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Abstract Cancer cells often exhibit fragmented mitochondria and dysregulated mitochondrial dynamics, but the underlying mechanism remains elusive. Here, we found that the mitochondrial protein death-associated protein 3 (DAP3) is localized to mitochondria and promotes the progression of hepatocellular carcinoma (HCC) by regulating mitochondrial function. DAP3 can promote the proliferation, migration, and invasion of HCC cells in vitro and in vivo by increasing mitochondrial respiration, inducing the epithelial-mesenchymal transition (EMT), and slowing cellular senescence. Mechanistically, DAP3 can increase mitochondrial complex I activity in HCC cells by regulating the translation and expression of MT-ND5. The phosphorylation of DAP3 at Ser185 mediated by AKT is the key event mediating the mitochondrial localization and function of DAP3 in HCC cells. In addition, the DAP3 expression in HCC samples is inversely correlated with patient survival. Our results revealed a mechanism by which DAP3 promotes mitochondrial function and HCC progression by regulating MT-ND5 translation and expression, indicating that DAP3 may be a therapeutic target for HCC.

Abstract Reservoir computing (RC) is a bio-inspired neural network structure which can be implemented in hardware with ease. It has been applied across various fields such as memristors, and electrochemical reactions, among which the micro-electro-mechanical systems (MEMS) is supposed to be the closest to sensing and computing integration. While previous MEMS RCs have demonstrated their potential as reservoirs, the amplitude modulation mode was found to be inadequate for computing directly upon sensing. To achieve this objective, this paper introduces a novel MEMS reservoir computing system based on stiffness modulation, where natural signals directly influence the system stiffness as input. Under this innovative concept, information can be processed locally without the need for advanced data collection and pre-processing. We present an integrated RC system characterized by small volume and low power consumption, eliminating complicated setups in traditional MEMS RC for data discretization and transduction. Both simulation and experiment were conducted on our accelerometer. We performed nonlinearity tuning for the resonator and optimized the post-processing algorithm by introducing a digital mask operator. Consequently, our MEMS RC is capable of both classification and forecasting, surpassing the capabilities of our previous non-delay-based architecture. Our method successfully processed word classification, with a 99.8% accuracy, and chaos forecasting, with a 0.0305 normalized mean square error (NMSE), demonstrating its adaptability for multi-scene data processing. This work is essential as it presents a novel MEMS RC with stiffness modulation, offering a simplified, efficient approach to integrate sensing and computing. Our approach has initiated edge computing, enabling emergent applications in MEMS for local computations.

Drought is projected to intensify under warming climate and will continuously threaten global food security. Assessing the risk of yield loss due to drought is key to developing effective agronomic options for farmers and policymakers. However, little has been known about determining the likelihood of reduced crop yield under different drought conditions and defining thresholds that trigger yield loss at the regional scale in Australia. Here, we estimated the dependence of yield variation on drought conditions and identified drought thresholds for 12 Australia's key wheat producing regions with historical yield data by developing bivariate models based on copula functions. These identified drought thresholds were used to investigate drought statistics under climate change with an ensemble of 36 climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that drought-induced yield loss was region-specific. The drought thresholds leading to the same magnitude of wheat yield reduction were smaller in regions of southern Queensland and larger in Western Australia mainly due to different climate and soil conditions. Drought will be more frequent and affect larger areas under future warming climates. Based on our results, we advocate for more effective crop management options, particularly in regions where wheat yield is vulnerable to drought in Australia. This will mitigate potential drought impacts on crop production and safeguard global food security.

Background: Increasing global overweight and obesity rates not only increase the prevalence of myocardial infarction (MI), but also exacerbate ischemic injury and result in worsened prognosis. Currently, there are no drugs that can reverse myocardial damage once MI has occurred, therefore discovering drugs that can potentially limit the extent of ischemic damage to the myocardium is critical. Resveratrol is a polyphenol known for its antioxidant properties, however whether prolonged daily intake of resveratrol during obesity can protect against MI-induced damage remains unexplored. Methods: We established murine models of obesity via high-fat/high-fructose diet, along with daily administrations of resveratrol or vehicle, then performed surgical MI to examine the effects and mechanisms of resveratrol in protecting against myocardial ischemic injury. Results: Daily administration of resveratrol in obese mice robustly protected against myocardial ischemic injury and improved post-MI cardiac function. Resveratrol strongly inhibited oxidative and DNA damage via activating SIRT3/FOXO3a-dependent antioxidant enzymes following MI, which were completely prevented upon administration of 3-TYP, a selective SIRT3 inhibitor. Hence, the cardioprotective effects of prolonged resveratrol intake in protecting obese mice against myocardial ischemic injury was due to reestablishment of intracellular redox homeostasis through activation of SIRT3/FOXO3a signaling pathway. Conclusion: Our findings provide important new evidence that supports the daily intake of resveratrol, especially in those overweight or obese, which can robustly decrease the extent of ischemic damage following MI. Our study therefore provides new mechanistic insight and suggests the therapeutic potential of resveratrol as an invaluable drug in the treatment of ischemic heart diseases.

Abstract Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.

Abstract Background The c-Jun N-terminal kinase (JNK) pathway is an evolutionarily conserved regulator of cell death, which is essential for coordinating tissue homeostasis. In this study, we have characterized the Drosophila Ste20-like kinase Slik as a novel modulator of JNK pathway-mediated apoptotic cell death. Results First, ectopic JNK signaling-triggered cell death is enhanced by slik depletion whereas suppressed by Slik overexpression. Second, loss of slik activates JNK signaling, which results in enhanced apoptosis and impaired tissue homeostasis. In addition, genetic epistasis analysis suggests that Slik acts upstream of or in parallel to Hep to regulate JNK-mediated apoptotic cell death. Moreover, Slik is necessary and sufficient for preventing physiologic JNK signaling-mediated cell death in development. Furthermore, introduction of STK10, the human ortholog of Slik, into Drosophila restores slik depletion-induced cell death and compromised tissue homeostasis. Lastly, knockdown of STK10 in human cancer cells also leads to JNK activation, which is cancelled by expression of Slik. Conclusions This study has uncovered an evolutionarily conserved role of Slik/STK10 in blocking JNK signaling, which is required for cell death inhibition and tissue homeostasis maintenance in development.

To explore the mediating effect of emotion regulation strategies on the correlation between parental emotion socialization and internalizing problems in adolescents, as well as the moderating effect of gender, a questionnaire survey was administered to 1078 junior high school students (Mage = 13.96 ± 1.00). The results revealed that supportive parental emotion socialization was negatively correlated with adolescents internalizing problems, whereas non-supportive parental emotion socialization was positively correlated with such problems. Cognitive reappraisal and expressive suppression strategies functioned as parallel mediators in the relationship between supportive parental emotion socialization and adolescent internalizing problems, while only expressive suppression mediated the correlation between non-supportive emotion socialization and adolescent internalizing problems. Gender did not exhibit a moderating effect on the mediation model. These findings suggest that supportive parental responses to adolescents’ negative emotions can reduce the incidence of depression and anxiety by cultivating increased utilization of cognitive reappraisal strategies and decreased reliance on expressive suppression strategies among adolescents, whereas non-supportive responses exacerbate the occurrence of depression and anxiety by promoting greater utilization of expressive suppression strategies. In addition, no significant gender differences were observed in the mediation effects. These findings emphasize the importance of prevention programs focusing on parental emotion socialization in adolescence.

