Variation Trend Research Articles

Line Scanning Thermography for Rail Base Defect Detection

Rail base defects present significant maintenance challenges within the railway industry, as they are difficult to detect before they lead to failure. While various in-motion nondestructive evaluation (NDE) methods exist for inspecting rail, none of the existing NDE methods can inspect the rail base area reliably and efficiently. This paper presents finite element analysis (FEA) and experimental results applying a line scanning thermography (LST) approach developed for rail base area inspection. This work demonstrates the LST approach for dynamic inspection of thick steel components containing surface and subsurface anomalies. Initially, FEA was used to help design the experimental setup, then to compare trends in surface temperature variations with those from experimental trials. Through motorized testing, test specimens were moved through a region heated by three stationary line heaters, utilizing LST to capture temperature variations on the surface of each sample. The results have shown that subsurface features 6.3 mm in diameter and with aspect ratios greater than 1.5 were detectable in all specimens. This is a promising development that warrants further study.

Prediction of interface morphology formed by the oblique gas jet impinging on a liquid surface

This study presents a theoretical analysis of the oblique gas jet impingement process on a liquid surface, elucidating the evolution of the flow field distribution and the influence of jet parameters on cavity shape dynamics. By integrating surface tension effects, the existing Blanks and Chandrasekhara model was refined to develop an advanced predictive model for cavity morphology. The theoretical framework was substantiated through numerical simulations and corroborated with experimental measurements of cavity dimensions, captured using state-of-the-art machine vision technology. The findings reveal a consistent trend in cavity dimension variations: an increase in the cavity surface width with the elevation of the impinging angle from the vertical and an escalation in gas jet velocity. Conversely, a reduction in the impinging angle coupled with an increase in jet velocity leads to a deeper cavity. To enhance the predictive accuracy, the model underwent iterative optimization, incorporating experimental data and accounting for jet parameters. The refined model demonstrated achieved a maximum error of 0.135 mm and a minimum error of 0.03 mm, providing reliable forecasts of cavity depth, which is pivotal for applications in fluid dynamics and related engineering fields.

Prediction of ionospheric TEC during the occurrence of earthquakes in Indonesia using ARMA and CoK models

Predicting ionospheric Total Electron Content (TEC) variations associated with seismic activity is crucial for mitigating potential disruptions in communication networks, particularly during earthquakes. This research investigates applying two modelling techniques, Autoregressive Moving Average (ARMA) and Cokriging (CoK) based models to forecast ionospheric TEC changes linked to seismic events in Indonesia. The study focuses on two significant earthquakes: the December 2004 Sumatra earthquake and the August 2012 Sulawesi earthquake. GPS TEC data from a BAKO station near Indonesia and solar and geomagnetic data were utilized to assess the causes of TEC variations. The December 2004 Sumatra earthquake, registering a magnitude of 9.1–9.3, exhibited notable TEC variations 5 days before the event. Analysis revealed that the TEC variations were weakly linked to solar and geomagnetic activities. Both ARMA and CoK models were employed to predict TEC variations during the Earthquakes. The ARMA model demonstrated a maximum TEC prediction of 50.92 TECU and a Root Mean Square Error (RMSE) value of 6.15, while the CoK model predicted a maximum TEC of 50.68 TECU with an RMSE value of 6.14. The August 2012 Sulawesi earthquake having a magnitude of 6.6, revealed TEC anomalies 6 days before the event. For both the Sumatra and Sulawesi earthquakes, the GPS TEC variations showed weak associations with solar and geomagnetic activities but stronger correlations with the earthquake-induced electric field for the considered two stations. The ARMA model predicted a maximum TEC of 54.43 TECU with an RMSE of 3.05, while the CoK model predicted a maximum TEC of 52.90 TECU with an RMSE of 7.35. Evaluation metrics including RMSE, Mean Absolute Deviation (MAD), Relative Error, and Normalized RMSE (NRMSE) were employed to assess the accuracy and reliability of the prediction models. The results indicated that while both models captured the general trend in TEC variations, nuances emerged in their responses to seismic events. The ARMA model demonstrated heightened sensitivity to seismic disturbances, particularly evident on the day of the earthquake, whereas the CoK model exhibited more consistent performance across pre- and post-earthquake periods.

