Modeling Critical Infrastructure Interdependency: The Case of the Mexico City Metro Transport System

ABSTRACT

“Critical infrastructures” are exceedingly complex and highly interconnected. In order to gain a full understanding and comprehensive awareness of the risks associated with critical infrastructures it becomes essential to consider in a coherent way all the aspects that may cause a failure of such systems. That is, there is a need for a systemic approach to interdependencies among critical infrastructures. The article presents the application of a systemic safety management system (SSMS) model to interdependency modeling for the case of the Mexico City Metro transport network. The model has highlighted that interdependencies occur vertically and horizontally. Horizontal interdependency occurs at every level of recursion and can be: operational, managerial, and environmental. Vertical interdependency, on the other hand, occurs between two levels of recursion only. The SSMS model has shown the potential to be used to model interdependencies among critical infrastructures. It is hoped that the approach presented may help to gain a better understanding of critical infrastructure interdependency.     

Research advances by using interoperable e-science infrastructures

Computational simulations and thus scientific computing is the third pillar alongside theory and experiment in todays science. The term e-science evolved as a new research field that focuses on collaboration in key areas of science using next generation computing infrastructures (i.e. co-called e-science infrastructures) to extend the potential of scientific computing. During the past years, significant international and broader interdisciplinary research is increasingly carried out by global collaborations that often share a single e-science infrastructure. More recently, increasing complexity of e-science applications that embrace multiple physical models (i.e. multi-physics) and consider a larger range of scales (i.e. multi-scale) is creating a steadily growing demand for world-wide interoperable infrastructures that allow for new innovative types of e-science by jointly using different kinds of e-science infrastructures. But interoperable infrastructures are still not seamlessly provided today and we argue that this is due to the absence of a realistically implementable infrastructure reference model. Therefore, the fundamental goal of this paper is to provide insights into our proposed infrastructure reference model that represents a trimmed down version of ogsa in terms of functionality and complexity, while on the other hand being more specific and thus easier to implement. The proposed reference model is underpinned with experiences gained from e-science applications that achieve research advances by using interoperable e-science infrastructures.     

Human Initiated Cascading Failures in Societal Infrastructures

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%.     

Incorporating the impacts of climate change into infrastructure life cycle assessments: A case study of pavement service life performance

Climate change is expected to impact both the operational and structural performance of infrastructures such as roads, bridges, and buildings. However, most past life cycle assessment (LCA) studies do not consider how the operational/structural performance of infrastructure will be affected by a changing climate. The goal of this research was to develop a framework for integrating climate change impacts into LCA of infrastructure systems. To illustrate this framework, a flexible pavement case study was considered where life‐cycle environmental impacts were compared across a climate change scenario and several time horizons. The Mechanistic‐Empirical Pavement Design Guide (MEPDG) was utilized to capture the structural performance of each pavement performance scenario and performance distresses were used as inputs into a pavement LCA model that considered construction and maintenance/rehabilitation materials and activities, change in relative surface albedo, and impacts due to traffic. The results from the case study suggest that climate change will likely call for adaptive design requirements in the latter half of this century but in the near‐to‐mid term, the international roughness index (IRI) and total rutting degradation profile was very close to the historical climate run. While the inclusion of mechanistic performance models with climate change data as input introduces new uncertainties to infrastructure‐based LCA, sensitivity analyses runs were performed to better understand a comprehensive range of result outcomes. Through further infrastructure cases the framework could be streamlined to better suit specific infrastructures where only the infrastructure components with the greatest sensitivity to climate change are explicitly modeled using mechanistic‐empirical modeling routines.     

Creating a Fit Between BPR and IT Infrastructure: A Proposed Framework for Effective Implementation

As business imperatives change and new high-capability information technologies (IT) appear, organizations recognize the need to remain at the forefront of change by reengineering their business processes and implementing enabling responsive IT infrastructures. However, experience in this context indicates a lack of comprehension of essential elements and their mutual relationships that can contribute to the success of business-process change-implementation efforts. This article proposes a framework for managing IT for effective business-process redesign (BPR) implementation. After establishing BPR principles, components, and the relationship of BPR to some organizational and technological approaches, it presents the role and benefits of IT in BPR. The article then discusses in detail the core elements of the framework. Its theme is that an IT infrastructure that covers issues of BPR strategy development, IT strategic alignment, IT infrastructure development, IT sourcing, legacy systems reengineering, IS integration, and IS function competence is essential and critical for effective implementation.     

Imagining the Highway: Anticipating Infrastructural and Environmental Change in Belize

ABSTRACT

This article examines the social and political, as well physical, construction of infrastructure, by attending to the implications of a highway yet to be built. In southern Belize, where the development of rural road networks figures strongly in historical narratives of political and environmental change, the recent paving of a major domestic highway has had distinctive implications for livelihoods and land rights among the predominantly Maya population of rural Toledo district. At the time of research, a plan for a new paved highway to the Guatemalan border animated longstanding debates over territoriality, environment and development, even as the details remained elusive. Bringing political ecology into conversation with attention to the perception of sensory environments, and the affective power of anticipation, I argue for extending anthropological conversations about infrastructure to encompass the meanings and consequences of imagined infrastructures for the ways people encounter, experience and enact social and environmental change.     

