Resilience Assignment Framework using System Dynamics and Fuzzy Logic.

This paper is concerned with the development of a conceptual framework that measures the resilience of the transport network under climate change related events. However, the conceptual framework could be adapted and quantified to suit each disruption’s unique impacts. The proposed resilience framework evaluates the changes in transport network performance in multi-stage processes; pre, during and after the disruption. The framework will be of use to decision makers in understanding the dynamic nature of resilience under various events. Furthermore, it could be used as an evaluation tool to gauge transport network performance and highlight weaknesses in the network. In this paper, the system dynamics approach and fuzzy logic theory are integrated and employed to study three characteristics of network resilience. The proposed methodology has been selected to overcome two dominant problems in transport modelling, namely complexity and uncertainty. The system dynamics approach is intended to overcome the double counting effect of extreme events on various resilience characteristics because of its ability to model the feedback process and time delay. On the other hand, fuzzy logic is used to model the relationships among different variables that are difficult to express in numerical form such as redundancy and mobility

A network mobility indicator using a fuzzy logic approach

This paper introduces a methodology to assess the mobility of a road transport network from the 3 network perspective. In this research, the mobility of the road transport network is defined as the 4 ability of the road transport network to connect all the origin-destination pairs within the network with 5 an acceptable level of service. Two mobility attributes are therefore introduced to assess the physical 6 connectivity and the road transport network level of service. Furthermore, a simple technique based 7 on a fuzzy logic approach is used to combine mobility attributes into a single mobility indicator in 8 order to measure the impact of disruptive events on road transport network functionality. 9 The application of the proposed methodology on a hypothetical Delft city network shows the ability of the technique to estimate variation in the level of mobility under different scenarios. The method allows the study of demand and supply side variations on overall network mobility, providing a new tool for decision makers in understanding the dynamic nature of mobility under various events. The method can also be used as an evaluation tool to gauge the highway network mobility level, and to highlight weaknesses in the network

Increased prevalence of precancerous changes in relatives of gastric cancer patients: critical role of H. pylori

Background & Aims:Helicobacter pylori is believed to predispose to gastric cancer by inducing gastric atrophy and hypochlorhydria. First-degree relatives of patients with gastric cancer have an increased risk of developing gastric cancer. The aim of this study was to determine the prevalence of atrophy and hypochlorhydria and their association with H. pylori infection in first-degree relatives of patients with gastric cancer. Methods:H. pylori status, gastric secretory function, and gastric histology were studied in 100 first-degree relatives of patients with noncardia gastric cancer and compared with those of controls with no family history of this cancer. Results: Compared with healthy controls, relatives of patients with gastric cancer had a higher prevalence of hypochlorhydria (27% vs. 3%) but a similar prevalence of H. pylori infection (63% vs. 64%). Relatives of cancer patients also had a higher prevalence of atrophy (34%) than patients with nonulcer dyspepsia (5%) matched for H. pylori prevalence. Among the relatives of cancer patients, the prevalence of atrophy and hypochlorhydria was increased only in those with evidence of H. pylori infection, was greater in relatives of patients with familial cancer than in relatives of sporadic cancer index patients, and increased with age. Eradication of H. pylori infection produced resolution of the gastric inflammation in each subject and resolution of hypochlorhydria and atrophy in 50% of the subjects. Conclusions: Relatives of patients with gastric cancer have an increased prevalence of precancerous gastric abnormalities, but this increase is confined to those with H. pylori infection. Consequently, prophylactic eradication of the infection should be offered to such subjects

An operational indicator for network mobility using fuzzy logic.

