Association between composite dietary antioxidant index and stroke among individuals with diabetes

BACKGROUND Recent research has underscored the potentially protective role of dietary antioxidants against chronic conditions,such as cardiovascular diseases and stroke.The composite dietary antioxidant index(CDAI),which reflects the overall intake of key dietary antioxidants,has been identified as a crucial metric for exploring this relationship.Although previous research has shown a negative correlation between CDAI levels and stroke risk in prediabetic individuals,there remains a substantial gap in understanding this association among individuals with diabetes,who are at an inherently greater risk for cerebrovascular events.AIM To investigate the association between CDAI and stroke risk in individuals with diabetes.METHODS Using a cross-sectional study design,this investigation analyzed data from the National Health and Nutrition Examination Survey spanning from 2003 to 2018 that included 6735 participants aged over 20 years with diabetes.The CDAI was calculated from 24-h dietary recalls to assess intake of key antioxidants:Vitamins A,C,and E;carotenoids;selenium;and zinc.Multivariate logistic regression and restricted cubic spline analysis were used to rigorously examine the relationship between CDAI and stroke risk.RESULTS The participant cohort,with an average age of 59.5 years and a slight male majority,reflected the broader demographic characteristics of individuals with diabetes.The analysis revealed a strong inverse relationship between CDAI levels and stroke risk.Remarkably,those in the highest quintile of CDAI demonstrated a 43%lower prevalence of stroke compared to those in the lowest quintile,even after adjustments for various confounders.This finding not only highlights the negative association between CDAI and stroke risk but also underscores the significant potential of antioxidant-rich diets in reducing stroke prevalence among patients with diabetes.CONCLUSION Our findings suggested that CDAI was inversely associated with stroke prevalence among patients with diabetes.These results suggest incorporating antioxidant-rich foods into dietary regimens as a potential strategy for stroke prevention.

Combined Pollution and Pollution Index of Heavy Metals in Red Soil

A field experiment was conducted to study the effects of Pb, Cd, Cu, Zn and As coexisting in red soilon growth of rice (Oryza sativa L.), mung bean (Vigna rabiata (Linn.) Wilczek), alfalfa (Medicago sativaL.), slash pine (Pinus elliottii Engelm.) and aspen (Populus L.). Results showed that rice, mung bean andalfalfa were significantly innuenced by combined pollution of the heavy metals. The contents of Pb, cd andAs in rice grains greatly exceeded the National Standards for Food Hygiene of China. Heavy metals at ahigh concentration seriously retarded growth of mung bean and alfalfa, but not so obviously with slash pineand aspen. The composite index is suggested for evaluating the relativity of combined pollution witll heavymetals in soil.

Drillability prediction in some metamorphic rocks using composite penetration rate index(CPRI)–An approach

Assessment of drillability of rocks is vital in the selection,operation,and performance evaluation of cutting tools used in various excavation machinery deployed in mining and tunneling.The commonly used rock drillability prediction methods,namely,drilling rate index(DRI)and Cerchar hardness index(CHI)have limitations in predicting the penetration rate due to differential wear of the cutting tool in rocks with varied hardness and abrasivity.Since cutting tools get blunt differently in different rocks,the stress beneath the tip of the bit decreases until it reaches a threshold value beyond which the penetration rate becomes constant.In this research,a new composite penetration rate index(CPRI)is suggested based on the investigations on four metamorphic rocks viz.quartzite,gneiss,schist and phyllite with varied hardness-abrasivity values.The penetration-time behavior was classified into active,moderate,passive,and dormant phases based on the reduction in penetration rate at different stages of drilling.A comparison of predicted penetration rate values using DRI and CPRI with actual penetration rate values clearly establishes the supremacy of CPRI.Micro-structure and hardness-based index was also developed and correlated with CPRI.The new indices can help predict cutting tool penetration and its consumption more accurately.

