Liver regeneration of living donor after liver donation for transplantation: Disparity in the left and right remnant liver.

Donor safety is crucial for living donor liver transplantation (LDLT), and sufficient liver regeneration significantly affects outcomes of living donors. This study aimed to investigate clinical factors associated with liver regeneration in living donors. The study retrospectively reviewed 380 living donors who underwent liver donation at Chang Gung Memorial Hospital in Linkou. The clinical characteristics and medical parameters of donors were analyzed and compared according to liver donation graft type. There were 355 donors (93.4%) with right hemi-liver donations and 25 donors (6.6%) with left hemi-liver donations. Left hemi-liver donors had a higher body mass index (BMI) and a larger ratio of remnant liver volume (RLV) to total liver volume (TLV). However, the 2 groups showed no significant difference in the liver regeneration ratio. The type of remnant liver (P < .001), RLV/body weight (P = .027), RLV/TLV (P < .001), serum albumin on postoperative day 7 and total bilirubin levels on postoperative day 30 were the most significant factors affecting liver regeneration in living donors. In conclusion, adequate liver regeneration is essential for donor outcome after liver donation. The remnant liver could eventually regenerate to an adequate volume similar to the initial TLV before liver donation. However, the remnant left hemi-liver had a faster growth rate than the remnant right hemi-liver in donors.

Ecological risk assessment and spatial-temporal differentiation of soil and water resources in the Hefei metropolitan area.

There are important ways to solve the ecological risk problems of regional water resources and soil resources, and to promote the benign development of soil and water resources, involving scientific evaluation of the ecological risk of soil and water resources in Hefei metropolitan area, clarifying the intrinsic evolution law of ecological risk and identifying the characteristics of spatial and temporal variations. Based on the conceptual model of "ST-QS-RR", the evaluation indicator system is constructed, the CRITIC method is used to assign weights, and the TOPSIS method, kernel density method, markov chain and resistance model are used to measure and analyse the spatial and temporal characteristics of ecological risk of soil and water resources, and to explore the main factors that cause ecological risk of soil and water resources. The results of the study show that: (1) Hefei metropolitan area and its cities show a steady decline and the characteristics of "high in the north and low in the south, high in the west and low in the east". (2) Most of the subsystems in the Hefei metropolitan area and the cities show a decreasing trend, with its resistance factors mainly concentrated in the QS system. (3) There is club convergence in Hefei metropolitan area. When the type of adjacent domain is higher, the change of risk type is more sensitive.

Balancing growth targets and environmental regulations: An empirical analysis of dual policy impact on corporate environmental responsibility-insights from China.

Balancing economic growth with environmental conservation poses a universal challenge for governments worldwide. This study investigates the intricate interplay between governments' economic-environmental trade-offs and their implementation of policies aimed at promoting Corporate Environmental Responsibility (CER). Given the discretion of Chinese local governments in economic and environmental policy, we take China as a case study. To conduct this research, we first merge critical data on China's economic growth targets and environmental regulations with information on listed enterprises. Then, we employ a "U-shaped" relationship model to examine the impact of these trade-offs on CER implementation. The results reveal that: (1)The effective fulfillment of CER by enterprises is primarily driven by stricter environmental regulations. (2) Economic growth targets can, to some extent, diminish the policy effect of environmental regulations on CER fulfillment. (3)The crowding-out effect of economic growth targets is particularly pronounced within specific subsets of enterprises, including state-owned enterprises, heavily polluting firms, and those facing high profit pressure. These findings imply that when local governments implement contradictory policies, they must consider not only enterprises' political connections and economic contributions but also pay close attention to the survival dilemma of enterprises. This balancing act aims to harmonize conflicting policy objectives. This research deepens the understanding of how institutional and policy frameworks impact enterprise engagement in CER, especially within the context of governments' economic-environmental trade-offs. It sheds light on the strategies employed by China and other emerging economies to effectively leverage contradictory policies to foster sustainable green growth.

Intraspecific variations of leaf hydraulic, economic, and anatomical traits in Cinnamomum camphora along an urban-rural gradient.