Fibrotic skin diseases, such as keloids, are pathological results of aberrant tissue healing and are characterized by overgrowth of dermal fibroblasts. Remdesivir (RD), an antiviral drug, has been reported to have pharmacological activities in a wide range of fibrotic diseases. However, whether RD function on skin fibrosis remains unclear. Therefore, in our study, we explored the potential effect and mechanisms of RD on skin fibrosis both in vivo and in vitro. As expected, the results demonstrated that RD alleviated BLM-induced skin fibrosis and attenuates the gross weight of keloid tissues in vivo. Further studies suggested that RD suppressed fibroblast activation and autophagy both in vivo and in vitro. In addition, mechanistic research showed that RD attenuated fibroblasts activation by the TGF-β1/Smad signaling pathway and inhibited fibroblasts autophagy by the PI3K/Akt/mTOR signaling pathway. In summary, our results demonstrate therapeutic potential of RD for skin fibrosis in the future.

Soil microbes drive soil organic carbon (SOC) mineralization. Because microbial groups differ in metabolic efficiency and respond differently to temperature variation, it is reasonable to expect a close association of SOC mineralization and its temperature sensitivity (Q10 which is defined as the factor of the change of soil carbon mineralization induced by 10 °C temperature increase) with microbial community diversity and composition. However, these relations have rarely been tested. Here, we conducted an incubation experiment to assess the temperature responses of microbial α diversity and the relative abundance of microbial r- and K-strategists in soils from a wide range of ecosystems across a climate gradient in the southeast Tibet. The results indicated that the instantaneous α diversity and the relative abundance of r- and K-strategists are significantly (P

Abstract Background The fixation method of syndesmotic injuries in ankle fractures remains controversial. The goal of the study was to compare radiographic and clinical outcomes between anterior inferior tibiofibular ligament (AITFL) anatomical repair with syndesmosis screw fixation in syndesmotic injuries. Methods We analyzed 62 patients who were treated with AITFL anatomical repair or syndesmosis screw fixation for syndesmotic injuries in an advanced teaching hospital between March 2016 and March 2019. Fixation was performed with AITFL anatomical repair in 30 patients (AAR group) and syndesmosis screw in 32 patients (SS group). Radiographic evaluations were the differences in mean anterior and posterior (A difference and P difference) tibiofibular distance between injured and uninjured ankle computed tomography (CT) scan at 6 months postoperatively. Clinical evaluation of patients was done using the American Orthopaedic Foot & Ankle Society (AOFAS) Ankle Hindfoot Score, the Olerud-Molander Ankle (OMA) score and visual analogue scale (VAS) score at 1, 3, 6 months and 1, 2 years postoperatively. Results The A difference and P difference on CT was no differences (1.6 ± 0.8 mm, 1.3 ± 0.7 mm vs. 1.5 ± 0.7 mm, 1.2 ± 0.7 mm) between the two groups (All of P > 0.05). The AAR group had higher mean AOFAS score (65.6 ± 5.9, 82.3 ± 4.2, 87.6 ± 5.6 vs. 61.8 ± 5.2, 79.1 ± 4.0, 83.8 ± 4.9; P = 0.008, 0.003, 0.007) and higher mean OMA score (45.7 ± 8.7, 79.2 ± 6.5, 84.1 ± 5.3 vs. 40.4 ± 7.3, 74.8 ± 6.3, 80.3 ± 5.8; P = 0.012, 0.009, 0.010)) at 1, 3 and 6 months postoperatively. The AAR group had lower mean VAS scores (2.6 ± 1.2, 1.7 ± 0.7 vs. 3.4 ± 1.2, 2.2 ± 1.1; P = 0.018, 0.038) at 1 and 3 months postoperatively. Conclusions The results of this study suggest that the AITFL anatomical repair technique could effectively improve ankle function during daily activity. Therefore, AITFL anatomical repair technique is expected to become a better fixation method for syndesmotic injuries.

Abstract This study proposed a matched field source localization method based on tensor decomposition. By considering the advantages of tensors in multidimensional data processing, a three‐dimensional tensor signal model of space‐time‐frequency is constructed, and the signal subspace is estimated using high‐order singular value decomposition. The source position is estimated by matching the measured data tensor signal subspace with the replica field tensor signal subspace. The S5 event data of SWellEx‐96 is processed by the proposed tensor‐based matched‐field processing (TMFP). The comparison with the results of conventional matched field processing shows that TMFP has a better suppression effect on ambient noise under low SNR and better source localization performance.

Liver-resident natural killer cells develop locally and have multiple immunological roles in situ. Here the authors investigate the gut-liver axis and show the impact of the intestinal microbiota on the development of liver-resident natural killer cells.

The structure and function of plant communities in alpine meadow ecosystems are potentially susceptible to climate warming. Here, we utilized a unique field manipulation experiment in an alpine meadow on the Qinghai-Tibetan Plateau and investigated the responses of plant species diversity, composition, biomass, and net primary productivity (NPP) at both community and functional group levels to whole-soil-profile warming (3–4 °C across 0–100 cm) during 2018–2021. Plant species diversity, biomass and NPP (both above- and belowground) at the community level showed remarkable resistance to warming. However, plant community composition gradually shifted over time. Over the whole experimental warming period, aboveground biomass of legumes significantly decreased by 45%. Conversely, warming significantly stimulated aboveground biomass of forbs by 84%, likely because of better growth and competitive advantages from the warming-induced stimulation of soil water and other variables. However, warming showed minor effects on aboveground biomass of grasses and sedges. Overall, we emphasize that experimental warming may significantly affect plant community composition in a short term by triggering adjustments in plant interspecific competition or survival strategies, which may cause potential changes in plant productivity over a more extended period and lead to changes in carbon source-sink dynamics in the alpine meadow ecosystem.

