A Modified AVI Model for Groundwater Vulnerability Mapping: Case Studies in Southern Italy

Many methods for evaluating the aquifer’s vulnerability to pollution have been developed in the past four decades by using geographic information system (GIS) tools. However, even if the aquifer vulnerability concept is well defined and the methods have been constantly tested and compared, the problem of the choice of the best “standard” method remains. To meet these objectives, aquifer vulnerability maps are of crucial importance. The choice of method depends on several factors, including the scale of the project, the hydrogeological characteristics of the area, and data availability. Among the many methods, the AVI (Aquifer Vulnerability Index) method has been widely used as it considers only two physical parameters. The AVI Index represents the hydraulic resistance of an aquifer to vertical flow, as a ratio between the thickness of each sedimentary unit above the uppermost aquifer (D, length), and the estimated hydraulic conductivity (K, length/time) of each of these layers. The AVI Index has a time dimension and is divided into five classes. In order to avoid a widespread presence of the higher vulnerability classes, especially in shallow aquifers, the AVI classification has been modified using statistical methods. The study reports the application of the modified AVI method for groundwater pollution vulnerability, in three different areas of southern Italy, highlighting the limitations of the method in alluvial aquifers and the differences with other methods.

Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data

The aim of this study was to explore the bus operating state of the city bus passenger corridor, taking the minimum bus operating cost and passenger travel cost as the objective function, taking passenger flow demand and operating income as the constraint, and considering the average speed change of the bus line in the bus corridor at different times. This paper proposes a dynamic optimization model of bus route schedule based on bus Integrated Circuit Card (IC Card) data. The optimization variable is the departure frequency of the candidate lines. To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. The method includes the calibration of generalized cost functions for passengers and bus companies and grasps the characteristics of bus operating speed changes and the design of departure strategies under different decision preferences. The validity and applicability of the proposed method are verified by a numerical example. We mainly carried out the following work: (1) Dynamic analysis of the time dimension of the bus departure interval takes into account the changes in passenger time characteristics during peak periods. (2) Seven schemes of weight ratio of passenger waiting time cost and bus operation cost were designed, and the departure intervals with different benefit orientations of passengers and operators were discussed, respectively, so as to select the corresponding departure schemes for decision makers under different decision preferences. The results show that (1) the total cost of the 7 different weighting schemes is lower than the actual value by 6.90% to 18.20%; (2) when decision makers need to bias the weight to the bus company, the weight ratio α : β between passengers and bus company is 0.25 : 0.75 which works best. The frequency of departures has been reduced by 6, and at the same time, the total optimized cost is reduced by 18.2%; (3) when decision makers need to bias the weight to the passengers, the weight ratio α : β between the passengers and bus company is 0.75 : 0.25 which works best. The frequency of departures has been increased by 19, and at the same time, the total optimized cost is reduced by 17.7%; and (4) when decision makers consider passengers and bus companies equally, the weight ratio α : β between passengers and bus companies is 0.5 : 0.5, the optimization cost is the closest to the actual cost, the optimization cost is reduced by 6.9%, and the frequency of departures has been increased by 5. The results show that the model in this paper provides a new idea for the information mining of bus routes in the research based on the bus IC Card data and provides an effective tool for the management of different operation decision preferences.

Scenario Expression Method for Regional Geological Structures

Knowing the GIS expression of geological phenomena is an important basis for the combination of geology and GIS. Regional geological structures include folds, faults, strata, rocks, and other typical geological phenomena and are the focus of geological GIS research. However, existing research on the GIS expression of regional geological structure focuses on the expression of the spatial and attribute characteristics of geological structures, and our knowledge of the expression of the semantic, relationship, and evolution processes of geological structures is not comprehensive. In this paper, a regional geological structure scene expression model with the semantic terms positional accuracy, geometric shape, relationship type, attribute type, and time-type attributes and operations is proposed. A regional geological structure scenario markup language (RGSSML) and a method for mapping it with graphics are designed to store and graphically express regional geological structure information. According to the geological time scale, a temporal reference coordinate system is defined to dynamically express the evolution of regional geological structures. Based on the dynamic division of the time dimension of regional geological structures, the expression method of “time dimension + space structure” for the regional geological structure evolution process is designed based on the temporal model. Finally, the feasibility and effectiveness of the regional geological structure scene expression method proposed in this paper is verified using the Ningzhen Mountain (Nanjing section) as an example. The research results show that the regional geological structure scene expression method designed in this paper has the following characteristics: (1) It can comprehensively express the spatial characteristics, attribute characteristics, semantics, relationships, and evolution processes of regional geological structures; (2) it can be used to realize formalized expression and unified storage of regional geological information; and (3) it can be used to realize dynamic expression of the regional geological structure evolution process. Moreover, it has significant advantages for the expression of regional geological structure semantics, relationships, and evolution processes. This study improves our knowledge of the GIS expression of regional geological structures and is expected to further promote the combination and development of geology and GIS.

