Robust Computational Frameworks for Power Grid Reliability, Vulnerability and Resilience Analysis

The power grid is one of the largest man-made critical infrastructures. It has been designed to distribute electric power from generating units to residential, commercial and industrial end-users. Due to the continuous increasing of electrical penetration, the availability and reliability of network is of paramount importance. In addition, the continuous increasing of renewable generators posed a further challenges to the stability of the network due to their dependencies on environmental changes, which are drifting weather scenarios towards extremes. Hence, resilience is becoming a major concern for the future power grid. In order to respond promptly to those important changes, the resilience of the such critical infrastructure has to be augmented. This can only be achieved with the availability of robust computational models that allow to design a better network, robustly validated and updated the results. Ideally, a computational framework for the assessment of power grid resilience should capture all the relevant physical interactions between components, subsystems and the system as a whole. Furthermore, uncertain and heterogeneous environmental factors have to be accounted for and their effect on safety-related metrics explicitly modelled and quantified. This is necessary to reveal power grid risks, hazards and identity situation for which an immediate safety and resilience enhancement is necessary. In this thesis, the existing power grid safety-related concepts (i.e. reliability, risk, vulnerability and resilience) and ancillary uncertainty quantification methods are analysed. The major weakness in existing quantification frameworks has been identified as the way a lack of data required by the frameworks and the treatment of such imprecise information. To overcome this limitation, a novel and robust methods for the uncertainty quantification in power grid safety-critical evaluations has been developed. The main contributions of this dissertation are a set of novel tools for the assessment of power grid reliability, vulnerability and resilience and accounting for a rigorous treatment of lack of data uncertainty. These methods have a limited need for artificial model assumptions, which might alter the quality of the available information and, with it, the validity of safety-critical decisions. One of the key elements for a resilient grid is the system ability to learn from past events, improving the grid structure, operations and policies. For this reason, a Reinforcement Learning framework for optimal decision-making under uncertainty has been investigated. This allows to equip the systems with learning capabilities, which is a fundamental component of the resilience concept, and it optimizes operation and maintenance decisions. The developed frameworks can be used to investigate the effect of threatening scenarios (such as extreme weather conditions, multiple contingencies and cascading events) on the grid safety performance. The validity of the approaches has been tested on scaled-down power grids and prognostic health management as well on realistic models of existing systems (e.g. the IEEE reliability test system). These tools provide a valuable contribution to the research community and industrial practitioners as they can help to discern whether the available information suffices to answer a reliability, vulnerability or resilience related question. If the information is limited and additional data has to be gathered, the method informs the decision-maker with the most relevant and sensitive factors, i.e. a basic indication on where to start collecting data so that an expected reduction in uncertainty is maximised

A reinforcement learning framework for optimal operation and maintenance of power grids

International audienc

From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information

In this paper we present a framework for addressing a variety of engineering design challenges with limited empirical data and partial information. This framework includes guidance on the characterisation of a mixture of uncertainties, efficient methodologies to integrate data into design decisions, and to conduct reliability analysis, and risk/reliability based design optimisation. To demonstrate its efficacy, the framework has been applied to the NASA 2020 uncertainty quantification challenge. The results and discussion in the paper are with respect to this application

Lectin-like bacteriocins from pseudomonas spp. utilise D-rhamnose containing lipopolysaccharide as a cellular receptor

Lectin-like bacteriocins consist of tandem monocot mannose-binding domains and display a genus-specific killing activity. Here we show that pyocin L1, a novel member of this family from Pseudomonas aeruginosa, targets susceptible strains of this species through recognition of the common polysaccharide antigen (CPA) of P. aeruginosa lipopolysaccharide that is predominantly a homopolymer of d-rhamnose. Structural and biophysical analyses show that recognition of CPA occurs through the C-terminal carbohydrate-binding domain of pyocin L1 and that this interaction is a prerequisite for bactericidal activity. Further to this, we show that the previously described lectin-like bacteriocin putidacin L1 shows a similar carbohydrate-binding specificity, indicating that oligosaccharides containing d-rhamnose and not d-mannose, as was previously thought, are the physiologically relevant ligands for this group of bacteriocins. The widespread inclusion of d-rhamnose in the lipopolysaccharide of members of the genus Pseudomonas explains the unusual genus-specific activity of the lectin-like bacteriocins

Patients’ Perceptions of Memory Functioning Before and After Surgical Intervention to Treat Medically Refractory Epilepsy.

