MoMA Algorithm: A Bottom-Up Modeling Procedure for a Modular System under Environmental Conditions

The functioning of complex systems relies on subsystems (modules) that in turn are composed of multiple units. In this paper, we focus on modular systems that might fail due to wear on their units or environmental conditions (shocks). The lifetimes of the units follow a phase-type distribution, while shocks follow a Markovian Arrival Process. The use of Matrix-Analytic methods and a bottom-up approach for constructing the system generator is proposed. The use of modular structures, as well as its implementation by the Modular Matrix-Analytic (MoMA) algorithm, make our methodology flexible in adapting to physical changes in the system, e.g., incorporation of new modules into the current model. After the model for the system is built, the modules are seen as a ‘black box’, i.e., only the contribution of the module as a whole to system performance is considered. However, if required, our method is able to keep track of the events within the module, making it possible to identify the state of individual units. Compact expressions for different reliability measures are obtained with the proposed description, optimal maintenance strategies based on critical operative states are suggested, and a numerical application based on a k-out-of-n structure is developed.Spanish Ministry of Science and Innovation-State Research Agency PID2020-120217RB-I00 PID2021-123737NB-I00Junta de Andalucia B-FQM-284-UGR20 CEX2020-001105-/AEI/10.13039/50110001103

Inflation Targeting in Financially Stable Economies: Has it been Flexible Enough?

The events surrounding the financial crisis and recession of 2008-2009 required significant policy responses by central banks. For formal inflation targeters (IT) a natural question arises about whether IT frameworks were flexible enough to address this unprecedented policy environment. In this paper we tackle this question by assessing the policy responses to the crisis of nine IT central banks that did not face systemic problems in their banking or financial systems. We first document substantial deviations of actual policy responses from prescriptions of conventional monetary policy reaction functions, beginning in the second half of 2008. Although several explanations for the deviations are offered, highlighting the extreme challenges at the time, we can more easily reconcile the findings with a decline in the persistence of monetary policy, again, in all cases. Second, we document the banks’ non-monetary-policy measures adopted at the time, and estimate their impact on local money markets (both in local currency and US dollars) and on exchange rates. While these measures helped broadly to normalize markets, firm conclusions on the effectiveness of specific measures are elusive, owing to the difficulty in comparing the different mix of measures adopted across countries and the significant heterogeneity in specific economies’ responses to these non-monetary policy measures.

A study to develop a low temperature battery suitable for space probe applications final report

Low temperature batteries for deep space probes and extending battery usefulness by heatin

Markov and Semi-markov Chains, Processes, Systems and Emerging Related Fields

This book covers a broad range of research results in the field of Markov and Semi-Markov chains, processes, systems and related emerging fields. The authors of the included research papers are well-known researchers in their field. The book presents the state-of-the-art and ideas for further research for theorists in the fields. Nonetheless, it also provides straightforwardly applicable results for diverse areas of practitioners

High Resolution Multi-parametric Diagnostics and Therapy of Atrial Fibrillation: Chasing Arrhythmia Vulnerabilities in the Spatial Domain

After a century of research, atrial fibrillation (AF) remains a challenging disease to study and exceptionally resilient to treatment. Unfortunately, AF is becoming a massive burden on the health care system with an increasing population of susceptible elderly patients and expensive unreliable treatment options. Pharmacological therapies continue to be disappointingly ineffective or are hampered by side effects due to the ubiquitous nature of ion channel targets throughout the body. Ablative therapy for atrial tachyarrhythmias is growing in acceptance. However, ablation procedures can be complex, leading to varying levels of recurrence, and have a number of serious risks. The high recurrence rate could be due to the difficulty of accurately predicting where to draw the ablation lines in order to target the pathophysiology that initiates and maintains the arrhythmia or an inability to distinguish sub-populations of patients who would respond well to such treatments. There are electrical cardioversion options but there is not a practical implanted deployment of this strategy. Under the current bioelectric therapy paradigm there is a trade-off between efficacy and the pain and risk of myocardial damage, all of which are positively correlated with shock strength. Contrary to ventricular fibrillation, pain becomes a significant concern for electrical defibrillation of AF due to the fact that a patient is conscious when experiencing the arrhythmia. Limiting the risk of myocardial injury is key for both forms of fibrillation. In this project we aim to address the limitations of current electrotherapy by diverging from traditional single shock protocols. We seek to further clarify the dynamics of arrhythmia drivers in space and to target therapy in both the temporal and spatial domain; ultimately culminating in the design of physiologically guided applied energy protocols. In an effort to provide further characterization of the organization of AF, we used transillumination optical mapping to evaluate the presence of three-dimensional electrical substrate variations within the transmural wall during acutely induced episodes of AF. The results of this study suggest that transmural propagation may play a role in AF maintenance mechanisms, with a demonstrated range of discordance between the epicardial and endocardial dynamic propagation patterns. After confirming the presence of epi-endo dyssynchrony in multiple animal models, we further investigated the anatomical structure to look for regional trends in transmural fiber orientation that could help explain the spectrum of observed patterns. Simultaneously, we designed and optimized a multi-stage, multi-path defibrillation paradigm that can be tailored to individual AF frequency content in the spatial and temporal domain. These studies continue to drive down the defibrillation threshold of electrotherapies in an attempt to achieve a pain-free AF defibrillation solution. Finally, we designed and characterized a novel platform of stretchable electronics that provide instrumented membranes across the epicardial surface or implanted within the transmural wall to provide physiological feedback during electrotherapy beyond just the electrical state of the tissue. By combining a spatial analysis of the arrhythmia drivers, the energy delivered and the resulting damage, we hope to enhance the biophysical understanding of AF electrical cardioversion and xiii design an ideal targeted energy delivery protocol to improve upon all limitations of current electrotherapy