The Changes in World Oil Prices, Monetary Factors, and Foreign Index Toward Composite Index Movement： Indonesian Case for the Period of 2005-2011

Capital market is one of the drivers of the economy through the formation of capital investor excess as well as an indicator of a country＇s economy. Movement of stock price index is often influenced by many factors, derived from the company＇s performance, monetary factor, and changes in world oil prices. This study highlights the problem in world oil prices due to political turmoil in the Middle East. The samples are taken from the Jakarta Composite Stock Price Index （JCI）, oil prices, Indonesian inflation rate, Certificate of Bank Indonesia＇s （CBI） rate, and the reserve assets, during the period from January 2005 to December 2011 （84 months）. Using the data published by the Bank of Indonesia, reports of the Central Bureau of Statistics （Biro Pusat Statistik, BPS）, and other relevant sources, the data analyzed through the Eviews 7.1. The main objective of this study is to examine the effect of oil prices, foreign stock price index, and monetary variables （inflation rate, CBI rate, country＇s foreign reserves, and others） toward the JCI analyzed through the error correction model （ECM）. Hypothesis testing with the F-test for the 95% confidence level indicates that the oil price, exchange rate （Indonesian Rupiah （IDR）/United States Dollar （USD））, CBI rate, foreign exchange reserves, the Dow Jones Index, and the Taiwan stock index, both simultaneously as well as partially have a significant influence on the JCI.

Assessing fire severity in Turkey's forest ecosystems using spectral indices from satellite images

Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.

VisCI:A visualization framework for anomaly detection and interactive optimization of composite index

Composite index is always derived with the weighted aggregation of hierarchical components,which is widely utilized to distill intricate and multidimensional matters in economic and business statistics.However,the composite indices always present inevitable anomalies at different levels oriented from the calculation and expression processes of hierarchical components,thereby impairing the precise depiction of specific economic issues.In this paper,we propose VisCI,a visualization framework for anomaly detection and interactive optimization of composite index.First,LSTM-AE model is performed to detect anomalies from the lower level to the higher level of the composite index.Then,a comprehensive array of visual cues is designed to visualize anomalies,such as hierarchy and anomaly visualization.In addition,an interactive operation is provided to ensure accurate and efficient index optimization,mitigating the adverse impact of anomalies on index calculation and representation.Finally,we implement a visualization framework with interactive interfaces,facilitating both anomaly detection and intuitive composite index optimization.Case studies based on real-world datasets and expert interviews are conducted to demonstrate the effectiveness of our VisCI in commodity index anomaly exploration and anomaly optimization.

Analyses of Political Crisis Impact on Tourism:A Panel Counterfactual Approach with Internet Search Index

Existing research has shown that political crisis events can directly impact the tourism industry.However,the current methods suffer from potential changes of unobserved variables,which poses challenges for a reliable evaluation of the political crisis impacts.This paper proposes a panel counterfactual approach with Internet search index,which can quantitatively capture the change of crisis impacts across time and disentangle the effect of the event of interest from the rest.It also provides a tool to examine potential channels through which the crisis may affect tourist outflows.This research empirically applies the framework to analyze the THAAD event on tourist flows from the Chinese Mainland to South Korea.Findings highlight the strong and negative short-term impact of the political crisis on the tourists' intentions to visit a place.This paper provides essential evidence to help decision-makers improve the management of the tourism crisis.

Surgical approach affecting long-term urinary continence status after robot-assisted laparoscopic prostatectomy prospectively evaluated using self-reported functional status(Expanded Prostate Cancer Index Composite,EPIC-26)

Purpose:The aim of the study was to examine the influence of the surgical approach for robot-assisted laparoscopic prostatectomy(RALP)on long-term urinary continence status in the era of self-reported functional status measures using the Expanded Prostate Cancer Index Composite 26.Materials and methods:This is a prospective evaluation of 232 patients undergoing RALP between September,2019 and September,2020.Urinary continence status and postoperative incontinence(pad usage)were evaluated 12 months after RALP using Expanded Prostate Cancer Index Composite 26 questionnaires.Patients were categorized according to their surgical approach and outcome into the following groups:successful nerve sparing(NS),primarily without nerve sparing(prim.NNS),and no nerve sparing by secondary resection(NNS by SR).The median levels of their questionnaire outcomes were evaluated and compared using the Wilcoxon rank sum test with continuity correction.Results:Urinary continence status 12 months after RALP differed significantly between the NS and prim.NNS(p=0.0071)and the NS and NNS by SR(p=0.0076)groups.There was no significant difference between the prim.NNS and NNS by SR(p=0.53)groups.Pad usage 12 months after RALP had no significant difference with regard to SR of the neurovascular bundle(p=0.14).Conclusions:Patient-reported outcomes of long-term urinary continence status seem to show no difference in postoperative continence,regardless of whether a non-nerve-sparing result was planned or reached through SR.Instead,preservation of neurovascular bundle seems to lead to better long-term continence rates.