Investigating Caregiving Dynamics and Subjective Cognitive Decline: An Analysis Using BRFSS Database Insights

Background: Subjective cognitive decline (SCD), characterized by self-reported memory or cognitive difficulties, is an increasing concern among older adults. This study utilizes data from the Behavioral Risk Factor Surveillance System (BRFSS) to examine SCD prevalence, professional consultation patterns, and caregiving dynamics among U.S. adults aged 45 years and older. Objectives: To explore trends in the prevalence of SCD, the extent of professional consultation among those experiencing SCD, and recent caregiving activities. The study aims to identify demographic variations and assess changes over time. Methods: This cross-sectional study analyzes BRFSS data from 2020 and 2022, which includes self-reported data on cognitive symptoms, professional consultation, and caregiving activities. Descriptive statistics and age-adjusted prevalence estimates were computed for SCD, professional consultation, and caregiving activities. Comparative analyses were performed to identify trends between 2020 and 2022, and to assess variations across demographic groups. Results: Between 2020 and 2022, the age-adjusted prevalence of SCD among adults aged 45 and older rose from 9.7% to 11.7%, affecting both genders. Prevalence increased from 9.4% to 11.8% for males and from 10.0% to 11.7% for females. In 2022, Black non-Hispanic adults had a prevalence of 12.2%, Hispanic adults 12.3%, Asian non-Hispanic adults 9.4%, Hawaiian or Pacific Islander non-Hispanic adults 9.9%, American Indian or Alaska Native non-Hispanic adults 21.1%, and Multiracial non-Hispanic adults 19.2%. Professional consultation rates declined from 47.7% to 44.3%. Caregiving for individuals with dementia or cognitive impairment was reported by 22.4% in 2020, decreasing slightly to 21.3% in 2022. General caregiving showed a slight increase from 18.9% to 19.5%. Variations in SCD prevalence and caregiving activities were observed across gender, race, and ethnicity. Conclusion: The study highlights a rising trend in SCD and variations in professional consultation and caregiving dynamics. These findings emphasize the need for targeted public health strategies to address cognitive decline and support caregivers. Enhancing access to healthcare and caregiver resources is crucial for improving outcomes for affected individuals and their caregivers.

A theoretical analysis of the effect of hydrostatic pressure on cerium oxide for renewable energy applications

The characteristics of cubic cerium oxide (CeO2) have been investigated using density functional theory (DFT) using the PBE-GGA exchange–correlation functional. This study mainly focused on the structural, elastic, and optoelectronic properties of the CeO2 under the application of external hydrostatic pressure. It is observed that lattice constants and volume tend to decrease with increasing pressure. Based on the observed trends in lattice constants variations, CeO2 exhibits compressibility at high-pressure conditions, although it remains structurally unchanged throughout the pressure range of 0 to 100 GPa. Applying pressure within the range of 0 to 100 GPa reveals a distinct characteristic associated with the emergence of electronic bandgap opening. The material displays an indirect energy bandgap, with its magnitude increasing from 2.659 eV to 4.055 eV under rising pressure. To deeply understand the impact of external pressure on the optical behaviour of CeO2, extensive investigation has been conducted on several optical parameters such as the dielectric function, refractive index, optical reflectivity, absorption coefficient, optical conductivity, and loss function throughout the energy range up to 50 eV. However, there is a tendency for optical parameters to show sharpening peaks that shift somewhat towards higher energies. Furthermore, we have also tested the impact of bandgap modulation induced in CeO2 by proposing a CsSnBr3-based solar cell with the One-Dimensional Solar Cell Capacitance Simulator software. Based on our findings, the use of cubic cerium oxide may find its potential to enhance the performance of optoelectronic and renewable energy devices.

A hybrid physics-corrected neural network for RUL prognosis under random missing data

In order to accurately predict the remaining useful life (RUL) of mechanical equipment under conditions of missing data, this paper proposes a novel integrated framework for data repair and RUL prediction, named DRTCR. DRTCR possesses the dual functionality of missing data repair and RUL prediction. Initially, considering the underlying trends and periodic fluctuations in the signals, polynomial and trigonometric functions are incorporated into the implicit feature matrix (IFM) generated by Gaussian random functions. This approach involves constructing a data repair deep learning framework primarily based on LSTM and CNN. This framework facilitates the repair of missing data. Furthermore, this paper introduces the integration of trend, correlation, and robustness within the LSTM units. A predictive unit named TCRcell is devised, which enhances the feature extraction capability of the prediction model. Additionally, a corrective unit within TCRcell is constructed, predominantly centered around discrete Fourier transform (DFT) and discrete wavelet transform (DWT) as frequency domain feature extraction techniques. This incorporation introduces the physical mechanism information into DRTCR and refines the predictive outcomes of TCRcell. The global frequency perspective of DFT aids in capturing the overall trend in signal variations, while DWT precisely captures localized temporal details in the time series, resulting in a dynamically corrected TCRcell prediction outcome that combines both global trends and local intricacies. Finally, experimental validation was conducted to assess the predictive performance and robustness of DRTCR.

