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.

Exploring deep learning for landslide mapping:A comprehensive review

A detailed and accurate inventory map of landslides is crucial for quantitative hazard assessment and land planning.Traditional methods relying on change detection and object-oriented approaches have been criticized for their dependence on expert knowledge and subjective factors.Recent advancements in highresolution satellite imagery,coupled with the rapid development of artificial intelligence,particularly datadriven deep learning algorithms(DL)such as convolutional neural networks(CNN),have provided rich feature indicators for landslide mapping,overcoming previous limitations.In this review paper,77representative DL-based landslide detection methods applied in various environments over the past seven years were examined.This study analyzed the structures of different DL networks,discussed five main application scenarios,and assessed both the advancements and limitations of DL in geological hazard analysis.The results indicated that the increasing number of articles per year reflects growing interest in landslide mapping by artificial intelligence,with U-Net-based structures gaining prominence due to their flexibility in feature extraction and generalization.Finally,we explored the hindrances of DL in landslide hazard research based on the above research content.Challenges such as black-box operations and sample dependence persist,warranting further theoretical research and future application of DL in landslide detection.

Comprehensive assessment on dynamic roof instability under fractured rock mass conditions in the excavation disturbed zone

The damage process of fractured rock mass showed that the fracture in rocks induced roof collapse in Yangchangwan Coal Mine, China. The rock mass was particularly weak and fractured. There occurred 6 large-scale dynamical roof falls in the excavation disturbed zone （EDZ） with the collapsing volume of 216 m^3. First, the field detailed geological environment, regional seismic dynamics, and dynamic instability of roadways were generally investigated. Second, the field multiple-index monitoring measurements for detecting the deep delamination of the roof, convergence deformation, bolt-cable load, acoustic emission （AE） characteristic parameters, total AE events, AE energy-releasing rate, rock mass fracture, and damage were arranged. Finally, according to the time-space-strength relations, a quantitative assessment of the influence of rock-mass damage on the dynamic roof instability was accomplished.

Application of Biomarkers to Quantitative Source Assessment of Oil Pools

Recent detailed organic geochemical and geological investigation indicate that oils of the Bamianhe oilfield, Bohai Bay Basin, East China are the mixture of less mature oils and normal oils derived from the ES4 mudstones and shales with a wide range of thermal maturity from immature to middle-maturity, and most of the oils were proved to be sourced from the depocenter of the Niuzhuang Sag immediately adjacent to the Bamianhe oilfield. Two approaches to quantify the amount of immature oils mixed through quantitative biomarkers were established. One is a relatively simple way only through organic geochemical analysis while the other is to be combined with basin modeling. Selecting biomarkers as proxies is the crucial point in both of them. The results show that the less mature oils mixed in the Bamianhe oilfield is less than 10% and 18% respectively based on the two approaches, which coincide with the results of oil-source rock correlation.

Quantitative assessment of the surface crack density in thermal barrier coatings

In this paper, a modified shear-lag model is developed to calculate the surface crack density in thermal barrier coatings（TBCs）. The mechanical properties of TBCs are also measured to quantitatively assess their surface crack density. Acoustic emission（AE） and digital image correlation methods are applied to monitor the surface cracking in TBCs under tensile loading. The results show that the calculated surface crack density from the modified model is in agreement with that obtained from experiments. The surface cracking process of TBCs can be discriminated by their AE characteristics and strain evolution. Based on the correlation of energy released from cracking and its corresponding AE signals, a linear relationship is built up between the surface crack density and AE parameters, with the slope being dependent on the mechanical properties of TBCs.

A Quantitative Method for Active Fault Migration Distance Assessment on both Sides of Mid-Ocean Ridges——Based on Multi-Beam Data