Urbanization brings numerous benefits to residents, but it also introduces complex, variable, and heterogeneous habitat conditions to urban plants, resulting in an arid and hot urban environment that decreases tree growth and the ecological service capacity of trees. In this study, we evaluated leaf hydraulic, economic, and anatomical traits and their covariations of Cinnamomum camphora along an urban-rural gradient in Hefei, Eastern China. We found that Cinnamomum camphora in urban adopted a conservative hydraulic strategy with low leaf turgor loss point (Tlp), leaf hydraulic conductance (Kleaf), and leaf water potential resulting in 50 % loss of hydraulic conductance (P50), as well as a quick investment-return economic strategy with low unit leaf dry matter content (LMA) and high leaf nitrogen content (Leaf N). P50, Kleaf and LMA were significantly positively correlated with the urban-rural gradient (PC1urban-rural gradient), while Leaf N exhibited a negative correlation with it. The results showed a trade-off between intraspecific safety and efficiency in leaf hydraulic traits along the urban-rural gradient and an intraspecific coordinated variation in leaf hydraulic and economic traits. In addition, based on the analysis of a trait coordination network, it was revealed that leaf mesophyll and stomata were key structures for trait adjustment and coordination. Furthermore, our findings offer a significant theoretical underpinning for the effective management of landscape trees and the strategic planning of urban tree species.

Virtual ecological technology: Concepts, systems, and application perspectives.

Virtual ecological technology is a new technology that builds the foundation of a digital ecological system, simulates the process of ecological evolution, and establishes a global knowledge analysis system based on a unified spatio-temporal benchmark. It is a new direction for the interdisciplinary integration and development of eco-logy, geographic information science, computer science and other subjects towards modernization, informatization, and intelligence. Research, development, and application of virtual ecological technology is of great significance for the development of ecology as a discipline, ecosystem management, and regional sustainable development. Curren-tly, research on virtual ecological technology is still in its infancy and lacks a complete and clearly defined framework, making it difficult to support systematic iterative development and scientific analysis. In this paper, starting from the main theories and objectives of modern ecology, we summarized the main contents and technical requirements of virtual ecological construction, and proposed a key technical system of virtual ecology that integrated vir-tual geography and digital twin technology. From the perspective of application scenarios, we analyzed the application capabilities of virtual ecological technology in air pollution and energy analysis. Finally, we summarized the deve-lopment potential of virtual ecological technology in the digital construction of the ecological environment, intelligent computing, and realistic expression of different levels of ecological space resources transformation under the background of new generation of information technology, both at the local computing point breakthrough and the global technology point fusion aspects. This would enrich and advance the technical capabilities that support China's ecological space resource transformation.

The synergistic effect of digital economy and manufacturing structure upgrading on carbon emissions reduction: Evidence from China.

Promoting the integration of the digital economy with the manufacturing-based real economy is beneficial to avoid the detachment of economic development from tangible industries. Whether the low-carbon transformation can be achieved in this integration process is also an important issue. So, taking China for instance, we theoretically analyze the impact mechanism of the integration of the digital economy with three major categories of manufacturing (labor-intensive, capital-intensive, and technology-intensive) on carbon emissions, and empirically test those effects based on 30 provinces in China from 2011 to 2019. The following conclusions are drawn: (1) The development of the digital economy can reduce carbon emissions. (2) The integration of the digital economy with different categories within the manufacturing industry causes different effects on carbon emissions reduction, shown as a structural upgrading type of carbon emissions reduction, i.e., the deeper integration between digital economy and technology-intensive manufacturing contributes to a multiplier effect in carbon emissions reduction. (3) The efficiency improvements benefited from the integration with the digital economy in technology-intensive manufacturing are the main reason for the structural upgrading type of carbon emissions reduction. Therefore, policy should aim at accelerating the integration of the digital economy with advanced manufacturing to realize comprehensive low-carbon transformation.