A Time-varying Equivalent Circuit Modeling and Measuring Approach for Intracardiac Communication in Leadless Pacemakers.

Intracardiac wireless communication is crucial for the development of multi-chamber leadless cardiac pacemakers (LCP). However, the time-varying characteristics of intracardiac channel pose major challenges. As such, mastering the dynamic conduction properties of the intracardiac channel and modeling the equivalent time-varying channel are imperative for realizing LCP multi-chamber pacing. In this paper, we present a limiting volume variational approach based on the electrical properties of cardiac tissues and trends in chamber volume variation. This approach was used to establish a quasi-static and a continuous time-varying equivalent circuit model of an intracardiac channel. An equivalence analysis was conducted on the model, and a discrete time-varying equivalent circuit phantom grounded on the cardiac cycle was subsequently established. Moreover, an ex vivo cardiac experimental platform was developed for verification. Results indicate that in the frequency domain, the congruence between phantom and ex vivo experimental outcomes is as high as 94.3%, affirming the reliability of the equivalent circuit model. In the time domain, the correlation is up to 75.3%, corroborating its effectiveness. The proposed time-varying equivalent circuit model exhibits stable and standardized dynamic attributes, serving as a powerful tool for addressing time-varying challenges and simplifying in vivo or ex vivo experiments.

Solar irradiance variability around Asia Pacific: Spatial and temporal perspective for active use of solar energy

This study discusses solar irradiance variability in the spatial and temporal domains for the active use of solar energy. The spatial domain was calculated using the difference between one location and another in a focused small tile area. The principal component analysis (PCA) was used for this analysis in the spatial and temporal domain. The Umbrella Effect Index (UI) was calculated to determine the probability of an umbrella effect event within a specific time range. This study discusses solar irradiance variability using solar irradiance data analyzed every 10 min from high-temporal observations of geostationary satellites in the Asia-Pacific region. This study shows that solar heterogeneity around the Asia-Pacific ranges from 0–135 W/m2 with a high tendency in the area around the equator and highlands. In addition, this study also shows that the Asia Pacific region has umbrella effect events of approximately 50–2224 h/year with an index ranging approximately 0–0.34. This study presents the annual analysis and seasonal trends of solar irradiance variability over the entire study area. Determining seasonal trends is important because electricity demand fluctuates significantly as seasons progress. An integrated analysis of heterogeneity and UI revealed trends in spatiotemporal variations in solar irradiance. This approach provides useful information for optimizing and managing the locations for installing solar power plants. Moreover, an evaluation of existing solar power plants is presented. Evaluations based on spatiotemporal data reveal impossible characteristics using traditional approaches that use long-term simple averages or typical solar irradiance data. This research shows the distributed photovoltaic (PV) system in wide area can increase the stability of solar energy supply to the grid.

Diagenetic evolution of Upper Cretaceous carbonate sequences (Sarvak Formation) in the Abadan Plain, Iran: evidence from petrographic, elemental, stable, and strontium isotopic data