Fracture-fissure systems found at mid-ocean ridges are dominating conduits for the circulation of metallogenic fluid.Ascertaining the distribution area of active faults on both sides of mid-ocean ridges will provide a useful tool in the search for potential hydrothermal vents,thus guiding the exploration of modern seafloor sulfides.Considering the MidAtlantic Ridge 20°N–24°N(NMAR)and North Chile Rise(NCR)as examples,fault elements such as Fault Spacing(?S)and Fault Heave(?X)can be identified and quantitatively measured.The methods used include Fourier filtering of the multi-beam bathymetry data,in combination with measurements of the topographic slope,curvature,and slope aspect patterns.According to the Sequential Faulting Model of mid-ocean ridges,the maximal migration distance of an active fault on either side of mid-ocean ridges—that is,the distribution range of active faults—can be measured.Results show that the maximal migration distance of active faults at the NMAR is 0.76–1.01 km(the distance is larger at the center than at the ends of this segment),and at the NCR,the distribution range of active faults is 0.38–1.6 km.The migration distance of active faults on the two study areas is positively related to the axial variation of magma supply.In the NCR study area,where there is an abundant magma input,the number of faults within a certain distance is mainly affected by the variation of lithospheric thickness.Here a large range of faulting clearly corresponds to a high proportion of magmatism to seafloor spreading near mid-ocean ridges(M)value,and in the study area of the NMAR,there is insufficient magmatism,and the number of faults may be controlled by both lithospheric thickness and magma supply,leading to a less obvious positive correlation between the distribution range of active faults and M.

Quantitative Assessment on the Embodied Environmental Impact of Concrete with or without Fly Ash

According to the life cycle assessment and the environmental design method of industry prnduction, a quantitative assessment model for the embodied environmetal impact of concrete with or without fly ash was proposed. The environmental burden impact indicator （ EBII ）, the resources depletion impact indicator （RDII）, and the environmental impact comprehensive indicator （EICI） are defined. The specific environmental impact values of different grade concretes with or wittout fly ash were presented. In the embodied process of concrete with or without fly ash, the key potential environmental impact categories are global warming and dust endsskin, and it is an effective way for reducing the embndied environmental impact of concrete to mix fly ash and lower grade cenwat . The method presented in this paper makes it possible to quantitatively assess the embodied environmental impact of concrete with or without .fly ash. The results calculated in this paper can be used to quantitatively assess the life cycle environmental impact of construction materials and buildings.

Quantitative Risk Assessment with Data Mining for Formaldehyde Content of Imported Textile

The assessment of potential risks posed by formaldehyde in clothing to consumers is of increasing concern worldwide,for free formaldehyde is harmful to human. Some papers focus on hazard and exposure assessment,using quantitative and semi-quantitative method, rather than assessment for the factors related to formaldehyde content. In order to perform early-warning research and risk management,the quantitative risk assessment is used to analyze the imported textile testing data and find the factors related to formaldehyde content. K-means algorithm is the core of the method. It can be concluded that the disqualified textiles have relations with main fiber components,fabric color,season month,and brand. Then the data in the same attribute are clustered by Kmeans algorithm. The different classes are defined as related danger level,respectively severe,moderate,and light.

Quantitative Assessment of Implicit Environmental Impacts of Construction Projects

Assessment system of implicit environmental impacts was established including environmental impact indicator, resources consumption indicator and energy consumption indicator. The quantification of environmental impact indicators is based on the life cycle assessment system of the Society of Environmental Toxicology and Chemistry （SETAC） and the evaluation software BEES. Normalization reference values and weights of 12 categories of environmental impacts were identified, and the environmental impact indicators in the phases of raw material extraction, transportation, manufacturing, use and end of life were analyzed. By analyzing the environmental performance of a university refectory as a case study, it is demonstrated that human health, global wanning and acidification are the first three environmental impacts in 12 categories. The total implicit environmental impact load per square meter of this project is 18.448 × 10 ^-2 standard human equivalent weight. Moreover, 97.3% of total environmental impacts occur in the phase of raw material extraction.

Quantitative Assessment and Zonation of Regional Crustal Stability in China

On the basis of the synthetic analysis of present regional tectonic stress field in China, this paper follows three steps to do crustal stability assessment: (1) zonation of preevaluation area for regional crustal stability assessment and zonation; (2) choice, taking value and weight distribution of quantitative evaluation indices and determination of evaluation standards; (3) assessment and zonation of regional crustal stability using fuzzy mathematics in China.

Study on Quantitative Assessment for the Social Risk of Major Geological Disasters

Based on the analysis of social risk of geological disasters,the index system of social risk evaluation was established. To assess the social risk quantitatively,a quantitative evaluation model of the social risk was established based on AHP,and the social risk of geological disasters was graded. Finally,the evaluation model was applied in a case.

