Measurement of Radon Concentration and Estimation of Cancer Risk in Twenty-Four Model Houses in the Town of Koudougou

The objective of our study is to evaluate the concentration of radon (86Rn) inside houses in the town of Koudougou in order to estimate its impact on the health of the population. Indeed, when uranium-rich minerals are found near the surface of the ground, radon concentrations can reach tens of becquerels per cubic meter in enclosed spaces. Given the nature of the geological base of Burkina Faso, this situation is quite probable and certain places that are sometimes poorly ventilated (house, school, office, etc.) can have radon levels high enough to constitute a health problem for occupants. Thus, twenty-four (24) sample houses were identified. In each house, the Corentium digital detector was between 0.8 m and 2 m for at least one week in a place where the occupants estimate that they spend more time of time and measure the concentration of radon in the long term and short term. The recorded data allowed us to determine the Absorbed Dose and the Annual Effective Dose of radon gas for each house in order to estimate the Risk of Cancer and the probable Number of Cases of Lung Cancer per million inhabitants. Thus, the results indicate that the long-term radon concentration varies between 6 Bq/m3 and 285 Bq/m3 respectively in houses 11 and 4 compared to 1 Bq/m3 to 208 Bq/m3 in the short term in the same houses. Also, in the long term, in control houses 1, 3 and 4, the radon level is above the recommended threshold interval. For the short term, these are houses 1, 3, 4 and 17 respectively with 110 Bq/m3, 142 Bq/m3, 208 Bq/m3 and 105 Bq/m3. As for the long-term and short-term effective doses, only houses 1, 3, 4, 17 and 24 have values between 3 - 10 Sv/year. The estimation of the relative risk of lung cancer gives values relatively close to unity and between 1.006 and 1.142 with an average of 1.035 and that of the Number of Lung Cancer Cases per million inhabitants gives values between 8 and 166 with an average of 42. Thus, we can conclude that with the exception of houses 1, 3, 4 and 17, the radon concentrations are relatively low in the twenty-four control houses in the city of Koudougou. The lifestyle of the populations can well explain this situation when we know that people are in the habit of always leaving doors and windows open, especially when they are not sleeping. We can therefore say that the risk of population exposure to radon gas is relatively low in the town of Koudougou.

Brain age estimation:premise,promise,and problems

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North America.Since old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

Wadi Kufranja catchment (126.3 km2), northern Jordan, was selected to estimate annual soil loss using the Revised Universal Soil Loss Equation (RUSLE), remote sensing (RS), and geographic information system (GIS). RUSLE factors (R, K, LS, C and P) were computed and presented by raster layers in a GIS environment, then multiplied together to predict soil erosion rates, and to generate soil erosion risk categories and soil erosion severity maps. The estimated potential average annual soil loss is 10 ton·ha-1·year-1 for the catchment, and the potential erosion rates from recognized erosion classes ranged from 0.0 to 1850 ton·ha-1·year-1. About 42.1% (5317.23 ha) of the catchment area was predicted to have moderate risk of erosion, with soil loss between 5 - 25 ton·ha-1·year-1. Risk of erosion is severe to extreme over 31.2% (3940.56 ha) of the catchment, where calculated soil loss is 25 - 50 and >50 ton·ha-1·year-1. Apart from the gentle slopes of the alluvial fan (Krayma town and surroundings), the lower and the middle reaches of the watershed suffer from severe to extreme erosion risk. High terrain, slope steepness, removal of vegetation, and poor conservation practices are the most prominent causes of soil erosion.

An Application of Bayesian Inference on the Modeling and Estimation of Operational Risk Using Banking Loss Data

Bayesian inference method has been presented in this paper for the modeling of operational risk. Bank internal and external data are divided into defined loss cells and then fitted into probability distributions. The distribution parameters and their uncertainties are estimated from posterior distributions derived using the Bayesian inference. Loss frequency is fitted into Poisson distributions. While the Poisson parameters, in a similar way, are defined by a posterior distribution developed using Bayesian inference. Bank operation loss typically has some low frequency but high magnitude loss data. These heavy tail low frequency loss data are divided into several buckets where the bucket frequencies are defined by the experts. A probability distribution, as defined by the internal and external data, is used for these data. A Poisson distribution is used for the bucket frequencies. However instead of using any distribution of the Poisson parameters, point estimations are used. Monte Carlo simulation is then carried out to calculate the capital charge of the in- ternal as well as the heavy tail high profile low frequency losses. The output of the Monte Carlo simulation defines the capital requirement that has to be allocated to cover potential operational risk losses for the next year.