Ultrafast and Cost-Effective Fabrication of High-Performance Carbon-Based Flexible Thermoelectric Hybrid Films and Their Devices.

Due to their cost-effectiveness and industry-scale feasibility, carbon-based composites have been considered to be promising thermoelectric materials for low-grade power generation. However, current fabrications for carbon-based composites are time-consuming, and their thermoelectric properties are still low. Herein, we develop an ultrafast and cost-effective hot-pressing method to fabricate a novel carbon-based hybrid film, which consists of ionic liquid/phenolic resin/carbon fiber/expanded graphite. This method only costs no more than 15 min. We found that the expanded graphite as the major component enables high flexibility and the introduction of phenolic resin and carbon fiber enhances the shear resistance and toughness of the film, while the ion-induced carrier migration contributes to a high power factor of 38.7 µW m-1 K-2 at 500 K in the carbon-based hybrid film. After the comparison based on the ratios between the power factor with fabrication time and cost among the current conventional carbon-based thermoelectric composites, our hybrid films show the best cost-effective property. Besides, a flexible thermoelectric device, assembled by the as-designed hybrid films, shows a maximum output power density of 79.3 nW cm-2 at a temperature difference of 20 K. This work paves a new way to fabricate cost-effective and high-performance carbon-based thermoelectric hybrids with promising application potential.

How does Chinese-style fiscal decentralization affect green technology innovation?

Green technology innovation is crucial to green transformation. Accordingly, the influence of Chinese-style fiscal decentralization on green technology innovation is contingent on whether effective green competition can occur among hierarchical governments. Against this backdrop, the Spatial Durbin Model is used to empirically estimate the impact of Chinese-style fiscal decentralization on green technology innovation, which utilized the panel data of 30 provinces in China from 2010 to 2020. The findings revealed a significant spatial agglomeration effect for green technology innovation in various regions. Besides, fiscal decentralization is evidenced to not only have a positive spatial spillover effect on green technology innovation but also promote green technology innovation at the local level and in surrounding areas, indicating that local governments have formed green preferences and facilitated green innovation technology competition. Moreover, further analysis of induced resource allocation reveals that financial support and environmental regulation have adverse inhibitory and positive promotion effects on green technology innovation, respectively. Furthermore, foreign direct investment, research and development intensity, knowledge reserve level, and industrial structure have varying spatial spillover effects on the level of green technology innovation. In light of these findings, this study recommended that the Chinese government further improves its fiscal decentralization, implements green performance evaluation of local governments, and enhances the coordinated development of various innovation incentives.

Does new-type urbanization curb haze pollution? A case study from China.

The rapid urbanization process has led to a high concentration of population and economic activities in urban space, thus leading to severe environmental pollution. The concept of new-type urbanization has been proposed in China to combat the pollution associated with urbanization. This study analyzes the interaction effect of new-type urbanization with land, industry, and technology on haze pollution, using Chinese provincial-level panel data, and employs a STIRPAT model with interaction terms for empirical testing. The results find that new-type urbanization can significantly reduce the national haze pollution level; meanwhile, the optimization of intensive urban land use level, industrial structure, and technological innovation can interact with it to promote haze reduction, and there is regional heterogeneity. The improvement of intensive urban land use and industrial structure in the central region will significantly enhance the haze reduction effect of new-type urbanization, while the improvement of technological innovation in the west will instead weaken its haze reduction effect, and the interaction in the eastern region is not significant. This research provides a theoretical basis for better implementation of new-type urbanization construction and effective promotion of green and sustainable urban development.

Assessment of the influence on left ventricle by potassium oxonate and hypoxanthine-induced chronic hyperuricemia.