ABSTRACT This study investigates the diagenetic evolution and geochemical variations within the Sarvak Formation by integrating the core, thin-section, scanning electron microscopy, X-ray diffraction, trace elements, carbon-oxygen, and strontium isotopic data from three wells in the Abadan Plain. The formation displays diverse diagenetic processes, influenced by multiple exposure surface condition including the Cenomanian-Turonian boundary (CT-ES) and middle Turonian (mT-ES). Meteoric diagenesis, shaped by tectonic activities and eustatic sea level changes, played a pivotal role, leading to dissolution (karstification), brecciation, cementation, and palaeosol formation. Geochemical analysis revealed significant elemental variations across the studied wells. Magnesium (Mg) exhibited peaks at sequence boundaries, responding to facies changes, while iron (Fe) and manganese (Mn) concentrations increased below disconformities, reflecting changes in redox conditions and karstification. Sodium (Na) concentrations varied with facies changes, showing peaks at sequence boundaries, indicative of palaeoexposure events. Strontium (Sr) isotopes aided in delineating stratigraphic positions of palaeoexposure surfaces and absolute dating of sequences. Increases in87Sr/86Sr ratios below disconformities suggested subaerial exposure events, with shorter durations at CT-ES and longer durations at mT-ES, contributing to dissolution features development. The δ13Ccarb and δ18Ocarb values indicated severe meteoric diagenesis below sequence boundaries, characterized by dissolution and reprecipitation of calcium carbonate as low-magnesium calcite (LMC) cements. Cross plots of δ13Ccarb vs. δ18Ocarb displayed inverted-J patterns, indicative of meteoric diagenesis effects. Comparison with previous studies highlighted similar trends in geochemical variations, with notable differences in element concentrations between wells. This study enhances our understanding of diagenetic history of the Sarvak Formation in the Abadan Plain and, in a larger scale, provides insights into diagenetic evolution of palaeoexposure-related carbonate sequences.

Organophosphate esters in milk across thirteen countries from 2020 to 2023: Concentrations, sources, temporal trends and ToxPi priority to humans

Recent increases in organophosphate ester (OPE) application have led to their widespread presence, yet little is known about their temporal trends in food. This study collected milk samples from 13 countries across three continents during 2020–2023, finding detectable OPEs in all samples (range: 2.25–19.7; median: 7.06 ng/g ww). Although no statistical temporal differences were found for the total OPEs during the 4-year sampling campaign, it was interesting to observe significant variations in the decreasing trend for Cl-OPEs and concentration variations for aryl-OPEs and alkyl-OPEs (p < 0.05), indicating changing OPE use patterns. Packaged milk exhibited significant higher OPE levels than those found in directly collected raw unpackaged milk, and milk with longer shelf-life showed higher OPE levels, revealing packaging material as a contamination source. No significant geographical differences were observed in milk across countries (p > 0.05), but Shandong Province, a major OPE production site in China, showed relatively higher OPE concentrations. The Monte Carlo simulation of estimated daily intakes indicated no exposure risk from OPEs through milk consumption. The molecular docking method was used to assess human hormone binding affinity with OPEs, amongst which aryl-OPEs had the highest binding energies. The Toxicological-Priority-Index method which integrated chemical property, detection frequency, risk quotients, hazardous quotients and endocrine-disrupting effects was employed to prioritize OPEs. Aryl-OPEs showed the highest scores, deserving attention in the future.

Prediction Model for Trends in Submarine Cable Burial Depth Variation Considering Dynamic Thermal Resistance Characteristics

Fault problems associated with submarine cables caused by variations in their burial depth are becoming increasingly prominent. To address the difficulty of detecting the burial depth of submarine cables and trends in its variation, a prediction model for submarine cable burial depth was proposed which considers the dynamic characteristics of thermal resistance. First, a parallel thermal circuit model of a three-core submarine cable was established, and a formula for calculating the submarine cable’s burial depth was derived based on a formula for calculating the submarine cable’s core temperature. Then, the calculation result was corrected by considering the dynamic characteristics of the thermal resistance of the submarine cable’s structural materials. On this basis, feature vectors associated with the seabed cable burial depth calculation data and time nodes were mined by a convolutional neural network and used as the input parameters of a long short-term memory network for optimization and training, and a prediction model for trends in seabed cable burial depth variation was obtained. Finally, an example analysis was carried out based on the actual electrical parameter data of submarine cables buried by an offshore oil and gas platform. The results showed that the prediction model for trends in variations in the burial depth of submarine cables based on the CNN-LSTM neural network can achieve high prediction accuracy and prediction efficiency.

Electrode potentials involving atoms and ions of metals in intermediate oxidation states in aqueous solutions

