Quantitative parameters in novel spectral computed tomography:Assessment of Ki-67 expression in patients with gastric adenocarcinoma

BACKGROUND The level of Ki-67 expression has served as a prognostic factor in gastric cancer.The quantitative parameters based on the novel dual-layer spectral detector computed tomography(DLSDCT)in discriminating the Ki-67 expression status are unclear.AIM To investigate the diagnostic ability of DLSDCT-derived parameters for Ki-67 expression status in gastric carcinoma(GC).METHODS Dual-phase enhanced abdominal DLSDCT was performed preoperatively in 108 patients with gastric adenocarcinoma.Primary tumor monoenergetic CT attenuation value at 40-100 kilo electron volt(kev),the slope of the spectral curve(λ_(HU)),iodine concentration(IC),normalized IC(nIC),effective atomic number(Z^(eff))and normalized Z^(eff)(nZ^(eff))in the arterial phase(AP)and venous phase(VP)were retrospectively compared between patients with low and high Ki-67 expression in gastric adenocarcinoma.Spearman’s correlation coefficient was used to analyze the association between the above parameters and Ki-67 expression status.Receiver operating characteristic(ROC)curve analysis was performed to compare the diagnostic efficacy of the statistically significant parameters between two groups.RESULTS Thirty-seven and 71 patients were classified as having low and high Ki-67 expression,respectively.CT_(40 kev-VP),CT_(70 kev-VP),CT_(100 kev-VP),and Z^(eff)-related parameters were significantly higher,but IC-related parameters were lower in the group with low Ki-67 expression status than the group with high Ki-67 expression status,and other analyzed parameters showed no statistical difference between the two groups.Spearman’s correlation analysis showed that CT_(40 kev-VP),CT_(70 kev-VP),CT_(100 kev-VP),Z^(eff),and n Z^(eff) exhibited a negative correlation with Ki-67 status,whereas IC and nIC had positive correlation with Ki-67 status.The ROC analysis demonstrated that the multi-variable model of spectral parameters performed well in identifying the Ki-67 status[area under the curve(AUC)=0.967;sensitivity 95.77%;specificity 91.89%)].Nevertheless,the differentiating capabilities of singlevariable model were moderate(AUC value 0.630-0.835).In addition,the nZ_(VP)^(eff) and nIC_(VP)(AUC 0.835 and 0.805)showed better performance than CT_(40 kev-VP),CT_(70 kev-VP) and CT_(100 kev-VP)(AUC 0.630,0.631 and 0.662)in discriminating the Ki-67 status.CONCLUSION Quantitative spectral parameters are feasible to distinguish low and high Ki-67 expression in gastric adenocarcinoma.Z^(eff) and IC may be useful parameters for evaluating the Ki-67 expression.

A methodological framework of landslide quantitative risk assessment in areas with incomplete historical landslide information

Landslide risk assessment(LRA)is of great significance to hazard prevention and mitigation.However,the historical landslide information is incomplete in most areas,which makes the landslide quantitative risk assessment(LQRA)extremely difficult.This research proposed a set of frameworks for LQRA,so as to achieve LQRA in areas with incomplete historical landslide information.Firstly,we constructed the convolutional neural network(CNN)model suitable for landslide susceptibility assessment(LSA)by studying the structure and hyperparameters optimization of CNN.Secondly,we proposed a method to calculate the temporal probability by using the Poisson model based on the time range of historical landslides occurrence,and then conducted landslide hazard assessment(LHA).Then,we established a mathematical model for landslide intensity of shallow landslide based on landslide area and slope,aiming at solving the problem that it is difficult to calculate landslide intensity due to the lack of landslide volume and velocity.Based on the landslide intensity and the hazard-resistant capacity of the element at risk,we assessed the landslide vulnerability.Finally,population risk map and economic risk map are obtained based on the landslide hazard,vulnerability,and estimated value of the elements at risk.The proposed LQRA framework was applied to Tumen City,China for testing and field validation.From the results,the CNN model built can help improve the accuracy of LSA.The proposed temporal probability calculation method is conducive to the completion of LHA in areas with incomplete historical landslide information.The established landslide intensity mathematical model has certain credibility.Since the landslide risk map is obtained through appropriate simplification and substitution estimation,its final value cannot be used as an accurate prediction of future losses,but it can be used as a reference for the extent of potential losses,so as to determine the areas where hazard prevention and mitigation measures need to be taken.

Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

Effect of a comprehensive geriatric assessment nursing intervention model on older patients with diabetes and hypertension

BACKGROUND The Comprehensive Geriatric Assessment(CGA)was introduced late in China and is primarily used for investigating and evaluating health problems in older adults in outpatient and community settings.However,there are few reports on its application in hospitalized patients,especially older patients with diabetes and hypertension.AIM To explore the nursing effect of CGA in hospitalized older patients with diabetes and hypertension.METHODS We performed a retrospective single-center analysis of patients with comorbid diabetes mellitus and hypertension who were hospitalized and treated in the Jiangyin Hospital of Traditional Chinese Medicine between September 2020 and June 2022.Among the 80 patients included,40 received CGA nursing interventions(study group),while the remaining 40 received routine nursing care(control group).The study group's comprehensive approach included creating personalized CGA profiles,multidisciplinary assessments,and targeted inter-ventions in areas,such as nutrition,medication adherence,exercise,and mental health.However,the control group received standard nursing care,including general and medical history collection,fall prevention measures,and regular patient monitoring.After 6 months of nursing care implementation,we evaluated the effectiveness of the interventions,including assessments of blood glucose levels fasting blood glucose,2-h postprandial blood glucose,and glycated hemoglobin,type A1c(HbA1c);blood pressure indicators such as diastolic blood pressure(DBP)and systolic blood pressure(SBP);quality of life as measured by the 36-item Short Form Survey(SF-36)questionnaire;and treatment adherence.RESULTS After 6 months,the nursing outcomes indicated that patients who underwent CGA nursing interventions experienced a significant decrease in blood glucose indicators,such as fasting blood glucose,2-h postprandial blood glucose,and HbA1c,as well as blood pressure indicators,including DBP and SBP,compared with the control group(P<0.05).Quality of life assessments,including physical health,emotion,physical function,overall health,and mental health,showed marked improvements compared to the control group(P<0.05).In the study group,38 patients adhered to the clinical treatment requirements,whereas only 32 in the control group adhered to the clinical treatment requirements.The probability of treatment adherence among patients receiving CGA nursing interventions was higher than that among patients receiving standard care(95%vs 80%,P<0.05).CONCLUSION The CGA nursing intervention significantly improved glycemic control,blood pressure management,and quality of life in hospitalized older patients with diabetes and hypertension,compared to routine care.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Discrepancy between Patients’ and Nurses’ Estimates of Patients’ Activities of Daily Living for Fall Risk Assessment: A Quantitative Observational Study

Background: Patient falls are a serious problem in a rehabilitation unit. Although patient falls have been described in the healthcare literature for more 60 years, and many risk assessment tools have been developed, the rate of falls in hospitals in Japan has remained unchanged for the last 8 years. A previous study reported that about 50% of patients in rehabilitation estimated their fall risk lower than that estimated by their nurses. We believe that patients in rehabilitation tend to overestimate their ability to perform ADLs. Aim: To identify discrepancies between patients’ and nurses’ estimates of patients’ ability to perform activities of daily living (ADL) and clarify any relationship between the discrepancies and patient falls. Methods: Participants comprised 82 patients (42 men) admitted to a rehabilitation unit in Osaka, Japan from July to December of 2017. Patients and their nurses answered the same questionnaire about patients’ ability to perform ADL. The questionnaire was developed based on the Functional Independence Measure (FIM) and administered at admission, at 1 month after admission, and at discharge. Participants were classified into the overestimating group and the accurately estimating/underestimating group, and groups were compared using Wilcoxon rank-sum tests. Results: The mean age of participants was 76.4 years. At admission, approximately 72% of participants estimated their own ability to perform ADL higher than did the nurses. The percentage of overestimating participants dropped to 30% at discharge. Fifteen of the participants experienced a fall;all were in the overestimating group. The ADL Discrepancy and fall-assessment scores for these 15 participants were significantly higher than those of other participants. Conclusions: There are discrepancies between patients’ and nurses’ estimates of patients’ ability to perform ADL and had important significance for assessing their risk of fall. And minimizing the discrepancy may support the prevention of falls.

