Weather-related fragility modelling of critical infrastructure:a power and railway case study

Climate change has led to more frequent and severe extreme weather events, which impact critical infrastructure networks such as railway and power systems. Although infrastructure networks are interdependent, the analysis to understand the impact of weather events on infrastructure systems is usually performed in sector-specific silos. A methodology to examine how the same weather events affect different infrastructure sectors is presented, in order to understand cross-sectoral impact of extreme weather for interconnected regional infrastructure. Fragility modelling was used to examine the impact of temperature and rainfall on power and rail system failures using the West Midlands (in the UK) as a case study. The results demonstrated that the impact of temperature was broadly consistent across both infrastructure networks, showing less impact until specific upper and lower thresholds are passed; these thresholds were found to be similar for the different infrastructure networks evaluated, but railway infrastructure was found to be impacted more by lower temperatures. A growing correlation between the number of faults on power and railway systems was also found for both rainfall and temperature, indicating the value in coordinating preparation and planning efforts. For infrastructure operators and owners, regional resilience forums and other decision makers, this study provides an approach to assess the regional impact of extreme weather across multiple infrastructure sectors. The results give useful insights to inform the allocation of resources in response to extreme weather events

Predicting the magnitude and timing of peak electricity demand:A competition case study

As weather dependence of the electricity network grows, there is an increasing need to predict the time at which the network peak load will occur. Improving forecasts of peak hour can lead to more accurate scheduling of generation as well as the ability to use flexibility to improve system utilisation or defer capital investment. While there are extensive benchmark models for forecasting electricity demand, their efficacy at forecasting the time or shape of the peak remains to be seen. Global forecasting competitions provide a unique opportunity to compare multiple methodologies under common performance criteria and incentives. The methodology and results are detailed from the Big Data and Energy Analytics Laboratory Challenge 2022 used by the team ‘peaky-finders’ and investigates the suitability of using hourly methods to forecast daily peak magnitude, time, and shape. The resulting approach provides a reproducible ensemble benchmark against which to evaluate more complex methods. Results indicate that simple regression techniques can perform well and outperform more complicated methods during seasons with low hourly variability, however ensemble methods show higher accuracy overall. The results also highlight the significant impact of extreme weather on forecast accuracy, demonstrating the importance of forecasting processes that are resilient to extreme weather.<br/

Explaining anomalous responses to treatment in the Intensive Care Unit

The Intensive Care Unit (ICU) provides treatment to critically ill patients. When a patient does not respond as expected to such treatment it can be challenging for clinicians, especially junior clinicians, as they may not have the relevant experience to understand the patient’s anomalous response. Datasets for 10 patients from Glasgow Royal Infirmary’s ICU have been made available to us. We asked several ICU clinicians to review these datasets and to suggest sequences which include anomalous or unusual reactions to treatment. Further, we then asked two ICU clinicians if they agreed with their colleagues’ assessments, and if they did to provide possible explanations for these anomalous sequences. Subsequently we have developed a system which is able to replicate the clinicians’ explanations based on the knowledge contained in its several ontologies; further the system can suggest additional explanations which will be evaluated by the senior consultant

Predicting the magnitude and timing of peak electricity demand: A competition case study

As weather dependence of the electricity network grows, there is an increasing need to predict the time at which the network peak load will occur. Improving forecasts of peak hour can lead to more accurate scheduling of generation as well as the ability to use flexibility to improve system utilisation or defer capital investment. While there are extensive benchmark models for forecasting electricity demand, their efficacy at forecasting the time or shape of the peak remains to be seen. Global forecasting competitions provide a unique opportunity to compare multiple methodologies under common performance criteria and incentives. The methodology and results are detailed from the Big Data and Energy Analytics Laboratory Challenge 2022 used by the team ‘peaky-finders’ and investigates the suitability of using hourly methods to forecast daily peak magnitude, time, and shape. The resulting approach provides a reproducible ensemble benchmark against which to evaluate more complex methods. Results indicate that simple regression techniques can perform well and outperform more complicated methods during seasons with low hourly variability, however ensemble methods show higher accuracy overall. The results also highlight the significant impact of extreme weather on forecast accuracy, demonstrating the importance of forecasting processes that are resilient to extreme weather