Abstract Alpine shrub meadows hold significant importance as grassland ecosystems on the Qinghai‐Tibetan Plateau (QTP). They provide a range of vital ecosystem services (ESs) and are commonly utilized as summer pastures by herders, resulting in short grazing periods and high grazing intensities. Unfortunately, these practices have led to varying degrees of degradation, thereby affecting the sustainable provision of ESs. However, the current knowledge regarding changes in ESs and their characteristics under the influence of degradation, particularly the differences between alpine shrub and alpine meadow ecosystems, is insufficient. To address this gap, this study aimed to investigate and analyse changes in four ESs within alpine shrub meadows across different levels of degradation, as well as explore their relationships. The research was conducted in a summer pasture located in the northeastern QTP. The findings revealed a substantial reduction of 85.9% in forage supply due to degradation in alpine shrub meadows. Moreover, regulating services experienced a decline followed by an increase in instances of heavy degradation. Trade‐offs were observed between provisioning and regulating services, while synergistic relationships were identified among different regulating services. Degradation exacerbated imbalances between provisioning and regulating services, whereas light degradation allowed for a better equilibrium between the two. Comparatively, alpine meadows exhibited higher levels of forage supply and carbon storage services, whereas alpine shrub ecosystems displayed greater nutrient supply and water retention services. It was observed that changes in ESs and relationship patterns within alpine shrub meadows were significantly influenced by the presence of alpine meadows. Consequently, safeguarding the structural integrity of alpine meadows and addressing conflicts over ESs is essential to ensure coordination and sustainability of ESs within alpine shrub meadows. The outcomes of this study provide valuable insights for ecosystem management and ecological restoration initiatives in alpine shrub meadows on the QTP.

Metal chalcogenides have shown promising performances for renewable hydrogen evolution and such activities are sensitive to the material electronic structures. Here, authors modulate the electronic properties of molybdenum sulfide in 1T'''-MoS2 for hydrogen evolution electrocatalysis.

The response of soil organic carbon to climate warming may be soil depth-dependent, but remains unquantified in situ. Here the authors show that warming induces more proportional soil carbon losses in topsoil than in subsoil, particularly from high-latitudinal carbon-rich soils.

In the field of computational fluid dynamics (CFD), smoothed particle hydrodynamics (SPH) is very suitable for simulating problems with large deformation, free surface flow and other types of flow scenarios. However, traditional smoothed particle hydrodynamics methods suffer from the problem of high computation complexity, which constrains their application in scenarios with accuracy requirements. DualSPHysics is an excellent smoothed particle hydrodynamics software proposed in academia. Based on this tool, this paper presents a largescale parallel smoothed particle hydrodynamics framework: parallelDualSPHysics, which can solve the simulation of large-scale free surface flow. First, an efficient domain decomposition algorithm is proposed. And the data structure of DualSPHysics in a parallel framework is reshaped. Secondly, we proposed a strategy of overlapping computation and communication to the parallel particle interaction and particle update module, which greatly improves the parallel efficiency of the smoothed particle hydrodynamics method. Finally, we also added the pre-processing and post-processing modules to enable parallelDualSPHysics to run in modern high performance computers. In addition, a thorough evaluation shows that the 3 to 120 million particles tested can still maintain more than 90% computing efficiency, which demonstrates that the parallel strategy can achieve superior parallel efficiency.

IntroductionThe functions of terrestrial ecosystems are mainly maintained by bacteria, as a key component of microorganisms, which actively participate in the nutrient cycling of ecosystems. Currently, there are few studies have been carried out on the bacteria contributing to the soil multi-nutrient cycling in responding to climate warming, which hampers our obtainment of a comprehensive understanding of the ecological function of ecosystems as a whole.MethodsIn this study, the main bacteria taxa contributing to the soil multi-nutrient cycling under the long-term warming in an alpine meadow was determined based onphysichemical properties measurement and high-throughput sequencing, and the potential reasons that warming altered the main bacteria contributing to the soil multi-nutrient cycling were further analyzed.ResultsThe results confirmed that the bacterial β-diversity was crucial to the soil multi-nutrient cycling. Furthermore, Gemmatimonadetes, Actinobacteria, and Proteobacteria were the main contributors to the soil multi-nutrient cycling, and played pivotal roles as keystone nodes and biomarkers throughout the entire soil profile. This suggested that warming altered and shifted the main bacteria contributing to the soil multi-nutrient cycling toward keystone taxa.DiscussionMeanwhile, their relative abundance was higher, which could make them have the advantage of seizing resources in the face of environmental pressures. In summary, the results demonstrated the crucial role of keystone bacteria in the multi-nutrient cycling under the climate warming in the alpine meadow. This has important implications for understanding and exploring the multi-nutrient cycling of alpine ecosystems under the global climate warming.

(1) Background: Heart failure (HF) is the final stage of multiple cardiac diseases, which have now become a severe public health problem worldwide. β-Adrenergic receptor (β-AR) overactivation is a major pathological factor associated with multiple cardiac diseases and mediates cardiac fibrosis and inflammation. Previous research has demonstrated that Bruton’s tyrosine kinase (BTK) mediated cardiac fibrosis by TGF-β related signal pathways, indicating that BTK was a potential drug target for cardiac fibrosis. Zanubrutinib, a second-generation BTK inhibitor, has shown anti-fibrosis effects in previous research. However, it is unclear whether Zanubrutinib can alleviate cardiac fibrosis induced by β-AR overactivation; (2) Methods: In vivo: Male C57BL/6J mice were treated with or without the β-AR agonist isoproterenol (ISO) to establish a cardiac fibrosis animal model; (3) Results: In vivo: Results showed that the BTK inhibitor Zanubrutinib (ZB) had a great effect on cardiac fibrosis and inflammation induced by β-AR. In vitro: Results showed that ZB alleviated β-AR-induced cardiac fibroblast activation and macrophage pro-inflammatory cytokine production. Further mechanism studies demonstrated that ZB inhibited β-AR-induced cardiac fibrosis and inflammation by the BTK, STAT3, NF-κB, and PI3K/Akt signal pathways both in vivo and in vitro; (4) Conclusions: our research provides evidence that ZB ameliorates β-AR-induced cardiac fibrosis and inflammation.

One new phenylpropenol ester (1) and three new lindenane sesquiterpenes (2–4) were isolated from the whole plant of Chloranthus japonicus together with three known lindenane derivatives (5–7). Their structures were determined based on detailed spectroscopic and electronic circular dichroism computational analyses. Compound 4 showed moderate efficacy in inhibiting cell migration, invasion, and vasculogenic mimicry (VM) in human of hepatocarcinoma (HCC) HepG2 cells. Furthermore, compound 4 could alter the expression of the proteins Vimentin, N-cadherin, Snail1 and E-cadherin by down-regulating the expression of Twist1, which indicated that its antimetastatic effect was associated with restraining the epithelial-mesenchymal transition (EMT) in HepG2 cells.

