Systematic whole-genome sequencing reveals an unexpected diversity among actinomycetoma pathogens and provides insights into their antibacterial susceptibilities

Mycetoma is a neglected tropical chronic granulomatous inflammatory disease of the skin and subcutaneous tissues. More than 70 species with a broad taxonomic diversity have been implicated as agents of mycetoma. Understanding the full range of causative organisms and their antibiotic sensitivity profiles are essential for the appropriate treatment of infections. The present study focuses on the analysis of full genome sequences and antibiotic inhibitory concentration profiles of actinomycetoma strains from patients seen at the Mycetoma Research Centre in Sudan with a view to developing rapid diagnostic tests. Seventeen pathogenic isolates obtained by surgical biopsies were sequenced using MinION and Illumina methods, and their antibiotic inhibitory concentration profiles determined. The results highlight an unexpected diversity of actinomycetoma causing pathogens, including three Streptomyces isolates assigned to species not previously associated with human actinomycetoma and one new Streptomyces species. Thus, current approaches for clinical and histopathological classification of mycetoma may need to be updated. The standard treatment for actinomycetoma is a combination of sulfamethoxazole/trimethoprim and amoxicillin/clavulanic acid. Most tested isolates had a high IC (inhibitory concentration) to sulfamethoxazole/trimethoprim or to amoxicillin alone. However, the addition of the β-lactamase inhibitor clavulanic acid to amoxicillin increased susceptibility, particularly for Streptomyces somaliensis and Streptomyces sudanensis. Actinomadura madurae isolates appear to have a particularly high IC under laboratory conditions, suggesting that alternative agents, such as amikacin, could be considered for more effective treatment. The results obtained will inform future diagnostic methods for the identification of actinomycetoma and treatment

Mirubactin C rescues the lethal effect of cell wall biosynthesis mutations in Bacillus subtilis

Growth of most rod-shaped bacteria is accompanied by the insertion of new peptidoglycan into the cylindrical cell wall. This insertion, which helps maintain and determine the shape of the cell, is guided by a protein machine called the rod complex or elongasome. Although most of the proteins in this complex are essential under normal growth conditions, cell viability can be rescued, for reasons that are not understood, by the presence of a high (mM) Mg(2+) concentration. We screened for natural product compounds that could rescue the growth of mutants affected in rod-complex function. By screening > 2,000 extracts from a diverse collection of actinobacteria, we identified a compound, mirubactin C, related to the known iron siderophore mirubactin A, which rescued growth in the low micromolar range, and this activity was confirmed using synthetic mirubactin C. The compound also displayed toxicity at higher concentrations, and this effect appears related to iron homeostasis. However, several lines of evidence suggest that the mirubactin C rescuing activity is not due simply to iron sequestration. The results support an emerging view that the functions of bacterial siderophores extend well beyond simply iron binding and uptake

The First Passage Time Problem: Analytical, Numerical and Statistical Methods (with R and Mathematica)

The First Passage Time (FPT) problem corresponds to detect the epoch when a stochastic process crosses a constant or a time varying threshold for the first time. Deriving the density, distribution and moments of this random variable is of paramount interest in many scientific fields and applications, such as probability theory, statistics, finance, neuroscience, psychology, reliability theory, etc. Despite the FPT problem has been widely analytically investigated for unidimensional processes, explicit expressions of the FPT density are available only for the Wiener process, for a special case of the Ornstein-Uhlenbeck (OU) process and of the Cox-IngersollRoss (also known as Feller or square-root) process, and for some processes which can be obtained through suitable measure or spacetime transformations of the previous processes. For other processes it has been proved that the FPT distribution function can be obtained as solution of several different integral equations, which however tend to be very difficult to be solved analytically. This has determined the development of ad hoc numerical methods for the solution of integral equations and related tasks (e.g. equations for the moments) arising from the FPT problem. At the same time, there has been an increasing need to provide algorithms for the simulation of FPTs. Indeed simulations can be used to explore the theoretical properties of the model, as well as to approximate the FPT density, moments and other quantities of interest. But simulations of FPTs arrive with their own set of problems. Apart from pure numerical issues, there is a reasonable chance of missing the exact time of the first crossing when the process is being time discretized. There are possibilities to reduce or even even eliminate this error, e.g. considering bridge processes or sampling from the true FPT distribution, but again formulae and algorithms for this have only been provided for very few processes and most of the time for constant thresholds. Additionally exact simulation is only possible for a small class of processes. For more general ones, one has to rely on approximation schemes. Apart from presenting results scattered around multiple papers in a unified notation, the goal of this thesis is to implement a software that is able to deal with simulation of FPTs from a broad class of processes and general thresholds, numerical computation of results for the FPT of the Wiener, the Ornstein Uhlenbeck and the Feller process, and check for possible measure transformation. A code for checking whether a given diffusion process can be linked back to a Wiener or Feller process has been implemented in Mathematica, while simulations, computations of moments and FPT density approximation have been implemented in Rcpp, which is an interface between the computing environment R [1] and C++, which drastically reduces the computational time in comparison to other R based algorithms.submitted by Bernhard Kepplinger, BScUniversität Linz, Masterarbeit, 2017(VLID)219352