Mangrove wetlands distribution status identification, changing trend analyzation and carbon storage assessment of China

This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s coastline.Visual interpretation,geological surveys,and ISO clustering unsupervised classification methods are employed to interpret mangrove distribution from remote sensing images from 2021,utilizing ArcGIS software platform.Furthermore,the carbon storage capacity of mangrove wetlands is quantified using the carbon storage module of InVEST model.Results show that the mangrove wetlands in China covered an area of 278.85 km2 in 2021,predominantly distributed in Hainan,Guangxi,Guangdong,Fujian,Zhejiang,Taiwan,Hong Kong,and Macao.The total carbon storage is assessed at 2.11×10^(6) t,with specific regional data provided.Trends since the 1950s reveal periods of increase,decrease,sharp decrease,and slight-steady increases in mangrove areas in China.An important finding is the predominant replacement of natural coastlines adjacent to mangrove wetlands by artificial ones,highlighting the need for creating suitable spaces for mangrove restoration.This study is poised to guide future mangroverelated investigations and conservation strategies.

Evaluating reservoir suitability for large-scale hydrogen storage:A preliminary assessment considering reservoir properties

With rising demand for clean energy,global focus turns to finding ideal sites for large-scale underground hydrogen storage(UHS)in depleted petroleum reservoirs.A thorough preliminary reservoir evaluation before hydrogen(H_(2))injection is crucial for UHS success and safety.Recent criteria for UHS often emphasize economics and chemistry,neglecting key reservoir attributes.This study introduces a comprehensive framework for the reservoir-scale preliminary assessment,specifically tailored for long-term H_(2) storage within depleted gas reservoirs.The evaluation criteria encompass critical components,including reservoir geometry,petrophysical properties,tectonics,and formation fluids.To illustrate the practical application of this approach,we assess the Barnett shale play reservoir parameters.The assessment unfolds through three key stages:(1)A systematic evaluation of the reservoir's properties against our comprehensive screening criteria determines its suitability for H_(2) storage.(2)Using both homogeneous and multilayered gas reservoir models,we explore the feasibility and efficiency of H_(2) storage.This phase involves an in-depth examination of reservoir behavior during the injection stage.(3)To enhance understanding of UHS performance,sensitivity analyses investigate the impact of varying reservoir dimensions and injection/production pressures.The findings reveal the following:(a)Despite potential challenges associated with reservoir compaction and aquifer support,the reservoir exhibits substantial promise as an H_(2) storage site.(b)Notably,a pronounced increase in reservoir pressure manifests during the injection stage,particularly in homogeneous reservoirs.(c)Furthermore,optimizing injection-extraction cycle efficiency can be achieved by augmenting reservoir dimensions while maintaining a consistent thickness.To ensure a smooth transition to implementation,further comprehensive investigations are advised,including experimental and numerical studies to address injectivity concerns and explore storage site development.This evaluation framework is a valuable tool for assessing the potential of depleted gas reservoirs for large-scale hydrogen storage,advancing global eco-friendly energy systems.

Conceptual carbon-reduction process design and quantitative sustainable assessment for concentrating high purity ethylene from wasted refinery gas