Cellular cytoplasmic xanthine oxidase (XO)-mediated uric acid synthesis and extracellular excess uric acid exposure are both causes of cardiomyocytic injury under the condition of hyperuricemia (HUA). Potassium oxonate suppresses uric acid degradation to increase extracellular concentration, while hypoxanthine is the catalytic substrate of XO. We aimed to observe cardiac damage in a chronic HUA mouse model induced by potassium oxonate and hypoxanthine. The mouse model was established by the co-administration of potassium oxonate and hypoxanthine for eight weeks. Then, left ventricular parameters were examined by echocardiographic evaluation, and the heart tissues were harvested for further histopathological analysis. The results showed that plasma uric acid was persistently elevated in the model mice, which demonstrated the stable establishment of chronic HUA. The left ventricular anterior wall was significantly thickened in the model group compared with the blank control group. After the end of modeling, the left ventricular anterior wall thickness of the hyperuricemic mice increased compared with that of blank group. The histological analysis showed and myocardial structure disorganization in the model group compared with the blank control. The above cardiac impairment changes could be attenuated by allopurinol pretreatment. This study systematically assessed cardiac damage in a chronic HUA mouse model. In addition, it provides useful information for future HUA-associated heart injury mechanism investigation and therapeutic treatment evaluation.

[Enrichment and Ecological Risk Assessment of Available Phosphorus in Paddy Soil of Fujian Province Over Past 40 years].

The ecological risks such as water eutrophication caused by soil phosphorus loss have attracted extensive attention, and its dynamic changes and enrichment effects are the basis for formulating reasonable control measures. In this study, based on the paddy soils of 1.8×106 hm2 in Fujian province, the dynamic changes and ecological risks of available phosphorus in paddy soils over the past 40 years were analyzedusing a soil database of 1:50000. The soil database contained 1471, 215534, and 2895 paddy soil samples in different periods, respectively. The paddy soil samples were derived from the 1982 Second National Soil Census, the 2008 Ministry of Agriculture and Rural Areas Soil Testing and Formulated Fertilization Project and the 2018 Ministry of Agriculture, and the Rural Areas Arable Land Quality Monitoring Project, respectively. The results showed that from 1982 to 2018, the content of available phosphorus in paddy soils increased by 47 mg·kg-1, and the enriched area reached 1.65×106 hm2, accounting for 91% of the total paddy soils in Fujian province. From 1982 to 2008, the available phosphorus content of paddy soils in Fujian province increased by 28 mg·kg-1, with the enriched area reaching 1.47×106 hm2, accounting for 82% of the total paddy soils in Fujian province. From 2008 to 2018, the available phosphorus content of paddy soils in Fujian province increased by 19 mg·kg-1, with the enriched area reaching 1.22×106 hm2, accounting for 69% of the total paddy soils in Fujian province. Further ecological risk assessment showed that from 2008 to 2018, the area of paddy soil with ecological phosphorus enrichment risk in the province gradually increased, mainly distributed in percogenic paddy soils and hydromorphic paddy soils with a slope of less than 2°. In the future, effective phosphorus fertilizer management measures should be formulated for different types of paddy soil to prevent the occurrence of environmental problems such as water eutrophication.

Multi-Step Attack Detection Based on Pre-Trained Hidden Markov Models.

Currently, hidden Markov-based multi-step attack detection models are mainly trained using the unsupervised Baum-Welch algorithm. The Baum-Welch algorithm is sensitive to the initial values of model parameters. However, its training uses random or average parameter initialization methods, which frequently results in the model training into a local optimum, thus, making the model unable to fit the alert logs well and thereby reducing the detection effectiveness of the model. To solve this issue, we propose a pre-training method for multi-step attack detection models based on the high semantic similarity of alerts in the same attack phase. The method first clusters the alerts based on their semantic information and pre-classifies the attack phase to which each alert belongs. Then, the distance of the alert vector to each attack stage is converted into the probability of generating alerts in each attack stage, replacing the initial value of Baum-Welch. The effectiveness of the proposed method is evaluated using the DARPA 2000 dataset, DEFCON21 CTF dataset, and ISCXIDS 2012 dataset. The experimental results show that the hidden Markov multi-step attack detection method based on pre-training of the proposed model parameters had higher detection accuracy than the Baum-Welch-based, K-means-based, and transfer learning differential evolution-based hidden Markov multi-step attack detection methods.