The effects of climate change on permafrost have been well documented in many studies, whereas the effect of climate change on seasonally frozen ground (SFG) is still poorly understood. We used the observed daily freeze depth of SFG and environmental factors data from the period 2007–2016 to examine the seasonal and inter-annual variation of SFG. We quantitatively evaluated the effects of environmental factors on SFG using a boosted regression tree analysis. The results show that, on a seasonal scale, the lower layer soil frost starts freezing in mid-November, with the maximum freeze depth occurring in late March (209 cm), and then begins to thaw in both the lower and upper layers. We identified four stages of the freeze-thaw cycle: the non-frozen phase, initial freezing, deep freezing, and thawing. Furthermore, the thawing process of SFG mainly took place in the upper layer, but the freezing rate of the lower layer from mid-November to early February was similar to the thawing rate of late April to late June. On the inter-annual scale, the maximum freeze depth showed a significant increasing trend (p < 0.05). However, the freeze-thaw duration declined significantly (p < 0.05), which was correlated with the decrease in the period when surface soil temperature is below 0°C. The mean soil temperature and soil heat flux were the most important environmental indicators affecting seasonal variation of SFG depth, and the cumulative negative air and soil temperatures were the dominant factors affecting inter-annual variation of maximum freeze depth. Our results might provide insight into predicting hydrological and ecological responses to future climate change in frozen-ground regions.

Bio-based polymers can reduce dependence on nonrenewable petrochemical resources and will be beneficial for future sustainable developments due to their low carbon footprint. In this work, the feasibility of bio-based polyamide 56 (PA56) substituting petroleum-based PA66 is systematically investigated. The crystallization, melting, and decomposition temperature of PA56 were all lower than that of PA66. PA56 formed a γ crystal type with larger grain size and took a longer amount of time to complete the crystallization process since its crystallization rate was lower than that of PA66. Compared with PA66, PA56 exhibited a higher tensile strength of 71.3 ± 1.9 MPa and specific strength of 64.8 ± 2.0 MPa but lower notched impact strength. More importantly, the limited oxygen index and vertical combustion measurement results indicated that the flame retardancy of PA56 was better than PA66, and the LOI values and the UL94 result of PA56 were 27.6% ± 0.9% and V-2. It is worth noting that the PA56 fiber had superior biodegradability compared to the PA66 fiber. PA56 showed significant biodegradation from the eighth week, whereas PA66 remained clean until the sixteenth week (without obvious biodegradation taking place). Eventually, PA56 did not show significant differences compared to PA66 in terms of thermal and mechanical properties. However, PA56 had great advantages in flame retardancy and biodegradability, indicating that the bio-based PA56 could potentially replace petroleum-based PA66 in many fields.

One of the challenges of managing grasslands sustainably is the conflict between the different ecosystem services they provide. This is especially evident in the Qinghai-Tibetan Plateau (QTP) region, where fragile alpine ecosystems make balancing the needs of grassland conservation and development difficult. However, our current understanding of the relationships and drivers of ecosystem services in degraded alpine shrub meadows on the QTP is insufficient. To address this, we studied forage provisioning and water retention services in a degraded alpine shrub meadow in the northeastern QTP. We analyzed the changes and relationships between these services at different levels of degradation and identified those factors that influenced ecosystem service relationships. The results showed that the forage supply service and the water retention service of the alpine shrub meadow increased and decreased by 23.6% and 27.07%, respectively, due to degradation. The trade-offs between these two services varied depending on the degree of degradation, with light and moderate degradation showing a preference for water retention service, and heavy and extreme degradation showing a preference for forage supply. Water retention was constrained by forage supply and both services showed an exponential function form of decay. The physical and chemical properties of the soil in the alpine shrub meadow remained relatively stable during the degradation process, with only soil organic carbon (SOC), total potassium (TK), and total nitrogen (TN) decreasing significantly. SOC may have indirectly influenced the relationship between the two services by affecting water retention. This study provides insights into alpine shrub meadow management and conservation on the QTP.

To address the issues of not accurately identifying ice types and thickness in current fiber-optic ice sensors, in this paper, we design a novel fiber-optic ice sensor based on the reflected light intensity modulation method and total reflection principle. The performance of the fiber-optic ice sensor was simulated by ray tracing. The low-temperature icing tests validated the performance of the fiber-optic ice sensor. It is shown that the ice sensor can detect different ice types and the thickness from 0.5 to 5 mm at temperatures of −5 °C, −20 °C, and −40 °C. The maximum measurement error is 0.283 mm. The proposed ice sensor provides promising applications in aircraft and wind turbine icing detection.

An understanding of soil moisture conditions is crucial for hydrological modeling and hydrological processes. However, few studies have compared the differences between the dynamics of soil moisture content and soil moisture response to precipitation infiltration under different types of vegetation on the Qinghai-Tibet Plateau (QTP). In this study, a soil moisture sensor was used for continuous volumetric soil moisture measurements during 2015 and 2016, with the aim of exploring variations in soil moisture and its response to precipitation infiltration across two vegetation types (alpine meadow and alpine shrub). Our results showed that temporal variations in soil moisture at the surface (0–20 cm) and middle soil layers (40–60 cm) were consistent with precipitation patterns for both vegetation types. However, there was a clear lag in the soil moisture response to precipitation for the deep soil layers (80–100 cm). Soil moisture content was found to be significantly positively related to precipitation and negatively related to air temperature. Aboveground biomass was significantly negatively associated with the surface soil moisture content (0–20 cm) during the growing season. Statistically significant differences were observed between the soil water content of the surface, middle, and deep soil layers for the two vegetation types (p < 0.05). Soil moisture (19.81%) in the surface soil layer was significantly lower than that in the deep soil layer (24.75%) for alpine shrubs, and the opposite trend was observed for alpine meadows. The maximum infiltration depth of alpine shrubs was greater than that of alpine meadows under extremely high-precipitation events, which indicates that alpine shrubs might be less susceptible to surface runoff under extreme precipitation events. Furthermore, low precipitation amounts did not affect precipitation infiltration for either vegetation type, whereas the infiltration depth increased with precipitation for both vegetation types. Our results suggest that a series of small precipitation events may not have the same effect on soil moisture as a single large precipitation event that produces the equivalent total rainfall.

Evapotranspiration is a key component in the terrestrial water cycle, and accurate evapotranspiration estimates are critical for water irrigation management. Although many applicable evapotranspiration models have been developed, they are largely focused on low-altitude regions, with less attention given to alpine ecosystems. In this study, we evaluated the performance of fourteen reference evapotranspiration (ET0) models by comparison with large weight lysimeter measurements. Specifically, we used the Bowen ratio energy balance method (BREB), three combination models, seven radiation-based models, and three temperature-based models based on data from June 2017 to December 2018 in a humid alpine meadow in the northeastern Qinghai–Tibetan Plateau. The daily actual evapotranspiration (ETa) data were obtained using large weighing lysimeters located in an alpine Kobresia meadow. We found that the performance of the fourteen ET0 models, ranked on the basis of their root mean square error (RMSE), decreased in the following order: BREB > Priestley-Taylor (PT) > DeBruin-Keijman (DK) > 1963 Penman > FAO-24 Penman > FAO-56 Penman–Monteith > IRMAK1 > Makkink (1957) > Makkink (1967) > Makkink > IRMAK2 > Hargreaves (HAR) > Hargreaves1 (HAR1) > Hargreaves2 (HAR2). For the combination models, the FAO-24 Penman model yielded the highest correlation (0.77), followed by 1963 Penman (0.75) and FAO-56 PM (0.76). For radiation-based models, PT and DK obtained the highest correlation (0.80), followed by Makkink (1967) (0.69), Makkink (1957) (0.69), IRMAK1 (0.66), and IRMAK2 (0.62). For temperature-based models, the HAR model yielded the highest correlation (0.62), HAR1, and HAR2 obtained the same correlation (0.59). Overall, the BREB performed best, with RMSEs of 0.98, followed by combination models (ranging from 1.19 to 1.27 mm day−1 and averaging 1.22 mm day−1), radiation-based models (ranging from 1.02 to 1.42 mm day−1 and averaging 1.27 mm day−1), and temperature-based models (ranging from 1.47 to 1.48 mm day−1 and averaging 1.47 mm day−1). Furthermore, all models tended to underestimate the measured ETa during periods of high evaporative demand (i.e., growing season) and overestimated measured ETa during low evaporative demand (i.e., nongrowing season). Our results provide new insights into the accurate assessment of evapotranspiration in humid alpine meadows in the northeastern Qinghai–Tibetan Plateau.