Risk of Waterborne Parasitic Infection among Vegetables Producers in the City of Ouagadougou, Burkina Faso: An Attempt to Quantify Them Using the Quantitative Microbiological Risk Assessment Method

The use of wastewater in urban agriculture has been promoted as an alternative to water scarcity and as a means to increase soil fertilizer. However, the use of wastewater in urban agriculture raises major public health concerns, mainly due to the often high concentration of pathogenic micro-organisms. Waterborne parasites are a major health concern in this regard, especially in endemic areas, mainly due to the high environmental resistance of eggs/cysts combined with a low infectious dose. In this study, the parasitological risk to vegetables producers in Ouagadougou using polluted water was evaluated through the quantitative microbiological risk analysis method. For this purpose, the search for and quantification of viable parasite eggs and cysts in irrigation water was coupled with epidemiological surveillance of vegetables producers in Ouagadougou. Protozoa and helminths belonging to 9 species were recorded and samples analyzed. These include Ancylostoma sp., Ascaris lumbricoides, tapeworm’s sp, Strongyloides stercoralis, Entamoeba histolytica, Giardia lamblia. Despite the variability of isolated parasitic species, Ancylostoma sp. eggs were common and severe to all types of water. Moreover, epidemiological approach showed that there were more parasitic species found in irrigation water and also other parasitic species circulating among vegetable farmers. In addition, there is no statistical significant association between the type of water used for irrigation and the carried parasites by vegetable gardeners. However, contamination of the groups using the raw wastewater is once higher than those using well water. When one is interested in the groups using treated wastewater as a source of irrigation, these risks of contaminations are halved. These contaminations are halved when one looks at groups using treated wastewater as a source of irrigation water. Still, whatever the type of water used by the gardeners, they have a probability of infection with Ancylostoma sp. of around 9.83 × 10−1 pppy.

Quantitative Assessment of Building Constructability Using BIM and 4D Simulation

Despite the fact that applying constructability concepts in building designs have led to savings estimated within a range of 1% to 14% of the capital cost, the construction industry still lacks an advanced tool to assess and check for constructability implementations in designs. Therefore, the objective of this research is to propose a quantitative assessment of building constructability, which transforms the subjective assessment of constructability knowledge to a quantified value so that it is easy to analyze and improve building design. The proposed methodology uses the advancement of object oriented Building Information Model (BIM) and 4D simulation model to serve as a data repository models for the constructability assessment platform. Factors affecting constructability of building designs have been identified and relatively weighted using Analytical Hierarchy Process (AHP) technique based on a questionnaire survey collected throughout the Canadian provinces. Evaluation criteria are also developed to assist the designer to evaluate the design proposals. The outcome shows that the proposed method provides the designer an accurate and faster mode in evaluating project constructability by using the parametric features from BIM and taking the advantage of spatial relationship between building components.

Cosmetic Safety and Risk Assessment Under the “New” Regulations

Regulations for the Supervision and Administration of Cosmetics was promulgated by the State Council on June 29,2020 and will take effect on January 1,2021.Compared with the previous Regulations on Health Supervision of Cosmetics,there are more items proposed for the safety of cosmetics.In this paper,the main changes of the safety supervision of cosmetics by comparing the“new”and“old”regulations were summarized with the potential influences on different groups(government,cosmetic enterprises and consumers)discussed.The important laws and regulations on cosmetic safety and risk assessment in China with recently added in vitro testing methods were summarized and the principal theory of cosmetic quantitative risk assessment was introduced.

Research progress of magnetic resonance imaging on the correlation between coronary plaque properties and pericoronal fat

Because of the small size of coronary plaque and its continuous beating with the heart,the assessment of the nature of coronary atherosclerotic plaques by magnetic resonance imaging remains a challenge in current research.Recent studies have shown that changes in the pericoronary fat environment are closely related to the nature of coronary atherosclerotic plaques.At present,the new multi-modal magnetic resonance technology can quantitatively assess the changes of pericorral fat environment,which is expected to effectively evaluate the properties of coronary artery plaque.Therefore,it is of greater clinical importance to study pericoronary fat.Advances in the biological significance of pericoronary fat,comparative imaging for pericoronary fat assessment and clinical applications of its imaging will be reviewed.

