Large-scale Conditions Research Articles

Innovative computational model for optimal deep coal mining under large-scale crustal stress conditions

Innovative computational model for optimal deep coal mining under large-scale crustal stress conditions

Three-dimensional quasi-complete information numerical simulation of gravity anomalies and parallel computing on CPU-GPU

Abstract In order to improve the efficiency and accuracy of numerical simulation of gravity anomalies in large-scale complex models, this paper proposes a method for three-dimensional numerical simulation of gravity anomalies under arbitrary terrain, and implements its CPU-GPU parallel acceleration scheme. By performing a two-dimensional Fourier transform along the horizontal direction, three-dimensional partial differential satisfied by gravitational potential are transformed into one-dimensional ordinary differential equations in different wavenumbers, reducing computational and storage requirements. Moreover, the ordinary differential equations in different wavenumbers are independent of each other and have good parallelism. By retaining the vertical direction as the spatial domain and introducing traveling wave decomposition, the effects caused by upper and lower boundaries are eliminated. The vertical grid is arbitrary. A two-dimensional quasi-complete information Fourier transform is utilized to enhance both the accuracy and efficiency of the Fourier transform process, allowing both uniform and non-uniform flexible sampling. Based on the high parallelism, one-dimensional ordinary differential equations are solved in parallel using CPU, and quasi-complete information Fourier transform are computed in parallel using GPU. An abnormal sphere is designed to analyze the wavenumber spectral distribution characteristics of the anomalous potential and summarize the wavenumber sampling rules. The logarithmic uniform sampling in the wavenumber domain has high accuracy. Compared with Gauss-FFT, the quasi-complete information Fourier transform selects fewer wavenumbers and exhibits higher accuracy. The computational efficiency is greatly enhanced through the use of single-precision CPU-GPU parallel scheme, and a model with tens of millions of nodes only takes a few seconds. Two terrain models are designed to verify the algorithm’s adaptability to arbitrary complex terrains. This is significant for achieving fine inversion imaging and interpretation of gravity anomalies under large-scale complex conditions.

Systematic Upstream Large-Scale Control of Subtropical Low-Cloud Properties

Abstract It has recently been shown that the slow adjustment of the atmospheric boundary layer (ABL) to perturbations of the large-scale atmospheric conditions translate into an upstream control of the low-cloud cover (LCC) variability at climatological timescales in the subtropics. In this study we expand upon this recent study to investigate upstream control of the climatology of low-cloud radiative effect (CRE), as well as cloud properties relevant to their radiative effect: cloud liquid water path (LWP), and cloud optical depth (COD).We use machine-learning statistical models with feature selection capabilities (random-forests) to determine the influence of the local and upstream large-scale conditions in monthly data. These conditions are determined using back-trajectories in monthly-mean wind fields. Total CRE, dominated by the shortwave contribution, exhibits a dependence on upstream Estimated Inversion Strength (EIS), but not on upstream Sea-Surface Temperature (SST) as LCC does. Upstream control of COD was present but was not as consistent as LCC or CRE across different regions and cloud regimes, while LWP does not exhibit strong upstream control at all. This implies that the control of other boundary layer properties could explain the differences in response between LCC and CRE to SST and EIS. Looking at five subtropical eastern basins, it appears that key lead times are region-specific. The inclusion of upstream control provides significant improvements to the predictive skill of statistical models over local linear regression, with improvements in variance explained well over 20% in many cases.

Effect of temperature on growth, metabolism, and gas exchange in Hermetia illucens larvae reared under commercial and laboratory conditions