Allowing for shocks in portfolio mortality models

The COVID-19 pandemic creates a challenge for actuaries analysing experience data that include mortality shocks. Without sufficient local flexibility in the time dimension, any analysis based on the most recent data will be biased by the temporarily higher mortality. Also, depending on where the shocks sit in the exposure period, any attempt to identify mortality trends will be distorted. We present a methodology for analysing portfolio mortality data that offer local flexibility in the time dimension. The approach permits the identification of seasonal variation, mortality shocks and occurred-but-not reported deaths (OBNR). The methodology also allows actuaries to measure portfolio-specific mortality improvements. Finally, the method assists actuaries in determining a representative mortality level for long-term applications like reserving and pricing, even in the presence of mortality shocks. Results are given for a mature annuity portfolio in the UK, which suggest that the Bayesian information criterion is better for actuarial model selection in this application than Akaike’s information criterion.

Modeling the Sustainable Development Nexus as a Complex-Coupled System

This chapter begins with defining complex systems, presents an overview of the applied science of dynamical systems by focusing on the main components of complexity and chaos, and introduces the concept of dimensionality of systems. Systems have structural and temporal (dynamic) components – they exist in space and time. This chapter focuses on the time dimension, called temporality. The authors classify a third dimension, chaos (randomness), and illustrate that all systems can be defined according to their structure, dynamics, and chaos. These three dimensions constitute the dimensionality of systems, which can be used to define and categorize all types of systems. A system dynamics model to quantify the progress and interactions among the United Nation's Sustainable Development Goals (SDG) is introduced. The benefits and limitations of a system dynamics modeling approach in this context are then discussed.

Development, Application and Challenges of Set Pair Analysis in Environmental Science from 1989 to 2020: A Bibliometric Review

Set pair analysis is a new intelligent algorithm for dealing with complex uncertain problems, and it is widely used in environmental science because of its concise structure and scalability of results. However, it is still unclear about the development stage distribution of set pair analysis in environmental science and the specific development and application in key areas. Therefore, based on the method of bibliometrics, this paper studies the development, application and challenges of set pair analysis in environmental science over the past 32 years (1989–2020). The analysis found that in terms of time dimension, the development process of set pair analysis is divided into three stages: the initial stage (1989–2011); the rapid development stage (2012–2015); the steady development stage (2016 to present). In terms of specific fields, this article focuses on the development and application of set pair analysis in the three fields of ecology, water resources, and atmospheric environmental science. It is found that set pair analysis is mainly used for environmental assessment, diagnosis and prediction. In particular, the development of partial connection numbers is a new research trend of set pair analysis, which plays an important role in environmental assessment, diagnosis and prediction. However, the current set pair analysis also has the shortcomings of strong subjectivity, an imperfect theoretical system, and unbalanced development at home and abroad. Only when these deficiencies are solved, can the development of set pair analysis in environmental science be further promoted.

Human Emergency Behaviour Characteristics in Large-scale Emergencies Based on Mobile Communication Data

The characteristics of human emergency behaviour under the emergency are a crucial scientific issue in basic emergency management research. The analysis of time dynamic aspects of human behaviour based on electronic footprint data provides a new method for quantitative investigation of this problem. Previous studies generally assumed that human behaviours were randomly distributed in time, but few studies studied the impact of emergencies and carried out prediction methods through social media data. Using mobile QQ space communication data, this paper from four kinds of emergencies and one kind of conventional event data, digging out the statistical characteristic on the time dimension of human communication behaviour, and in case of any emergencies, such as public security mode of evolution, to explore intrinsic emergency regularity of the impact of human communication behaviour model and further predict human behaviour characteristics. We found that the communication peaks accompanying an emergency are local in time, resulting in a communication avalanche that importantly engages eyewitness social networks. In mobile QQ space communication, the probability distribution of the interval time of the Posting behaviour sequence shows the statistical characteristics of power-law and approximate exponential tail. Compared with most of the typical Posting behaviour, the probability distribution of the interval time of the Posting behaviour sequence is higher. At the same time, the mnemonic is lower than most of the typical Posting behaviour, with a weak anti- mnemonic. These results are theoretically helpful in understanding the regularity of the impact of emergencies on human communication behaviour patterns and have potential application value in predicting the impact degree of crises and the analysis and classification of human social attributes.

