patterns without increasing radio-frequency hardware complexity. We examine how such blockage-dependent interference influences the relationship between spectral efficiency and energy efficiency, and develop an energy-aware EDMA framework that jointly considers pinching-antenna locations and transmit power allocation under quality-of-service constraints. The resulting coupled design problem is solved through an alternating optimization procedure. EDMA is compared with conventional time-division multiple access (TDMA) using a unified hardware and power-consumption model. Numerical results reveal clear energy-efficiency threshold behaviors with respect to blockage intensity, user population, and service requirements. The results further show that EDMA can significantly outperform TDMA in specific operating regimes. Full article

The Earth’s climate is an open nonlinear system, sustained far from thermodynamic equilibrium by solar radiation and energy and matter exchange among its four major subsystems: atmosphere, ocean, land, and cryosphere. Among these four subsystems, the ocean significantly influences and sustains Earth’s climate over decadal to millennial timescales. Although modern numerical models increasingly capture intricate dynamical details, the fundamental concepts of large-scale ocean variability are less frequently explored. This study revisits ocean circulation through the lens of self-organization theory and synergetics. The key synergetic concepts of mode competition, order parameters, and the slaving principle are interpreted within the framework of general ocean circulation and the Atlantic Meridional Overturning Circulation (AMOC). The Brusselator, a simplified model of a nonlinear dynamical system initially developed in chemical kinetics, serves as a conceptual analog for ocean circulation energy conversion. Despite its high abstraction, this proxy model effectively captures essential bifurcation behaviors, such as Hopf bifurcation transitions and limit-cycle behaviors. This clarifies feedback regulation, instability, and potential regime transitions in the AMOC. The synthesis in this study is intended for an interdisciplinary readership and highlights the broader applicability of synergetic principles to the complex Earth climate system maintained far from equilibrium. Full article

This paper introduces a compact sub-6 GHz multiple-input multiple-output (MIMO) antenna array developed for 5G smartphone applications. The design employs eight planar inverted-F antenna (PIFA) elements arranged to realize dual-band and dual-polarized operation. The antenna achieves impedance bandwidths of 3.3–3.7 GHz (11.4%) and 5.3–5.8 GHz (10%), covering key sub-6 GHz fifth-generation (5G) bands. To enhance diversity performance, the elements are distributed along the edges of the smartphone mainboard, enabling excitation of orthogonal polarization modes while maintaining an overall board size of 75 mm × 150 mm on an FR4 substrate. Even without the use of dedicated decoupling structures, the closely spaced antenna elements exhibit satisfactory isolation levels, varying between −12 dB and −22 dB across the operating bands. The antenna array achieves wide impedance bandwidths of approximately 400 MHz at 3.5 GHz and more than 500 MHz at 5.5 GHz, supporting high data-rate communication. In addition, the proposed system demonstrates very low correlation and active reflection, with envelope correlation coefficient (ECC) values below 0.002 and total active reflection coefficient (TARC) levels better than −20 dB. User interaction effects are also investigated, and the results confirm acceptable SAR levels and stable radiation behavior in the presence of the human body. Owing to its planar, dual-band/dual-polarization capability and compliance with safety requirements, the proposed antenna represents a promising practical solution for contemporary 5G handheld devices and future multi-band mobile platforms. Full article