Abstract The world’s socio-economic development is continuously increasing the demand for efficient production of food, feed, and energy from the agricultural sector. In this respect, the emerging production of black soldier fly larvae (BSFL) represents a promising system to upscale low-quality resources to higher-quality resources usable as feed or biodiesel. To optimize BSFL production it is critical to establish methods that are relevant to examine how rearing conditions, including temperature, affect growth, metabolism, and body composition at large scale. In a first set of experiments, we therefore compared how small-scale laboratory respirometry chambers (600 larvae) support gas exchange, growth, and metabolism in BSFL with similar measurements obtained from large-scale commercial conditions (>12 million larvae) at ∼34-35 °C. Having observed that small- and large-scale systems generated comparable measurements of growth and metabolism, we used our small-scale respirometry system to examine in detail how substrate rearing temperature ranging from 27.0 to 41.9 °C influenced growth, metabolism, and body composition in BSFL. Here we found that 7-day growth of BSFL was stable and high at 27, 35, and 39 °C, while a rearing temperature of ∼42 °C caused a severe, but sublethal, depression of growth and metabolism. Despite the general similarities in total growth at 27, 35, and 39 °C, we found considerable acceleration of metabolism and development at the two higher rearing temperatures (35 and 39 °C). In contrast, the lower rearing temperature (27 °C) resulted in reduced CO2 production per kg larvae produced and the was associated with a higher crude protein to crude lipid ratio in larvae after the 7-day growth period. Based on these findings we discuss how continued monitoring of gas exchange in production systems holds a potential to optimize production in the emerging industry of large-scale commercial insect production.

Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day

The current throughput of conventional organic chemical synthesis is usually a few experiments for each operator per day. We develop a robotic system for ultra-high-throughput chemical synthesis, online characterization, and large-scale condition screening of photocatalytic reactions, based on the liquid-core waveguide, microfluidic liquid-handling, and artificial intelligence techniques. The system is capable of performing automated reactant mixture preparation, changing, introduction, ultra-fast photocatalytic reactions in seconds, online spectroscopic detection of the reaction product, and screening of different reaction conditions. We apply the system in large-scale screening of 12,000 reaction conditions of a photocatalytic [2 + 2] cycloaddition reaction including multiple continuous and discrete variables, reaching an ultra-high throughput up to 10,000 reaction conditions per day. Based on the data, AI-assisted cross-substrate/photocatalyst prediction is conducted.

Teleconnection between the Reproductive Parameters of the Bearded Vulture and Macroclimatic Oscillations: Implications for Conservation

ABSTRACT The Bearded Vulture (Gypaetus barbatus) is a scavenging bird of prey that was once widespread on the Iberian Peninsula. Its current distribution in Spain is limited to specific mountain ranges, including the Aragonese Pyrenees. The decline of the Iberian population has been linked to factors acting at a microscale level, such as the use of poisons, illegal hunting, and a decrease in extensive livestock farming. There are, however, other factors acting on a biogeographical scale that are not currently being considered and may also be affecting the viability of populations. The aim of this case study was to investigate the influences of large-scale environmental conditions on temporal variation in the reproductive parameters of the Bearded Vulture breeding population in the Aragonese Pyrenees. We tested the degree to which each of 26 macroclimatic oscillation indices with an effect on regional weather conditions were teleconnected with three reproductive parameters (hatching rate, fledging rate, and productivity). Two indices—the Tropical Northern Atlantic and East Atlantic/West Russia Pattern—were temporally correlated with Bearded Vulture reproductive parameters. The study results provide novel information to facilitate Bearded Vulture conservation because no previous studies have addressed this issue from a biogeographical and macroecological perspective. The results could have important implications for the management and conservation of the species and its successful reintroduction in other territories.

From Polar Day to Polar Night: A Comprehensive Sun and Star Photometer Study of Trends in Arctic Aerosol Properties in Ny-Ålesund, Svalbard

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources.

Seismic capacity evaluation of a reinforced concrete frame infilled with precast modular block wall for enhancing the horizontal load

