Coming into the Anthropocene

This essay reviews Professor Jonathan Cannon’s Environment in the Balance. Cannon’s book admirably analyzes the Supreme Court’s uptake of, or refusal of, the key commitments of the environmental-law revolution of the early 1970s. In some areas the Court has adapted old doctrines, such as Standing and Commerce, to accommodate ecological insights; in other areas, such as Property, it has used older doctrines to restrain the transformative effects of environmental law. After surveying Cannon’s argument, this review diagnoses the historical moment that has made the ideological division that Cannon surveys especially salient: a time of stalled legislation, political deadlock, and highly contested regulatory and judicial interpretation. This analysis, however, does not limit the interest of Cannon’s analysis to this political moment. Rather, Cannon’s integration of legal and cultural analysis has great promise for the Anthropocene, the dawning era when human decisions and values will be among the most important forces shaping the planet. In the future, it will be necessary to think of environmental law as both reflecting and producing ideas of the value and meaning of the natural world. Cannon’s analysis is an excellent starting point for an Anthropocene approach

The speed of sequential asymptotic learning

In the classical herding literature, agents receive a private signal regarding a binary state of nature, and sequentially choose an action, after observing the actions of their predecessors. When the informativeness of private signals is unbounded, it is known that agents converge to the correct action and correct belief. We study how quickly convergence occurs, and show that it happens more slowly than it does when agents observe signals. However, we also show that the speed of learning from actions can be arbitrarily close to the speed of learning from signals. In particular, the expected time until the agents stop taking the wrong action can be either finite or infinite, depending on the private signal distribution. In the canonical case of Gaussian private signals we calculate the speed of convergence precisely, and show explicitly that, in this case, learning from actions is significantly slower than learning from signals

Exploring Blockchain Adoption Supply Chains: Opportunities and Challenges

Acquisition Management / Grant technical reportAcquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsIn modern supply chains, acquisition often occurs with the involvement of a network of organizations. The resilience, efficiency, and effectiveness of supply networks are crucial for the viability of acquisition. Disruptions in the supply chain require adequate communication infrastructure to ensure resilience. However, supply networks do not have a shared information technology infrastructure that ensures effective communication. Therefore decision-makers seek new methodologies for supply chain management resilience. Blockchain technology offers new decentralization and service delegation methods that can transform supply chains and result in a more flexible, efficient, and effective supply chain. This report presents a framework for the application of Blockchain technology in supply chain management to improve resilience. In the first part of this study, we discuss the limitations and challenges of the supply chain system that can be addressed by integrating Blockchain technology. In the second part, the report provides a comprehensive Blockchain-based supply chain network management framework. The application of the proposed framework is demonstrated using modeling and simulation. The differences in the simulation scenarios can provide guidance for decision-makers who consider using the developed framework during the acquisition process.Approved for public release; distribution is unlimited

The Quantitative Significance of the Transsulfuration Enzymes for H2S Production in Murine Tissues

The enzymes of the transsulfuration pathway, cystathionine --synthase (CBS) and cystathionine --lyase (CSE), are important for the endogenous production of hydrogen sulfide (H2S), a gaseous signaling molecule. The relative contributions of CBS and CSE to H2S generation in different tissues are not known. In this study, we report quantification of CBS and CSE in murine liver and kidney and their contribution to H2S generation in these tissues and in brain at saturating substrate concentrations. We show that CBS protein levels are significantly lower than those of CSE; 60-fold and 20-fold in liver and kidney, respectively. Each enzyme is more abundant in liver compared with kidney, twofold and sixfold for CBS and CSE, respectively. At high substrate concentrations (20-mM each cysteine and homocysteine), the capacity for liver H2S production is approximately equal for CBS and CSE, whereas in kidney and brain, CBS constitutes the major source of H2S, accounting for -80% and -95%, respectively, of the total output. At physiologically relevant concentrations of substrate, and adjusting for the differences in CBS versus CSE levels, we estimate that CBS accounts for only 3% of H2S production by the transsulfuration pathway enzymes in liver. Antioxid. Redox Signal. 15, 363-372.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90506/1/ars-2E2010-2E3781.pd

Continuous Processing and Efficient in Situ\textit{in Situ} Reaction Monitoring of a Hypervalent Iodine(III) Mediated Cyclopropanation Using Benchtop NMR Spectroscopy