The direct emission of waste refinery gas after combustion will cause a severe greenhouse effect.Recovering high-value-added ethylene from wasted refinery gas has fundamental economic and environmental significance. Due to the complexity of the composition of refinery waste gas, designing and optimizing the whole recovery process is still a challenging task. Herein, a novel process(SCOAS) was proposed to obtain polymer-grade ethylene from wasted refinery gas through a direct separation process,and heat pump-assisted thermal integration optimization(HPSCOAS) was carried out. The unique feature of the novel approach is that a new stripper and ethylene reabsorber follow the dry gas absorber to ensure ethylene recovery and methane content. An industrial model, shallow cooling oil absorption(SCOA), and concentration combined cold separation system of ethylene unit using wasted refinery gas was established to analyze the technology and environment. Based on the detailed process modeling and simulation results, the quantitative sustainability assessment of economy and environment based on product life cycle process is carried out. The results show that compared with the traditional process when the same product is obtained, the total annual cost of the HPSCOAS process is the lowest, which is 15.4% lower than that of the SCOA process and 6.1% lower than that of the SCOAS process. In addition,compared with the SCOA process and the HPSCOAS process, the SCOAS process has more environmental advantages. The non-renewable energy consumed by SCOAS is reduced by about 24.8% and 6.1%, respectively. The CO_(2) equivalent is reduced by about 38.6% and 23.7%.

Lead, Zinc and Iron Pollutants Load Assessment in Selected Rivers in Southern Nigeria: Implications for Domestic Uses

The aim of the study is to comparatively assess the concentrations of lead, zinc and iron in Rivers Ase, Warri and Ethiope, in Nigeria. Monthly water samples were collected from six randomly selected sites along the rivers course. 72 water samples were collected from each river at 0 - 15 cm depths. Samples were analysed based on the standard methods recommended by the WHO for testing lead, zinc and iron. The assessment of the water quality was done using the Water Quality Index (WQI) of the Canadian Council of Ministers of the Environment (CCME-WQI). While hypotheses were tested using ANOVA. Findings indicated that CCME-WQI values were 47.3, 66.52 and 78.7. This meant that the water quality of River Ase is impaired and departed from desirable levels, while that of Warri and Ethiope were considered to occasionally be impaired and depart from desirable levels. The ANOVA model showed that there is a significant variation in heavy metal load in the selected rivers at P < 0.05. River water was put to domestic uses such as drinking (20.5%) preparing food (17.8%), bathing (19.8%), washing clothes and dishes (21.3%), brushing teeth (13.3%), and catering for domestic animals (7.5%). Poverty (49.5%) was the major reason for the use of river water for domestic purposes. The locals highlighted that they usually suffer from cholera (26.8%), diarrhoea (25.8%), dysentery (24%) and typhoid (23.5%) as a result of using the river water. The study recommended routine monitoring of anthropogenic and geologic activities, testing of the water regularly amongst others.

Development of Localized Assessment of Municipal Wastewater Disposal Risks

A means to develop a comparative assessment of the risks of available wastewater effluent disposal options on a local scale needs to be developed to help local decision-makers make decisions on options such as direct or indirect potable reuse options. These options have garnered more interest as a result of water supply limitations in many urban areas. This risk assessment was developed from a risk assessment developed at the University of Miami in 2001 and Florida Atlantic University (FAU) in 2023. Direct potable reuse and injection wells were deemed to have the lowest risk in the most recent study by FAU. However, the injection well option may not be available everywhere. As a result, a more local means to assess exposure risk is needed. This paper outlines the process to evaluate the public health risks associated with available disposal alternatives which may be very limited in some areas. The development of exposure pathways can help local decision-makers define the challenges, and support later expert level analysis upon which public health decisions are based.

A risk assessment method considering risk attributes and work safety informational needs and its application