Beyond standardization: dynamic software infrastructures for systems biology

Progress in systems biology is seriously hindered by slow production of suitable software infrastructures. Biologists need infrastructure that easily connects to work that is done in other laboratories, for which standardization is helpful. However, the infrastructure must also accommodate the specifics of their biological system, but appropriate mechanisms to support variation are currently lacking. We argue that a minimal computer language, and a software tool called a generator, can be used to quickly produce customized software infrastructures that 'systems biologists really want to have'.     

Using federated data sources and Varian Learning Portal framework to train a neural network model for automatic organ segmentation

PurposeIn this study we trained a deep neural network model for female pelvis organ segmentation using data from several sites without any personal data sharing. The goal was to assess its prediction power compared with the model trained in a centralized manner.MethodsVarian Learning Portal (VLP) is a distributed machine learning (ML) infrastructure enabling privacy-preserving research across hospitals from different regions or countries, within the framework of a trusted consortium. Such a framework is relevant in the case when there is a high level of trust among the participating sites, but there are legal restrictions which do not allow the actual data sharing between them. We trained an organ segmentation model for the female pelvic region using the synchronous data distributed framework provided by the VLP.ResultsThe prediction performance of the model trained using the federated framework offered by VLP was on the same level as the performance of the model trained in a centralized manner where all training data was pulled together in one centre.ConclusionsVLP infrastructure can be used for GPU-based training of a deep neural network for organ segmentation for the female pelvic region. This organ segmentation instance is particularly difficult due to the high variation in the organs’ shape and size. Being able to train the model using data from several clinics can help, for instance, by exposing the model to a larger range of data variations. VLP framework enables such a distributed training approach without sharing protected health information.     

Numerical investigations of rib fracture failure models in different dynamic loading conditions

Rib fracture is one of the most common thoracic injuries in vehicle traffic accidents that can result in fatalities associated with seriously injured internal organs. A failure model is critical when modelling rib fracture to predict such injuries. Different rib failure models have been proposed in prediction of thorax injuries. However, the biofidelity of the fracture failure models when varying the loading conditions and the effects of a rib fracture failure model on prediction of thoracic injuries have been studied only to a limited extent. Therefore, this study aimed to investigate the effects of three rib failure models on prediction of thoracic injuries using a previously validated finite element model of the human thorax. The performance and biofidelity of each rib failure model were first evaluated by modelling rib responses to different loading conditions in two experimental configurations: (1) the three-point bending on the specimen taken from rib and (2) the anterior–posterior dynamic loading to an entire bony part of the rib. Furthermore, the simulation of the rib failure behaviour in the frontal impact to an entire thorax was conducted at varying velocities and the effects of the failure models were analysed with respect to the severity of rib cage damages. Simulation results demonstrated that the responses of the thorax model are similar to the general trends of the rib fracture responses reported in the experimental literature. However, they also indicated that the accuracy of the rib fracture prediction using a given failure model varies for different loading conditions.     

Strategies for Meeting EU End-of-Life Vehicle Reuse/Recovery Targets

Disposal of end-of-life vehicles (ELVs) is a relatively new focus of the European policy community. Technical requirements for car design and minimum reuse and recovery rates for end-of-life vehicles are the subject of a recent European Union directive on ELVs. This directive is expected to induce changes in the infrastructure required for ELV processing, and presents a substantial challenge to maintaining such an infrastructure as economically viable.
This paper assesses current and emerging ELV recycling technologies, in order to provide guidelines for the development of future ELV recycling strategies. Emphasis is given to technologies dedicated to automobile shredder residue (ASR) recovery, as an alternative/complement to more labor-intensive dismantling activities. The ultimate goal is to develop a vision of the type of ASR processing technology that could emerge in the future.
The analysis is based on a model developed to simulate ELV processing infrastructures, and shredding data are taken from full-scale experiments. The results obtained show that ASR mechanical separation and recycling technologies may enable more extensive recycling and contribute to achieving European Union recycling targets, and can thus be considered as far more promising than technologies based on energy recovery.     

有害藻华预警预测技术研究进展

近年来有害藻华频繁发生且危害严重,对有害藻华预警预测技术的研究可为有害藻华的预警预报、生态学防治及防灾减灾提供借鉴.本文从有害藻华的运动预测预警、指标临界值预警、数据驱动模型和生态数学模型4个方面介绍了国内外有害藻华的预警技术研究进展,分析了各类预警技术的优劣,并提出了基于细胞特征预测蓝藻生长速率以及基于藻类群落特征预警蓝藻水华的新思路.     

Critical patch size generated by Allee effect in gypsy moth, Lymantria dispar (L.)