In this study, we propose a new concept for seismic retrofitting using precast modular block walls (PMBWs) to improve and complement the shortcomings of conventional retrofitting methods for reinforced concrete (RC) frames infilled with shear walls, masonry walls, and precast panels. The PMBW retrofitting method maximizes the advantages of factory-produced modular blocks, innovatively enhancing the constructability and integrity of connections between the existing frame and the infilled PMBW. Additionally, the PMBW reinforcement method improves seismic resistance without significantly increasing structural weight, and the required amount of reinforcement can easily be calculated because the strengthening technique involves typical frame infilling. For RC buildings with non-seismic details dominated by shear failure, the application of this seismic reinforcement method readily ensures sufficient strength. A pseudo-dynamic test was conducted on a full-scale two-story frame, based on an existing RC building with non-seismic details, to evaluate the restoring force characteristics, strength enhancement effects, reinforcement strain, and seismic response control capabilities of the PMBW reinforcement system. Based on the pseudo-dynamic test results, the restoring force characteristics for nonlinear dynamic analysis of the PMBW-reinforced specimen were identified. Finally, nonlinear dynamic analysis was conducted using the proposed restoring force characteristics, and the results were compared with the pseudo-dynamic test results. The unreinforced RC frame experienced shear failure at a design basis earthquake magnitude of 200 cm/s2. However, the frame reinforced with the PMBW sustained only minor damage. Even at higher magnitudes under maximum considered earthquake conditions of 300 cm/s2 and large-scale earthquake conditions of 400 cm/s2, only a slight amount of damage was projected from the analysis. Thus, the newly developed PMBW frame infilling system shows great promise for seismic reinforcement.

Inhibition of polyphenol oxidase for preventing browning in edible mushrooms: A review.

Edible mushrooms are rich in nutrients and bioactive compounds, but their browning affects their quality and commercial value. This article reviews various methods to inhibit polyphenol oxidase (PPO)-induced browning in mushrooms. Physical methods such as heat treatment, low temperatures, irradiation, and ultrasound effectively reduce PPO activity but may affect mushroom texture and flavor. Chemical inhibitors, including synthetic chemicals and natural plant extracts, provide effective PPO inhibition but require careful monitoring of their content. Biological methods, including gene editing and microbial fermentation, show promise in targeting PPO genes and enhancing antioxidant production. Combining these methods offers a comprehensive strategy for preserving mushroom quality, extending shelf life, and maintaining nutritional value. PRACTICAL APPLICATION: These approaches can be applied in the food industry to improve post-harvest mushroom preservation, enhance product quality, and reduce waste, benefiting both producers and consumers. Further research and innovation are needed to optimize the practical application of these methods in large-scale processing and storage conditions.

The role of diabatic heating/cooling in outer rainbands in the secondary eyewall formation and evolution in a numerically simulated tropical cyclone

In this study, the role of diabatic heating/cooling in outer rainbands (ORBs) in the formation and evolution of the secondary eyewall of a numerically simulated tropical cyclone (TC) is investigated. This is done through a series of sensitivity experiments under idealized conditions using a high-resolution cloud-resolving atmospheric model. The results show that artificially increasing diabatic heating in rainbands enhances convective activities in ORBs and leads to an earlier secondary eyewall formation (SEF), and later the faster weakening and earlier dissipation of the primary eyewall. Reducing diabatic heating in ORBs weakens the rainbands and delays the SEF but prolongs the duration of the double eyewall structure if the SEF occurs. Reducing diabatic cooling in ORBs enhances convective activity in rainbands but has little effect on convection in the primary eyewall prior to the SEF. However, it results in a widened eyewall structure and a stronger TC after the eyewall replacement. Increasing diabatic cooling in ORBs largely suppresses convection in rainbands and prohibits the SEF. These results demonstrate that diabatic heating/cooling in ORBs plays important roles in the SEF and evolution. Since diabatic heating/cooling in rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the critical importance of large-scale environmental moist condition to the formation and evolution of secondary eyewall in TCs. In addition, it is also found that when the area-averaged diabatic heating rate in ORBs becomes similar in magnitude to that in the primary eyewall, the secondary eyewall forms. Plain language summaryPrevious studies have demonstrated the importance of diabatic heating/cooling in outer rainbands to the structure and intensity changes of tropical cyclones (TCs) with a single eyewall. It is unclear whether and how diabatic heating/cooling in outer rainbands may affect the formation and evolution of the secondary eyewall in TCs. These issues have been addressed based on a series of sensitivity experiments under idealized conditions using a high-resolution atmospheric model. Results show that diabatic heating in outer rainbands is favorable for the secondary eyewall formation (SEF). Increasing diabatic heating in outer eyewall can lead to faster weakening and thus earlier dissipation of the primary eyewall. Diabatic cooling in outer rainbands suppresses convection in outer rainbands and prohibits the SEF. Since diabatic heating/cooling in outer rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the importance of the large-scale environmental moist condition to the SEF of TCs. We also found that when the area-averaged diabatic heating rate in outer rainbands becomes similar in magnitude to that in the primary eyewall, the secondary eyewall would form, which can be considered as a measure of the SEF in TCs. Key points1.Increasing diabatic heating in outer rainbands leads to earlier SEF, and faster weakening and earlier dissipation of the primary eyewall.2.Increasing diabatic cooling in outer rainbands suppresses convective activity in outer rainbands and is unfavorable for the SEF.3.When the area-averaged diabatic heating rate in outer rainbands and the eyewall become similar in magnitude, the secondary eyewall forms.

