Ground Temperature Research Articles

Investigating hydrological processes using explainable deep-learning models

This paper examines how meteorological factors influence streamflow. It is crucial for water resources planning and management. It develops three deep learning models (LSTM, RF and GBM) and compares their performance with multiple linear regression (MLR). LSTM is identified as the best model, and SHAP is used to analyze the contributions of different factors to streamflow. The model is applied to the Tang River catchment in China. The results indicate that: 1) DL models outperform MLR in nonlinear regression; 2) the ranking of meteorological factors contributing to streamflow is: precipitation, evaporation, relative humidity, sunshine duration, ground temperature, and wind speed; 3) these factors affect streamflow within a 12-day lead time, with significant contributions closer to the prediction date; 4) during droughts, precipitation has a reduced effect on streamflow, suggesting groundwater recharge is likely recharged by groundwater. The model enhances our understanding of how meteorological factors interact with streamflow dynamics.

Imaging and clinical manifestations of hematogenous dissemination in melioidosis

BackgroundAlthough there is a high incidence of hematogenous infections in melioidosis, a tropical infectious disease, there are few systematic analyses of hematogenous melioidosis in imaging articles. A comprehensive clinical and imaging evaluation of hematogenous melioidosis be conducted in order to achieve early diagnosis of the disease.Materials and methodsWe conducted an analysis of 111 cases of melioidosis diagnosed by bacteriological culture between August 2001 and September 2022. The analysis focused on observing the main manifestations of chest imaging and clinical data, including nodules, cavities, consolidation, ground glass opacity(GGO), pleural effusion, centrilobular nodules, and temperature, leucocyte count, diabetes, etc. Our study involved univariate and multivariate analyses to identify significant diagnostic variables and risk predictive factors.ResultsA total of 71.2% (79/111) of melioidosis cases were caused by hematogenous infection, and the most common organ involved was the lungs (88.5%, 100/113). The incidence of sepsis in patients with lung abnormalities was high (73%, 73/100), and the mortality rate of septic shock was 22% (22/100). Univariate analysis showed that the radiologic signs of blood culture-positive cases were more likely to have bilateral pulmonary and subpleural nodules (p = 0.003), bilateral GGO (p = 0.001), bilateral hydrothorax (p = 0.011). The multivariate analysis revealed a significant improvement in the area under the receiver operating characteristic curve (AUC) when comparing the model that included both clinical and radiologic variables to the model with clinical variables alone. The AUC increased from 0.818 to 0.932 (p = 0.012). The most important variables in the logistic regression with backward elimination were found to be nodule, GGO, and diabetes.ConclusionThe combination of CT features and clinical variables provided a valuable and timely warning for blood borne infectious melioidosis.

Estimating monthly NO2, O3, and SO2 concentrations via an ensemble three-stage procedure with downscaled satellite remote sensing data and ground measurements

The gaseous air pollutants nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), in addition to particulate matter (PM2.5), are known to be associated with many adverse health effects. However, exposure estimates may not be available in rural or mountainous areas without monitoring stations. In this study, we retrieved satellite remote sensing data for NO2, O3, and SO2 from the Ozone Monitoring Instrument (OMI) L3 products. Together with ground measurements (air monitoring stations and meteorological and land use data), we estimated the monthly NO2, O3, and SO2 concentrations with a spatial resolution of 3×3 km across Taiwan from 2005 to 2019. A three-stage estimation procedure was utilized: in Stage 1, an ensemble generalized additive model (GAM) and machine learning method were used to determine the spatiotemporal variations; in Stage 2, the remote sensing data were downscaled; and in Stage 3, the downscaled concentrations were reused in the Stage 1 procedure for fine-tuning estimations. We obtained overall leave-one-out cross-validation (LOOCV) R2 values ranging from 0.927-0.950, 0.704-0.721, and 0.601-0.716, and root-mean-square-errors (RMSEs) ranging from 1.59-2.28, 3.81-4.18, and 0.67-1.32 ppb for NO2, O3, and SO2, respectively, via the random forest procedure. The annual NO2 and SO2 concentrations greatly improved from 2005-2019, especially in the western residential area of Taiwan. However, despite these improvements in air quality, the annual O3 concentrations tended to increase from 2015–2019. This might be due to the complex mixtures of precursors (e.g., NO2), atmospheric circulation, barriers of the Central Mountain Ridge, and increasing ground temperatures over the past decade. The proposed multistage estimation procedure performed well over the whole island with complex terrain and topography. The study outcomes may provide epidemiological information for long-term ambient exposure estimates and guidance for future administrative policies.

