The downstream product transformation of lignin depolymerization is of great interest in the production of high-value aromatic chemicals. However, this transformation is often impeded by chemical oxidation under harsh reaction conditions. In this study, we demonstrate that hypohalites generated in situ by the vanadium-containing chloroperoxidase from Curvularia inaequalis (CiVCPO) can halogenate various electron-rich and electron-poor phenol and phenolic acid substrates. Specifically, CiVCPO enabled decarboxylative halogenation, deformylative halogenation, halogenation, and direct oxidation reactions. The versatile transformation routes for the valorization of phenolic compounds showed up to 99% conversion and 99% selectivity, with a turnover number of 60,700 and a turnover frequency of 60 s^-1 for CiVCPO. This study potentially expands the biocatalytic toolbox for lignin valorization.

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Recently, the edge resource provisioning schemes were defined considering the low-latency Mobile Edge Computing (MEC) paradigm. Most of these models only consider batterypowered devices like smart-phones, thus are agnostic to the
energy harvesting techniques that achieves a green MEC system. Further, most of the studies on MEC assume unlimited edge resources which is not the case as it is with the conventional data-centers (public clouds). Hence, unrestricted use of edge resources is not ideal. This work mainly considers two problems: (1) the offloading of data traffic from the Internet of Things (IoT) devices that rely on energy harvesting to the MEC entities and (2) assignment of the resources at the MEC. The novelty of this paper lies in the energy scavenging based architecture
that is developed over the Contiki OS. Secondly, saving the energy for computations to maximize the lifetime of the sensing nodes by performing the execution of the computationallyintensive tasks at the edge which is a single hop away. The proposed architecture uses the ambient triggers to form the sensor network and establish links with computationally capable resources located at the edge. Further, a mathematical model to manage the resources at the edge is proposed. Finally, we evaluate a threshold-policy for optimizing the resources participating in an edge computation service for an IoT scenario and discuss the
improvements achieved.@en

N ext Generation Gravity Missions (NGGMs) expected to be launched in the mid-term future have set high anticipations for an enhanced monitoring of mass transport in the Earth system, establishing their products applicable to new scientific fields and serving societal needs. The European Space Agency (ESA) has issued several studies on concepts of NGGMs. Following this tradition, the project “Additional Constellations & Scientific Analysis Studies of the Next Generation Gravity Mission” picks up where the previous study ESA-SC4MGV left off. One of the ESA-ADDCON project objectives is to investigate the impact of different orbit configurations and parameters on the gravity field retrieval. Given a two-pair Bender-type constellation, consisting of a polar and an inclined pair, choices for orbit design such as the altitude profile during mission lifetime, the length of retrieval period, the value of sub-cycles and the choice of a prograde over a retrograde orbit are investigated. Moreover, the problem of aliasing due to ocean tide model inaccuracies, as well as methods for mitigating their effect on gravity field solutions are investigated in the context of NGGMs. The performed simulations make use of the gravity field processing approach where low-resolution gravity field solutions are co-parameterized in short-term periods (e.g. daily) together with the long-term solutions (e.g. 11-day solution). This method proved to be beneficial for NGGMs (ESA-SC4MGV project) since the enhanced spatio-temporal sampling enables a selfde- aliasing of high-frequency atmospheric and oceanic signals, which may now be a part of the retrieved signal. The @en