This paper proposes a fuzzy logic model for assessing the mobility of road transport networks from a network perspective. Two mobility attributes are introduced to account for the physical connectivity and road transport network level of service. The relative importance of the two mobility attributes has been established through the fuzzy inference reasoning procedure that was implemented to estimate a single mobility indicator. The advantage of quantifying two mobility attributes is that it improves the ability of the mobility indicator developed to assess the level of mobility under different types of disruptive events. A case study of real traffic data from seven British cities shows a strong correlation between the proposed mobility indicator and the Geo distance per minute, demonstrating the applicability of the proposed fuzzy logic model. The second case study of a synthetic road transport network for Delft city illustrates the ability of the proposed network mobility indicator to reflect variation in the demand side (i.e. departure rate) and supply side (i.e. network capacity and link closure). Overall, the proposed mobility indicator offers a new tool for decision makers in understanding the dynamic nature of mobility under various disruptive events

A novel performance monitoring framework for health research systems: experiences of the National Institute for Health Research in England.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: The National Institute for Health Research (NIHR) was established in 2006 with the aim of creating an applied health research system embedded within the English National Health Service (NHS). NIHR sought to implement an approach for monitoring its performance that effectively linked early indicators of performance with longer-term research impacts. We attempted to develop and apply a conceptual framework for defining appropriate key performance indicators for NIHR. METHOD: Following a review of relevant literature, a conceptual framework for defining performance indicators for NIHR was developed, based on a hybridisation of the logic model and balanced scorecard approaches. This framework was validated through interviews with key NIHR stakeholders and a pilot in one division of NIHR, before being refined and applied more widely. Indicators were then selected and aggregated to create a basket of indicators aligned to NIHR's strategic goals, which could be reported to NIHR's leadership team on a quarterly basis via an oversight dashboard. RESULTS: Senior health research system managers and practitioners endorsed the conceptual framework developed and reported satisfaction with the breadth and balance of indicators selected for reporting. CONCLUSIONS: The use of the hybrid conceptual framework provides a pragmatic approach to defining performance indicators that are aligned to the strategic aims of a health research system. The particular strength of this framework is its capacity to provide an empirical link, over time, between upstream activities of a health research system and its long-term strategic objectives

Film and digital periapical radiographs for the measurement of apical root shortening

Objectives: The aim of this study was to compare the accuracy and agreement of scanned film and digital periapical radiographs for the measurement of apical root shortening. Study design: Twenty-four film and digital [phosphor plate sensor (PPS)] periapical radiographs were taken using the long-cone paralleling technique for six extracted teeth before and after 1mm of apical root trimming. All teeth were mounted using a typodont and the radiographs were recorded using a film holder and polysiloxane occlusal index for each tooth to ensure standardization during the different radiographic exposures. The film radiographs were scanned and the tooth length measurements for the scanned film and digital (PPS) images were calculated using Image-J-Link 1.4 software (http://rebweb.nih.gov/ij/index.html) for the two groups. The accuracy and agreement among the tooth length measurements from each group and the true tooth length measurements were calculated using intra-class correlation (ICC) tests and Bland and Altman plots. Results: A high level of agreement was found between the true tooth length measurements and the scanned film measurements (ICC=0.979, limit of agreement 0.579 to -0.565) and the digital (PPS) radiograph measurements (ICC= 0.979, limit of agreement 0.596 to -0.763). Moreover, a high level of agreement was found between the scanned film and digital (PPS) radiographs for the measurement of tooth length ICC=0.991, limit of agreement 0.411-0.231. Conclusion: Film and digital (PPS) periapical radiographs are accurate methods for measuring apical root shortening with a high level of agreement

Towards Autonomous Cyber Operation Agents: Exploring the Red Case

Recently, reinforcement and deep reinforcement learning (RL/DRL) have been applied to develop autonomous agents for cyber network operations(CyOps), where the agents are trained in a representative environment using RL and particularly DRL algorithms. The training environment must simulate CyOps with high fidelity, which the agent aims to learn and accomplish. A good simulator is hard to achieve due to the extreme complexity of the cyber environment. The trained agent must also be generalizable to network variations because operational cyber networks change constantly. The red agent case is taken to discuss these two issues in this work. We elaborate on their essential requirements and potential solution options, illustrated by some preliminary experimentations in a Cyber Gym for Intelligent Learning (CyGIL) testbed.Comment: Presented at 2nd International Workshop on Adaptive Cyber Defense, 2023 (arXiv:2308.09520