Modified Observation Model in Tightly-Coupled INS/GPS Integration

The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.

Experimental Study on In-situ Leaching and Electrokinetic Remediation of Composite Heavy Metal-contaminated Soil

[Objectives] This study was conducted to investigate in-situ leaching and electrokinetic combined remediation of composite heavy metal-contaminated soil.[Methods] Leaching and electrokientic combined remediation was applied to remediate artificially-simulated composite Cd,Cu,Pb,and Zn-contaminated soil.The electrokinentic remediation of the soil was carried out using EDTA and acetic acid as the eluents with electrodes placed on the top and bottom of the soil,to investigate the effects of different types and concentrations of eluents,reaction time and energization methods on the remediation.[Results]Applying electrodynamic force to the leaching remediation process achieved good removal effects of Cd,Cu,Pb,and Zn in the soil.Compared with pure leaching,the leaching and electrokinetic combined remediation saved 23.8% of EDTA consumption.EDTA showed the ability to complex heavy metals better than acetic acid,and after 10 d of reaction,the 0.1 mol/L EDTA achieved very good removal effects on Cd,Cu,Pb,and Zn from the upper and middle layers of the soil column,exhibiting removal rates of 94.4%,93.3%,91.4% and 92.8% in the upper layer and 87.2%,88.2%,83.3% and 84.6%,respectively.Compared with the conventional experiments,the intermittent energization method and the voltage-increasing method improved the removal rates of Cd,Cu,Pb and Zn by 6.3%,6.1%,5.9%and 6%,and 0.6%,0.9%,0.5% and 0.4%,respectively,and saved 46.8% and 10.3% of energy consumption,respectively.[Conclusions]The study provides reference for the remediation of composite heavy metal-contaminated soil.

Discussion on Preparation and Application of BiOIO_(3)-based Composite Materials

BiOIO3 is a layered semiconductor photocatalyst,which has good chemical properties and has attracted wide attention from researchers because of its unique structure.However,pure BiOIO3 has defects such as insufficient response to visible light and easy recombination of photogenerated electrons.Therefore,in recent years,scholars have tried to modify BiOIO3 to expand its light absorption range,reduce the recombination of photogenerated electron-hole pairs and reduce its limitations,thereby improving its visible light catalytic performance.Current researches focus on the improvement of the catalytic activity of photocatalytic materials from morphology control,precious metal deposition,ion doping and construction of heterojunctions.

Electrokinetics-magnetic/alkali Composite-modified Biochar for Remediation of Cd-contaminated soil

[Objectives]This study was conducted to explore the removal performance and mechanism of heavy metal Cd in soil by combining electrokinetic technology and modified biochar.[Methods]The electrokinetics-magnetic/alkali composite-modified biochar method was applied to remediate Cd-contaminated soil.[Results]When remediating the soil for 120 h under electric field strength of 2 V/cm with 0.1 mol/L citric acid as the electrolyte,the current periodically varied with the remediation time.Cd^2+in the soil dissociated and migrated from the soil surface,and the addition of the magnetic/alkali composite-modified biochar in the cathode area affected the hydrolysis balance of heavy metal Cd^2+ions and maintained soil pH in a low range.The exchangeable Cd content at the test sampling points near the cathode area was relatively high,and the organic Cd area was evenly distributed.The average removal rate of Cd in the soil was up to 90.31%.The hexagonal anode device configuration enhanced the electromigration performance and made the soil pH and conductivity change within a certain range,which was beneficial to the migration of Cd2+and improved the removal rate of soil heavy metal Cd.[Conclusions]This study provides a theoretical basis for the treatment of soil heavy metal pollution and the resource utilization of composite-modified biochar.

区域土壤环境质量类生命体演化树理论及方法

Soil environmental quality(SEQ)refers to the soil's suitability within a definite period and spacial boundary and its adaptability to environmental factors.It serves as a measure of environmental conditions relevant to soil fertility,environmental quality,and health[1,2].However,due to human activities such as industrialization,urbanization,and agriculture,SEQ worldwide is threatened by physical,chemical,and biological characteristics.

Associations Between Air Temperature and Daily Varicella Cases—Jinan City,Shandong Province,China,2019–2021

What is already known about this topic?The impact of air temperature on varicella has been studied,but there is limited research exploring its effect on varicella by gender and age group.What is added by this report?We conducted a time series analysis to examine the differential effects of air temperature on varicella infection across different demographic groups.Our findings indicate that lower temperatures have a more pronounced influence on varicella incidence among males and children compared to females and adults.What are the implications for public health practice?These findings can assist in identifying populations that are vulnerable to temperature-related varicella and in guiding the implementation of effective measures for varicella control.