Allee effects are important dynamical mechanisms in small-density populations in which per capita population growth rate increases with density. When positive density dependence is sufficiently severe (a 'strong' Allee effect), a critical density arises below which populations do not persist. For spatially distributed populations subject to dispersal, theory predicts that the occupied area also exhibits a critical threshold for population persistence, but this result has not been confirmed in nature. We tested this prediction in patterns of population persistence across the invasion front of the European gypsy moth (Lymantria dispar) in the United States in data collected between 1996 and 2008. Our analysis consistently provided evidence for effects of both population area and density on persistence, as predicted by the general theory, and confirmed here using a mechanistic model developed for the gypsy moth system. We believe this study to be the first empirical documentation of critical patch size induced by an Allee effect.     

SpeQuloS: a QoS service for hybrid and elastic computing infrastructures

The large choice of Distributed Computing Infrastructures (DCIs) available allows users to select and combine their preferred architectures amongst Clusters, Grids, Clouds, Desktop Grids and more. In these hybrid DCIs, elasticity is emerging as a key property. In elastic infrastructures, resources available to execute application continuously vary, either because of application requirements or because of constraints on the infrastructure, such as node volatility. In the former case, there is no guarantee that the computing resources will remain available during the entire execution of an application. In this paper, we show that Bag-of-Tasks (BoT) execution on these “Best-Effort” infrastructures suffer from a drop of the task completion rate at the end of the execution. The SpeQuloS service presented in this paper improves the Quality of Service (QoS) of BoT applications executed on hybrid and elastic infrastructures. SpeQuloS monitors the execution of the BoT, and dynamically supplies fast and reliable Cloud resources when the critical part of the BoT is executed. SpeQuloS offers several features to hybrid DCIs users, such as estimating completion time and execution speedup. Performance evaluation shows that BoT executions can be accelerated by a factor 2, while offloading less than 2.5 % of the workload to the Cloud. We report on several scenarios where SpeQuloS is deployed on hybrid infrastructures featuring a large variety of infrastructures combinations. In the context of the European Desktop Grid Initiative (EDGI), SpeQuloS is operated to improve QoS of Desktop Grids using resources from private Clouds. We present a use case where SpeQuloS uses both EC2 regular and spot instances to decrease the cost of computation while preserving a similar QoS level. Finally, in the last scenario SpeQuloS allows to optimize Grid5000 resources utilization.     

Contentious connections: infrastructure,dignity, and collective life in Accra,Ghana

Infrastructural systems have emerged as productive ethnographic sites for analysing political subjectivities and rationalities. Through the case of shared electricity and prepaid meters in the compound housing system of Accra, Ghana, I suggest that infrastructures’ political potential lies in their imaginative and hermeneutic abilities to foster desires for dignity, sustain well-being, and question moral ideals of collective life. In contrast to recent anthropological work that has emphasized the material basis of infrastructures as ‘techno-political’ devices materializing certain logics of rule and governance, I reclaim a poetics of sociality whereby infrastructures mobilize a politics of (unwanted) collective life. Through the ‘electricity stories’ circulated by tenants, I chart how the moral economy of infrastructure in a context of collective precarity redistributes marginalization and freedom in ways that always exceed political rationales of energy reforms and policies.     

Climate change,species distribution models,and physiological performance metrics: predicting when biogeographic models are likely to fail

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CT_max, and the upper lethal limit, defined as LT_max. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.     

A solution approach for deriving alternative fuel station infrastructure requirements

When an alternative fuel is introduced, the infrastructure through which that fuel is made available to the market is often underdeveloped. Transportation service providers relying on such infrastructures are unlikely to adopt alternative fuel vehicles as it may impose long detours for refueling. In this paper, we design and apply a new solution approach to derive minimum infrastructure requirements, in terms of the number of alternative fuel stations. The effectiveness of our approach is demonstrated by applying it to the case of introducing liquefied natural gas (LNG) as a transportation fuel in The Netherlands. From this case, we learn that, depending on the driving range of the LNG trucks and the size of area on which those trucks operate, a minimum of 5–12 LNG fuel stations is necessary to render LNG trucks economically and environmentally beneficial.     

Propagation of Curved Activation Fronts in Anisotropic Excitable Media

We study theoretical and numerical propagation of autowave fronts in excitable two-variable (activator-inhibitor) systems with anisotropic diffusion. A general curvature-velocity relation is derived for the case that the inhibitor diffusion is neglected. This relation predicts the break of an activation front when the front curvature exceeds a critical value, which is corroborated by computer simulations of a particular reaction-diffusion model. Some qualitative effects associated with the inhibitor diffusion are studied numerically. It is found that the critical value of curvature decreases with an increase in the inhibitor diffusion coefficient. The core of a spiral wave increases in size and turns through an angle which depends on the inhibitor diffusion coefficient. PACS Numbers: 05.50. +q, 05.70. Ln., 82.40. -g, 87.10. +e