Genetic resistance is a cornerstone for managing clubroot (Plasmodiophora brassicae). However, when used repeatedly, a clubroot resistance (CR) gene can be broken rapidly. In this study, canola inbred/hybrid lines carrying one or two CR genes (Rcr1/CRaM and Crr1rutb) were assessed against P. brassicae pathotype X by repeated exposure to the same inoculum source under a controlled environment. Lines carrying two CR genes, either Rcr1 + Crr1rutb or CRaM + Crr1rutb, showed partial resistance. Selected lines were inoculated with a field pathotype X population (L-G3) at 5 × 106 resting spores/g soil, and all clubs were returned to the soil they came from six weeks after inoculation. The planting was repeated for five cycles, with diseased roots being returned to the soil after each cycle. The soil inoculum was quantified using qPCR before each planting cycle. All lines with a single CR gene were consistently susceptible, maintaining high soil inoculum levels over time. The lines carrying two CR genes showed much lower clubroot severity, resulting in a 10-fold decline in soil inoculum. These results showed that the CR-gene stacking provided moderate resistance against P. brassicae pathotype X, which may also help reduce the pathogen inoculum buildup in soil.

An MEMS resonant accelerometer is a temperature-sensitive device because temperature change affects the intrinsic resonant frequency of the inner silicon beam. Most classic temperature compensation methods, such as algorithm modeling and structure design, have large errors under rapid temperature changing due to the hysteresis of the temperature response of the accelerometer. To address this issue, we propose a novel reservoir computing (RC) structure based on a nonlinear silicon resonator, which is specifically improved for predicting dynamic information that is referred to as the input–output-improved reservoir computing (IOI-RC) algorithm. It combines the polynomial fitting with the RC on the input data mapping ensuring that the system always resides in the rich nonlinear state. Meanwhile, the output layer is also optimized by vector concatenation operation for higher memory capacity. Therefore, the new system has better performance in dynamic temperature compensation. In addition, the method is real-time, with easy hardware implementation that can be integrated with MEMS sensors. The experiment’s result showed a 93% improvement in IOI-RC compared to raw data in a temperature range of −20–60 °C. The study confirmed the feasibility of RC in realizing dynamic temperature compensation precisely, which provides a potential real-time online temperature compensation method and a sensor system with edge computing.

Alpine shrub-meadow is an important ecosystem type on the Qinghai-Tibetan Plateau, providing a variety of ecosystem services while supporting the livelihoods of pastoralists. However, there is a clear lack of understanding of the changes in spatial patterns and ecosystem services of alpine shrub-meadow degradation. This study combined aerial photography and ground surveys to investigate and analyse the impact of degradation on the spatial patterns of alpine shrub-meadow and their ecosystem services, and the relationships between the spatial patterns and ecosystem services. The results showed that degradation led to fragmentation and patchiness in alpine shrub-meadow, as evidenced by a decrease in the proportion of shrub and meadow area and average patch size, as well as the complexity of patch boundaries and shapes. Light and moderate degradation reduced all ecosystem services in alpine shrub-meadow, with carbon storage, nutrient supply and water retention services decreased by an average of 27.4%, 17.3% and 13.8% respectively, while forage supply services decreased by 65.2% at heavy degradation, and the reduction in alpine meadow ecosystem services was even greater. Regulating services increased again at heavy degradation due to the accumulation and slow decomposition of plant underground roots, and rodent activity. The spatial patterns of the meadow layer were more closely related to its ecosystem services than the shrub layer, and fragmentation and patchiness were positively related to ecosystem services. Our findings suggest that the impact of degradation on alpine shrub-meadow ecosystem services may be non-linear and that the relationships between spatial patterns and ecosystem services need to be interpreted with caution and should be analysed comprehensively with a wider range of influencing factors. Our results have implications for grassland restoration and ecosystem service management on the Qinghai-Tibetan Plateau.

Abstract The response of grassland soil bacterial community characteristics to different grazing intensities is central ecological topics. However, the underlying mechanisms between bacterial abundance, diversity index, and grazing intensity remain unclear. We measured alpine meadow soil bacterial gene richness and diversity index under four grazing intensities using 16S rDNA sequence analysis on the Tibetan Plateau. The results suggest that extreme grazing significantly decreased alpine meadow both bacterial gene abundance and diversity index (p

Abstract Background Acute renal injury (AKI) caused by hypotension often occurs in elderly patients after gastrointestinal tumor surgery. Although vasoactive drugs can increase effective filtration pressure, they may increase renal vascular resistance and reduce renal blood flow. The effect of methoxamine on renal function is not clear. Methods After obtaining written informed consent, 180 elderly patients undergoing elective gastrointestinal tumor surgery were randomly allocated into two groups: M group (continuous infusion of methoxamine at 2 μg/kg/min) and N group (continuous infusion of normal saline). The patients’ mean arterial pressure was maintained within 20% of baseline by a continuous infusion of methoxamine or normal saline. Maintenance fluid was kept at 5 mL/kg/h. According to Kidney disease improve global outcome (KDIGO) guidelines, creatinine was measured at 1, 2 and 7 days after operation, and urine volume at 6, 12 and 24 h after operation was measured to evaluate the occurrence of AKI. 162 patients were included in the final data analysis. Results Significant differences in the incidence of postoperative Acute kidney injury (M group: 7.5%; N group: 18.3%; P

Abstract Aboveground biomass (AGB) and belowground biomass (BGB) allocation and productivity–richness relationship are controversial. Here, we assessed AGB and BGB allocation and the productivity–richness relationship at community level across four grassland types based on the biomass data collected from 80 sites across the Qinghai Plateau during 2011–2012. The reduced major axis regression and general linear models were used and showed that (a) the median values of AGB were significantly higher in alpine meadow than in other three grassland types; the ratio of root to shoot (R/S) was significantly higher in desert grassland (36.06) than intemperate grassland (16.60), alpine meadow (13.35), and meadow steppe (19.46). The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. (b) The slopes between log AGB and log BGB in the temperate grassland and meadow steppe were 1.09 and 1, respectively, whereas that in the desert grassland was 1.12, which was significantly different from the isometric allocation relationship. A competitive relationship between AGB and BGB was observed in the alpine meadow with a slope of −1.83, indicating a trade‐off between AGB and BGB in the alpine meadow. (c) A positive productivity–richness relationship existed across the four grassland types, suggesting that the positive productivity–richness relationship might not be affected by the environmental factors at the plant location. Our results provide a new insight for biomass allocation and biodiversity–ecosystem functioning research.