The electrode potentials of metal atoms (M+/M0 and M2+/M0 couples) were calculated from their standard electrode potentials in water minus the standard molar Gibbs energy of formation of the atoms in the gas phase, ΔfG0(Mgas0), and the Gibbs energy of hydration in solution, ΔhydG°. Electrode potentials are appreciably shifted (by 2.0–2.5 V) toward negative values relative to the potentials of the solid metals. For the univalent metals Cu0, Ag0, and Au0 (d10s1 electronic configuration), the electrode potentials of M+/M0 couples are –2.73, –1.90, and –1.82 V; for Ga0, In0, and Tl0 (d10s2p1 electronic configuration), they are –3.14, –2.45, and –1.99 V, respectively. For bivalent transition metals of period IV with the d5+ns2 configuration, the potentials of M2+/M0 couples are –2.50 V for Mn0, –2.45 V for Fe0, –2.33 V for Co0, –2.34 for Ni0, –1.29 V for Cu0, and –1.34 V for Zn0. For Cd0 and Hg0 (d10s2 configuration), the potentials are –0.87 and + 0.42 V. Estimation of the electrode potentials of bivalent metals in the intermediate and unstable oxidation states (M2+/M+ and M+/M0 couples) revealed their significant difference. In the case of Zn, Cd, and Hg, this difference is particularly noticeable, as large as 2–3 V, because of different configurations of the M+ (d10s1) and M0 (d10s2) electronic shells. Regular trends in variations of the electrode potentials in the periods and groups of the periodic table were revealed. In going from the atomic-molecular to the solid state, the chemical activity of the metals decreases. The metal surface catalyzes the reactions that are thermodynamically unfavorable in the solution volume.

Recent-year variations in O3 pollution with high-temperature suppression over central China

By analyzing environmental and meteorological monitoring data over recent years of 2015–2022, the Twain-Hu Basin (THB) in central China was identified as a regional O3 pollution center over China with the highest increasing trend at 1.10 %⸱yr−1 in interannual variations of O3 concentrations with deteriorating O3 pollution over recent years. We explored the spatiotemporal variations in O3 pollution in the THB with ozone suppression (OS) under high air temperature over metropolitan, small urban, and mountainous areas. The bipolarized interannual trends in interannual O3 variations in urban and mountainous areas over central China were characterized with the increasing and decreasing 90th percentiles of the daily maximum 8-h (MDA8-90) O3 concentrations respectively in polluted urban areas and clean mountainous areas over recent eight years. The changes of the near-surface O3 concentrations with air temperature exhibited the inflection points of OS from increasing to decreasing O3 at air temperature of 30.5 °C in mountainous areas, 32.5 °C in small urban areas, and 34.5 °C in metropolitan areas, and the intensity of OS was estimated in the ranking with mountainous areas (−2.30 μg⸱m−3⸱°C−1) > small urban areas (−1.96 μg⸱m−3⸱°C−1) > metropolitan areas (−1.54 μg⸱m−3⸱°C−1), indicating that the OS was more significant over the lower-O3 mountainous areas. This study has implications for understanding O3 pollution variations with the meteorological drivers.

Anti-IL-6 Receptor Treatment in Giant Cell Arteritis Patients Reduces Levels of IL-1β-Receptor Antagonist but Not IL-1β

This work aimed to investigate a potential link between serum IL-1β levels in patients with giant cell arteritis (GCA) and their responsiveness to combined anti-IL-6 receptor (IL-6R) and glucocorticoid (GC) treatments within the context of two separate clinical trials. IL-1β levels were analyzed in serum samples of two prospective clinical trials investigating tocilizumab in GCA patients using quantitative Polymerase Chain Reaction (qPCR) based Proximity Ligation Assays (PLA). In the phase II randomized controlled trial, serum samples from five patients were quantified at two critical time points: the commencement of the trial (Week 2) and the conclusion of the trial (Week 52). In the GUSTO trial, serum samples from nine patients were similarly analyzed using PLA at Day 0 and Week 52. Furthermore, for the GUSTO trial, serum samples from 18 patients were assessed for IL-1β and IL-1RN at six time points: days 0, 3, and 10, weeks 4, 24, and 52 by a second assay (Proximity Extension Assay, PEA). PLA results from both studies indicated that IL-1β levels were below 1 pg/mL in most of the patients, resulting in notable signal deviations within the same samples. In the analysis of the GUSTO trial, both PLA and PEA exhibited similar trends in IL-1β variations among patients from day 0 to week 52. Notably, the PEA analysis did not show significant variation over time. Furthermore, we did not find a correlation of IL-1β levels with active disease as compared to remission, but interestingly, the measurement of IL-1β receptor antagonist (IL-1RN) revealed a substantial decrease over time. Our study shows that IL-1RN but not IL-1β concentration in serum samples could be directly related to anti-IL-6R treatment in patients diagnosed with GCA.

Why Is the Bandgap of GaP Indirect While That of GaAs and GaN Are Direct?

