The risk level evaluation of foundation pit construction has the characteristics of fuzziness and randomness. Based on the theory of cloud model, a new model of risk level of foundation pit ...construction is discussed to comprehensively analyze the fuzziness and randomness of foundation pit construction risk assessment. Firstly, the evaluation index system of foundation pit construction risk level is established according to the field monitoring value, and then the cloud numerical characteristics of each evaluation factor belonging to different risk levels are calculated. According to the cloud digital characteristics of each evaluation factor, the determination degree of each evaluation factor belonging to different risk levels can be obtained. Finally, the weight and determination degree of the evaluation factor can be calculated comprehensively to obtain the comprehensive certainty degree of foundation pit construction risk, so as to determine the foundation pit construction risk level. The results of practical application and comparison with other evaluation methods show that this model is effective and feasible for risk classification of foundation pit construction, and has the advantages of simple calculation process and reliable results, which also provides a reference for the analysis of other similar problems.
The study investigates the rapid intensification (RI) of tropical cyclones (TCs) in the Northwestern Pacific. We found that rapid changes in the maximum wind speed (Vmax) and the minimum central ...pressure (Pmin) are not always concurrent. RI cases can be categorized into three types: (a) RIv, only Vmax strengthens rapidly; (b) RIp, only Pmin decreases rapidly; (c) RIpv, rapid changes in Vmax and Pmin occur concurrently. At the onset of RI, RIv‐type TCs exhibit the weakest intensity and the smallest size, with deep convection concentrated in the inner‐core region; RIp‐type TCs are characterized by the strongest cyclone intensity and the largest outer‐core size, with strong convection covering the inner‐ and outer‐core regions; RIpv‐type TCs show moderate intensity, size, and convection distribution. For RIpv, significant strengthening of wind profile is concentrated in the inner‐core region, while for RIp it is more prominent in the outer‐core.
Plain Language Summary
The rapid intensification (RI) of tropical cyclones (TCs) continues to pose challenges in both operational forecasting and scientific research. The maximum wind speed (Vmax) and the minimum central pressure (Pmin) are two commonly used TC intensity indicators. In most of existing studies, one single indicator (usually Vmax) is used to investigate the RI process. Whether there is a difference between RI cases defined by 24‐hr strengthening of Vmax and 24‐hr deepening of Pmin is an issue deserving discussion. The study found that rapid changes in Vmax and Pmin are not always concurrent. In the cases where only Vmax strengthens rapidly, the outer‐core size of TC expands slowly. While in the cases where only Pmin deepens rapidly, the enhancement of outer circulation is distinctive. Since the Pmin, as an integral variable, reflects TC information of both the intensity and the size, RI cases classified via these two commonly used indicators (Vmax and Pmin) could help us further understand the relationship between TC intensity and size.
Key Points
Rapid changes in the maximum wind speed (Vmax) and the minimum central pressure (Pmin) are not always concurrent in tropical cyclones (TCs)
TCs that only experience a rapid increase in Vmax (RIv) tend to have a significantly weaker lifetime maximum intensity
The evident expansion of the outer circulation occurs in TCs of which only Pmin deepens rapidly (RIp)
ABSTRACT In this paper, we use a recently compiled data set, which comprises 118 galactic-scale strong gravitational lensing (SGL) systems to constrain the statistical property of the SGL system as ...well as the curvature of the universe without assuming any fiducial cosmological model. Based on the singular isothermal ellipsoid (SIE) model of the SGL system, we obtain that the constrained curvature parameter is close to zero from the SGL data, which is consistent with the latest result of Planck measurement. More interestingly, we find that the parameter f in the SIE model is strongly correlated with the curvature . Neglecting this correlation in the analysis will significantly overestimate the constraining power of SGL data on the curvature. Furthermore, the obtained constraint on f is different from previous results: (68% confidence level C.L.), which means that the standard singular isothermal sphere (SIS) model (f = 1) is disfavored by the current SGL data at more than a C.L. We also divide all of the SGL data into two parts according to the centric stellar velocity dispersion and find that the larger the value of for the subsample, the more favored the standard SIS model is. Finally, we extend the SIE model by assuming the power-law density profiles for the total mass density, , and luminosity density, , and obtain the constraints on the power-law indices: and at a 68% C.L. When assuming the power-law index , this scenario is totally disfavored by the current SGL data, .
Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to ...increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients' clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464-0.9778), 0.9760 (0.9613-0.9906), and 0.9246 (0.8763-0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.
Cellulose has been explored as a tentative renewable carbon source to convert into micro- and meso-porous carbon (MMC) via carbonizing cellulose aerogel at a temperature of 700°C without further ...activation. The obtained MMC materials based on cellulose possess a specific surface area of 646m2g−1, a pore volume of 0.4403m3g−1, with an optimal pore structure that consists of the micropores in average size of 1.49nm and the mesopores in the range of 2.25∼3.32nm. A two-electrode symmetric supercapacitor based on the MMC materials exhibits a comparable high electrochemical performance with a large capacitance (up to 160Fg−1 at 0.2Ag−1), an high energy density of 17.81 Wh kg−1 at a power density of 180.11W kg−1 in the voltage range of 0V to 1.8V. The mesoporous can provide a good channel to further facilitate the electrolyte ion penetrating inner pores, while the microporous can store more electrolyte ions. The above cooperative effect of MMC is the key to the high-performance of the supercapacitors.