Analysis of the Heat Transfer Performance of a Buried Pipe in the Heating Season Based on Field Testing

Ground source heat pump (GSHP) systems have been widely used in the field of shallow geothermal heating and cooling because of their high thermal efficiency and environmental friendliness. A borehole heat exchanger (BHE) is the key part of a ground source heat pump system, and its performance and investment cost have a direct and significant impact on the performance and cost of the whole system. The ground temperature gradient, air temperature, seepage flow rate, and injection flow rate affect the heat exchange performance of BHEs, but most of the research on BHEs lacks field test verification. Therefore, this study relied on the results of a field thermal response test (TRT) based on a distributed optical fiber temperature sensor (DOFTS) and site hydrological, geological, and geothermal data to establish a corrected numerical model of buried pipe heat transfer and carry out the heat transfer performance analysis of a buried pipe in the heating season. The results showed that the ground temperature gradient of the test site was about 3.0 °C/100 m, and the temperature of the constant-temperature layer was about 9.17 °C. Increasing the air temperature could improve the heat transfer performance. The temperature of the surrounding rock and soil mass of the single pipe spread uniformly, and the closer it was to the buried pipe, the lower the temperature. When there is groundwater seepage, the seepage carries the cold energy generated by a buried pipe’s heat transfer through heat convection to form a plume zone, which can effectively alleviate the phenomenon of cold accumulation. With an increase in seepage velocity, the heat transfer of the buried pipe increases nonlinearly. The heat transfer performance can be improved by appropriately reducing the temperature and velocity of the injected fluid. Selecting a backfill material with higher thermal conductivity than the ground body can improve the heat transfer performance. These research results can provide support for the optimization of the heat transfer performance of a buried tube heat exchanger.

An integrated dataset of ground hydrothermal regimes and soil nutrients monitored in some previously burned areas in hemiboreal forests in Northeast China during 2016–2022

Abstract. Under a warming climate, the occurrence of wildfires has been becoming increasingly more frequent in boreal forests and Arctic tundra over the last few decades. Wildfires can cause radical changes in forest ecosystems and the permafrost environment, such as the irreversible degradation of permafrost, succession of boreal forests, rapid and massive losses of soil carbon stock, and increased periglacial geohazards. Since 2016, we have gradually and more systematically established a network for studying soil nutrients and monitoring the hydrothermal state of the active layer and near-surface permafrost in the northern Da Xing'anling Mountains in Northeast China. Soil moisture content (depth of 0–9.4 m), soil organic carbon content (0–3.6 m), total nitrogen content (0–3.6 m), and total phosphorus and potassium content (0–3.6 m) datasets were obtained in 2016 via field sampling and subsequent laboratory tests. Ground temperature (0–20 m) and active layer thickness (2017–2022) datasets were obtained using thermistor cables that were permanently installed in boreholes or interpolated with these temperatures. The present data can be used to simulate changes in permafrost features under a changing climate and wildfire disturbances and to explore the changing interactive mechanisms of the fire–permafrost–carbon system in hemiboreal forests. Furthermore, they can provide baseline data for studies and action plans to support the carbon neutralization initiative and assessment of the ecological safety and management of the permafrost environment. These datasets can be easily accessed via the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.300933, Li and Jin, 2024).

Study and Analysis of the Thunder Source Location Error Based on Acoustic Ray-Tracing