Many III–V semiconductors possess direct bandgaps and are thus widely applied in optoelectronics. Although GaN (either in wurtzite phase or zinc blende phase), GaAs, and GaSb are well‐known direct‐gap semiconductors, GaP exhibits an indirect bandgap nevertheless. In this work, the generic rule of energy gaps in GaN, GaP, and GaAs of the zinc blende phase is analyzed, and the trends of gap variation are studied concerning the lattice constant and anion electronegativity. It turns out that GaP actually manifests a normal behavior, the reason why GaN surprisingly has a direct gap is analyzed through examining and perturbing its valence band as well as conduction band (CB). The CB electron shows a non‐negligible probability to emerge near the N cores. The attractive nucleus potential pulls down the CB more strongly at Γ, which is in principle further supported through an analysis of the Kronig–Penney model. The difference between GaP and GaN in this respect is also analyzed in detail.

Experimental and numerical investigation on the effect of frequency combinations on PFOA defluorination by dual-frequency ultrasound coupling persulfate

Due to the synergistic contribution, dual-frequency ultrasound can significantly enhance the degradation of organic contaminants, but the effects of different frequency combinations have not been clarified and need to be explored. In this study, several frequency combinations were designed firstly both in experimental exploration and numerical simulation within the dual-frequency ultrasound coupling persulfate (PS) system to investigate the effect of frequency combinations on the degradation of perfluorooctanoic acid (PFOA). The monitoring parameters included the defluorination percentage and the simulated maximum expansion ratio (Rmax/R0). The simulated maximum expansion ratios in different frequency combinations showed a high correlation with their defluorination results, indicating that the discrepancy in defluorination effects of different frequency combinations was mostly attributed to their various maximum expansion ratios. Additionally, various maximum expansion ratios could result in different maximum solution temperatures, and the increase in temperature was found positive for PFOA defluorination in this study. In addition, the synergistic parameters that affected the maximum expansion ratio were analyzed, including the phase difference, frequency ratio, and frequency value. The obtained results showed that the maximum expansion ratio varied with different phase differences, and the frequency ratio could affect the variation trend. For the same fundamental frequency, the larger the frequency ratio, the smaller the maximum expansion ratio. Under the same phase difference and frequency ratio, the larger the frequency value, the lower the cavitation.

Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study

Objective. This study aims to investigate the biological effectiveness of Spread-Out Bragg-Peak (SOBP) proton beams with initial kinetic energies 50–250 MeV at different depths in water using TOPAS Monte Carlo code. Approach. The study modelled SOBP proton beams using TOPAS time feature. Various LET-based models and Repair-Misrepair-Fixation model were employed to calculate Relative Biological Effectiveness (RBE) for V79 cell lines at different on-axis depths based on TOPAS. Microdosimetric Kinetic Model and biological weighting function-based models, which utilize microdosimetric distributions, were also used to estimate the RBE. A phase-space-based method was adopted for calculating microdosimetric distributions. Main results. The trend of variation of RBE with depth is similar in all the RBE models, but the absolute RBE values vary based on the calculation models. RBE sharply increases at the distal edge of SOBP proton beams. In the entrance region of all the proton beams, RBE values at 4 Gy i.e. RBE(4 Gy) resulting from different models are in the range of 1.04–1.07, comparable to clinically used generic RBE of 1.1. Moving from the proximal to distal end of the SOBP, RBE(4 Gy) is in the range of 1.15–1.33, 1.13–1.21, 1.11–1.17, 1.13–1.18 and 1.17–1.21, respectively for 50, 100, 150, 200 and 250 MeV SOBP beams, whereas at the distal dose fall-off region, these values are 1.68, 1.53, 1.44, 1.42 and 1.40, respectively. Significance. The study emphasises application of depth-, dose- and energy- dependent RBE values in clinical application of proton beams.

Ecological Environment Assessment and Driving Mechanism Analysis of Nagqu and Amdo Sections of Qinghai-Xizang Highway Based on Improved Remote Sensing Ecological Index