This paper proposes an adaptive energy management strategy for hybrid electric vehicles by combining deep reinforcement learning (DRL) and transfer learning (TL). This work aims to address the defect of DRL in tedious training time. First, an optimization control modeling of a hybrid tracked vehicle is built, wherein the elaborate powertrain components are introduced. Then, a bi-level control framework is constructed to derive the energy management strategies (EMSs). The upper-level is applying the particular deep deterministic policy gradient (DDPG) algorithms for EMS training at different speed intervals. The lower-level is employing the TL method to transform the pre-trained neural networks for a novel driving cycle. Finally, a series of experiments are executed to prove the effectiveness of the presented control framework. The optimality and adaptability of the formulated EMS are illuminated. The founded DRL and TL-enabled control policy is capable of enhancing energy efficiency and improving system performance.

Alpine grassland has very important water conservation function. Grassland degradation seriously affects the water conservation function; moreover, there is little understanding of the change of water state during grassland restoration. Our study aims to bridge this gap and improve our understanding of changes in soil moisture during the restoration process. In this study, the water storage, vegetation, and meteorology of a non-degradation grassland (grazing intensity of 7.5 sheep/ha) and a severely degraded grassland (grazing intensity of 12–18 sheep/ha) were monitored in the Qinghai-Tibet Plateau for seven consecutive years. We used correlation, stepwise regression, and the boosted regression trees (BRT) model analyses, five environmental factors were considered to be the most important factors affecting water storage. The severely degraded grassland recovered by light grazing treatment for 7 years, with increases in biomass, litter, and vegetation cover, and a soil-water storage capacity 41.9% higher in 2018 compared to that in 2012. This increase in soil-water storage was primarily due to the increase in surface soil moisture content. The key factors that influenced water storage were listed in a decreasing order: air temperature, litter, soil heat flux, precipitation, and wind speed. Their percentage contributions to soil-water storage were 50.52, 24.02, 10.86, 7.82, and 6.77%, respectively. Current and future climate change threatens soil-water conservation in alpine grasslands; however, grassland restoration is an effective solution to improve the soil-water retention capacity in degraded grassland soils.

Water use efficiency is an important indicator of drought tolerance in plants. The response of the water use efficiency to different grazing intensities and adaptive mechanisms in alpine meadows remains unclear. To understand the changes in water use in alpine meadow ecosystems under different grazing gradients, grazing systems have to be optimized, and severely receding grasslands should be effectively restored. This study analyzed the response of water use efficiency of plant dominant species, coexisting species, and functional group-level plants to grazing intensity using the δ13C index in an alpine meadow. We found that grazing increased the leaf carbon isotope composition in plants (δ13C) of Gramineae by 3.37% and grazing at a moderate level significantly increased it by 4.84% (P < 0.05). In addition, an increase in δ13C was observed in the functional groups of Cyperaceae (3.45%), Leguminosae (0.81%), and Forb (1.40%). However, some dominant species and coexisting species showed the highest δ13C values under moderate grazing. These results indicate that moderate grazing may significantly improve the water use efficiency of species in alpine meadows. The path analysis showed that water use efficiency was negatively correlated with evapotranspiration (P < 0.05), soil water content, soil organic carbon, and soil bulk density. Nevertheless, there was a positive correlation between water use efficiency and the available nitrogen. This study concluded that moderate grazing could improve the efficiency of grassland water use to a certain extent. Additionally, soil evapotranspiration was the main driving factor affecting the water use efficiency of alpine meadows.

Soil water retention capacity is an essential component of the land surface processes and hydrological cycles. Although the effect of grassland degradation on soil water retention capacity have been well documented, few studies have focused on how soil hydrological properties vary between different vegetation types on the Qinghai-Tibet Plateau (QTP). This study selected three vegetation types: Potentilla fruticosa shrub (PFS), Kobresia pygmaca meadow (KPM), and Kobresia humilis meadow (KHM), and aimed to explore the variations and factors controlling soil water retention capacity across the three types. Results showed that the soil water retention capacity was higher in PFS than in KPM and KHM across 0–40 cm, whereas the 0–30 cm plant available water content was much lower in PFS than in KPM and KHM. Meanwhile, the soil properties within the different soil layers varied significantly between vegetation types. The 0–10 cm clay and silt contents were significantly higher in PFS than in the other two vegetation types, whereas the soil bulk density (BD) was lower in PFS than in KHM and KPM. Furthermore, the 0–50 cm soil capillary porosity (CP) was significantly higher in PFS than in KPM and KHM, except at 0–10 cm. Besides, the 0–10 cm soil organic matter (SOM) was significantly higher in KPM than in PFS and KHM, owing to its highest root biomass. Overall, the soil water retention capacity was most strongly influenced by CP, followed by BD, TP, SOM and root biomass, whereas the soil non-capillary porosity and soil particle size distribution exerted no significant impact on soil water retention capacity. Our results suggested that the alpine shrub had a stronger soil water retention capacity than the alpine meadow.

Soil moisture dynamics play an active role in ecological and hydrological processes. Although the variation of the soil water moisture of multiple ecosystems have been well-documented, few studies have focused on soil hydrological properties by using a drying and weighing method in a long time series basis in the Qinghai-Tibet Plateau (QTP). In this study, 13 year (2008–2020) time-series observational soil moisture data and environmental factors were analyzed in a humid alpine Kobresia meadow on the Northern Qinghai–Tibetan Plateau. The results showed no significant upward trend in soil water content during the 2008–2020 period. In the growth season (May–October), the soil water content showed a trend of decreasing firstly, then increasing, and finally, decreasing. Correlation analysis revealed that five meteorology factors (temperature, humidity, net radiation, dew point temperature, and vapor pressure) and a biomass element (above-ground biomass) had a significant effect on the soil moisture, and air temperature impacted the soil water variation negatively in 0–50 cm, indicating that global warming would reduce soil moisture. Humidity and net radiation made a difference on shallow soil (0–10 cm), while dew point temperature and vapor pressure played a role on the deep soil (30–50 cm). Above-ground biomass only effected 30–50 cm soil moisture variation, and underground biomass had little effect on the soil moisture variation. This indirectly indicated that below-ground biomass is not limited by soil moisture. These results provide new insights for the rational allocation of water resources and management of vegetation in alpine meadows, in the context of climate change.

