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.

Classification System for Desertification and Its Quantitative Assessment Methodology in China

Based on the desertification definition of United Nations Convention to Combat Desertification and features of desertification in China, three-level hierarchical classification system for desertification and quantitative assessment methodology of desertification degree were developed and used to evaluate desertification danger degree across the country. The system is composed of three components: type of desertification, type of land utilization and degree of desertification. The type of desertification monitored in China was divided into 4 major categories, 15 sub-categories and 52 types. Vegetation coverage, soil characteristics, and topography are considered as three major indicators for quantitative assessment of desertified land. A simple, yet practically sound mathematical assessment model was built using these indicators. Furthurmore, a regional land desertification warning model was also constructed on the basis of the ratios of non-desertified land area to desertified land area in different degrees. The warning result of wind-erosion desertification at county scale for 12 provinces in northern China was also calculated by this model.

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.

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.

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 risk assessment & leak detection criteria for a subsea oil export pipeline

A quantitative risk assessment （QRA） based on leak detection criteria （LDC） for the design of a proposed subsea oil export pipeline is presented in this paper. The objective of this QRA/LDC study was to determine if current leak detection methodologies were sufficient, based on QRA results, while excluding the use of statistical leak detection; if not, an appropriate LDC for the leak detection system would need to be established. The famous UK PARLOC database was used for the calculation of pipeline failure rates, and the software POSVCM from MMS was used for oil spill simulations. QRA results revealed that the installation of a statistically based leak detection system （LDS） can significantly reduce time to leak detection, thereby mitigating the consequences of leakage. A sound LDC has been defined based on QRA study results and comments from various LDS vendors to assist the emergency response team （ERT） to quickly identify and locate leakage and employ the most effective measures to contain damage.

Quantitative assessment of flight safety under atmospheric icing conditions

A quantitative assessment method is proposed to sense the specific effects of atmospheric icing conditions on flight safety. A six degree-of-freedom computational flight dynamics model is used to study the effects of ice accretion on aircraft dynamics, and a pilot model is also involved. In order to investigate icing severity under different icing conditions, support vector regression is applied in establishing relationship between aircraft icing parameter and weather conditions. Considering the characteristics of aircraft icing accidents, a risk probability assessment model optimized by the particle swarm method is developed to measure the safety level. In particular, angle of attack is chosen as a critical parameter in this method. Results presented in the paper for a series of simulation show that this method captures the basic effects of atmospheric icing conditions on flight safety, which may provide an important theoretical reference for icing accidents avoidance.

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.

Quantitative assessment model for gastric cancer screening

AIM: To set up a mathematic model for gastric cancer screening and to evaluate its function in mass screening for gastric cancer.METHODS: A case control study was carried on in 66patients and 198 normal people, then the risk and protective factors of gastric cancer were determined, including heavy manual work, foods such as small yellow-fin tuna, dried small shrimps, squills, crabs, mothers suffering from gastric diseases, spouse alive, use of refrigerators and hot food,etc. According to some principles and methods of probability and fuzzy mathematics, a quantitative assessment model was established as follows: first, we selected some factors significant in statistics, and calculated weight coefficient for each one by two different methods; second, population space was divided into gastric cancer fuzzy subset and non gastric cancer fuzzy subset, then a mathematic model for each subset was established, we got a mathematic expression of attribute degree (AD).RESULTS: Based on the data of 63 patients and 693 normal people, AD of each subject was calculated. Considering the sensitivity and specificity, the thresholds of AD values calculated were configured with 0.20 and 0.17, respectively.According to these thresholds, the sensitivity and specificity of the quantitative model were about 69% and 63%.Moreover, statistical test showed that the identification outcomes of these two different calculation methods were identical (P＞0.05).CONCLUSION: The validity of this method is satisfactory.It is convenient, feasible, economic and can be used to determine individual and population risks of gastric cancer.