E-Bayesian estimation for competing risk model under progressively hybrid censoring

This paper considers the Bayesian and expected Bayesian（E-Bayesian） estimations of the parameter and reliability function for competing risk model from Gompertz distribution under Type-I progressively hybrid censoring scheme（PHCS）. The estimations are obtained based on Gamma conjugate prior for the parameter under squared error（SE） and Linex loss functions. The simulation results are provided for the comparison purpose and one data set is analyzed.

Variations in Toxic Metal Levels of Two Fish Species, Pomatomus saltatrix and Dicentrarchus labrax, and Risk Estimation for Children

The concentrations of five toxic metals were monthly determined in two fish species,obtained from fish markets in Turkey during 2010—2011.For the determinations,AAS and ICP-AES were used.The obtained lead concentrations for all studied Pomatomus saltatrix(mean 635μg·kg-1)and Dicentrarchus labrax(mean 463μg·kg-1)samples were found to be significantly higher than the maximum allowances concentration(MAC)of 300μg·kg-1.Mean chromium(324μg·kg-1)and Cu(940μg·kg-1)concentrations in Pomatomus saltatrix were higher than in Dicentrarchus labrax(268μg Cr·kg-1 and 600μg Cu·kg-1)while Ni in Pomatomus saltatrix(216μg·kg-1)was lower in Dicentrarchus labrax(291μg·kg-1).The estimated non-carcinogenic and carcinogenic health risks by the Target Hazard Quotient and target carcinogenic risk indicate that there are no sytemic effects,and the risk of developing cancer over a human lifetime is between 2~9in 1 000 000.

Estimation of Potential Risk of Reservoir-Induced Earthquake for the Proposed Hydroelectric Project on the Yangtze Gorges

The proposed hydroelectric project on the Yangtze Gorges will be one of the largest power stations in the world.The problem of induced seismicity to the project has attracted much attention throughout China and the world.A research program has been carried out by the State Seismological Bureau of China.Based on the size of the reservoir and the lithology,geological structure,permeability,stress state,and previous seismicity in the region,the potential risk of reservoir-induced seismicity has been estimated.The results suggest that,after impoundment in the reservoir area,the possibility of induced seismicity cannot be completely ruled out.The areas with potential risk may be in some gorges composed of karstified carbonate and plutonic granite around the dam site.However,the magnitude is expected to be limited owing to the small dimension of the induced seismogenic faults.

Debris Flows Risk Analysis and Direct Loss Estimation:the Case Study of Valtellina di Tirano,Italy

andslide risk analysis is one of the primary studies providing essential instructions to the subsequent risk management process. The quantification of tangible and intangible potential losses is a critical step because it provides essential data upon which judgments can be made and policy can be formulated. This study aims at quantifying direct economic losses from debris flows at a medium scale in the study area in Italian Central Alps. Available hazard maps were the main inputs of this study. These maps were overlaid with information concerning elements at risk and their economic value. Then, a combination of both market and construction values was used to obtain estimates of future economic losses. As a result, two direct economic risk maps were prepared together with risk curves, useful to summarize expected monetary damage against the respective hazard probability. Afterwards, a qualitative risk map derived using a risk matrix officially provided by the set of laws issued by the regional government, was prepared. The results delimit areas of high economic as well as strategic importance which might be affected by debris flows in the future. Aside from limitations and inaccuracies inherently included in risk analysis process, identification of high risk areas allows local authorities to focus their attention on the “hot-spots”, where important consequences may arise and local （large） scale analysis needs to be performed with more precise cost-effectiveness ratio. The risk maps can be also used by the local authorities to increase population’s adaptive capacity in the disaster prevention process.

NONPARAMETRIC ESTIMATION OF BIVARIATE SURVIVAL FUNCTION UNDER THE COMPETING RISKS CASE

Estimation of the bivariate survival function under the competing risks caseis considered.We give an explicit formula for the estimator from a decomposition of thebivariate survival function based on competing risks,which is almost sure consistent.