Tough and anisotropic Janus hydrogel for tendon injury repair with controlled release of bFGF in tendon microenvironment

To address the high complexity and challenging nature of large-scale tendon injury repair, an innovative Janus structured hydrogel patch (JAHP@bFGF) was designed in this study. The patch combines microenvironmental responsiveness with efficient repair function, aiming to optimise and accelerate the tendon healing process. The outer layer is a PVA/SA/Na3Cit hydrogel with excellent mechanical properties, protein resistance, and low friction, which provides firm support to the tendon and reduces adhesions to ensure the recovery of gliding function. The inner layer of TCSB@bFGF microgel responds intelligently to changes in the microenvironment, precisely regulates the release of bFGF, promotes cell proliferation and migration, accelerates tissue regeneration, and has high adhesion strength and antimicrobial properties, which significantly reduces the risk of postoperative infection. Experimental results show that JAHP@bFGF significantly optimises the healing process, accelerates the repair speed and improves the repair quality under simulated large-scale tendon injury conditions. The unique Janus surface design and the intelligent drug release function, in synergy, not only bring new hope to patients with large-scale tendon injuries, but also provide an important reference for the application of biomedical materials in the repair of complex tissues, which heralds the arrival of the era of more efficient and personalised tendon repair.

Surprisingly good fit of pressure-based cropland condition map and bird census data at the national scale

As the world is struggling to halt the rapid decline of biodiversity, the assessment and mapping of ecosystem condition is getting ever increasing attention. Croplands are artificial ecosystems, but as they occupy a large portion of land, they significantly influence biodiversity. Yet, there is a knowledge gap about their suitability to support and maintain wildlife on a national scale. Large-scale condition mapping is meant to address this gap; the good condition of croplands includes their ability to support biodiversity. However, the lack of suitable databases is often a challenge when creating such maps. As there is a strong causal relation between pressures on the ecosystem and its condition, pressure indicators can be used as proxies to approximate condition when more direct indicators are lacking. The validation of condition maps based on pressure proxies is a key but challenging step. In this study, we tested a previously designed pressure-based cropland condition map for Hungary using bird census data. Besides validating the composite condition indicator, we also tested some key elements of the mapping process, such as the choice of variables and thresholds.Using multiple comparisons of means by Tukey’s contrast and Random Forest modelling, we examined the relationship of (1) the continuous pressure-based cropland condition variables, (2) their rescaled, ordinal version (called sub-indicators), and (3) the composite cropland condition indicator (sum of the sub-indicators) with a biodiversity measure, the standardised relative richness of characteristic farmland bird species (rRRCS). To get a picture of the spatial patterns of the examined relationships across Hungary, individual Random Forest models were constructed for all the spatial units of the bird census database, using focal analysis with a 30 km radius moving window.We found significant differences in the mean rRRCS for nearly all sub-indicator categories, signifying that the literature-derived thresholds were mostly sound. Categories with higher (better) condition scores had higher mean rRRCS; the differences are significant in the mid-range but not in the extreme categories, indicating a need for a meaningful simplification of the categories. The goodness-of-fit (R2) of the Random Forest models was found to be high, but it is spatially heterogeneous (ranged from 0.69 to 0.89, with a median value of 0.81), similarly to the variable importance. The proportion of semi-natural areas proved to be the most important condition variable. The proportion of maize and alfalfa were more important than parcel size. Our results show that condition maps based on pressure proxies can reflect patterns of biodiversity surprisingly well. They also highlight the spatial context dependence of the uncertainty of condition maps.

