Supersymmetric extension of universal enveloping vertex algebras

In this paper, we study the construction of the supersymmetric extensions of vertex algebras. In particular, for $N = n \in \mathbb{Z}_{+}$, we show the universal enveloping $N = n$ supersymmetric (SUSY) vertex algebra of an $N = n$ SUSY Lie conformal algebra can be extended to an $N = n' > n$ SUSY vertex algebra. We also show the $N = 2$ SUSY affine vertex algebra of level $0$ associated with a Lie superalgebra, which is an $N = 2$ SUSY extension of the affine vertex algebra of level $0$, can be embedded as an $N = 2$ SUSY vertex subalgebra into an $N = 2$ superconformal vertex algebra.Comment: 25 pages; added references and some comments in section

commodities and environmental impacts in an ecological–economic model

Abstract In contrast to macroscopic tools, life cycle assessment (LCA) starts from the microstructure of an economic system: the production and consumption of functional flows. Due to the level of resolution required for function-level details, the model used for LCA has relied on process-specific data and has treated the product system as a stand-alone system instead of a system embedded within a broader economic system. This separation causes various problems, including incompleteness of the system and loss of applicability for a variety of analytical tools developed for LCA or economic models. This study aims to link the functional flow-based, micro-level LCA system to its embedding, commodity-based, meso-or macro-level economic system represented by input -output accounts, resulting in a comprehensive ecological -economic model within a consistent and flexible mathematical framework. For this purpose, the LCA computational structure is reformulated into a functional flow by process framework and reintroduced in the context of the input -output tradition. It is argued that the model presented here overcomes the problem of incompleteness of the system and enables various analytical tools developed for LCA or inputoutput analysis (IOA) to be utilised for further analysis. The applicability of the model for cleaner production and supply chain management is demonstrated using a simplified product system and structural path analysis as an example.

Water Embodied in Bioethanol in the United States

Prior studies have estimated that a liter of bioethanol requires 263−784 L of water from corn farm to fuel pump, but these estimates have failed to account for the widely varied regional irrigation practices. By using regional time-series agricultural and ethanol production data in the U.S., this paper estimates the state-level field-to-pump water requirement of bioethanol across the nation. The results indicate that bioethanol’s water requirements can range from 5 to 2138 L per liter of ethanol depending on regional irrigation practices. The results also show that as the ethanol industry expands to areas that apply more irrigated water than others, consumptive water appropriation by bioethanol in the U.S. has increased 246% from 1.9 to 6.1 trillion liters between 2005 and 2008, whereas U.S. bioethanol production has increased only 133% from 15 to 34 billion liters during the same period. The results highlight the need to take regional specifics into account when implementing biofuel mandates

Measuring Ecological Impact of Water Consumption by Bioethanol Using Life Cycle Impact Assessment

Purpose Though the development of biofuel has attracted numerous studies for quantifying potential water demand applying life cycle thinking, the impacts of biofuel water consumption still remain unknown. In this study, we aimed to quantify ecological impact associated with corn-based bioethanol water consumption in Minnesota in responding to different refinery expansion scenarios by applying a life cycle impact assessment method. Methods This ecological damage assessment method for quantifying water consumption impacts was proposed by Pfister et al. in 2009 (Environ Sci Technol 43: 4098–4104, 2009) using an impact characterization factor integrating terrestrial net primary production and precipitation. In this study, we derived the spatially explicit eco-damage characterization factors for 81 watersheds in Minnesota and compiled location-specific water consumption data for all current and planned bioethanol production facilities and feedstock production. The ecological damage caused by bioethanol production (ΔEQEtOH in m2⋅yr) was then calculated on both watershed and refinery-plant levels. Additional refinery expansion scenarios were established for testing the effectiveness in changing ΔEQEtOH. Results and discussion The results show that ecological impact ΔEQEtOH varied by more than a factor of 3 between watersheds. Minnesota consumed 40 billion liters of water to produce 2.3 billion liters of ethanol as of 2007 (17 L water per liter of ethanol). The geographical distribution of ΔEQEtOH was shown to be uneven with a cluster of high-impact regions around the center of the state. The planned refinery expansion is expected to increase the state’s corn ethanol production capacity by 75% and ΔEQEtOH by 65%. However, strategically locating the planned expansion in the low-impact areas is expected to minimize the increases in ΔEQEtOH down to 19% from 65%. Conclusions The scenario analysis shows that strategically sourcing corn from low-impact regions can result in significantly less water use impact compared to a baseline scenario. The results indicate that employing the water consumption impact assessment can provide additional insights in policy making. The environmental impacts related to the change of plant infrastructure and agricultural practices associated with the development of the renewable energy industry should be considered as well for identifying the most sustainable alternatives

TPU as Cryptographic Accelerator

Polynomials defined on specific rings are heavily involved in various cryptographic schemes, and the corresponding operations are usually the computation bottleneck of the whole scheme. We propose to utilize TPU, an emerging hardware designed for AI applications, to speed up polynomial operations and convert TPU to a cryptographic accelerator. We also conduct preliminary evaluation and discuss the limitations of current work and future plan