Mechanisms of action of inhaled fibers, particles and nanoparticles in lung and cardiovascular diseases

<p>Abstract</p> <p>Background</p> <p>A symposium on the mechanisms of action of inhaled airborne particulate matter (PM), pathogenic particles and fibers such as silica and asbestos, and nanomaterials, defined as synthetic particles or fibers less than 100 nm in diameter, was held on October 27 and 28, 2005, at the Environmental Protection Agency (EPA) Conference Center in Research Triangle Park, North Carolina. The meeting was the eighth in a series of transatlantic conferences first held in Penarth, Wales, at the Medical Research Council Pneumoconiosis Unit (1979), that have fostered long-standing collaborations between researchers in the fields of mineralogy, cell and molecular biology, pathology, toxicology, and environmental/occupational health.</p> <p>Results</p> <p>The goal of this meeting, which was largely supported by a conference grant from the NHLBI, was to assemble a group of clinical and basic research scientists who presented and discussed new data on the mechanistic effects of inhaled particulates on the onset and development of morbidity and mortality in the lung and cardiovascular system. Another outcome of the meeting was the elucidation of a number of host susceptibility factors implicated in adverse health effects associated with inhaled pathogenic particulates.</p> <p>Conclusion</p> <p>New models and data presented supported the paradigm that both genetic and environmental (and occupational) factors affect disease outcomes from inhaled particulates as well as cardiopulmonary responses. These future studies are encouraged to allow the design of appropriate strategies for prevention and treatment of particulate-associated morbidity and mortality, especially in susceptible populations.</p

A–C Estrogens as Potent and Selective Estrogen Receptor-Beta Agonists (SERBAs) to Enhance Memory Consolidation under Low-Estrogen Conditions

Estrogen receptor-beta (ERβ) is a drug target for memory consolidation in postmenopausal women. Herein is reported a series of potent and selective ERβ agonists (SERBAs) with in vivo efficacy that are A–C estrogens, lacking the B and D estrogen rings. The most potent and selective A–C estrogen is selective for activating ER relative to seven other nuclear hormone receptors, with a surprising 750-fold selectivity for the β over α isoform and with EC50s of 20–30 nM in cell-based and direct binding assays. Comparison of potency in different assays suggests that the ER isoform selectivity is related to the compound’s ability to drive the productive conformational change needed to activate transcription. The compound also shows in vivo efficacy after microinfusion into the dorsal hippocampus and after intraperitoneal injection (0.5 mg/kg) or oral gavage (0.5 mg/kg). This simple yet novel A–C estrogen is selective, brain penetrant, and facilitates memory consolidation

Synthesis and Evaluation of 4-Cycloheptylphenols as Selective Estrogen Receptor-β Agonists (SERBAs)

A short and efficient route to 4-(4-hydroxyphenyl)cycloheptanemethanol was developed, which resulted in the preparation of a mixture of 4 stereoisomers. The stereoisomers were separated by preparative HPLC, and two of the stereoisomers identified by X-ray crystallography. The stereoisomers, as well as a small family of 4-cycloheptylphenol derivatives, were evaluated as estrogen receptor-beta agonists. The lead compound, 4-(4-hydroxyphenyl)cycloheptanemethanol was selective for activating ER relative to seven other nuclear hormone receptors, with 300-fold selectivity for the β over α isoform and with EC50 of 30–50 nM in cell-based and direct binding assays

Exotic Differentiable Structures and General Relativity

We review recent developments in differential topology with special concern for their possible significance to physical theories, especially general relativity. In particular we are concerned here with the discovery of the existence of non-standard (``fake'' or ``exotic'') differentiable structures on topologically simple manifolds such as $S^7$, \R and $S^3\times {\bf R^1}.$ Because of the technical difficulties involved in the smooth case, we begin with an easily understood toy example looking at the role which the choice of complex structures plays in the formulation of two-dimensional vacuum electrostatics. We then briefly review the mathematical formalisms involved with differentiable structures on topological manifolds, diffeomorphisms and their significance for physics. We summarize the important work of Milnor, Freedman, Donaldson, and others in developing exotic differentiable structures on well known topological manifolds. Finally, we discuss some of the geometric implications of these results and propose some conjectures on possible physical implications of these new manifolds which have never before been considered as physical models.Comment: 11 pages, LaTe