Spatial Dynamics of Chickenpox Outbreaks in Rapidly Developing Regions:Implications for Global Public Health

Objective The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to children.However,certain factors influencing local chickenpox outbreaks have not been studied.Here,we examined the relationship between spatial clustering,heterogeneity of chickenpox outbreaks,and socioeconomic factors in Southern China.Methods We assessed chickenpox outbreak data from Southern China between 2006 and 2021,comprising both relatively fast-growing parts and slower sub-regions,and provides a representative sample of many developing regions.We analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran’s I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q statistics.Results There were significant spatial heterogeneity in the risk of chickenpox outbreaks,with strong correlations between chickenpox risk and various factors,particularly demographics and living environment.Furthermore,interactive effects among specific are factors,such as population density and per capita residential building area,percentage of households with toilets,percentage of rental housing,exhibited q statistics of 0.28,0.25,and 0.24,respectively.Conclusion This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions,revealing the socioeconomic factors affecting disease transmission.These implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts.

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual(LSR)algorithm is commonly used in the Receiver Autonomous Integrity Monitoring(RAIM).However,LSR algorithm presents high Missed Detection Risk(MDR)caused by a large-slope faulty satellite and high False Alert Risk(FAR)caused by a small-slope faulty satellite.In this paper,the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite.Based on the analysis of the vertical critical slope,the optimal decentralized factor is defined and the optimal test statistic is conceived,which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions.To construct a new test statistic approximating to the optimal test statistic,the Optimal Decentralized Factor weighted LSR(ODF-LSR)algorithm is proposed.The new test statistic maintains the sum of pseudo-range residual squares,but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor.The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists,and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists.The performance of the ODFLSR algorithm is demonstrated by simulation experiments.

Natural and Socioeconomic Factors and Their Interactive Effects on House Collapse Caused by Typhoon Mangkhut

Typhoons are an environmental threat that mainly affects coastal regions worldwide.The interactive effects of natural and socioeconomic factors on the losses caused by typhoon disasters need further examination.In this study,GeoDetector was used to quantify the determinant powers of natural and socioeconomic factors and their interactive effects on the rate of house collapse in Guangdong and Guangxi Provinces of southeast China caused by Typhoon Mangkhut in 2018.We further identify the dominant factors that influenced the disaster losses.The local indicators of spatial association method was then introduced to explain the spatial heterogeneity of the disaster losses under the influence of the dominant factor.The results indicate that both natural and socioeconomic factors significantly affected the house collapse rate.The maximum precipitation was the dominant factor,with a q value of 0.21,followed by slope and elevation,with q values of 0.17 and 0.13,respectively.Population density and per capita gross domestic product had q values of 0.15 and0.13,respectively.Among all of the interactive effects of the influencing factors,the interactive effect of elevation and the ratio of brick-wood houses had the greatest influence(q=0.63)on the house collapse rate.These results can contribute to the formulation of more specific safety and property protection policies.

Spatial-temporal heterogeneity and determinants of HIV prevalence in the Mano River Union countries

Background:Utilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa.However,the situation in the Mano River Union(MRU)countries is largely unknown.This research aims to perform an ecological study to determine the HIV prevalence patterns in MRU.Methods:We analyzed Demographic and Health Survey(DHS)and AIDS Indicator Survey(AIS)data on HIV prevalence in MRU from 2005 to 2020.We examined the country-specifc,regional-specifc and sex-specifc ratios of respondents to profle the spatial–temporal heterogeneity of HIV prevalence and determine HIV hot spots.We employed Geodetector to measure the spatial stratifed heterogeneity(SSH)of HIV prevalence for adult women and men.We assessed the comprehensive correct knowledge(CCK)about HIV/AIDS and HIV testing uptake by employing the Least Absolute Shrinkage and Selection Operator(LASSO)regression to predict which combinations of CCKs can scale up the ratio of HIV testing uptake with sex-specifc needs.Results:In our analysis,we leveraged data for 158,408 respondents from 11 surveys in the MRU.From 2005–2015,Cote d’Ivoire was the hot spot for HIV prevalence with a Gi_Bin score of 3,Z-Score 8.0–10.1 and P<0.001.From 2016 to 2020,Guinea and Sierra Leone were hot spots for HIV prevalence with a Gi_Bin score of 2,Z-Score of 3.17 and P<0.01.The SSH confrmed the signifcant diferences in HIV prevalence at the national level strata,with a higher level for Cote d’Ivoire compared to other countries in both sexes with q-values of 0.61 and 0.40,respectively.Our LASSO model predicted diferent combinations of CCKs with sex-specifc needs to improve HIV testing uptake.Conclusions:The spatial distribution of HIV prevalence in the MRU is skewed and the CCK about HIV/AIDS and HIV testing uptake are far below the threshold target set by UNAIDS for ending the epidemic in the sub-region.Geodetector detected statistically signifcant SSH within and between countries in the MRU.Our LASSO model predicted that diferent emphases should be implemented when popularizing the CCK about HIV/AIDS for adult women and men.