Development and validation of an emergency bloodstream infection score for predicting in-hospital mortality in patients with community-acquired bloodstream infections

BACKGROUND:Community-acquired bloodstream infections(CABSIs)are common in the emergency departments,and some progress to sepsis and even lead to death.However,limited information is available regarding the prediction of patients with high risk of death.METHODS:The Emergency Bloodstream Infection Score(EBS)for CABSIs was developed to visualize the output of a logistic regression model and was validated by the area under the curve(AUC).The Mortality in Emergency Department Sepsis(MEDS),Pitt Bacteremia Score(PBS),Sequential Organ Failure Assessment(SOFA),quick Sequential Organ Failure Assessment(qSOFA),Charlson Comorbidity Index(CCI),and McCabe–Jackson Comorbid Classification(MJCC)for patients with CABSIs were computed to compare them with EBS in terms of the AUC and decision curve analysis(DCA).The net reclassification improvement(NRI)index and integrated discrimination improvement(IDI)index were compared between the SOFA and EBS.RESULTS:A total of 547 patients with CABSIs were included.The AUC(0.853)of the EBS was larger than those of the MEDS,PBS,SOFA,and qSOFA(all P<0.001).The NRI index of EBS in predicting the in-hospital mortality of CABSIs patients was 0.368(P=0.04),and the IDI index was 0.079(P=0.03).DCA showed that when the threshold probability was<0.1,the net benefit of the EBS model was higher than those of the other models.CONCLUSION:The EBS prognostic models were better than the SOFA,qSOFA,MEDS,and PBS models in predicting the in-hospital mortality of patients with CABSIs.

Study on Environmental Risk and Economic Benefits of Rotation Systems in Farmland of Erhai Lake Basin

This study was designed to find out an optimised planting system of reducing non-point （source） pollution by analyzing the reasons and the factors of influence non-point pollution in farmland of Erhai Lake basin. The results showed that incomes, residual nitrogen in soil, and the loss of nitrogen in surface water in rice-garlic system were higher than those in rice-fava bean system. There were positive correlations between the nitrogen loss of farmland, nitrogen inputs, residual nitrogen in soil, and incomes of farmland. Economic benefits and environment benefits are both appropriate, if the area of rice-garlic system would be reduced to 53% and the area of rice-fava bean system increased to 36% of total cropping area in the investigated watershed. Adjustment of planting structure and introduction of reasonable rotation systems is considered an effective measure of controlling agricultural non-point pollution in watersheds of Erhai Lake.

Adaptive economic and ecological forest management under risk

Background： Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape. In addition, the fluctuations of wood prices influence greatly forest revenues. Methods： Markov decision process models （MDPs） offer a rigorous and practical way of developing optimum management strategies, given these multiple sources of risk. Results： Examples illustrate how such management guidelines are obtained with MDPs for combined ecological and economic objectives, including diversity of tree species and size, landscape diversity, old growth preservation, and carbon sequestration. Conclusions： The findings illustrate the power of the MDP approach to deal with risk in forest resource management. They recognize that the future is best viewed in terms of probabilities. Given these probabilities, MDPs tie optimum adaptive actions strictly to the state of the forest and timber prices at decision time. The methods are theoretically rigorous, numerically efficient, and practical for field implementation.

Potential Ecological Risks of Heavy Metals in Soils of Shandong Peninsula Blue Economic Zone

In this research, soil samples were collected from Shandong Peninsula Blue Economic Zone to investigate heavy metal pollutions in this region and to evaluate the potential ecological risks of heavy metal pollutants based on Hakanson Potential Ecological Risk Indexes. According to the results, Hg was the primary heavy metal pollutant in Blue Economic Zone, followed by Cd, Cu, and Pb as prevalent pollutants. Heavy metals ranked in order of their pollution degrees are: Hg>Cd>Cu>Pb>Zn>Cr>As;the potential ecological risks of heavy metals follow the order of Hg>Cd>As>Pb>Cu>Cr>Zn. Heavy metal pollutions did exist in this region to a certain extent, and the percentage of potential ecological risk in “strong” and “severe” degree reached up to 13.75%. This composite risk characteristic was subject to the restriction of Hg and Cd mainly distributed in Laizhou-Zhaoyuan- Yantai, Muping-Rushan Goldmine, and other densely-populated regions, threatening the safety production of crops. The combined effects of geological background and human activities, e.g. gold mining and domestic pollutants, were the main causes of high potential ecological risks of heavy metals in local environment.