Real-time NMR spectroscopy has proven to be a rapid and an effective monitoring tool to study the hypervalent iodine(III) mediated cyclopropanation. With the ever increasing number of new synthetic methods for carbon−carbon bond formation, the NMR $\textit{in situ}$ monitoring of reactions is becoming a highly desirable enabling method. In this study, we have demonstrated the versatility of benchtop NMR using inline and online real-time monitoring methods to access mutually complementary information for process understanding, and we developed new approaches for real-time monitoring addressing challenges associated with better integration into continuous processes.University of Cambridge (Daphne Jackson Fellowship), iCON through CMAC (Grant ID: RG74817), Engineering and Physical Sciences Research Council (Critical Mass grant (Grant ID: EP/K009494K/1), Core Capability grant (Grant ID: EP/K039520/1

Toward sustainable serverless computing

Although serverless computing generally involves executing short-lived “functions,” the increasing migration to this computing paradigm requires careful consideration of energy and power requirements. serverless computing is also viewed as an economically-driven computational approach, often influenced by the cost of computation, as users are charged for per-subsecond use of computational resources rather than the coarse-grained charging that is common with virtual machines and containers. To ensure that the startup times of serverless functions do not discourage their use, resource providers need to keep these functions hot, often by passing in synthetic data. We describe the real power consumption characteristics of serverless, based on execution traces reported in the literature, and describe potential strategies (some adopted from existing VM and container-based approaches) that can be used to reduce the energy overheads of serverless execution. Our analysis is, purposefully, biased toward the use of machine learning workloads because: (1) workloads are increasingly being used widely across different applications; (2) functions that implement machine learning algorithms can range in complexity from long-running (deep learning) versus short-running (inference only), enabling us to consider serverless across a variety of possible execution behaviors. The general findings are easily translatable to other domains.PostprintPeer reviewe

Gravitational Collapse of Dust with a Cosmological Constant

The recent analysis of Markovic and Shapiro on the effect of a cosmological constant on the evolution of a spherically symmetric homogeneous dust ball is extended to include the inhomogeneous and degenerate cases. The histories are shown by way of effective potential and Penrose-Carter diagrams.Comment: 2 pages, 2 figures (png), revtex. To appear in Phys. Rev.

Majority Dynamics and Aggregation of Information in Social Networks

Consider n individuals who, by popular vote, choose among q >= 2 alternatives, one of which is "better" than the others. Assume that each individual votes independently at random, and that the probability of voting for the better alternative is larger than the probability of voting for any other. It follows from the law of large numbers that a plurality vote among the n individuals would result in the correct outcome, with probability approaching one exponentially quickly as n tends to infinity. Our interest in this paper is in a variant of the process above where, after forming their initial opinions, the voters update their decisions based on some interaction with their neighbors in a social network. Our main example is "majority dynamics", in which each voter adopts the most popular opinion among its friends. The interaction repeats for some number of rounds and is then followed by a population-wide plurality vote. The question we tackle is that of "efficient aggregation of information": in which cases is the better alternative chosen with probability approaching one as n tends to infinity? Conversely, for which sequences of growing graphs does aggregation fail, so that the wrong alternative gets chosen with probability bounded away from zero? We construct a family of examples in which interaction prevents efficient aggregation of information, and give a condition on the social network which ensures that aggregation occurs. For the case of majority dynamics we also investigate the question of unanimity in the limit. In particular, if the voters' social network is an expander graph, we show that if the initial population is sufficiently biased towards a particular alternative then that alternative will eventually become the unanimous preference of the entire population.Comment: 22 page

3D virtual planning of temporomandibular joint ankylosis using computed tomography a case report in a 4-year-old female patient

Ankylosis is a Greek word meaning a stiff joint. Temporomandibular joint (TMJ) ankylosis is the development of complete or incomplete limitation of movement of the TMJ by bone or fi brous tissue. The etiology and treatment of TMJ ankylosis have been well documented in the literature, with trauma and infection being the leading causes.Radiographically, ankylosis presents features that facilitate the diagnosis. However, its visualization is not precise involving conventional radiographic technique. With the evolution of radiographic techniques, computed tomography (CT) became an essential tool in the diagnosis of the ankylosis of TMJ and presented a valid reconstructed image of an ankylosis. The aim of this paper is to report a case of TMJ ankylosis in a 4-year-old girl and describe the importance tomographic images related ankylosis of TMJ by threedimensional (3D) CT, using several slices as axial, coronal, and 3D reformatted images as a guide for presurgical treatment planning of an ankylosis