Utilizing Dynamic Data to Quickly Evaluate Advantageous Channels and Applications

In response to the high cost and difficulty of high-speed development and testing data in offshore oil fields, this paper proposes to use the most easily available production performance data as the basis and use the grey correlation method to calculate the correlation coefficient between oil and water wells to characterize the degree of development of advantageous channels. The consistency between the calculated results of this method and the tracer test results is over 80%. Based on the fitting results, the correlation coefficient exceeds 0.74 to determine the existence of an advantageous channel. According to the research results of grey correlation method, Bohai K oilfield has completed the combined profile control and flooding measures, and the daily oil production has increased by 20 m3/d. This method is simple, fast, and can achieve quantitative evaluation, which saves time and investment compared to offshore testing. It has strong application and reference value for the development of other offshore water injection oilfields.

Quantitative assessment of the supply,demand and flows of ecosystem services in the Yangtze River Basin,China

Ecosystem service flow is essential for transporting,transforming,and maintaining ecosystem services and connecting supply and demand.This study attempted to quantitatively assess the supply and demand flows of ecosystem services in the Yangtze River Basin in 2000,2010,and 2020;assess the evolution of the spatial patterns of ecosystem service flow at the provincial,watershed and urban agglomeration scales;and design a zoning standard for ecosystem service flow.The results showed as follows.1)Between 2000 and 2020,the Yangtze River had a progressive drop in its freshwater supply,water conservation service and carbon sequestration service flows.The decline rates for these services were measured at 10.90%,11.11%,and 5.17%,respectively.The climate regulation service flow exhibited a pattern of initial fall followed by a subsequent increase,characterized by a decline rate of 35.53%.2)The lowest was the ecosystem service flow in the lower reaches of the Yangtze River and the Yangtze River Delta urban agglomeration.Freshwater supply service flow and water conservation service flow were the highest in the upper reaches of the Yangtze River and the Chengdu-Chongqing urban agglomeration.Carbon sequestration service flow and climate regulation service flow were the highest in the middle reaches of the Yangtze River Basin and the urban agglomeration in the middle reaches of the Yangtze River.3)From 2000 to 2020,the change ratios of the area proportion of the confluence,flow,and outflow areas in the Yangtze River Basin were 1.06,3.17,and 0.86,respectively.The results of this research could offer decision support for regulating ecosystem services in the Yangtze River Basin,promoting sustainable regional development and achieving rational use of the basin resources.

Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution.However,there is,currently,nearly no standard technical framework for objective and quantitative intelligence evaluation.In this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation theories.On this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment results.Experiment results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

Desertification dynamic and the relative roles of climate change and human activities in desertification in the Heihe River Basin based on NPP

Relative roles of climate change and human activities in desertification are the hotspot of research on desertification dynamic and its driving mechanism.To overcome the shortcomings of existing studies,this paper selected net primary productivity （NPP） as an indicator to analyze desertification dynamic and its impact factors.In addition,the change trends of actual NPP,potential NPP and HNPP （human appropriation of NPP,the difference between potential NPP and actual NPP） were used to analyze the desertification dynamic and calculate the relative roles of climate change,human activities and a combination of the two factors in desertification.In this study,the Moderate Resolution Imaging Spectroradiometer （MODIS）-Normalised Difference Vegetation Index （NDVI） and meteorological data were utilized to drive the Carnegie-Ames-Stanford Approach （CASA） model to calculate the actual NPP from 2001 to 2010 in the Heihe River Basin.Potential NPP was estimated using the Thornthwaite Memorial model.Results showed that 61％ of the whole basin area underwent land degradation,of which 90.5％ was caused by human activities,8.6％ by climate change,and 0.9％ by a combination of the two factors.On the contrary,1.5％ of desertification reversion area was caused by human activities and 90.7％ by climate change,the rest 7.8％ by a combination of the two factors.Moreover,it was demonstrated that 95.9％ of the total actual NPP decrease was induced by human activities,while 69.3％ of the total actual NPP increase was caused by climate change.The results revealed that climate change dominated desertification reversion,while human activities dominated desertification expansion.Moreover,the relative roles of both climate change and human activities in desertification possessed great spatial heterogeneity.Additionally,ecological protection policies should be enhanced in the Heihe River Basin to prevent desertification expansion under the condition of climate change.