Cost-Effective Fabrication of Micro-Nanostructured Superhydrophobic Polyethylene/Graphene Foam with Self-Floating, Optical Trapping, Acid-/Alkali Resistance for Efficient Photothermal Deicing and Interfacial Evaporation.

Solar evaporation is one of the most attractive and sustainable approaches to address worldwide freshwater scarcity. Unfortunately, it is still a crucial challenge that needs to be confronted when the solar evaporator faces harsh application environments. Herein, a promising polymer molding method that combines melt blending and compression molding, namely micro extrusion compression molding, is proposed for the cost-effective fabrication of lightweight polyethylene/graphene nanosheets (PE/GNs) foam with interconnected vapor escape channels and surface micro-nanostructures. A contact angle of 155 ± 2°, a rolling angle of 5 ± 1° and reflectance of ≈1.6% in the wavelength range of 300-2500 nm appears on the micro-nanostructured PE/GNs foam surface. More interestingly, the micro-nanostructured PE/GNs foam surface can maintain a robust superhydrophobic state under dynamic impacting, high temperature and acid-/alkali solutions. These results mean that the micro-nanostructured PE/GNs foam surface possesses self-cleaning, anti-icing and photothermal deicing properties at the same time. Importantly, the foam exhibits an evaporation rate of 1.83 kg m-2 h-1 under 1 Sun illumination and excellent salt rejecting performance when it is used as a self-floating solar evaporator. The proposed method provides an ideal and industrialized approach for the mass production of solar evaporators suitable for practical application environments.

Social Determinants of Health and Delirium Occurrence and Duration in Critically Ill Adults.

Social determinants of health may affect ICU outcome, but the association between social determinants of health and delirium remains unclear. We evaluated the association between three social determinants of health and delirium occurrence and duration in critically ill adults. DESIGN: Secondary, subgroup analysis of a cohort study. SETTING: Single, 36-bed mixed medical-surgical ICU in the Netherlands. PATIENTS: Nine hundred fifty-six adults consecutively admitted from July 2016 to February 2020. Patients admitted after elective surgery, residing in a nursing home, or not expected to survive greater than or equal to 48 hours were excluded. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Four factors related to three Center for Disease Control social determinants of health domains (social/community context [ethnicity], education access/quality [educational level], and economic stability [employment status and monthly income]) were collected at ICU admission from patients (or families). Well-trained ICU nurses evaluated patients without coma (Richmond Agitation Sedation Scale, -4, -5) and with the Confusion Assessment Method-ICU and/or a delirium day was defined by greater than or equal to 1 + Confusion Assessment Method-ICU and/or scheduled antipsychotic use. Multivariable logistic regression models controlling for ICU days and 10 delirium risk variables (before-ICU: age, Charlson, cognitive impairment, any antidepressant, antipsychotic, or benzodiazepine use; ICU baseline: Acute Physiology and Chronic Health Evaluation IV and admission type; daily ICU: Sequential Organ Failure Assessment, restraint use, coma, benzodiazepine, or opioid use) evaluated associations between each social determinant of health factor and both ICU delirium occurrence and duration. Delirium occurred in 393/956 patients (45.4%) for 2 days (1-5 d). Patients with low (vs high) income had more ICU delirium (p = 0.05). Multivariate analyses revealed no social determinants of health to be significantly associated with increased delirium occurrence or duration. Low (vs high) income was weakly associated with increased delirium occurrence (adjusted odds ratio, 1.83; 95% CI, 0.91-3.89). Low (vs high) education (adjusted relative risk, 1.21; 95% CI, 0.97-1.53) was weakly associated with a longer delirium duration. CONCLUSIONS: Social determinants of health did not affect ICU delirium in one Dutch region. Additional research across different countries/regions and where additional social determinants of health are considered is needed to define the association between social determinants of health and ICU delirium.

Design of a Spark Big Data Framework for PM2.5 Air Pollution Forecasting.