Socio-economic status and lifestyle factors are associated with achalasia risk: A population-based case-control study

AIM: To evaluate the association between various lifestyle factors and achalasia risk.METHODS: A population-based case-control study was conducted in Northern Ireland, including n = 151 achalasia cases and n = 117 age- and sexmatched controls. Lifestyle factors were assessed via a face-to-face structured interview. The association between achalasia and lifestyle factors was assessed by unconditional logistic regression, to produce odds ratios(OR) and 95% confidence interval(CI).RESULTS: Individuals who had low-class occupations were at the highest risk of achalasia(OR = 1.88, 95%CI: 1.02-3.45), inferring that high-class occupation holders have a reduced risk of achalasia. A history of foreign travel, a lifestyle factor linked to upper socioeconomic class, was also associated with a reduced risk of achalasia(OR = 0.59, 95%CI: 0.35-0.99). Smoking and alcohol consumption carried significantly reduced risks of achalasia, even after adjustment for socio-economic status. The presence of pets in the house was associated with a two-fold increased risk of achalasia(OR = 2.00, 95%CI: 1.17-3.42). Nochildhood household factors were associated with achalasia risk.CONCLUSION: Achalasia is a disease of inequality, and individuals from low socio-economic backgrounds are at highest risk. This does not appear to be due to corresponding alcohol and smoking behaviours. An observed positive association between pet ownership and achalasia risk suggests an interaction between endotoxin and viral infection exposure in achalasia aetiology.

The Effects of Uncertainty Risks on Consumption of Migrant Workers under the Economic New Normal

Based on the precautionary theory,this paper established a framework for consumption of migrant workers from the perspective of the uncertainty risk,and analyzed the effects of uncertain income risk on consumption of migrant workers using the quantile regression method.Results indicated that the income uncertainty significantly inhibits the consumption of migrant workers. The lower the consumption level or the lower the income level,the stronger the inhibitory effect will be. Uncertainty of expenditure also has a significant inhibitory effect on the consumption of migrant workers. Promoting urbanization of migrant workers and accelerating the reform of the household registration system can reduce the uncertainty risks faced by migrant workers,so as to raise the consumption expectation of migrant workers,release the consumption potential of migrant workers,and improve the living standards of migrant workers.

Global Risk Appetite,US Economic Policy Uncertainties and Cross-Border Capital Flow

Based on the global asset portfolio model,this paper created a panel threshold model using EPFR fund data to empirically test the non-linear spillover effects of US economic policy uncertainties on cross-border capital flow for emerging economies.Our study led to the following findings:(1)When the level of global investor risk tolerance is high,rising US EPU will induce a capital inflow into emerging economies,as manifested in the“portfolio rebalancing effect.”When the level of global investor risk tolerance is below a critical threshold,this gives rise to risk aversion and emerging economies will experience net capital outflow,i.e.the“flight to quality effect”.(2)Equity fund investors have a lower risk tolerance threshold than bond fund investors.(3)According to our heterogeneity analysis,more attention should be paid to monitoring capital flow through actively managed funds,ETF funds,and retail investor funds.The economy should increase financial efficiency and economic resiliency to mitigate capital outflow pressures from the external environment.

China’s Economy in the Advanced Stage of Industrialization:Tendencies and Risks

In 2010, China entered the advanced stage of industrialization, which coincided with the country＇s entry into a new stage of economic growth. However, this transition is associated with major risks, including adapting to decelerating economic growth. While recognizing the move toward a service-based economy, China must seek to prevent the risk of ＂manufacturing hollowing out. ＂＇ It must also avoid the ＂technology upgrade trap＂ while taking advantage of increasingly sophisticated industrial structures. Efforts must also be made to： （1） promote the integration of lT tools and meet risks arising from the New Industrial Revolution; （2） resolve liability risks arising from capacity reduction; and （3） expedite the transition to a functional industrial policy and prevent the failure of a functional industrial policy. In climbing up the global value chain, China must confront the competitive pressures from advanced and emerging economies on both high- and low-end processes of the global value chain.

Economic Risk Assessment of Future Debris Flows by Machine Learning Method

A reliable economic risk map is critical for effective debris-flow mitigation.However,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its application.To estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability map.We selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every year.The debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual susceptibility.We employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate susceptibilities.Simultaneously,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical results.Additionally,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and farmland.The economic loss of elements at risk was calculated based on physical vulnerabilities and their economic values.Therefore,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow channels.In this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on buildings.The results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire risk.These findings can provide a scientific support for the effective mitigation of future debris flows.

Preventing crash in stock market:The role of economic policy uncertainty during COVID‑19

This paper investigates the impact of economic policy uncertainty(EPU)on the crash risk of US stock market during the COVID-19 pandemic.To this end,we use the GARCHS(GARCH with skewness)model to estimate daily skewness as a proxy for the stock market crash risk.The empirical results show the significantly negative correlation between EPU and stock market crash risk,indicating the aggravation of EPU increase the crash risk.Moreover,the negative correlation gets stronger after the global COVID-19 outbreak,which shows the crash risk of the US stock market will be more affected by EPU during the epidemic.

