A novel unspecific peroxygenase from Agaricus bisporus var. bisporus for biocatalytic oxyfunctionalisation reactions

Unspecific peroxygenases (UPOs) represent an emerging class of catalysts for the selective oxyfunctionalisation of C–H- and C = C groups. Until now, only a few UPOs have been characterised. In this study, we report a new peroxygenase identified from the Unspecific Peroxygenase Database. The UPO from Agaricus bisporus var. bisporus (AbvbUPO)...

Edge security in smart inverters: Physical invariants based approach

The endeavour towards making power distribution systems (PDSs) smarter has made the interdependence on communication network indispensable. Further, prospective high penetration of intermittent renewable energy sources in the form of distributed energy resources (DERs) has resulted in the necessity for smart controllers on such DERs....

Estimating ammonia emissions using an adjoint-free 4D-Var approach: Using data assimilation to combine the LOTOS-EUROS model with LML and synthetic IRS satellite observations

Ammonia (NH3) is an important chemical compound in the nitrogen cycle. Ammonia is an essential nutrient and an important part of fertilizer, which in soil leads to increased growth of crops. However, the current excess of NH3 emissions is a hazard to environmental and human health. While ammonia<br/>emissions need to be reduced, the emission...

Volt-VA control using multi-port converters for voltage management in low voltage feeders

The increase in quantity and electrification of energy in residential areas pushes the existing distribution network to its limits. If left unchanged, the network will suffer from voltage violations caused by the increase of electric vehicle (EV) charging, energy generation by Photovoltaics (PV) panels and the phasing out of natural gas....

Recursive Kronecker-based Vector AutoRegressive identification for large-scale adaptive optics

This brief presents an algorithm for the recursive identification of Vector AutoRegressive (VAR) models of large dimensions. We consider a VAR model where the coefficient matrices can be written as a sum of Kronecker products. The algorithm proposed consists of recursively updating the Kronecker factor matrices at each new time step using...

Discovering Clusters in Power Networks from Orthogonal Structure of Spectral Embedding

This paper presents an integrated approach to partition similarity graphs, the task that arises in various contexts in power system studies. The approach is based on orthogonal transformation of row-normalized eigenvectors obtained from spectral clustering to closely fit the axes of the canonical coordinate system. We select the number of...

Variational data assimilation of satellite observations to estimate volcanic ash emissions

Volcanic eruptions release a large amount of volcanic ash, which can pose hazard to human and animal health, land transportation, and aviation safety. Volcanic Ash Transport and Dispersion (VATD) models are critical tools to provide advisory information and timely volcanic ash forecasts. Due to the complexity and the uncertainty of many dynamic...

A Study of Reduced Order 4D-VAR with a Finite Element Shallow Water Model

Forecast models often depend on unknown parameters, such as model initial and boundary conditions, or other tunable parameters not necessarily having any physical meaning. Calibration of these parameters to minimize errors between forecasted and observed states is called data assimilation. A common approach in this context are variational...

Economic Capital for the Trading Book

Economic Capital consists of an internally defined amount of capital that is necessary to over- come adverse market conditions. It plays an important role in risk management and business decisions. This thesis focuses on the Economic Capital of the trading book of an international bank Several types of risks need to be modelled and, in this...

Data Assimilation for Marine Ecosystem Models

In the presence of environmental issues caused by climate change and eutrophication, ecosystem models capable of providing accurate predictions are of considerable interest. Even the most advanced ecological models are not capable of reproducing reality perfectly, therefore it is essential to integrate them with the available observations. Data...

Leading Indicators for the Port of Rotterdam: Identifying and forecasting economic indicators to improve the process of making short-term forecasts for dry bulk throughput in the port of Rotterdam

Economic instability due to the financial crisis has caused major changes in the maritime industry, resulting in high uncertainty for the future. Market trends and developments have become increasingly important indicators for providing expectations for the future of throughput goods in seaports. Managers often use a Forecasting Support System ...

Modelling and Forecasting in the Dry Bulk Shipping Market

This dissertation proposes strategies not only for modelling price behavior in the dry bulk market, but also for modelling relationships between economic and technical variables of dry bulk ships, by using modern time series approaches, Monte Carlo simulation and other economic techniques. The time series modelling techniques, described...

Higher order saddlepoint approximations in the Vasicek portfolio credit loss model

This paper utilizes the saddlepoint approximation as an efficient tool to estimate the portfolio credit loss distribution in the Vasicek model. Value at Risk (VaR), the risk measure chosen in the Basel II Accord for the evaluation of capital requirement, can then be found by inverting the loss distribution. VaR Contribution (VaRC), Expected...