An Improved Phase-Derived Range Method Based on High-Order Multi-Frame Track-Before-Detect for Warhead Detection

It is crucial for a ballistic missile defense system to discriminate the true warhead from decoys. Although a decoy has a similar shape to the warhead, it is believed that the true warhead can be separated by its micro-Doppler features introduced by the precession and nutation. As is well known, the accuracy of the phase-derived range method, to extract micro-Doppler curves, can reach sub-wavelength. However, it suffers from an inefficiency of energy integration and high computational costs. In this paper, a novel phase-derived range method, using high-order multi-frame track-before-detect is proposed for micro-Doppler curve extraction under a low signal-to-noise ratio (SNR). First, the sinusoidal micro-Doppler range sequence is treated as the state, and the dynamic model is described as a Markov chain to obtain the envelopes and then the ambiguous phases. Instead of processing the whole frames, the proposed method only processes the latest frame at an arbitrary given time, which reduces the computational costs. Then, the correlation of all pairs of adjacent pulses is calculated along the slow time dimension to find the number of cells that the point scatterer crosses, which can be further used in phase unwrapping. Finally, the phase-derived range method is employed to get the micro-Doppler curves. Simulation results show that the proposed method is capable of extracting the micro-Doppler curves with sub-wavelength accuracy, even if SNR = −15 dB, with a lower computational cost.

Evolutionary Sequence of Spacetime and Intrinsic Spacetime and Associated Sequence of Geometries in Metric Force Fields I

Two classes of three-dimensional metric spaces are identified. They are the conventional three-dimensional metric space and a new ‘three-dimensional’ absolute intrinsic metric space. Whereas an initial flat conventional proper metric space IE′3 can transform into a curved three-dimensionalRiemannian metric space IM′3 without any of its dimension spanning the time dimension (or in the absence of the time dimension), in conventional Riemann geometry, an initial flat ‘three-dimensional’ absolute intrinsic metric space ∅IˆE3 (as a flat hyper-surface) along the horizontal, evolves into a curved ‘three-dimensional’ absolute intrinsic metric space ∅IˆM3, which is curved (as a curved hyper-surface) toward the absolute intrinsic metric time ‘dimension’ along the vertical, and it is identified as ‘three-dimensional’ absolute intrinsic Riemannian metric space. It invariantly projects a flat ‘three-dimensional’ absolute proper intrinsic metric space ∅IE′3ab along the horizontal, which is made manifested outwardly in flat ‘three-dimensional’ absolute proper metric space IE′3ab, overlying it, both as flat hyper-surfaces along the horizontal. The flat conventional three-dimensional relative proper metric space IE′3 and its underlying flat three-dimensional relative proper intrinsic metric space ∅IE′3 remain unchanged. The observers are located in IE′3. The projective ∅IE′3ab is imperceptibly embedded in ∅IE′3 and IE′3ab in IE′3. The corresponding absolute intrinsic metric time ‘dimension’ is not curved from its vertical position simultaneously with ‘three-dimensional’ absolute intrinsic metric space. The development of absolute intrinsic Riemannian geometry is commenced and the conclusion that the resulting geometry is more all-encompassing then the conventional Riemannian geometry on curved conventional metric space IM′3 only is reached.

Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma

ObjectivesThis study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple Overall Toxicity (MOTox) burden is proposed. The MOTox approach investigates the personalised evolution of high overall toxicity (high-MOTox) during the treatment.DesignRetrospective analysis of the MRC-BO06/EORTC-80931 randomised controlled trial for osteosarcoma.SettingInternational multicentre population-based study.ParticipantsA total of 377 patients with resectable high-grade osteosarcoma, who completed treatment within 180 days after randomisation without abnormal dosages (+25% higher than planned).InterventionsPatients were randomised to six cycles of conventional versus dose-intense regimens of doxorubicin and cisplatin. Non-haematological toxicity data were collected prospectively and graded according to the Common Terminology Criteria for Adverse Events (CTCAE).Main outcome measuresThe MOTox score described the overall toxicity burden in terms of multiple toxic AEs, maximum-severity episode and cycle time-dimension. Evolution of high-MOTox was assessed through multivariable models, that investigated the impact of personalised characteristics (eg, achieved chemotherapy dose, previous AEs or biochemical factors) cycle-by-cycle.ResultsA cycle-by-cycle analysis identifies different evolutions of MOTox levels during treatment, detecting differences in patients’ health. Mean MOTox values and percentages of patients with high-MOTox decreased cycle-by-cycle from 2.626 to 1.953 and from 57.8% to 36.6%, respectively. High-MOTox conditions during previous cycles were prognostic risk factors for a new occurrence (ORs range from 1.522 to 4.439), showing that patient’s history of toxicities played an important role in the evolution of overall toxicity burden during therapy. Conventional regimen may be preferred to dose-intense in terms of AEs at cycles 2–3 (p<0.05).ConclusionsThe novel longitudinal method developed can be applied to any cancer studies with CTCAE-graded toxicity data. After validation in other studies, the MOTox approach may lead to improvements in healthcare assessment and treatment planning.Trial registration numberISRCTN86294690; Post-results.