Cine magnetic resonance imaging for quantitative assessment of healthy volunteers and patients with organic small bowel disease

Objective The aim of the study was to use dynamic magnetic resonance imaging （MRI） to compare quantitative parameters of small bowel motility between healthy volunteers and patients with small bowel diseases in order to investigate the characteristics of normal and impaired bowel peristalsis. Methods A total of 44 healthy volunteers （20 men, 24 women; mean age： 36 years; range： 20-61 years） and 42 patients （28 men, 14 women; mean age： 44 years; range： 15-72 years） with organic small bowel disease were recruited in our hospital （Tongji Hospital, Tongji Medical College, Huazhong University of Sci- ence and Technology, Wuhan, China） in this prospective study approved by the hospital institutional review board. Imaging was performed using a 3.0-T scanner 45 minutes after standardized oral administration of 1500 mL non-absorbable fluid （2.5% mannitol）. A serial coronal scan was performed at selected planes for two minutes without breath-hold. Time-caliber curves were plotted at two well-distended small bowel loops in both healthy and patient groups regardless of location. Luminal diameter （LD）, contraction period （CP）, frequency of contraction （FC）, and amplitude-diameter ratio （ADR） were measured based on the graph. Results The characteristics of abnormal peristaltic parameters were assessed in different patients and compared to normal curves from healthy volunteers. A total of 37 segments with abnormal motility were confirmed by two readers in consensus, based on curve patterns and the presence of a stationary phase. Compared to normal peristalsis in healthy volunteers, five different patterns of impaired peristalsis were identified： Ⅰ, consecutive; Ⅱ, slow; Ⅲ, giant type; Ⅳ, uncoordinated; and V, akinetic. Dilated LDs were de- tected in all instances of abnormal peristalsis （P 〈 0.05）. Increased frequency was found in type Ⅰ [（8.73 ± 1.15）/min], while decreased frequency was detected in type Ⅲ peristalsis [（0.67 ± 0.29）/min]. There were no significant differences in frequency between type Ⅱ [（3.19 ±0.43）/min] and normal peristalsis [（3.45± 0.57）/min]. Apart from typeⅠ [（8.70± 0.75）/min], increased FCs were found in all other abnormal patterns. In type Ⅱ peristalsis, the average ADR value was 0.82 ± 0.08, comparable to the ADR value in the healthy group （0.83 ± 0.13）. Conclusion MR cine is an effective method for differentiating normal and abnormal small bowel peristal- sis. Plotting time-caliber curves and measuring quantitative MR cine parameters such as LD, CP, FC, and ADR offers more precise information about small bowel motility.

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 Assessment of Remotely Sensed Global Surface Models Using Various Land Classes Produced from Landsat Data in Istanbul

Digital elevation model （DEM） is the most popular product for three-dimensional （3D） digital representation of bare Earth surface and can be produced by many techniques with different characteristics and ground sampling distances （GSD）. Space-borne opti- cal and synthetic aperture radar （SAR） imaging are two of the most preferred and modern techniques for DEM generation. Using them, global DEMs that cover almost entire Earth are produced with low cost and time saving processing. In this study, we aimed to assess the Satellite pour robservation de la Terre-5 （SPOT-5）, High Resolution Stereoscopic （HRS）, the Advanced Space-borne Thermal Emission and Reflection Radiometer （ASTER）, and the Shuttle Radar Topography Mission （SRTM） C-band global DEMs, produced with space-borne optical and SAR imaging. For the assessment, a reference DEM derived from 1 ： 1000 scaled digital photogrammetric maps was used. The study is performed in 100 km2 study area in Istanbul including various land classes such as open land, forest, built-up land, scrub and rough terrain obtained from Landsat data. The analyses were realized considering three vertical accuracy types as fundamental, supplemental, and consolidated, defined by national digital elevation program （NDEP） of USA. The results showed that, vertical accuracy of SRTM C-band DEM is better than optical models in all three accuracy types despite having the largest grid spacing. The result of SPOT-5 HRS DEM is very close by SRTM and superior in comparison with ASTER models.

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.

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.

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.

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.

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.

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.