ОРТА КӨМІРТЕКТІ ФЕРРОМАРГАНЕЦ ТЕХНОЛОГИЯСЫН ЗЕРТТЕУ ЖӘНЕ ӘЗІРЛЕУ

This article presents the results of medium-carbon ferromanganese smelting from domestic manganese ores under large-scale laboratory conditions. Data on the production and demand for refined ferromanganese produced during the last successful year are provided. Since 2020, refined ferromanganese production has decreased by approximately 1,2 million tons, which is 18% lower than in 2019. This decline was caused by the outbreak of the coronavirus (COVID-19), which began in China in 2019, and the subsequent worldwide pandemic, as well as geopolitical conflicts (Russia — Ukraine), which started in 2021. Kazakhstan has significant reserves of manganese ores, which are in ferrous-manganese and carbonate states. X-ray phase analysis showed that manganese in the ores is represented by hydroxide, pyrolusite, and iron oxide. Medium-carbon ferromanganese was smelted in an electric furnace with a transformer power of 0.1 MVA. The chemical composition of the resulting alloy is as follows, %: Mn – 80-85; Si – 0,05-0,25; Fe – 1,8-3,0; P – 0,05-0,09; C – 1,5-2,0; MnO – 20-25; SiO₂ – 13,94-14,5; CaO – 23,35-24,85; MgO – 12,5-14,0. Thus, an optimal technological scheme for the production of a wide range of manganese ferroalloys was developed.

Atmospheric patterns associated with summer sub-daily rainfall extremes in western Europe

Large-scale atmospheric circulations are a significant driver of rainfall extremes. However, little attention has so far been devoted to understanding how large-scale circulation patterns influence sub-daily rainfall extremes. Using a gauge-based sub-daily rainfall dataset, we investigate the relationship between large-scale circulations and 3-hour extremes (defined here as ≥ 40 mm rainfall in 3 h) for western Europe. A set of 30 weather patterns (WPs) developed by the UK Met Office and reanalysis data of geopotential height at 500 hPa (z500) are used to represent large-scale atmospheric conditions. Strong associations with 3-hour extremes are found for a small number of WPs: over 50% of 3-hour rainfall extremes across Western Europe occur with just 5 WPs. Composites of z500 reveal the WPs resulting in southerly or south-westerly flow along the leading edge of a trough, accompanied by a ridge to the east or northeast, are most favourable for sub-daily rainfall extremes, with a statistically significant difference between the atmospheric conditions on WP days with a 3-hour extreme rainfall event compared to WP non-event days. Given that large-scale circulations are predictable much further in advance than individual extreme rainfall events, these identified relationships could therefore have important implications for forecasting, aiding in the early identification of periods with increased risk of short-duration rainfall extremes.

Impact of Alaska atmospheric blocking on the carbon flux in the Northeast Pacific Ocean

The Northeast Pacific Ocean (NEP) is one of the important carbon sinks in the global ocean. The causes of carbon flux changes in this region have been widely studied, but the physical processes associated with large scale climate variability remain controversial primarily due to scarcity of spatially and temporally continuous observations. In this study, we constructed a high-resolution sea surface partial pressure of CO2 (pCO2) from satellite observations for the NEP from 2003 to 2020 using the machine learning based XGBoost model. By analyzing the interannual large-scale high-latitude atmospheric dynamics and ocean physical conditions over the NEP, we find that the CO2 flux density (FCO2) anomalies have a strong correlation with the Alaskan atmospheric blocking events. In the region north of 48°N, anomalous cyclones triggered by atmospheric blocking increased sea surface height (SSH), which reduced the replenishment of dissolved inorganic carbon (DIC) from deep seawater, leading to enhanced carbon uptake. By contrast, in the region south of 48°N, the increase in sea surface temperature (SST) triggered by atmospheric blocking reduced the solubility of CO2 in seawater, resulting in a decrease in regional carbon flux. These results provide new perspectives for better understanding and predicting the effects of high-latitude atmospheric dynamics on regional ocean carbon fluxes.