Micro-patches are the basic unit of grazing ecosystems; the characteristics of these micro-patches are relatively stable in species under different grazing intensities in the same vegetation, but obviously different in terms of the distribution pattern. This leads to differentiation of plant community numerical characteristics under different grazing intensities. Understanding the driving force of soil nutrient variation in micro-patches under grazing disturbances will help us comprehend the regulation strategy and adaptation mechanisms of the ecosystem against over-disturbance. We designed four scales: spatial (three typical micro-patches), temporal serial (6 years), a degradation succession process (four key degradation stages), and recovery treatment (three treatments: the original grazing intensity based on herder preferences, half of the original grazing intensity, and zero grazing). The soil nutrient characteristics used to estimate stabilization were the typical soil total nutrient content (soil organic matter [SOM], total nitrogen [TN], total carbon [TC], inorganic carbon [IC], total phosphorus [STP], total potassium [TK], and pH), and available soil nutrients (NH4+, NO3−, phosphorous [avP], and potassium [avK]). Variations in the SOM, TC, IC, TN, STP, avK, and NO3− levels in the main root distribution layers (0–20 cm) on the spatial scale were 69.8–79.7%, 61.4–80.35%, 49.8–79.58%, 60.52–76.34%, 46.44–89.89%, 45.5–71.36%, and 59.21–65.38%, respectively, which accounted for the largest variation in the four scales, based on multivariable analysis. The variations in the avP and NH4+ content of the main root distribution layers (0–20 cm) at the temporal scale were 46.42–67.93% and 48.11–64.55%, respectively, which accounted for the greatest variation in the four scales, based on a multivariable analysis. Upon comparing the degradation succession stages and recovery treatment in each stage, we found that the variation in avP, avK, STP, TN, TC, SOM, TC, and TN content was greater at the degradation succession scale than at the recovery treatment scale. The soil nutrient content of the micro-patches exhibited the smallest decrease in the Gramineae-Kobresia transformation (G-KP) micro-patch, followed by the Gramineae micro-patches (G) and Kobresia micro-patches (KP). The number of G micro-patches decreased with increasing grazing intensity whereas the number of KP micro-patches increased. When the number of KP micro-patches increased to a certain degree, the number of G-KP micro-patches then increased as well. G-KP micro-patches, characterized by cracking in the mattic epipedon in alpine meadows, increased with the grazing intensity increasing in a certain degree in K. pygmaea meadows with mattic epipedon cracking (CP); the latter buffered the nutrient variation and maintained the soil nutrients’ relative stability in the ecosystem. Thus, CP formed the buffer stage for maintaining self-stabilization during a regime shift and was considered the withstanding stage during the alpine Kobresia meadow degradation process.

Abstract Grazing is an important modulator of both plant productivity and biodiversity in grassland community, yet how to determine a suitable grazing intensity in alpine grassland is still controversy. Here, we explore the effects of different grazing intensities on plant biomass and species composition, both at community level and functional group level, and examines the productivity–species richness relationship under four grazing patterns: no grazing (CK), light grazing (LG), moderate grazing, (MG) and heavy grazing (HG), attempt to determine a suitable grazing intensity in alpine grassland. The results were as follows. The total aboveground biomass (AGB) reduced with increasing grazing intensity, and the response of plant functional groups was different. AGB of both sedges and legumes increased from MG to HG, while the AGB of forbs reduced sharply and the grass AGB remained steady. There was a significant positive relationship between productivity and species richness both at community level and functional group level. In contrast, the belowground biomass (BGB) showed a unimodal relationship from CK to HG, peaking in MG (8,297.72 ± 621.29 g/m2). Interestingly, the grassland community tends to allocate more root biomass to the upper soil layer under increasing grazing intensities. Our results suggesting that moderate levels of disturbance may be the optimal grassland management strategy for alpine meadow in terms of root production.

Abstract Net primary production (NPP) is a fundamental property of natural ecosystems. Understanding the temporal variations of NPP could provide new insights into the responses of communities to environmental factors. However, few studies based on long‐term field biomass measurements have directly addressed this subject in the unique environment of the Qinghai‐Tibet plateau (QTP). We examined the interannual variations of NPP during 2008–2015 by monitoring both aboveground net primary productivity (ANPP) and belowground net primary productivity (BNPP), and identified their relationships with environmental factors with the general linear model (GLM) and structural equation model (SEM). In addition, the interannual variation of root turnover and its controls were also investigated. The results show that the ANPP and BNPP increased by rates of 15.01 and 143.09 g/m2 per year during 2008–2015, respectively. BNPP was mainly affected by growing season air temperature (GST) and growing season precipitation (GSP) rather than mean annual air temperature (MAT) or mean annual precipitation (MAP), while ANPP was only controlled by GST. In addition, available nitrogen (AN) was significantly positively associated with BNPP and ANPP. Root turnover rate averaged 30%/year, increased with soil depth, and was largely controlled by GST. Our results suggest that alpine Kobresia meadow was an N‐limited ecosystem, and the NPP on the QTP might increase further in the future in the context of global warming and nitrogen deposition.

Abstract The Qinghai–Tibet Plateau (QTP) is particularly sensitive to global climate change, especially to elevated temperatures, when compared with other ecosystems. However, few studies use long‐term field measurements to explore the interannual variations in plant biomass under climate fluctuations. Here, we examine the interannual variations of plant biomass within two vegetation types (alpine meadow and alpine shrub) during 2008–2017 and their relationships with climate variables. The following results were obtained. The aboveground biomass (AGB) and belowground biomass (BGB) response differently to climate fluctuations, the AGB in KPM was dominated by mean annual precipitation (MAP), whereas the AGB in PFS was controlled by mean annual air temperature (MAT). However, the BGB of both KPM and PFS was only weakly affected by climate variables, suggesting that the BGB in alpine ecosystems may remain as a stable carbon stock even under future global climate change. Furthermore, the AGB in PFS was significantly higher than KPM, while the BGB and R/S in KPM were significantly higher than PFS, reflecting the KPM be more likely to allocate more photosynthates to roots. Interestingly, the proportion of 0–10 cm root biomass increased in KPM and PFS, whereas the other proportions both decreased, reflecting a shift in biomass toward the surface layer. Our results could provide a new sight for the prediction how alpine ecosystem response to future climate change.