Field testing of repurposed electric vehicle batteries for price-driven grid balancing

Author's accepted manuscript (postprint).Available from 16/11/2020.acceptedVersio

Battery Storage Systems as Grid-Balancing Measure in Low-Voltage Distribution Grids with Distributed Generation

Due to the promoted integration of renewable sources, a further growth of strongly transient, distributed generation is expected. Thus, the existing electrical grid may reach its physical limits. To counteract this, and to fully exploit the viable potential of renewables, grid-balancing measures are crucial. In this work, battery storage systems are embedded in a grid simulation to evaluate their potential for grid balancing. The overall setup is based on a real, low-voltage distribution grid topology, real smart meter household load profiles, and real photovoltaics load data. An autonomous optimization routine, driven by a one-way communicated incentive, determines the prospective battery operation mode. Different battery positions and incentives are compared to evaluate their impact. The configurations incorporate a baseline simulation without storage, a single, central battery storage or multiple, distributed battery storages which together have the same power and capacity. The incentives address either market conditions, grid balancing, optimal photovoltaic utilization, load shifting, or self-consumption. Simulations show that grid-balancing incentives result in lowest peak-to-average power ratios, while maintaining negligible voltage changes in comparison to a reference case. Incentives reflecting market conditions for electricity generation, such as real-time pricing, negatively influence the power quality, especially with respect to the peak-to-average power ratio. A central, feed-in-tied storage performs better in terms of minimizing the voltage drop/rise and shows lower distribution losses, while distributed storages attached at nodes with electricity generation by photovoltaics achieve lower peak-to-average power ratios

Battery Storage Systems as Grid-Balancing Measure in Low-Voltage Distribution Grids with Distributed Generation

Due to the promoted integration of renewable sources, a further growth of strongly transient, distributed generation is expected. Thus, the existing electrical grid may reach its physical limits. To counteract this, and to fully exploit the viable potential of renewables, grid-balancing measures are crucial. In this work, battery storage systems are embedded in a grid simulation to evaluate their potential for grid balancing. The overall setup is based on a real, low-voltage distribution grid topology, real smart meter household load profiles, and real photovoltaics load data. An autonomous optimization routine, driven by a one-way communicated incentive, determines the prospective battery operation mode. Different battery positions and incentives are compared to evaluate their impact. The configurations incorporate a baseline simulation without storage, a single, central battery storage or multiple, distributed battery storages which together have the same power and capacity. The incentives address either market conditions, grid balancing, optimal photovoltaic utilization, load shifting, or self-consumption. Simulations show that grid-balancing incentives result in lowest peak-to-average power ratios, while maintaining negligible voltage changes in comparison to a reference case. Incentives reflecting market conditions for electricity generation, such as real-time pricing, negatively influence the power quality, especially with respect to the peak-to-average power ratio. A central, feed-in-tied storage performs better in terms of minimizing the voltage drop/rise and shows lower distribution losses, while distributed storages attached at nodes with electricity generation by photovoltaics achieve lower peak-to-average power ratios

Hybrid energy storage systems of energy- and power-dense batteries: a survey on modelling techniques and control methods

The impact of global warming and climate change has forced countries to introduce strict policies and decarbonization goals toward sustainable development. To achieve the decarbonization of the economy, a substantial increase of renewable energy sources is required to meed energy demand and to transition away from fossil fuels. However, renewables are sensitive to environmental conditions, which may lead to imbalances between energy supply and demand. Battery energy storage systems are gaining more attention for balancing energy systems in existing grid networks at various levels such as bulk power management, transmission and distribution, and for end-users. Integrating battery energy storage systems with renewables can also solve reliability issues related to transient energy production and be used as a buffer source for electrical vehicle fast charging. Despite these advantages, batteries are still expensive and typically built for a single application – either for an energy- or power-dense application – which limits economic feasibility and flexibility. This paper presents a theoretical approach of a hybrid energy storage system that utilizes both energy- and power-dense batteries serving multiple grid applications. The proposed system will employ second use electrical vehicle batteries in order to maximise the potential of battery waste. The approach is based on a survey of battery modelling techniques and control methods. It was found that equivalent circuit models as well as unified control methods are best suited for modelling hybrid energy storages for grid applications. This approach for hybrid modelling is intended to help accelerate the renewable energy transition by providing reliable energy storage