Two-stage stochastic approach for spinning reserve allocation in dynamic economic dispatch

A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation.

Online payment fraud:from anomaly detection to risk management

Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,without producing too many false alarms.This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud.In addition,classical machine learning methods must be extended,minimizing expected financial losses.Finally,fraud can only be combated systematically and economically if the risks and costs in payment channels are known.We define three models that overcome these challenges:machine learning-based fraud detection,economic optimization of machine learning results,and a risk model to predict the risk of fraud while considering countermeasures.The models were tested utilizing real data.Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15%compared to a benchmark consisting of static if-then rules.Optimizing the machine-learning model further reduces the expected losses by 52%.These results hold with a low false positive rate of 0.4%.Thus,the risk framework of the three models is viable from a business and risk perspective.

Clinical characteristics and risk factors of intracranial hemorrhage after spinal surgery

BACKGROUND Intracranial hemorrhage after spinal surgery is a rare and devastating complication.AIM To investigate the economic burden,clinical characteristics,risk factors,and mechanisms of intracranial hemorrhage after spinal surgery.METHODS A retrospective cohort study was conducted from January 1,2015,to December 31,2022.Patients aged≥18 years,who had undergone spinal surgery were included.Intracranial hemorrhage patients were selected after spinal surgery during hospitalization.Based on the type of spinal surgery,patients with intracranial hemorrhage were randomly matched in a 1:5 ratio with control patients without intracranial hemorrhage.The patients'pre-,intra-,and post-operative data and clinical manifestations were recorded.RESULTS A total of 24472 patients underwent spinal surgery.Six patients(3 males and 3 females,average age 71.3 years)developed intracranial hemorrhage after posterior spinal fusion procedures,with an incidence of 0.025%(6/24472).The prevailing type of intracranial hemorrhage was cerebellar hemorrhage.Two patients had a poor clinical outcome.Based on the type of surgery,30 control patients were randomly matched in 1:5 ratio.The intracranial hemorrhage group showed significant differences compared with the control group with regard to age(71.33±7.45 years vs 58.39±8.07 years,P=0.001),previous history of cerebrovascular disease(50%vs 6.7%,P=0.024),spinal dura mater injury(50%vs 3.3%,P=0.010),hospital expenses(RMB 242119.1±87610.0 vs RMB 96290.7±32029.9,P=0.009),and discharge activity daily living score(40.00±25.88 vs 75.40±18.29,P=0.019).CONCLUSION The incidence of intracranial hemorrhage after spinal surgery was extremely low,with poor clinical outcomes.Patient age,previous stroke history,and dura mater damage were possible risk factors.It is suggested that spinal dura mater injury should be avoided during surgery in high-risk patients.

Assessment of the Vulnerability of the Southwestern Coast of Benin to the Risk of Coastal Erosion and Flooding

The coastal zone of Benin is inherited from the last marine oscillations of the Quaternary. A rich and very fragile environment, it presented until the 1960s, a shoreline in dynamic equilibrium over the entire 125 km of coastal line. Since the 1960s, with the construction of important development infrastructures (ports, dams, groins), the Beninese coast is now subject to risks of coastal erosion and seasonal flooding due to the overflow of lagoon water bodies. The present study, based on socio-economic surveys in the communes of Ouidah, Comè and Grand Popo, exposes the extent of coastal risks and socio-economic and environmental damage in the southwestern coastal zone of Benin. The results show that in terms of land, 2.9 ha and 5.7 ha of land have been permanently lost to coastal erosion in the communes of Ouidah and Grand Popo respectively. Similarly, 212 ha of crops of all types were affected by the flooding, including 35 ha destroyed, i.e. 6.67 ha, 11.3 ha in Comè, 4.67 ha Ouidah and 14 ha Grand Popo. Also, 6435 buildings were affected, and 4235 huts were damaged. In addition, working tools, food stocks and other items are counted among the losses recorded by coastal hazards with their corollaries of diseases. The cost of losses and damages in the 08 districts amount to 418,000,000f cfa of which 266,000,000f cfa of damage and 152,000,000f cfa of loss.