The gob-side entry retaining plays an important role in improving working face ventilation, alleviating working face connection, and increasing mining revenue. According to the characteristics of the crossheading roof at the 2103 working face of a mine in Shanxi, a structural mechanics model of the roof was established to derive the theoretical formulae for the ultimate hanging arch length of the layered roof with anchors and the initial support resistance of the entry-side support. The influence factors of the ultimate hanging arch length were evaluated using local sensitivity analysis. Based on the theoretical study, the work proposed the collaborative support technology of the crossheading, collaborative support at the 2103 working face. The results showed that the ultimate hanging arch length was most influenced by the width of the plastic zone, followed by the width of the roadway, supporting strength, anchoring strength, layered thickness, and mining depth, while the ultimate tensile strength had little influence. The initial support resistance of the entry-side supports was closely related to the ultimate hanging arch length and the process of gob-side entry retaining. The improved entry-retaining supporting process could control the sharp surface convergence of the surrounding rocks of the entry retaining, the sinkage of the roof of the entry-retaining section was controlled below 100 mm, and that of the advanced section was controlled below 50 mm. The stability of the supports next to the entry is improved, and the needs of the site project are met.

The uniaxial compressive strength (UCS) of rock is one of the essential data in engineering planning and design. Correctly testing UCS of rock to ensure its accuracy and authenticity is a prerequisite for assuring the design of any rock engineering project. UCS of rock has a broad range of applications in mining, geotechnical, petroleum, geomechanics, and other fields of engineering. The application of the gradient boosting machine learning algorithms has been rarely used, especially for UCS prediction, and has performed well, based on the relevant literature of the study. In this study, four gradient boosting machine learning algorithms, namely, gradient boosted regression (GBR), Catboost, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost), were developed to predict the UCS in MPa of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan, using four input variables such as wet density (ρw) in g/cm3; moisture in %; dry density (ρd) in g/cm3; and Brazilian tensile strength (BTS) in MPa. Then, 106-point dataset was allocated identically for each algorithm into 70% for the training phase and 30% for the testing phase. According to the results, the XGBoost algorithm outperformed the GBR, Catboost, and LightGBM with coefficient of correlation (R2) = 0.99, mean absolute error (MAE) = 0.00062, mean square error (MSE) = 0.0000006, and root mean square error (RMSE) = 0.00079 in the training phase and R2 = 0.99, MAE = 0.00054, MSE = 0.0000005, and RMSE = 0.00069 in the testing phase. The sensitivity analysis showed that BTS and ρw are positively correlated, and the moisture and ρd are negatively correlated with the UCS. Therefore, in this study, the XGBoost algorithm was shown to be the most accurate algorithm among all the investigated four algorithms for UCS prediction of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan.

Measurement while drilling is an important part of the intelligent development of coal mines. The main purpose of this paper is to comprehensively analyze the response characteristics of borehole drilling parameters and find a better method to predict rock mechanical properties based on drilling parameters. Firstly, six concrete blocks and multiple specimens were prepared with different material ratios. Next, the concrete specimens were tested for mechanical properties in the laboratory. Meanwhile, the displacement, rotation speed, torque, and sound pressure level (SPL) were observed during the drilling of the concrete blocks. Finally, the response characteristics of drilling parameters such as rotation speed, rate of penetration (ROP), torque, and SPL were analyzed. Besides, multiple prediction models of rock mechanical parameters were obtained by data analysis. The research results indicate that the drilling process can be classified into the initial stage of drilling (fast speed) and the steady stage of drilling (slow speed). The torque work ratio accounts for more than 99%, which increases with the increase in rock strength. The penetration depth per revolution and torque work ratio are significantly related to rock uniaxial compressive strength, Brazilian tensile strength, cohesion, and elastic modulus. The ROP is the best choice for estimating rock mechanical parameters. This research provides an important reference for laboratory rock mechanics parameter testing and geological features detection based on drilling parameters.

This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.

This study, based on Bem’s (1974) gender schema theory, investigates gender differences in and the relationship between gender role characteristics and entrepreneurial self-efficacy (ESE) of 261 female and 265 male entrepreneurs in China. The results show that male and female entrepreneurs did not differ significantly in ESE or in masculine gender role characteristics, but differed significantly in feminine gender role characteristics. Examining four different stages in the entrepreneurial life cycle, we find that for female entrepreneurs, feminine characteristics had a positive influence on ESE in the searching and planning stages of entrepreneurship, and masculine characteristics had a positive influence on ESE in the searching stage. For male entrepreneurs, feminine characteristics had a positive influence on ESE in the searching and planning stages, and masculine characteristics had a positive influence on ESE in the marshaling and implementing stages. In addition, one feminine characteristic, “Friendly,” showed a positive association with male entrepreneurs’ ESE in the marshaling stage. Overall, the feminine gender role factor of “Friendly” and the masculine gender role factor of “Compete” played a greater role on ESE than other characteristics. Implications of the findings are discussed. This study contributes a new perspective to extant research on entrepreneurial self-efficacy and female entrepreneurship.

The Qinghai–Tibet Plateau (QTP) has an important function in ensuring the water ecological security of China, even Asia, and the soil water storage of alpine grassland is an important part of the ecosystem water. Grassland degradation directly affects the soil water storage capacity. However, the impact of degradation on specific soil storage capacity, especially alpine shrubs, is rarely studied. Here, we chose two plots of alpine non-degraded shrub and degraded shrub, using the automatic soil moisture monitoring system to study the change process of soil moisture storage, and then adopted the boosted regression tree (BRT) model to quantitatively evaluate the relative influence of environmental variables on soil water storage. Our results show: (1) The soil water storage in the growing season (May–September) is higher than that in the non-growing season (January–April and October–December), and the soil water storage reaches its highest in mid-July. (2) During the growing season, the 100 cm soil temperature was the most important factor affecting the seasonal variation in soil water storage, accounting for 51% of the total variation. During the non-growing season, the 40 cm soil temperature was the most important factor affecting the variation in soil water storage, accounting for 80% of the total variation. (3) The soil water storage of non-degraded Potentilla fruticosa shrub meadow increased by 6–25%, compared with degraded grassland shrub meadow during growing-season. (4) Various meteorological factors have a weak impact on soil water storage.

Reservoir computing (RC) is a potential neuromorphic paradigm for physically realizing artificial intelligence systems in the Internet of Things society, owing to its well-known low training cost and compatibility with nonlinear devices. Micro-electro-mechanical system (MEMS) resonators exhibiting rich nonlinear dynamics and fading behaviors are promising candidates for high-performance hardware RC. Previously, we presented a non-delay-based RC using one single micromechanical resonator with hybrid nonlinear dynamics. Here, we innovatively introduce a nonlinear tuning strategy to analyze the computing properties (the processing speed and recognition accuracy) of the presented RC. Meanwhile, we numerically and experimentally analyze the influence of the hybrid nonlinear dynamics using the image classification task. Specifically, we study the transient nonlinear saturation phenomenon by fitting quality factors under different vacuums, as well as searching the optimal operating point (the edge of chaos) by the static bifurcation analysis and dynamic vibration numerical models of the Duffing nonlinearity. Our results in the optimal operation conditions experimentally achieved a high classification accuracy of (93 ± 1)% and several times faster than previous work on the handwritten digits recognition benchmark, profit from the perfect high signal-to-noise ratios (quality factor) and the nonlinearity of the dynamical variables.