Atmospheric Deposition-Carried Pb, Zn, and Cd from a Zinc Smelter and Their Effect on Soil Microorganisms

Dust emissions from smelters, as a major contributor to heavy metal contamination in soils, could severely influence soil quality. Downwind surface soils within 1.5 km of a zinc smelter, which was active for 10 years but ceased in 2000, in Magu Town, Cuizhou Province, China were selected to examine Pb, Zn, and Cd concentrations and their fractionation along a distance gradient from a zinc smelter, and to study the possible effects of Pb, Zn, and Cd accumulation on soil microorganisms by comparing with a reference soil located at a downwind distance of 10 km from the zinc smelter. Soils within 1.5 km of the zinc smelter accumulated high levels of heavy metals Zn （508 mg kg^-1）, Pb （95.6 mg kg^-1）, and Cd （5.98 mg kg^-1） with low ratios of Zn/Cd （59.1-115） and Pb/Cd （12.4-23.4）. Composite pollution indices （CPIs） of surface soils （2.52-15.2） were 3 to 13 times higher than the reference soils. In metal accumulated soils, exchangeable plus carbonate-bound fractions accounted for more than 10% of the total Zn, Pb, and Cd. The saturation degree of metals （SDM） in soils within 1.5 km of the smelter （averaging 1.25） was six times higher than that of the reference soils （0.209）. A smaller soil microbial biomass was found more frequently in metal accumulated soils （85.1-438 μg C g^-1） than in reference soils （497 μg C g^-1）, and a negative correlation （P 〈 0.01） of soil microbial biomass carbon to organic carbon ratio （Cmic/Corg） with SDM was observed. Microbial consumption of carbon sources was more rapid in contaminated soils than in reference soils, and a shift in the substrate utilization pattern was apparent and was negatively correlated with SDM （R = -0.773, P 〈 0.01）. Consequently, dust deposited Pb, Zn, and Cd in soils from zinc smelting were readily mobilized, and were detrimental to soil quality mainly in respect of microbial biomass .

Relationship between Environmental Pollution of Coal Mine and Spectral Characteristics of Nearby Plants

Remote sensing technology, as the most advanced method for collecting data, along with the common ways often used in the past on research of environmental science, was integrated to study the relationship between environmental pollution of coal mine and spectral characteristics of nearby plants. With compositive index and mean reflectivity at near infrared, a regression equation was established, and a conclusion was made that spectral reflectivity can be used to distinguish regions with different pollution degree. Through testing with real status of the research region, it is verified that this kind of integration and conclusion not only are helpful for human being in controlling the movement law of pollutants and the corresponding change of coal mine environmental quality but also bring a new way for the research of environment problems of coal mine.

Study on the Urbanization Process of Kunming City and Its Impact on the Water Environment of Dianchi Lake

[ Objective] We aimed to analyze the urbanization process of Kunming City and its impact on the water environment of Dianchi Lake. [ Method ] Using the Analytic Hierarchy Process （AHP）, we assessed the urbanization leve of Kunming in 1998 -2008 based on composite indicator evaluation system. Afterwards, we calculated water pollution composite index of Dianchi Lake and introduced the EKC to set up a coupling relation- ship model between the urbanization level and water environment quality. [ Result] During 1998 -2008, the urbanization level of Kunming increased gradually, that is, it was lower than 30.0% before 2002, with slow growth; at the later stage, it grew fast, and reached 75.0% in 2008. Water pol- lution composite index of Dianchi Lake showed that Dianchi Lake was polluted seriously, especially Caohai. From the EKC, we can see that the re- lationship curves between the urbanization level of Kunming and water pollution composite index of Dianchi Lake were akin to inversed U shapes and still at an antagonistic stage at present. [ Condusion] The research could provide scientific references for discussing the relationship between urban- ization process and water environment.

Volatility Spillover Effect of the International Crude Oil Futures Price on Composite and Sector Indices between the Chinese and Australian Stock Markets