Huge amounts of data can be generated during long-term monitoring performed by structural health monitoring (SHM) and structural integrity management applications. Monitoring data can be corrupted, ...and the presence of abnormal data can distort information during signal processing, extract incorrect characteristics during system identification, produce false conclusions during damage detection, and ultimately lead to misjudgment of structural conditions during diagnosis and prognosis. Therefore, developing effective techniques to autonomously detect and classify anomalies becomes necessary and significant. Generally, conventional physics-based strategies can be straightforward, but their performance highly depends on prior knowledge of measurement. Recently, data-driven methods leveraging machine learning (ML) have been used to directly handle the task. This study proposes an ML-based classifier and improves it by incorporating the human-in-the-loop (HITL) learning. The classifier is built on a shallow neural network with high performance to address potential online or real-time applications for long-term monitoring. First, a field monitoring dataset is introduced, and various anomalies are defined to investigate the effectiveness. To further enhance the performance of the proposed classifier, the mislabels in the monitoring dataset are examined, and a correction technique is performed. Additionally, HITL ML is developed to overcome the disadvantages of the conventional correction technique. As a result, the proposed procedure can improve both the classifier and the field dataset, and the proposed classifier can now function as a fundamental component in achieving a continuous and autonomous SHM system.
Changes in the strength of trophic cascades over time have been associated with dramatic shifts in community structure and function. However, the pattern, process, and potential underlying mechanism ...of temporal variation in trophic cascades remains relatively unexplored. A top–down trophic cascade has been documented for the effects of predacious weaver ants Oecophylla smaragdina on the success of fig tree Ficus racemosa seed production. Ants cause high mortality of non‐pollinating fig wasps Sycophaga mayri that parasitize fruits, leading to greater success for the pollinating fig wasp–fig tree mutualists. Here, using a design in which pairs of branches were selected on a tree, and ants were excluded from one of each pair, we quantified the magnitude of the trophic cascade in the cool–dry, hot–dry and rainy (hot–wet) seasons in Xishuangbanna, southwest China. We also recorded the daily behavioral dynamics of ants and fig wasps in different seasons and analyzed the correlation between behavioral, activity and trophic cascade strength. We found that the strength of the trophic cascade was strong in the hot–dry season, diminished in the rainy season and disappeared in the cool–dry season in this system. The strength of species interactions between ants and non‐pollinating fig wasps, is positively correlated with trophic cascade strength, indicating that trophic cascade strength is determined by a top–down process when the community is well established. Moreover, because pollinating fig wasps, Ceratosolen fusciceps, play a central role in the establishment of fig wasp communities, when C. fusciceps wasps are absent, the community quickly disassembles as is the case in the cool–dry season. In summary, the strength of the trophic cascade is triggered by top–down processes, however, the occurrence of the trophic cascade is determined by a keystone species that plays a central role in assembly of the community.
Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification ...and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αβ T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αβ T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.
Using coal gangue as a subgrade filler will produce good benefits, and its application prospects are very broad. It is of great engineering and scientific value to study the improvement method and ...dynamic characteristics of coal gangue subgrade filler under traffic load. Combining the properties of coal gangue material, fly ash and lime and soil were added to improve the bearing behavior of coal gangue subgrade filler. Then, a compaction test was carried out using the principle of orthogonal experimental design. By analyzing the compaction test results, the optimal proportion of each additive was obtained. A large-scale dynamic triaxial test was carried out with the proportion of each admixture in the maximum dry density group in the compaction test. Based on the dynamic triaxial test results, the effect of confining pressure on the permanent strain was analyzed, the analysis model of permanent deformation and cycle number of traffic loading was proposed, and the correctness of the model was verified. In addition, a modified Hardin–Drnevich model was established, which can describe the dynamic stress–dynamic strain curve of coal gangue subgrade filler under traffic load, and then, the dynamic modulus and damping ratio were analyzed.
Objective. Selenium, as an antioxidant, has been implicated in the development of autoimmune thyroiditis (AIT). Many studies showed selenium supplementation could decrease thyroid autoantibodies in ...patients with AIT. However, the underlying mechanisms have not been well determined. Therefore, we performed a clinical study to investigate the possible mechanism of beneficial effects of selenium treatment on AIT patients. Methods. Forty euthyroid patients with AIT were randomized into two groups. Group I was treated with 200 μg/day selenium supplementation, and group II received a placebo over a 3-month period. Thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), antithyroglobulin antibody (TgAb), malondialdehyde (MDA), total antioxidant capacity (TAC), and superoxide dismutase (SOD) were measured before and 3 months after treatments. Additionally, twenty healthy volunteers also served as a control group for the evaluation of such parameters in basic condition. Results. Totally, 32 patients (group I, n = 18; group II, n = 14) completed the clinical study and were incorporated into the statistics. MDA level was higher and SOD activity and TAC were lower in patients compared to healthy individuals. After 3 months, TPOAb titer significantly decreased within group I (P<0.001) but did not change within group II (P=0.001). There were also no statistically significant changes in TSH and TgAb titers within the two groups (all P>0.05). Additionally, decreased MDA level (from 6.8 ± 1.3 nmol/ml to 4.9 ± 0.7 nmol/ml; P<0.001) and increased TAC (from 10.0 ± 1.9 mmol/l to 12.9 ± 3.1 mmol/l; P=0.003) and SOD activity (from 72.3 ± 10.3 U/ml to 84.3 ± 13.2 U/ml; P=0.007) were simultaneously observed after 3 months’ selenium treatment. Moreover, there was a negative correlation between TAC and TgAb/TPOAb and a positive correlation between MDA and TgAb/TPOAb in AIT patients. Conclusions. Our findings support the hypothesis that selenium treatment could decrease TPOAb titer via enforcing the defense against oxidative stress in euthyroid patients with AIT, which may be a potential underlying mechanism.
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