MARGINAL ABATEMENT COST CURVES FOR UK AGRICULTURAL GREENHOUSE GAS EMISSIONS

This paper addresses the challenge of developing a ‘bottom-up’ marginal abatement cost curve (MACC) for greenhouse gas emissions from UK agriculture. A MACC illustrates the costs of specific crop, soil, and livestock abatement measures against a ‘‘business as usual’’ scenario. The results indicate that in 2022 under a specific policy scenario, around 5.38 MtCO2 equivalent (e) could be abated at negative or zero cost. A further 17% of agricultural GHG emissions (7.85 MtCO2e) could be abated at a lower unit cost than the UK Government’s 2022 shadow price of carbon (£34 (tCO2e)-1). The paper discusses a range of methodological hurdles that complicate cost-effectiveness appraisal of abatement in agriculture relative to other sectors.Climate change, Marginal abatement costs, Agriculture, Environmental Economics and Policy, Resource /Energy Economics and Policy, Q52, Q 54, Q58,

Advancing Hardware Security Using Polymorphic and Stochastic Spin-Hall Effect Devices

Protecting intellectual property (IP) in electronic circuits has become a serious challenge in recent years. Logic locking/encryption and layout camouflaging are two prominent techniques for IP protection. Most existing approaches, however, particularly those focused on CMOS integration, incur excessive design overheads resulting from their need for additional circuit structures or device-level modifications. This work leverages the innate polymorphism of an emerging spin-based device, called the giant spin-Hall effect (GSHE) switch, to simultaneously enable locking and camouflaging within a single instance. Using the GSHE switch, we propose a powerful primitive that enables cloaking all the 16 Boolean functions possible for two inputs. We conduct a comprehensive study using state-of-the-art Boolean satisfiability (SAT) attacks to demonstrate the superior resilience of the proposed primitive in comparison to several others in the literature. While we tailor the primitive for deterministic computation, it can readily support stochastic computation; we argue that stochastic behavior can break most, if not all, existing SAT attacks. Finally, we discuss the resilience of the primitive against various side-channel attacks as well as invasive monitoring at runtime, which are arguably even more concerning threats than SAT attacks.Comment: Published in Proc. Design, Automation and Test in Europe (DATE) 201

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images