As a type of non-renewable industrial resource,petroleum is of great strategic significance to the development of each nation.Ever since the 19th century,an array of oil crises have incurred certain downturn of the world economy.Pertinent studies have implied that financial crisis is always prone to be accompanied with oil crisis,yet the relevance of crude oil to the stock market,the barometer of the macro-economy,is ambiguous.In order to avoid the risks induced by the volatility of oil price,the oil futures market has appeared,and at the same time,the financial property of crude oil has become far more evident.Owing to lack of mature mining and refining technology,China still imports large amounts of oil from abroad at present.Thus,the economy of China is susceptible to fluctuation in petroleum price.As for Australia,the only net importer among the member countries of the International Energy Agency(IEA),it fails to attain the target of holding 90 days of fuel reserves set by the agency.However,in 2013,Australian Lincoln Energy announced that a gigantic shale oil field with an estimated value of 21 trillion US dollars was found in the South of Australia,and that if that field is mined,Australia has the possibility to turn into a net exporter of crude oil.It can be expected that the Australia’s economic conditions would be closely related to the international oil to a certain extent.Based on the approaches of the first difference and co-integration,this paper delves into the volatility spillover effect of crude oil futures on the Chinese and Australian stock markets.According to the empirical findings,in the short run,the price of crude oil futures has a greater impact on the Australian composite index than on the Chinese composite index.However,crude oil futures are negatively related to the Chinese composite index in the long run.The price of crude oil futures has no significant impact on the Chinese sector indices,but it has a certain impact on the Australian utilities,energy,materials,and industrial sector indices.In the Chinese stock market,the movement of short-run effect to long-run effect of crude oil futures on sector indices is in the reverse direction.Finally,the price of crude oil futures has a significant volatility spillover effect only on the Australian utilities sector index.

ESTIMATING MULTI-COUNTRY PROSPERITY INDEX: A TWO-DIMENSIONAL SINGULAR SPECTRUM ANALYSIS APPROACH

With the development of the global economy, interaction among different economic entities from one region is intensifying, which makes it significant to consider such interaction when constructing composite index for each country from one region. Recent advances in signal extraction and time series analysis have made such consideration feasible and practical. Singular spectrum analysis （SSA） is a well-developed technique for time series analysis and proven to be a powerful tool for signal extraction. The present study aims to introduce the usage of the SSA technique for multi-country business cycle analysis. The multivariate SSA （MSSA） is employed to construct a model-based composite index and the two dimensional SSA （2D-SSA） is employed to establish the multi-country composite index. Empirical results performed on Chinese economy demonstrate the accuracy and stability of MSSA-based composite index, and the 2D-SSA based composite indices for Asian countries confirm the efficiency of the technique in capturing the interaction among different countries.

Extracting urban areas in China using DMSP/OLS nighttime light data integrated with biophysical composition information

DMSP/OLS nighttime light （NTL） image is a widely used data source for urbaniza- tion studies. Although OLS NTL data are able to map nighttime luminosity, the identification accuracy of distribution of urban areas （UAD） is limited by the overestimation of the lit areas resulting from the coarse spatial resolution. In view of geographical condition, we integrate NTL with Biophysical Composition Index （BCl） and propose a new spectral index, the BCl Assisted NTL Index （BANI） to capture UAD. Comparisons between BANI approach and NDVl-assisted SVM classification are carried out using UAD extracted from Landsat TM/ETM＋ data as reference. Results show that BANI is capable of improving the accuracy of UAD extraction using NTL data. The average overall accuracy （OA） and Kappa coefficient of sample cities increased from 88.53% to 95.10% and from 0.56 to 0.84, respectively. Moreover with regard to cities with more mixed land covers, the accuracy of extraction results is high and the improvement is obvious. For other cities, the accuracy also increased to varying de- grees. Hence, BANI approach could achieve better UAD extraction results compared with NDVl-assisted SVM method, suggesting that the proposed method is a reliable alternative method for a large-scale urbanization study in China＇s mainland.

Spatial Analysis on Content Distribution of Soil Heavy Metals Copper (Cu) and Cadmium (Cd) in Duanzhou District of Zhaoqing City

This paper used atomic absorption spectrophotometry to determine the content distribution of Cu and Cd in the soil of Duanzhou District,Zhaoqing City.The single factor index method,Nemerow comprehensive index method,pollution load index method,geoaccumulation index method,and potential ecological hazard index method were used to analyze the content and pollution status of Cu and Cd in the soil of Duanzhou District,providing a basis for understanding the pollution status of Cu and Cd in the soil of Zhaoqing City.

Demonstration Study on the Intrinsic Characteristic of Stock Complex Index on Shanghai Security Market

This paper takes the Shanghai Security market stock composite index as the research object, analyzes its intrinsic fractal essence characteristics by the application of fractal theory and the method, and computes the Hurst index, fractal dimension and correlated function of the highest prices of the complex index. Moreover, it studies characteristics of long term memory of the sample data and its variance along with time; study existence of chaotic attractors in data of the complex index by reconstructing the phase space of the index data. Finally, this paper carries on the related forecast demonstration study to the stock composite index. Results of the study have certain reference function to the actual problem.