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

Air Quality Assessment of Ubeji Community near Petroleum-Related Activities

The escalating global concern over air pollution requires rigorous investigations. This study assesses air quality near residential areas affected by petroleum-related activities in Ubeji Community, utilizing Aeroqual handheld mobile multi-gas monitors and air quality multi-meters. Air sampling occurred on three distinct days using multi-gas monitors and meters, covering parameters such as CO, NO2, CH4, NH3, VOCs, Particulate Matter, Temperature, Relative Humidity, and Air Quality Index. Soil and plant samples were collected and analyzed for physicochemical and organic components. Air pollutant concentrations showed significant fluctuations. Carbon monoxide (CO) ranged from 0.00 to 3.22 ppm, NO2 from 0.00 to 0.10 ppm, CH4 from 4.00 to 2083 ppm, NH3 from 371 to 5086 ppm, and VOCs from 414 to 6135 ppm. Soil analysis revealed low total nitrogen, and undetected BTEX levels. Plant samples displayed a pH range of 7.72 to 9.45. CO concentrations, although below WHO limits, indicated potential vehicular and industrial influences. Fluctuations in NO2 and CH4 were linked to traffic, industrial activities, and gas flaring. NH3 levels suggested diverse pollution sources. The result in this study highlights the dynamic nature of air pollution in Ubeji community, emphasizing the urgent need for effective pollution control measures. Although CO concentrations were within limits, continuous monitoring is essential. Elevated NO2 levels gave information on the impact of industrial activities, while high CH4 concentrations may be associated with gas flaring and illegal refining. The study recommends comprehensive measures and collaborative efforts to address these complex issues, safeguarding both the environment and public health. This study shows the potential synergy between air quality sensors and plants for holistic environmental health assessments, offering valuable insights for environmental assessments and remediation endeavours. The findings call for stringent regulations and collaborative efforts to address air pollution in Ubeji community comprehensively.

Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.

Nutritional Assessment Tools for Patients with Cancer:A Narrative Review

Cancer patients are at high risk of malnutrition,which can lead to adverse health outcomes such as prolonged hospitalization,increased complications,and increased mortality.Accurate and timely nutritional assessment plays a critical role in effectively managing malnutrition in these patients.However,while many tools exist to assess malnutrition,there is no universally accepted standard.Although different tools have their own strengths and limitations,there is a lack of narrative reviews on nutritional assessment tools for cancer patients.To address this knowledge gap,we conducted a non-systematic literature search using PubMed,Embase,Web of Science,and the Cochrane Library from their inception until May 2023.A total of 90 studies met our selection criteria and were included in our narrative review.We evaluated the applications,strengths,and limitations of 4 commonly used nutritional assessment tools for cancer patients:the Subjective Global Assessment(SGA),Patient-Generated Subjective Global Assessment(PG-SGA),Mini Nutritional Assessment(MNA),and Global Leadership Initiative on Malnutrition(GLIM).Our findings revealed that malnutrition was associated with adverse health outcomes.Each of these 4 tools has its applications,strengths,and limitations.Our findings provide medical staff with a foundation for choosing the optimal tool to rapidly and accurately assess malnutrition in cancer patients.It is essential for medical staff to be familiar with these common tools to ensure effective nutritional management of cancer patients.

Clinical validation of the early embryo viability assessment system: Analysis for the blastocyst morphology and pregnancy outcomes

Objective:To determine the relationship between the early embryo viability assessment(EEVA)and blastocyst morphological parameters and pregnancy outcomes.Methods:This retrospective cohort study was conducted on 291 intracytoplasmic sperm injection cycles including 2522 embryos with indications of prolonging embryo culture to the blastocyst stage in the Genea embryo review incubator,and 511 single vitrified-warmed blastocyst transfer cycles from January 2020 to June 2023.The EEVA system produced an EEVA score from E1(best)to E5(worse)for the potential of blastocyst formation.Blastocyst morphology was evaluated.The association between the EEVA score and each type of blastocyst morphology,implantation rate,clinical pregnancy,and ongoing pregnancy were assessed using generalized estimating equations.Results:The inner cell mass A(ICM A),trophectoderm A(TE A),blastocoele expansion degree of 3,4,5,6,7 rates were higher with lower the EEVA score.The adjusted odd ratio(aOR)(E5 vs E1)was 0.3 for ICM A,0.174 for TE A and 0.210 for BL3,4,5,6,7(all P<0.001),suggesting a significant association between lower EEVA scores and improved embryo quality.The implantation,clinical pregnancy,and ongoing pregnancy rate were also higher with lower the EEVA score.The aOR of E5 vs E1 was 0.245 for implantation,0.185 for clinical pregnancy and 0.200 for ongoing pregnancy rate(P<0.001).Conclusions:There were associations between blastocyst morphology,pregnancy outcome and EEVA scores.The good blastocyst morphology and pregnancy outcomes are higher with lower the EEVA score.

Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.