Error analysis and estimation of thunder source location results is a prerequisite for obtaining accurate location results of thunder sources, which is of great significance for a deeper understanding of the physical process of lightning channel discharges. Most of the thunder source location algorithms are based on the simplified model of the straight-line propagation of acoustic waves to determine the location of the thunder source; however, the acoustic wave is affected by the inhomogeneity of the atmosphere medium in the propagation process and its acoustic ray will be bent. Temperature and humidity are the main factors affecting the vertical distribution of the velocity of sound in the atmosphere, therefore, it is necessary to study the changes in location errors under the models of uniform vertical distribution of temperature only and uniform vertical distribution of humidity only. This paper focuses on the theory of acoustic ray-tracing in neglecting the presence of the wind and the acoustic attenuation and the theoretical derivation of the location error of thunder source inversion for the three models is carried out by using MATLAB R2019b programming. Then, simulation analysis and comparative study on the variation law of thunder source location error with the height of the source, ground temperature, ground humidity, and array position under the three models are carried out. The results of the study show that the maximum location error can be obtained from the straight-line propagation model, the location error obtained from the model of uniform vertical distribution of temperature only is the second, and the location error obtained from the model of uniform vertical distribution of humidity only is the least and can be negligible compared to the first two models. In the trend of error variation, the variation of location error with temperature and humidity is relatively flat in the first two models; however, the variation of location error with the height of the thunder source is more drastic, which can be more than 80%. The location error obtained from the array inversion closer to the thunder source increases linearly with the height of the thunder source, the location error obtained from the more distant array inversion shows a fast-decreasing trend at the height of the thunder source from 500 to 3500 m, and a flat trend above 3500 m. The location error varies relatively smoothly with the height of the thunder source, the ground temperature, and the ground humidity in the model of uniform vertical distribution of humidity only. In addition, the position of the array also has an important effect on lightning location. The further the horizontal distance from the source, the greater the location error will be obtained in the first two models, and when the thunder source is at a low height and detected at a long distance, the location error will be very large, so relevant data should be modified in actual observation.

Grey correlation analysis of the main influencing factors of wax deposition of waxy crude oil and determination of pigging period based on dynamic analysis

Normal temperature gathering and transportation has significant advantages in reducing energy consumption and cost. Due to the high wax content of crude oil in carbonate reservoirs, obvious wax deposition will occur in the process of gathering and transportation at room temperature. In this paper, according to the component analysis results of crude oil on site, the HEATANALOGY wax deposition model was used to calculate the wax deposition of different gathering pipelines. The main influencing factors of wax deposition were analyzed by grey correlation method. Finally, according to the pigging mechanical balance model, the safe pigging period is derived, and the relationship diagram of different pipe diameters, throughput and ground temperature is drawn. The results show that the wellhead temperature has the greatest influence on the initial wax deposition position and the peak wax deposition position of the pipe section. The flow rate has the greatest influence on the maximum wax deposition thickness of the tube wall. According to the relationship between the working conditions and the pigging cycle, it can be found that with the increase of the throughput, the pigging cycle decreases first and then increases. With the increase of ground temperature, the pigging cycle increases.

Enhancing artificial permafrost table predictions using integrated climate and ground temperature data: A case study from the Qinghai-Xizang highway

The complexities of permafrost changes, driven by climate warming and engineering activities, coupled with challenges in data acquisition, make it crucial and challenging to accurately predict the artificial permafrost table, particularly for subgrades in high-temperature unstable permafrost regions. To address this, this study developed a hybrid machine learning model (RF-LSTM-XGBoost) for permafrost table prediction. By analyzing climate change and ground temperature data from various positions and depths along the subgrade in the Tuotuo River section of the Qinghai-Xizang Highway, the Spearman correlation coefficient method was initially used to determine the important influencing factors. Random Forest (RF), Long Short-Term Memory Neural Network (LSTM), and Extreme Gradient Boosting (XGBoost) models were used to predict the artificial permafrost table, and grid search and cross-validation methods were employed to optimize the hyperparameters of each model. A linear weighted combination method based on the minimum cumulative absolute error was utilized to merge the models, and its performance was compared with the individual RF, LSTM, and XGBoost models. Subsequently, the feature importance of the variables in the machine learning model was analyzed. The results indicated a strong correlation between artificial permafrost table changes and factors such as daily average atmospheric temperature, subgrade surface ground temperature, and subgrade surface ground heat flux during the freezing-thawing cycle. The combined model highlighted daily atmospheric temperature as the most influential predictor, followed by ground heat flux, with the surface ground temperature being less impactful. The combined model demonstrated improved predictive accuracy, with MSE, MAPE, RMSE, MAE, and R2 values of 0.003, 0.052, 0.0085, 0.029, and 0.989, respectively, surpassing those of individual models. This model offers a rapid, accurate, and reliable approach for permafrost table prediction, advancing subgrade stability research in challenging permafrost environments.