In recent years, with rapid economic development, air pollution has become extremely serious, causing many negative effects on health, environment and medical costs. PM2.5 is one of the main components of air pollution. Therefore, it is necessary to know the PM2.5 air quality in advance for health. Many studies on air quality are based on the government's official air quality monitoring stations, which cannot be widely deployed due to high cost constraints. Furthermore, the update frequency of government monitoring stations is once an hour, and it is hard to capture short-term PM2.5 concentration peaks with little warning. Nevertheless, dealing with short-term data with many stations, the volume of data is huge and is calculated, analyzed and predicted in a complex way. This alleviates the high computational requirements of the original predictor, thus making Spark suitable for the considered problem. This study proposes a PM2.5 instant prediction architecture based on the Spark big data framework to handle the huge data from the LASS community. The Spark big data framework proposed in this study is divided into three modules. It collects real time PM2.5 data and performs ensemble learning through three machine learning algorithms (Linear Regression, Random Forest, Gradient Boosting Decision Tree) to predict the PM2.5 concentration value in the next 30 to 180 min with accompanying visualization graph. The experimental results show that our proposed Spark big data ensemble prediction model in next 30-min prediction has the best performance (R2 up to 0.96), and the ensemble model has better performance than any single machine learning model. Taiwan has been suffering from a situation of relatively poor air pollution quality for a long time. Air pollutant monitoring data from LASS community can provide a wide broader monitoring, however the data is large and difficult to integrate or analyze. The proposed Spark big data framework system can provide short-term PM2.5 forecasts and help the decision-maker to take proper action immediately.

Assessment of the association between red blood cell distribution width and disease activity in patients with systemic vasculitis.

The present study aimed to investigate whether red blood cell distribution width (RDW) could serve as a marker for estimating disease activity in patients with systemic vasculitis (SV). A total of 287 patients with SV and 64 age- and sex-matched healthy controls (HCs) were included in the present study. Biochemical indicators and hematologic parameters were evaluated in patients with SV and the HCs. Disease activity was assessed on the basis of the Birmingham Vasculitis Activity Score (BVAS). RDW was significantly elevated in patients with SV compared with HCs (P<0.05). A similar result was obtained for the comparison of patients with various disease states, active vs. inactive (P<0.05). RDW was significantly increased in patients with kidney injury compared with patients without kidney injury (P<0.05). The correlation analysis indicated that there were positive correlations between RDW and BVAS, erythrocyte sedimentation rate, high-sensitivity C-reactive protein, white blood cells and serum creatinine (Scr; all P<0.05). In addition, there was a significant negative correlation between RDW and hemoglobin levels (P<0.05). Multivariate logistic regression analysis indicated that RDW was independently correlated with patients with active SV. The combined diagnosis of RDW and Scr indicated that the sensitivity and specificity were 68.6 and 88.9%, respectively, in terms of assessing disease activity in patients with SV. Therefore, the present study suggested that RDW may serve as a useful index for estimating disease activity and kidney injury in patients with SV. Moreover, the combination of RDW and Scr may be more effective than RDW alone when assessing the risk of disease activity in patients with SV.

Efficient and economical approach for flexible photothermal icephobic copper mesh with robust superhydrophobicity and active deicing property.

Facing various problems caused by icing in daily life, preparing photothermal deicing materials with wide applicability in high efficiency and low cost is not only a current research hotspot but also a great challenge. Herein, an economical spray-coating method is applied to prepare high-efficiency flexible photothermal icephobic copper mesh using micro silicon carbide (SiC) particles as photothermal conversion material and nano silica (SiO2) particles as a surface superhydrophobic modifier. Owing to the excellent hierarchical micro-nanostructures, the SiC/SiO2 coated copper mesh exhibits a water contact angle (CA) of 162 ± 2° and a sliding angle (SA) of 3 ± 2°. Interestingly, the coated copper mesh exhibits exceptional mechanical durability against water droplet and water flow impact, repeated bending-twisting and tape-peeling. Benefitting from the robust superhydrophobicity, the SiC/SiO2 coating on the copper mesh can significantly delay the freezing time of the droplets and reduce the ice adhesion strength. Furthermore, the coated copper mesh well retains the good photothermal conversion and thermal conductivity properties of the micro SiC particles. Under NIR irradiation, the surface temperature of the coated copper mesh placed on the ice layer can increase by 35.3 °C in 220 s, so that it can rapidly melt the accumulated frost and ice layer on the inner wall of the refrigerator. The presented flexible photothermal icephobic copper mesh exhibits enormous potential when applied to remove ice from apparatus that is accessible, such as road, overhead transmission lines and power networks owing to its flexibility, economy, and high energy efficiency.