不确定性中的确定性--中国经济风险识别

为了揭示不确定性冲击下中国经济风险的确定性规律,本文基于预期经济增速分布,将不确定性与经济增长纳入“在险增长”的统一框架,以刻画经济不确定性与金融不确定性对经济风险的异质性影响。研究发现:不确定性冲击下的经济风险具有明显的确定性特征,伴随着不确定性升高,经济下行风险显著增加,经济上行风险较为稳定;当不确定性较低时,经济增速的潜在波动空间相对狭小,当不确定性较高时,经济增速具有较大的波动空间;不确定性与经济增长之间存在“双向反馈”的溢出循环机制,能够加剧不确定性的实际冲击效应;经济不确定性与金融不确定性对经济风险具有明显的异质性影响,无论是就冲击强度还是持续周期而言,经济不确定性的影响均更为显著。

我国企业ESG表现对其经济效益的影响研究——基于沪深上市企业

随着“碳达峰、碳中和”战略目标的提出,ESG投资概念成为资本市场关注的重点。在ESG信息披露成为企业刚需的时代背景下,企业环境表现与环境信息披露之间的因果关系变得更为复杂,ESG信息披露行为对企业经济效益的影响也有待讨论。为此,本文根据数据可得性筛选得到2008—2020年我国沪深板块上市的3685家企业上市公司作为研究样本,利用wind数据库、CSMAR上市公司环境研究等数据库,从企业ESG信息披露完整性及实际风险两个维度出发构建ESG发展指数,用于全面测度中国企业的ESG发展现状;同时尝试从债权人和股东投资信心等层面探讨企业ESG表现对其经济效益的传导机理。结果表明:企业ESG表现对于其经济效益呈现正向显著影响,且这种影响效应对于不同ESG表现水平和不同产权性质的企业具有异质性。影响路径分析结果显示,企业ESG表现能够提升投资者信心,进而显著改善了企业经济效益。

中国企业RCEP经贸合规与风险应对

RCEP协议的签署,为我国对外贸易和国际投资提供了更广阔的平台,为国内消费提供了种类更丰富、价格更优惠的进口产品。但与此同时,中国外贸企业面临的RCEP合规风险日趋复杂,也为企业开展合规工作带来了新的挑战。针对这一问题,政府方面需要加强政策支持、建立外经贸企业合规经营指数指标体系。企业也要主动作为,谋全局,谋长远,全面提升企业合规能力,在政府和企业同时发力中增强应对合规风险的能力。

数字经济时代区域经济下行风险防范与应对:基于GaR模型的实证分析

防范化解重大经济金融风险是保障我国经济高质量发展的关键,数字经济发展为积极应对经济下行压力、快速转换经济增长动力、统筹兼顾“稳增长”与“防风险”提供了新的契机。基于内生增长理论模型和“在险增长”(GaR)实证研究框架,演绎了数字经济发展的理论机理,使用我国2011-2022年期间226个地级市的季度数据测度了区域经济下行风险,实证考察了数字经济发展对区域经济下行风险的作用效果。结论表明:数字经济发展能够有力防范区域经济下行风险;通过促进产业转型升级、挖掘城市市场潜力、激活乡村消费活力以及增强大众创业动力,数字经济能够发挥资本渗透与技术溢出的间接效应。进一步分析表明,数字经济在缺乏区位优势、经济基础较弱的城市作用效果并不显著,加快数字基础设施建设能够调节风险防范效应的空间异质性。研究结果对研判宏观经济增长不确定性、加快发展新质生产力、推动经济实现质的有效提升和量的合理增长具有重要意义。

德国综合安全观:理论缘起、历史演进与实践评估

德国首份《国家安全战略》以“综合安全”为要义,具有理论逻辑和历史脉络可循。德国综合安全观兴起于冷战后,其内在逻辑是对欧洲主义安全观的继承性发展,聚焦两极秩序瓦解后的经济与社会秩序稳定以及应对域外冲突,注重非传统安全,安全参与者包含国家与非国家行为体。克里米亚危机后,传统军事威胁回归欧陆,德国综合安全观“防御性”与“韧性”融合并重。俄乌冲突冲击欧洲安全秩序,德国综合安全观愈发重视国家与联盟防御,并通过“多元化”与“联盟政治”等手段推进“去风险”策略,增强经济与社会韧性,同时也呈现出泛安全化、价值观化与权力政治的特质,其影响力辐射至“印太”地区与对华政策上。然而,德国综合安全政策实践仍面临诸多挑战。防御上,德国提升国防的政治承诺与其军事资源尚不匹配。韧性上,德国“去风险”策略受国际权力对比变化、中国市场红利、德国政界与商界意见的异质性以及德国国内经济成本的制约。为此,中国应客观看待德国安全政策转型的影响。

董事网络位置对企业风险承担的影响研究——来自中国上市公司的经验证据

风险承担是企业实现持续发展的重要因素。基于社会网络视角,本文运用中国A股上市公司2011~2022年的样本数据,实证研究了董事网络位置对企业风险承担的影响及其作用机理。结果表明:董事网络中心度显著提升了企业风险承担水平,结构洞对企业风险承担起到显著的抑制作用。知识溢出在董事网络中心度以及结构洞对企业风险承担的影响中均发挥遮掩效应;进一步研究发现,经济政策不确定性正向调节董事网络位置对企业风险承担水平的影响。基于研究结论,企业应该合理构建董事网络关系;优化董事网络结构,适度获取外部知识,提升决策质量。