Spatial variability of near-surface ground temperatures in a discontinuous permafrost area in Mongolia

Spatial variability of near-surface ground temperatures in a discontinuous permafrost area in Mongolia

Fracture mechanism and constitutive model considering post-peak plastic deformation of marble under thermal–mechanical action

Temperature plays an important impact on rock mechanical properties. In this paper, the mechanical properties, fracture mechanism and constitutive model of marble under 20–120 °C and 15 MPa are studied. The results show marble deformation can be divided into four stages: compaction, linear elasticity, crack propagation and post-peak failure. Stress–strain curve is not obviously affected by temperature. Macroscopic fracture characteristics change from shear failure to tensile mixed failure with temperature increasing. With the increase of temperature, the strength of marble tends to decrease, indicating that temperature increase has a weakening effect on marble, and there are temperature-sensitive areas of 20–60 °C and temperature sub-sensitive areas of 60–120 °C. The elastic modulus of marble decreases and Poisson’s ratio increases with increasing temperature. The energy evolution law of marble under different temperature is basically the same, which shows that before crack initiation, the energy dissipation is less, and after the damage and yielding occurs, the energy dissipation increases quickly. The energy dissipation in the failure process is mainly used for crack initiation-connection-penetration, as well as plastic deformation caused by friction and slip of cracks, and the plastic deformation and energy dissipation have good linear characteristics. The statistical damage constitutive model based on three-parameter Weibull distribution function can effectively reflect the characteristics of post-peak plastic deformation and strain softening. The weakening effect of marble at 20–120 °C is related to its internal moisture excitation. With the increase of temperature, water is stimulated to absorb and attach to the original relatively dry interface, which plays a role in lubrication. The relative motion friction resistance between solid particles or crack surfaces decreases, which leads to crack initiation and friction energy consumption reduction, changes the specific surface energy of rocks and weakens the strength of marble. The results provide a theoretical basis for predicting and evaluating the long-term stability and safety of surrounding rock of underground deep engineering in complex environment with high ground temperature and high geo-stress.

Simulation and experimental thermal analysis of ultrasonic vibration-assisted high-efficiency deep grinding of γ-TiAl blade tenon

Gamma titanium-aluminum intermetallic compounds (γ-TiAl) have attracted considerable attention in the aerospace industry because of their outstanding thermal stability and broad range of properties. To analyze the grinding temperature during high-efficiency deep grinding (HEDG) and ultrasonic vibration-assisted high-efficiency deep grinding (UVHEDG) of γ-TiAl materials, both an analytical thermal model and a finite element simulation model were developed. Subsequent comparison trials between HEDG and UVHEDG were conducted to validate the accuracy of the simulation. The results show that the final prediction error can be effectively maintained within 15 %, and the temperature measurement curve fits well when an ultrasonic heat influence factor is incorporated into the 3D finite element model. The introduction of ultrasonic vibrations into the HEDG reduced the maximum grinding temperature by 39.1 %, effectively preventing grinding burns. The highest temperature consistently occurred in the top zone of the blade tenon tooth due to different heat conduction paths caused by the complex profile. This led to a 32.4 % and 31.9 % reduction in the grinding temperature in the bottom zone under HEDG and UVHEDG, respectively. The surface roughness of the machined blade tenon tooth reached 0.664 μm at the top and 0.721 μm at the bottom under UVHEDG, whereas it was 0.735 μm and 0.843 μm under HEDG.

The microclimatic effects of the native shrub Ephedra californica (Mormon tea) in California drylands.

The impacts of climate change can be profound in many ecosystems worldwide, including drylands such as arid and semi-arid scrublands and grasslands. Foundation plants such as shrubs can provide microclimatic refuges for a variety of taxa. These shrubs can directly influence micro6 environmental measures, and indirectly increase the local environmental heterogeneity as a result. We examined the hypothesis that, in comparison to an open gap, foundation shrubs improve the microclimate beneath their canopy and that microclimate is in turn a significant predictor of annual vegetation. The following predictions were made: 1) mean air temperature (NSAT), ground temperature (SGT), and vapour pressure deficit (VPD) will be significantly lower under the shrubs than in the open microsites; 2) shrub canopy size predicts microclimate; 3) site-level aridity estimates and percent shrub cover influence annual plant abundance and richness; and 4) the site13 level mean of NSAT and VPD predict annual plant abundance and richness. Our study took place in Southwestern California, U.S.A. We used a handheld device with a probe to measure microclimatic variables such as near-surface air temperature (NSAT), near-surface relative humidity (NSRH), and surface ground temperature (SGT) at the shrub species Ephedra californica and in the open gap, across six sites in California, United States. Air temperature and RH were then used to calculate VPD. The mean number of vascular plant species across each site was also recorded. Only SGT was significantly reduced under shrub canopies. Canopy volume was not a significant predictor of all three microclimatic variables, demonstrating that even small, low-stature shrubs can have facilitative effects. Furthermore, total shrub cover and aridity at sites significantly predicted mean plant richness and abundance. There were significantly more plants associated with shrubs and there were significantly more species associated with the open. Mean air temperature and VPD at the site-level significantly predicted vegetation abundance and richness, though microsite-level differences were only significant for richness. Foundation shrubs are a focal point of resiliency in dryland ecosystems. Understanding their impact on microclimate can inform us of better management, conservation, and restoration frameworks.