Strategic interactions in environmental regulation enforcement: evidence from Chinese cities.

Environmental regulation policy is the main means of pollution control and emission reduction and plays an irreplaceable role in environmental governance. However, due to the competitive behavior of economic development, the local government cannot effectively use the efficiency of environmental regulation to reduce the emission of environmental pollution. Taking 284 prefecture-level cities in China from 2005 to 2016 as samples, this paper studies the strategic interaction of environmental regulation enforcement by local governments under different circumstances and its impact on environmental pollution, so as to provide reference for national overall environmental governance planning. Through the research, it is found that the strategic interaction of environmental regulation enforcement among Chinese cities is characterized by the race-to-the-top. And the strategic interaction of environmental regulation enforcement among cities of the same economic level has the strongest impact. Besides, the impact of environmental regulation on environmental pollution has different intensity in different scenarios, showing a non-positive correlation. Most importantly, the Pollution Paradise exists in some cities under special circumstances.

Fear of Virus or of Competitors? The Decision Rationales of Financial Managers Under COVID-19.

This paper surveyed 422 financial managers before the number of novel coronavirus (COVID-19) infections in China peaked and used path analysis to study the risk decision-making mechanisms of financial managers. The study found that whether financial managers developed coping strategies depends on their assessment of potential business revenue losses. There are two transmission paths: the direct effect refers to the risk perception directly caused by COVID-19, while the indirect effect refers to managers' fear that they will not make timely adjustments or will make judgment errors, resulting in the loss of competitive advantage. It is worth noting that the indirect effect exceeds the direct effect, which indicates that financial managers are more rational than ordinary people in dealing with COVID-19, that they are relatively more concerned about competitor changes, and that they may even view COVID-19 as an important opportunity to obtain a better competitive position.

A Nomogram Model Based on Noninvasive Bioindicators to Predict 3-Year Risk of Nonalcoholic Fatty Liver in Nonobese Mainland Chinese: A Prospective Cohort Study.

The purpose of this study is to establish and validate an accurate and personalized nonalcoholic fatty liver disease (NAFLD) prediction model based on the nonobese population in China. This study is a secondary analysis of a prospective study. We included 6,155 nonobese adults without NAFLD at baseline, with a median follow-up of 2.3 years. Univariate and multivariate Cox regression analyses were used to determine independent predictors. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize the selection of variables. Based on the results of multivariate analysis, a prediction model was established. Harrell's consistency index (C-index) and area under the curve (AUC) were used to determine the discrimination of the proposed model. The goodness of fit of the calibration model was tested, and the clinical application value of the model was evaluated by decision curve analysis (DCA). The participants were randomly divided into a training cohort (n = 4,605) and a validation cohort (n = 1,550). Finally, seven of the variables (HDL-c, BMI, GGT, ALT, TB, DBIL, and TG) were included in the prediction model. In the training cohort, the C-index and AUC value of this prediction model were 0.832 (95% confidence interval (CI), 0.820-0.844) and 0.861 (95% CI, 0.849-0.873), respectively. In the validation cohort, the C-index and AUC values of this prediction model were 0.829 (95% CI, 0.806-0.852) and 0.859 (95% CI, 0.841-0.877), respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. DCA demonstrated a clinically effective predictive model. Our nomogram can be used as a simple, reasonable, economical, and widely used tool to predict the 3-year risk of NAFLD in nonobese populations in China, which is helpful for timely intervention and reducing the incidence of NAFLD.