Evaluation and Driving Force Analysis of Marine Sustainable Development based on the Grey Relational Model and Path Analysis

With the rapid development of the marine economy,the demand for marine resources development and the pressure on marine environmental protection are gradually increasing.It is critical to evaluate and analyze the driving forces of marine sustainable development in order to promote the coordinated development of the marine economy,resources and environment.Taking Jiangsu Province of China as an example,this paper constructs an evaluation index system for marine sustainable development from the three aspects of marine economy,resources and environment,and calculates the weight of the variation coefficient for each indicator.Based on the grey relational model,the average value of the relational degree,calculated by the average value method of correlation coefficients and the weighting method,is then used to evaluate the status of marine sustainable development in this province.The comprehensive index model is used to analyze the dynamic trend of the evolution of marine sustainable development.The driving forces of marine sustainable development are analyzed by the path analysis method combined with the average values of the grey relational degree for each indicator.This analysis found that the marine sustainable development in 2016 and 2012 was good,the situation in 2007 was bad,and the remaining years were intermediate.Compared with the previous years,the optimal conditions of 2008 and 2012 were obvious.The main driving factors of marine sustainable development are cargo throughput of coastal ports,economic losses caused by storm surges in coastal areas,the area of marine nature reserves in coastal areas,coastal wind power generation capacity,and marine biodiversity.

Quantifying human well-being for sustainability research and policy

To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental barrier is the lack of quantitative indicators and models that integrate HWB with direct and indirect drivers of change in natural resources.While primary surveys provide the most valid HWB measures,extensive new data collection is often costly,especially for large-scale studies.Therefore,it is vital to develop methods and indices based on existing data(e.g.,census data,survey data)for real-world application.To address this,we propose a new method of using structural equation modeling to construct robust,spatially explicit HWB indices from existing data and demonstrate its validity and usefulness in Cambodia.Our method is scale-free and applicable to different frameworks and data sources and thus supports relatively easy replication in many other contexts.Further application and refinement could improve understanding of human-nature interactions,move toward robust theory development,and guide natural resource management decisions.

Foreign Trade Survey Data:Do They Help in Forecasting Exports and Imports?

Business survey,which starts from the microeconomic level,is a widely used short-term forecasting tool in practice.In this study,the authors examine whether foreign trade survey data collected by China’s Ministry of Commerce would provide reliable forecasts of China’s foreign trade.The research procedure is designed from three perspectives including forecast information test,turning point forecast,and out-of-sample value forecast.First,Granger causality test detects whether survey data lead exports and imports.Second,business cycle analysis,a non-model based method,is performed.The authors construct composite indexes with business survey data to forecast turning points of foreign trade.Third,model-based numerical forecasting methods,including the Autoregressive Integrated Moving Average Model with Exogenous Variables(ARIMAX)and the artificial neural networks(ANNs)models are estimated.Empirical results show that survey data granger cause imports and exports,the leading composite index provides signal for changes of trade cycles,and quantitative models including survey data generate more accurate forecasts than benchmark models.It is concluded that trade survey data has excellent predictive capabilities for imports and exports,which can offer some priorities for government policy-making and enterprise decision making.

Role of Intraseasonal Oscillation in a Compound Drought and Heat Event over the Middle of the Yangtze River Basin during Midsummer 2018

In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be linked with intraseasonal oscillations(ISOs) from different regions. However, specific roles of different ISOs on the development of the CDHE cannot be separated in the observational analysis. By using partial lateral forcing experiments driven by ISO in the Weather Research and Forecasting(WRF) model, we found that the midlatitude ISO generated by a westerly wave train in the upper troposphere played an important role in this heatwave and drought event in the northern MYRB, causing a regional average temperature rise of 1.65°C and intensification of drought over23.49% of the MYRB area. On the other hand, the ISO associated with the Pacific-Japan(PJ)-like teleconnection wave train in the lower troposphere induced a more pronounced impact on the event, causing an average temperature rise of 2.44°C, intensifying drought over 29.62% of the MYRB area. The MYRB was mainly affected by northward warm advection driven by the westward extension of the western North Pacific subtropical high in the early period of the CDHE development. In the late period, because of the establishment of a deep positive geopotential height field through the troposphere leading to intensive local subsidence, there was a remarkable temperature rise and moisture decrease in the MYRB. The results will facilitate a better understanding of the occurrence of CDHE and provide empirical precursory signals for subseasonal forecast of CDHE.