First insights into global permafrost-agroecosystems and recommendations for policymakers

First insights into global permafrost-agroecosystems and recommendations for policymakers Melissa Ward Jones discusses a recent paper published in Arctic, Antarctic, and Alpine Research of the first global study on permafrost-agroecosystems, published by members of the International Permafrost Association Permafrost-agroecosystem Action Group. When one thinks of high-latitude and mountainous regions, one usually thinks of cold and snow, not agriculture. But agriculture does occur in these areas. The climate of these regions limits the options for which crops to grow, and chosen animal species, such as yaks and reindeer, are adapted to cold. These regions also contain permafrost, or perennially frozen ground, a unique feature of these regions. The response to thawing permafrost, caused either by climate warming or land use change for cultivation, is varied (Ward Jones, 2024). These responses range from simple increases in ground temperatures to ground surface collapse when permafrost is ice-rich. The presence of permafrost and its response to thaw can add additional challenges to agricultural activities.

High-speed grinding: from mechanism to machine tool

AbstractHigh-speed grinding (HSG) is an advanced technology for precision machining of difficult-to-cut materials in aerospace and other fields, which could solve surface burns, defects and improve surface integrity by increasing the linear speed of the grinding wheel. The advantages of HSG have been preliminarily confirmed and the equipment has been built for experimental research, which can achieve a high grinding speed of more than 300 m/s. However, it is not yet widely used in manufacturing due to the insufficient understanding on material removal mechanism and characteristics of HSG machine tool. To fill this gap, this paper provides a comprehensive overview of HSG technologies. A new direction for adding auxiliary process in HSG is proposed. Firstly, the combined influence law of strain hardening, strain rate intensification, and thermal softening effects on material removal mechanism was revealed, and models of material removal strain rate, grinding force and grinding temperature were summarized. Secondly, the constitutive models under high strain rate boundaries were summarized by considering various properties of material and grinding parameters. Thirdly, the change law of material removal mechanism of HSG was revealed when the thermodynamic boundary conditions changed, by introducing lubrication conditions such as minimum quantity lubrication (MQL), nano-lubricant minimum quantity lubrication (NMQL) and cryogenic air (CA). Finally, the mechanical and dynamic characteristics of the key components of HSG machine tool were summarized, including main body, grinding wheel, spindle and dynamic balance system. Based on the content summarized in this paper, the prospect of HSG is put forward. This study establishes a solid foundation for future developments in the field and points to promising directions for further exploration.

Prediction of wellbore gas hydrate generation based on temperature-pressure coupling model in deepwater testing

With the advancement of oil and gas exploration and development technology, the development of the world's oil and gas resources is gradually advancing from land and shallow waters to deep waters. During the development of gas wells in deepwater regions, the temperature of the wellbore decreases from the bottom of the well to the wellhead, and therefore, common well conditions of high pressure, low temperature, and the presence of free water are encountered, which can lead to gas hydrate plugging of the pipeline and affect the transportation of natural gas. Simulation of temperature and pressure along the wellbore and identification of gas hydrate-generating zones in the wellbore can be used to take timely preventive measures and minimize losses. In this study, a wellbore gas hydrate generation and prediction model is developed by combining the mass, momentum, and energy conservation equations, and the model is solved by the fourth-order Runge-Kutta method, taking into account the temperature-pressure coupling in the wellbore. The effects of gas production, specific heat capacity, thermal conductivity, tubing size, test duration, and ground temperature gradient on the location of gas hydrate generation and the amount of inhibitor used were analyzed in a case study well in the South China Sea. Some suggestions for practical engineering operations, such as increasing the gas production in moderation and choosing smaller tubing sizes within the acceptable range, were given. The study's results can provide a theoretical basis for flow assurance for hydrocarbon production in the wellbore of deepwater gas wells.