The Physical Origin of the Stellar Initial Mass Function

Stars are among the most fundamental structures of our Universe. They comprise most of the baryonic and luminous mass of galaxies; synthesize heavy elements; and inject mass, momentum, and energy into the interstellar medium. They are also home to the planets. Because stellar properties are primarily decided by their mass, the so-called stellar initial mass function (IMF) is critical to the structuring of our Universe. We review the various physical processes and theories that have been put forward as well as the numerical simulations that have been carried out to explain the origin of the stellar IMF. Key messages from this review include the following: ▪Gravity and turbulence most likely determine the power-law, high-mass part of the IMF.▪Depending of the Mach number and the density distribution, several regimes are possible, including ΓIMF ≃ 0, −0.8, −1, or −1.3, where dN/d log M ∝ M ΓIMF . These regimes are likely universal; however, the transition between these regimes is not.▪Protostellar jets can play a regulating influence on the IMF by injecting momentum into collapsing clumps and unbinding gas.▪The peak of the IMF may be a consequence of dust opacity and molecular hydrogen physics at the origin of the first hydrostatic core. This depends weakly on large-scale environmental conditions such as radiation, magnetic field, turbulence, or metallicity. This likely constitutes one reason for the relative universality of the IMF.

Developing a Machine-Learning 'Smart' PCR Thermocycler, Part 1: Construction of a Theoretical Framework.

The use of PCR is widespread in biological fields. Some fields, such as forensic biology, push PCR to its limits as DNA profiling may be required in short timeframes, may be produced from minute amounts of starting material, and may be required to perform in the presence of inhibitory compounds. Due to the extreme high-throughput of samples using PCR in forensic science, any small improvement in the ability of PCR to address these challenges can have dramatic effects for the community. At least part of the improvement in PCR performance could potentially come by altering PCR cycling conditions. These alterations could be general, in that they are applied to all samples, or they could be tailored to individual samples for maximum targeted effect. Further to this, there may be the ability to respond in real time to the conditions of PCR for a sample and make cycling parameters change on the fly. Such a goal would require both a means to track the conditions of the PCR in real time, and the knowledge of how cycling parameters should be altered, given the current conditions. In Part 1 of our work, we carry out the theoretical groundwork for the ambitious goal of creating a smart PCR system that can respond appropriately to features within individual samples in real time. We approach this task using an open qPCR instrument to provide real-time feedback and machine learning to identify what a successful PCR 'looks like' at different stages of the process. We describe the fundamental steps to set up a real-time feedback system, devise a method of controlling PCR cycling conditions from cycle to cycle, and to develop a system of defining PCR goals, scoring the performance of the system towards achieving those goals. We then present three proof-of-concept studies that prove the feasibility of this overall method. In a later Part 2 of our work, we demonstrate the performance of the theory outlined in this paper on a large-scale PCR cycling condition alteration experiment. The aim is to utilise machine learning so that throughout the process of PCR automatic adjustments can be made to best alter cycling conditions towards a user-defined goal. The realisation of smart PCR systems will have large-scale ramifications for biological fields that utilise PCR.

Environmental risk evaluation for radionuclide transport through natural barriers of nuclear waste disposal with multi-scale streamline approaches