Purpose:One risk associated with epilepsy surgery is memory loss, but perhaps more important is how patients perceive changes in their memories. This longitudinal study evaluated changes in memory self-reports and investigated how self-reports relate to changes on objective memory measures in temporal or extratemporal epilepsy patients who underwent surgery. Methods: Objective memory (Wechsler Memory Scale–Revised) and subjective memory self-reports (Memory Assessment Clinics Self-Rating Scale) were individually assessed for 136 patients ∼6 months before and 6 months after surgery. A measure of depressive affect (Beck Depression Inventory–2nd Edition) was used to control variance attributable to emotional distress. Results: Despite a lack of significant correlational relationships between objective and subjective memory for the entire sample, significant correlations between objective memory scores and self-reports did emerge for a subset of patients who evidenced memory decline. Differences also were found in the subjective memory ratings of temporal lobe versus extratemporal patients. Temporal lobe patients rated their memories more negatively than did extratemporal patients and were more likely to report significant improvements in their memory after surgery. Conclusions: In general, patients were not accurate when rating their memories compared to other adults. However, patients with significant declines in their memories were sensitive to actual changes in their memories over time relative to their own personal baselines

Imaging of Bubonic Plague Dynamics by In Vivo Tracking of Bioluminescent Yersinia pestis

Yersinia pestis dissemination in a host is usually studied by enumerating bacteria in the tissues of animals sacrificed at different times. This laborious methodology gives only snapshots of the infection, as the infectious process is not synchronized. In this work we used in vivo bioluminescence imaging (BLI) to follow Y. pestis dissemination during bubonic plague. We first demonstrated that Y. pestis CO92 transformed with pGEN-luxCDABE stably emitted bioluminescence in vitro and in vivo, while retaining full virulence. The light produced from live animals allowed to delineate the infected organs and correlated with bacterial loads, thus validating the BLI tool. We then showed that the first step of the infectious process is a bacterial multiplication at the injection site (linea alba), followed by a colonization of the draining inguinal lymph node(s), and subsequently of the ipsilateral axillary lymph node through a direct connection between the two nodes. A mild bacteremia and an effective filtering of the blood stream by the liver and spleen probably accounted for the early bacterial blood clearance and the simultaneous development of bacterial foci within these organs. The saturation of the filtering capacity of the spleen and liver subsequently led to terminal septicemia. Our results also indicate that secondary lymphoid tissues are the main targets of Y. pestis multiplication and that colonization of other organs occurs essentially at the terminal phase of the disease. Finally, our analysis reveals that the high variability in the kinetics of infection is attributable to the time the bacteria remain confined at the injection site. However, once Y. pestis has reached the draining lymph nodes, the disease progresses extremely rapidly, leading to the invasion of the entire body within two days and to death of the animals. This highlights the extraordinary capacity of Y. pestis to annihilate the host innate immune response

Novel insights into the genomic basis of citrus canker based on the genome sequences of two strains of Xanthomonas fuscans subsp. aurantifolii

Background: Citrus canker is a disease that has severe economic impact on the citrus industry worldwide. There are three types of canker, called A, B, and C. The three types have different phenotypes and affect different citrus species. The causative agent for type A is Xanthomonas citri subsp. citri, whose genome sequence was made available in 2002. Xanthomonas fuscans subsp. aurantifolii strain B causes canker B and Xanthomonas fuscans subsp. aurantifolii strain C causes canker C. Results: We have sequenced the genomes of strains B and C to draft status. We have compared their genomic content to X. citri subsp. citri and to other Xanthomonas genomes, with special emphasis on type III secreted effector repertoires. In addition to pthA, already known to be present in all three citrus canker strains, two additional effector genes, xopE3 and xopAI, are also present in all three strains and are both located on the same putative genomic island. These two effector genes, along with one other effector-like gene in the same region, are thus good candidates for being pathogenicity factors on citrus. Numerous gene content differences also exist between the three cankers strains, which can be correlated with their different virulence and host range. Particular attention was placed on the analysis of genes involved in biofilm formation and quorum sensing, type IV secretion, flagellum synthesis and motility, lipopolysacharide synthesis, and on the gene xacPNP, which codes for a natriuretic protein. Conclusion: We have uncovered numerous commonalities and differences in gene content between the genomes of the pathogenic agents causing citrus canker A, B, and C and other Xanthomonas genomes. Molecular genetics can now be employed to determine the role of these genes in plant-microbe interactions. The gained knowledge will be instrumental for improving citrus canker control.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Conselho Nacional de Desenvolvimento CientIfico e Tecnologico (CNPq)Coordenacao para Aperfeicoamento de Pessoal de Ensino Superior (CAPES)Fundo de Defesa da Citricultura (FUNDECITRUS

Cyclic-di-GMP regulates lipopolysaccharide modification and contributes to Pseudomonas aeruginosa immune evasion

Pseudomonas aeruginosa is a Gram-negative bacterial pathogen associated with acute and chronic infections. The universal c-di-GMP second messenger is instrumental in the switch from a motile lifestyle to resilient biofilm as in the cystic fibrosis lung. The SadC diguanylate cyclase is associated with this patho-adaptive transition. Here we identified an unrecognized SadC partner, WarA, which we show is a methyltransferase in complex with a putative kinase WarB. We established that WarA binds to c-di-GMP, which potentiates its methyltransferase activity. Together, WarA and WarB have structural similarities with the bi-functional Escherichia coli LPS O antigen regulator WbdD. Strikingly, WarA influences P. aeruginosa O antigen modal distribution and interacts with the LPS biogenesis machinery. LPS is known to modulate the immune response in the host, and by using a zebrafish infection model, we implicate WarA in the ability of P. aeruginosa to evade detection by the host.BBSRC & Wellcome Trus