A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance

Remaining useful life(RUL)prediction is an advanced technique for system maintenance scheduling.Most of existing RUL prediction methods are only interested in the precision of RUL estimation;the adverse impact of overestimated RUL on maintenance scheduling is not of concern.In this work,an RUL estimation method with risk-averse adaptation is developed which can reduce the over-estimation rate while maintaining a reasonable under-estimation level.The proposed method includes a module of degradation feature selection to obtain crucial features which reflect system degradation trends.Then,the latent structure between the degradation features and the RUL labels is modeled by a support vector regression(SVR)model and a long short-term memory(LSTM)network,respectively.To enhance the prediction robustness and increase its marginal utility,the SVR model and the LSTM model are integrated to generate a hybrid model via three connection parameters.By designing a cost function with penalty mechanism,the three parameters are determined using a modified grey wolf optimization algorithm.In addition,a cost metric is proposed to measure the benefit of such a risk-averse predictive maintenance method.Verification is done using an aero-engine data set from NASA.The results show the feasibility and effectiveness of the proposed RUL estimation method and the predictive maintenance strategy.

Intermediate to Long-term Estimation of Strong Earthquake Risk Areas in the Chinese Mainland Based on Geodesic Measurements

Based on previous research results,present-day crustal deformation and gravity fields in the Chinese mainland are analyzed using the GPS data,leveling,gravity and cross-fault deformations. We analyzed strain accumulation of the major faults,and identified locked or high strain accumulation segments. Combining the effects of large earthquakes in the study area,the long-term (decade) probability of large earthquakes in the Chinese mainland is estimated.

Application of Dangerous Probability Function in Risk Estimation of Surface Rupture Earthquake: Taking the Lingwu Fault in Ningxia Region as an Example

Based on the fitting on paleoearthquake data of intra-plate regions in the northern part of China and giving a statistical model of time interdependence, the potential damage earthquakes in a definite future period and characteristics of present shocks along the Lingwu fault have been analyzed by using dangerous probability function and some new data concerned. We have inferred that the fault has entered a period that earthquakes will probably occur. There exists a potential danger that a strong earthquake with M\-S7.0～7.5 will occur in 10～100a.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Model-driven full system dynamics estimation of PMSM-driven chain shell magazine

Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.

An ArcGIS Geo-Morphological Approach for Snow Avalanche Zoning and Risk Estimation in the Province of Bergamo

This paper describes the results of a study developed, with a GIS approach, at the University of Bergamo, about snow avalanche zoning and risk assessment in the Province of Bergamo. The adoption of a simplified estimation model, presented here, nonetheless allowed achieving results in good accordance with those provided by previous, more rigorous studies at the Province of Bergamo. A following analysis has also been performed to estimate ski lifts, urban areas, power lines, highways, railroads and roads at possible risk. This is a work in progress, since further development has already been taken into account to enrich the risk model with more parameters describing land morphology and meteorology. These results will then be used to simulate accidents and to estimate the shortest routes for rescuers. Finally, the development of a geo-app for mobile devices could become a very useful and fast tool for avalanche risk areas information.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, 'two-step subsample bootstrap' based on moment estimation and maximum likelihood estimation (MLE), according to their theoretical bases and computation procedures. Then, the estimation results are analyzed together with those of normal method and empirical method. The empirical research of foreign exchange data shows that the EVT methods have good characters in estimating VaR under extreme conditions and 'two-step subsample bootstrap' method is preferable to MLE.

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.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

基于LDSCR-at-Risk的PPP项目可融资性评价

通过分析传统的偿债备付率适用性及政府和社会资本合作(PPP)项目的特点,认为传统的偿债备付率不适合于PPP项目可融资性评价。因此,为了评价中长期债务的可融资性,提出了“平准化偿债备付率”(LDSCR),即在借款偿还期内,各年可用于还本付息的资金折现到起始点的现值与贷款金额的比值;进一步提出“风险下的平准化偿债备付率”(LDSCR-at-Risk),即在给定的置信度下的平准化偿债备付率。运用蒙特卡洛仿真进行验证,结果表明:LDSCR-at-Risk可用于PPP项目的可融资性评价,且在可以评价具有风险的PPP项目可融资性的同时,还避免了如何确定项目的最低偿债备付率的问题,从而促进PPP项目融资的发展。