Non-monotonic effect of differential stress and temperature on mechanical property and rockburst proneness of granite under high-temperature true triaxial compression

Complicated geological conditions such as high geo-stress and high ground temperatures often have a significant impact on the mechanical behavior and failure potential of hard rocks in deep engineering. This study aims to investigate the mechanical behaviors and rockburst proneness of granite under high differential stress and high temperatures in deep-buried high-temperature tunnels. A comprehensive experimental study was conducted on the coupling behavior of granite under high-temperature and high differential stress by true triaxial compression tests. The strength and failure mechanism of granite as well as their relationship with high temperature and high differential stress were revealed. The rockburst proneness of granite from a deep-buried high geothermal tunnel was assessed based on the rock's ultimate energy storage characteristics. It shows the strength, failure mechanisms, and rockburst proneness of granite, are significantly correlated to the granite high-temperature high-stress conditions. The temperatures extend the strengthening range of the intermediate principal stress on the true triaxial peak strength of the granite. With increasing temperature and differential stress, secondary vertical cracks develop quickly to induce the macroscopic failure of granite. Under high temperatures, the failure of granite changes from compressive-shear failure to tensile-shear failure at low differential stress. High temperature coupled with high differential stress strengthens approximately 1.14 times the rockburst proneness of granite. The results are important for the safe construction, and disaster assessment of deep-buried high geothermal tunnels.

Association Between Climatic Factors and Varicella Incidence in Wuxi, East China, 2010-2019: Surveillance Study.

Varicella is a common infectious disease and a growing public health concern in China, with increasing outbreaks in Wuxi. Analyzing the correlation between climate factors and varicella incidence in Wuxi is crucial for guiding public health prevention efforts. This study examines the impact of meteorological variables on varicella incidence in Wuxi, eastern China, from 2010 to 2019, offering insights for public health interventions. We collected daily meteorological data and varicella case records from January 1, 2010, to December 31, 2019, in Wuxi, China. Generalized cross-validation identified optimal lag days by selecting those with the lowest score. The relationship between meteorological factors and varicella incidence was analyzed using Poisson generalized additive models and segmented linear regression. Subgroup analyses were conducted by gender and age. The study encompassed 64,086 varicella cases. Varicella incidence in Wuxi city displayed a bimodal annual pattern, with peak occurrences from November to January of the following year and lower peaks from May to June. Several meteorological factors influencing varicella risk were identified. A decrease of 1°C when temperatures were ≤20°C corresponded to a 1.99% increase in varicella risk (95% CI 1.57-2.42, P<.001). Additionally, a decrease of 1°C below 22.38°C in ground temperature was associated with a 1.36% increase in varicella risk (95% CI 0.96-1.75, P<.001). Each 1 mm increase in precipitation above 4.88 mm was associated with a 1.62% increase in varicella incidence (95% CI 0.93-2.30, P<.001). A 1% rise in relative humidity above 57.18% increased varicella risk by 2.05% (95% CI 1.26-2.84, P<.001). An increase in air pressure of 1 hPa below 1011.277 hPa was associated with a 1.75% rise in varicella risk (95% CI 0.75-2.77, P<.001). As wind speed and evaporation increased, varicella risk decreased linearly with a 16-day lag. Varicella risk was higher with sunshine durations exceeding 1.825 hours, with a 14-day lag, increasing by 1.30% for each additional hour of sunshine (95% CI 0.62-2.00, P=.006). Subgroup analyses revealed that teenagers and children under 17 years of age faced higher varicella risks associated with temperature, average ground temperature, precipitation, relative humidity, and air pressure. Adults aged 18-64 years experienced increased risk with longer sunshine durations. Additionally, males showed higher varicella risks related to ground temperature and air pressure compared with females. However, no significant gender differences were observed regarding varicella risks associated with temperature (male: P<.001; female P<.001), precipitation (male: P=.001; female: P=.06), and sunshine duration (male: P=.53; female: P=.04). Our preliminary findings highlight the interplay between varicella outbreaks in Wuxi city and meteorological factors. These insights provide valuable support for developing policies aimed at reducing varicella risks through informed public health measures.