The ecological environment along the Qinghai-Xizang highway is an important part of the construction of the ecological civilization in the Xizang region, and current research generally suffers from difficulties in data acquisition, low timeliness, and failure to consider the unique "alpine saline" environmental conditions in the study area due to the unique geographical environment of the Qinghai-Xizang plateau. Based on the GEE platform and the unique geographical environment of the study area, the remote sensing ecological index (RSEI) was improved, and a new saline remote sensing ecological index (SRSEI) applicable to the alpine saline region was constructed by using principal component analysis as an ecological environment quality evaluation index. The spatial distribution pattern and temporal variation trend of ecological environment quality along the Qinghai-Xizang Highway Nagqu-Amdo section were analyzed at multiple spatial and temporal scales using the ArcGIS 10.3 platform and geographic probes, and the driving mechanisms of eight control factors, including natural and human-made, on the spatial and temporal changes in SRSEI were investigated. The results showed that:① compared with RSEI, SRSEI was more sensitive to vegetation and had a stronger discriminatory ability in areas with sparse vegetation and severe salinization, which is suitable for ecological quality evaluation in alpine saline areas. ② The spatial scale of ecological environment quality in the study area had obvious geographical differentiation, and the areas with poor ecological quality were mainly concentrated in the northern Amdo County, whereas the areas with excellent and good quality grades were mainly distributed in the central-western and southeastern Nagqu areas. On the temporal scale, the ecological environment of the study area as a whole showed an improvement trend over 32 years, and the vegetation cover in the central-western and southeastern areas increased significantly, which had a strong improvement effect on the ecological environment. The improvement area was 1 425.98 km2, accounting for 99.82%. The mean value of SRSEI was 0.49, with an overall fluctuating upward trend and an average increase of 0.015 7 a-1. ③ The land use pattern was the most driving influence factor in the change of ecological environment quality in the study area, with an average q value of 0.157 6 over multiple years, and the influence of environmental factors was low. The multi-factor interaction results showed that the ecological environment in the study area was the result of multiple factors acting together, all factors had synergistic enhancement under the interaction, the influence of human factors was gradually increasing, and the interaction of the net primary productivity (NPP) of vegetation and land use pattern was the main interactive control factor of ecological environment quality in the study area. This study can provide a theoretical basis for ecological environmental protection and sustainable development along the Nagqu to Amdo section.

Calculation and Analysis of Equilibrium Position of Aerostatic Bearings Based on Bivariate Interpolation Method

The solution of equilibrium positions is a critical component in the calculation of the dynamic characteristic coefficients of aerostatic bearings. The movement of the rotor in one direction leads to bidirectional variations in the air film force, resulting in low efficiency when using conventional calculation methods. It can even lead to iterative divergence if the initial value is improperly selected. This study concentrates on the orifice throttling aerostatic bearings and proposes a novel method called the bivariate interpolation method (BIM) to calculate the equilibrium position. The equilibrium equation for the rotor under the combined influence of air film forces, gravity, and external loads is established. A calculation program based on the finite difference method is developed to determine the equilibrium position. The process of solving the equilibrium position and the convergence is compared with the secant method and the search method. Furthermore, the variation trend of the equilibrium position and stiffness when the external loads changes are studied based on the BIM. Finally, the correctness of the BIM to solve the equilibrium position is proved by comparing it with the experiment results. The calculation results indicate that the BIM successfully resolves the problem of initial value selection and exhibits superior computational efficiency and accuracy. The equilibrium position initially moves away from the direction of the external load as the load increases, and then this gradually approaches the load direction. The main stiffness increases with increases in the external load, while the variation in cross stiffness depends on the direction of the external load.

Occurrence Frequency of Global Atmospheric River (AR) Events: A Data Fusion Analysis of 12 Identification Data Sets

AbstractThe atmospheric river (AR) is a long, narrow, and transient corridor of strong horizontal water vapor transport. Various AR detection methods have been proposed, which have introduced significant uncertainty to the identified AR characteristics. This study has designed a data fusion algorithm to merge 12 data sets of different global and regional AR identification algorithms published by the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) covering the period from 1980 to 2016. It aims to conduct frequency statistics to further research the global distribution, interannual variation, the trends in poleward shifting, and the impacted factors of AR occurrence. The quantitative results indicate an overall increasing trend in interannual variation, with a more pronounced growth trend observed in the oceanic region between 40 and 60ºS. Additionally, the study identifies a poleward shift in the peak latitude of AR occurrence frequency, with speeds of 0.589° and 0.769° per decade in the Northern and Southern Hemispheres, respectively. This shift may be associated with the tropical poleward expansion. Upon examining the relationship between AR frequency and sea surface temperature (SST) as well as zonal wind, the study finds that distinct dominant factors influence AR in different regions. AR events near the 30°N/S ocean are influenced more significantly by zonal wind than by SST. These findings shed light on the global characteristics of AR occurrences and provide insights into the factors governing their variability across different areas.