Design Experiences on Single and Multi Radio Systems in Wireless Embedded Platforms

The progress of radio technology has made several flavors of radio available on the market.Wireless sensor network platform designers have used these radios to build a variety of platforms. Withnew applications and different types of radios on wireless sensing nodes, it is often hard to interconnectdifferent types of networks. Hence, often additional radios have to be integrated onto existingplatforms or new platforms have to be built. Additionally, the energy consumption of these nodes have to be optimized to meetlifetime requirements of years without recharging.In this thesis, we address two issues of single and multi radio platform designfor wireless sensor network applications - engineering issues and energy optimization.We present a set of guiding principles from our design experiences while building 3 real life applications,namely asset tracking, burglar tracking and finally in-situ psychophysiological stress monitoring of human subjects in behavioral studies.In the asset tracking application, we present our design of a tag node that can be hidden inside valuable personal assets such asprinters or sofas in a home. If these items are stolen, a city wide anchor node infrastructure networkwould track them throughout the city. We also present our design for the anchor node.In the burglar tracking application, we present the design of tag nodes and the issueswe faced while integrating it with a GSM radio. Finally, we discuss our experiencesin designing a bridge node, that connects body worn physiological sensorsto a Bluetooth enabled mobile smartphone. We present the software framework that acts as middleware toconnect to the bridge, parse the sensor data, and send it to higher layers of the softwareframework.We describe 2 energy optimization schemes that are used in the Asset Tracking and the Burglar Tracking applications, that enhance the lifetime of the individual applications manifold.In the asset tracking application,we design a grouping scheme that helps increase reliability of detection of the tag nodes at theanchor nodes while reducing the energy consumption of the group of tag nodes travelling together.We achieve an increase of 5 times improvement in lifetime of the entire group. In the Burglar Tracking application, weuse sensing to determine when to turn the GSM radio on and transmit data by differentiatingturns and lane changes. This helps us reduce the number of times the GSM radio is woken up, thereby increasing thelifetime of the tag node while it is being tracked. This adds 8 minutes of trackablelifetime to the burglar tracking tag node. We conclude this thesis by observing the futuretrends of platform design and radio evolution

Energy Markets and Economics Ⅱ

This issue brings together a collection of papers that provide economic insights into the modern energy market, which is still dominated by crude oil but has expanded to incorporate new energy sources in the form of coal, natural gas, and a mixture of renewable energy sources. Given the differences in the dynamics at play with different energy sources, particularly in relation to price determination, the impact they have on the environment, their importance in the energy mix and energy policy, and so forth, it has become imperative to check their behavior using economic models. Papers 1–3 provide some perspective on oil price determination by focusing on the time-varying nature of supply shocks linked to oil producers (Paper 1), OPEC’s announcements (2), and the heterogeneous interconnections of supply or demand shocks over time horizons and different countries (3). Papers 4–6 compare different energy sources within the energy market and other markets (4); explore the importance of energy storage in the electricity market (5); and examine the dynamic relationship between prices of substitutes (oil price) on the natural gas market in China (6). The final four studies examine the impact of renewable and nonrenewable energy on the macroeconomy and the environment

Integrated Workload Allocation and Condition-based Maintenance Threshold Optimisation

Effective asset management is considered key to reducing total costs of asset ownership while enhancing machine availability, guaranteeing security, and increasing productivity. Amongst all the activities involved in asset management, maintenance has been one of the major focus areas of academic research due to its potential in helping manufacturers to generate the most value from their assets. The emergence of condition-based maintenance (CBM) in which decisions are made based on the real-time condition of assets, has opened up new possibilities in developing more comprehensive approaches to improve the performance of production systems. For instance, a trend has been observed where attempts are made to couple CBM decisions with those on other production-related factors such as inventory control, spare parts management, and labour routing. The intrinsic link between the degradation behaviour of and the workload allocated to an asset, however, has not been sufficiently studied. Consequently, the potential benefits of intervening in machine degradation, either in the context of a single asset or a fleet of assets, are rarely explored. It is therefore essential that a systematic approach is at hand to improve system performance by exploiting the inter-relationship between production and maintenance. This thesis is dedicated to developing a dynamic integrated decision-making model to improve the system-level performance of a fleet of parallel assets. The aim of the model is to realise the potential benefits, mainly in the form of lower maintenance costs and reduced penalty costs incurred due to loss of production, by simultaneously optimising workload allocation and the CBM threshold. The decision-making model is implemented using an agent-based system involving two types of agents - 1) machine agents that reside within each individual machine; and 2) a coordinator agent that oversees the entire system. The integrated decision-making model is constituted of two components - 1) a workload-dependent condition-based maintenance optimisation model based on Gamma Process at the asset level through a machine agent; and 2) a workload allocation strategy at the system level implemented by a coordinator agent. Numerical analysis is performed to demonstrate the rationale behind the decision-making process, which is to reach the most desirable balance between maintenance costs and penalty costs incurred by loss of production. The capability of the model to reduce total costs is demonstrated via comparison with traditional strategies such as uniform and random workload allocation. Additionally, the sensitivity analysis conducted has helped to reveal the respective factors that impact the potential reduction in maintenance costs and that in penalty costs, which include the sensitivity of asset degradation to workloads, heterogeneity of assets, penalty cost for a unit of production loss, redundancy of the system, etc. The model presented in this study not only assists operation and maintenance managers to make decisions on the optimal combination of workload allocation and maintenance plans for assets in a production system, but also provides guidance on whether they should invest in workload control capabilities. Furthermore, the proposed approach allows practitioners to evaluate the long-term impacts of sudden events such as an increase in demand, a decrease in the number of redundant machines, and a change in the cost of maintenance actions