Effect of single/multi-particle grinding parameters on surface properties of bearing steel GCr15

Grinding surface residual stress (RS) has an important influence on the service life of parts. In this study, the mathematical model of grinding force (GF) and grinding temperature (GT) of single particle was established. The relationship between grinding parameters, grinding force-thermal coupling and residual stress of single particle was analyzed by numerical simulation. Meanwhile, aiming at the multi-grain grinding of aviation precision high-speed bearing rings, the experimental analysis of crystal fragmentation, element content and residual stress of service and non-service bearing rings were carried out. Based on the above, the following results were obtained: in the simulation, the residual stress in the Y direction > the residual stress in the X direction > the residual stress in the Z direction at the same grinding force and grinding temperature. In the experiment, (1) The grain size of bearing raceway before service was about 24 μm, and the grain size of bearing raceway after service was about 3 times smaller than that before service. (2) C, Si, Cr and Fe decreased by 0.83 %, 0.07 %, 1.09 % and 32.75 % respectively after crushing (after service). On the contrary, it increased 0.66 % O and 34.08 % Pr. The Pr element was mainly distributed in the broken grain boundaries. (3) After service, the tangential residual compressive stress decreased by 169.3 MPa, while the axial residual stress increased by 172.6 MPa.

Relationship between Newly Fallen Snow Density and Polarimetric Parameters Obtained from X-Band Radar Observations along the Sea of Japan Coast in January 2021

Abstract The density of newly fallen snow ρN is an important parameter for assessing accumulated snowfall depth. We examined the relationships between polarimetric parameters of X-band radar and the ρN in dry snow cases with ground temperatures less than 0°C. Our study was based on observations at Niigata Prefecture, Japan, along the coastal region of the Sea of Japan. This region is subjected primarily to sea-effect snow during the winter monsoon season, and convective clouds and rimed snow are common. We assumed that snow particles that accumulated on the ground originated from altitudes above an altitude with a temperature of −15°C, and we focused on the ratio of the differential phase KDP to radar reflectivity Zh, which is influenced by both aspect ratio and inverse particle size. We found that KDP/Zh at an altitude with a temperature of −15°C exhibited a greater magnitude for lower ρN values. Its correlation coefficient was the best among the polarimetric parameters that we examined. The difference in ice crystal flatness is highlighted rather than the difference in size because aggregation growth has not progressed at this altitude. On the basis of this result, we propose an empirical relationship between KDP/Zh at an altitude with a temperature of −15°C and ρN on the ground, thereby facilitating the estimation of snowfall depth by combining the estimated ρN with the liquid equivalent snowfall rate from, for example, Zh or KDP. Significance Statement This study aims to estimate the density of newly fallen (just-accumulated) snow from polarimetric radar observations. Understanding the newly fallen snow density will help to determine the exact snowfall depth. Focusing on polarimetric parameters at an altitude with a temperature of −15°C, we conducted radar and ground-based observations of snow particles and found that the newly fallen snow density of dry snow can be estimated. We were able to highlight the difference in ice crystal flatness before aggregation growth progressed by focusing on higher altitudes.

Latitudinal gradients of biodiversity and ecosystem services in protected and non-protected oak forest areas can inform climate smart conservation

Adaptive governance of areas set aside for future protection of biodiversity, sustainable production, and recreation requires knowledge about whether and how effects of area protection are modulated by climate change and redistribution of species. To investigate this, we compare biodiversity of plants (assessed using vegetation plots) and arthropods (collected with Malaise traps, analyzed using metabarcoding) and productivity (tree growth, determined using dendrochronology) in protected and non-protected oak (Quercus spp.) forests along a latitudinal gradient (55.6 °N – 60.8 °N) in Sweden. We also compare historical, recent and projected future climate in the region. In contrast to established global latitudinal diversity gradients, species richness of plants and arthropods increased northwards, possibly reflecting recent climate-induced community redistributions, but neither was higher in protected than in non-protected areas, nor associated with contemporary ground temperature. Species composition of arthropods also did not differ between protected and non-protected areas. Arthropod biomass increased with latitude, suggesting that the magnitude of cascading effects mediated via their roles as pollinators, herbivores, and prey for other trophic levels, varies geographically and will change with a moving climate. Annual growth rate of oaks (an ecosystem service in the form of biomass increase and carbon sequestration) was independent of latitude and did not differ between protected and non-protected areas. Our findings question the efficacy of contemporary designation and management of protected oak forests, and emphasize that development and implementation of modified climate smart conservation strategies is needed to safeguard ecosystem functioning, biodiversity, and recreational values of protected forest areas against future challenges.