Natural barriers, encompassing stable geological formations that serve as the final bastion against radionuclide transport, are paramount in mitigating the long-term contamination risks associated with the nuclear waste disposal. Therefore, it is important to simulate and predict the processes and spatial-temporal distributions of radionuclide transport within these barriers. However, accurately predicting radionuclide transport on the field scale is challenging due to uncertainties associated with parameter scaling. This study develops an integrated evaluation framework that combines upscaled parameters, streamline transport models, and response surface techniques to systematically assess environmental risk metrics and parameter uncertainties across different scales. Initially, upscaling methods are established to estimate the prior interval of critical transport parameters at the field scale, and streamline models are derived by considering the radionuclides transport with a variety of physicochemical mechanisms and geological characterizations in natural barriers. To assess uncertainty ranges of the risk metrics related to upscaled parameters, uncertainty quantification is performed on the ground of 5000 Monte Carlo simulations. The results indicate that the upscaled dispersivity of fractured media (αLf) has a relatively high sensitivity ranking on release dose for all nuclides, and upscaled matrix sorption coefficient (Kd) of Pu-242 strongly affects breakthrough time and release dose of Pu-242. Facilitated by robust response surface with the lowest R2 of 0.89, it is shown that the release doses of Pu-242 and Pb-210 increase under conditions of low Kd and αLf, respectively. Furthermore, statistical analysis reveals that employing limited laboratory-scale parameters results in narrower confidence intervals for risk metrics, while upscaling methods better account for the highly heterogeneous properties of large-scale field conditions. The developed risk evaluation framework provides valuable insights for utilizing upscaled parameters and modeling radionuclide transport within natural barriers under various scenarios.

“Zhuge Kongming becomes reborn as a clownish partygoer!”: Linguistic carnivalization, critical metapragmatics of danmu, and mediatized neoliberal (inter)subjectivity

The Chinese video-sharing platform of bilibili experiences a ‘Kongming fever’, wherein danmu commenters collectively parodize the historical figure Zhuge Kongming, a pre-existing indexical of Confucianist value beliefs institutionalized by the official authority. Drawing upon Bakhtinian carnivalesque (‘free and familiar contact’ and ‘parodic profanation’), the present study proposes the analytical framework of ‘linguistic carnivalization’ as a critical metapragmatic approach (i.e., subjectivity-oriented). The multimodal analysis of danmu comments reveals how digital users appropriate multiple semiotic resources to construct carnivalesque, including vulgar linguistic varieties from media culture, netspeak genre, poetic patterns of textual repetition, and inversive sign vehicles and rescripting. As a discursive-affective effect of such carnivalization processes, Kongming’s ‘serious’ Confucianist personae and indexed ideological expectations become playfully mediatized, profaned, and transformed into new images of personhood (‘livestreaming microcelebrity’ and ‘hedonic partygoer’) according to mass popular culture. In so doing, the Chinese netizens metapragmatically negotiate existing sociocultural hierarchies and reposition themselves as neoliberal subjects. This paper further suggests that the ‘inside-out’ and ‘down-to-earth’ power of linguistic carnivalization does not simply reside in creating aesthetic humor within a local cybercommunity, but importantly owns critical implications for illuminating variegated forms of neoliberal discourse and (re)production of neoliberal subjectivity under large-scale political economic conditions.

Possible influence of the large-scale environment on extreme waves over the Yellow Sea in boreal spring

The Yellow Sea (YS) is exposed to various weather systems, such as typhoons, monsoon activities, and extratropical cyclones, which can pose a major threat to the adjacent coastal regions through the development of energetic oceanic surface waves. Unusually severe surface wave events in the YS occur with considerable frequency during the boreal spring (March-April-May), but have received less attention compared to winter and summer. This study focuses on the characteristics of spring extreme wave height (EWH) events in the YS during 1979-2022, based on observational and long-term reanalysis datasets. Our analysis shows that extreme waves, i.e. daily maximum heights in the top 5% of all spring days, take about 12 h to build up to the peaks, while they decay more slowly after the peaks. During the extreme events, the Siberian High is found to extend anomalously eastward compared to spring climatology. Such an anomalous extension contributes to the increase of the sea level pressure gradient and the intensification of the surface wind speed in the YS. Meanwhile, in the range of 6 ∼ 24 h following the peaks of the EWH events in the YS, swells induced by strong northerly winds begin to have an impact in the YS. These swells contribute to maintaining higher wave energy levels in the YS for longer after the atmospheric source has been removed. We further explore the large-scale environmental conditions that could provide the predictability of extreme waves in the basin developed by these findings. This study presents implications for assessing the risks associated with extreme waves in coastal regions and for improving coastal management strategies in the YS.