Environmental Contaminant Concentrations in Canada Goose (\u3ci\u3eBranta canadensis\u3c/i\u3e) Muscle: Probabilistic Risk Assessment for Human Consumers

The issue of food insecurity affects millions of people in the United States every year. Often these people rely on soup kitchens, food banks, and shelters for proper meals, and these organizations often depend on donations to meet needs. One of the most limited food resources is meat. To help alleviate this problem, the U.S. Department of Agriculture Wildlife Services donates more than 60 tons of wild game (deer, moose, feral hogs, goats, geese, and ducks) to a variety of charitable organizations each year. Although commercially produced meat routinely undergoes screening for contaminants, potential exposure to environmental contaminants from eating wild game is not well characterized. In this study, the concentration of 17 contaminants of concern in the breast meat of wild geese was examined. These concentrations were then used in a probabilistic model to estimate potential risk associated with consumption of this meat. Based on model predictions, more than 99% of all adults were below exposure limits for all of the compounds tested. For all consumer age classes modeled, consumption of wild goose meat may expose a small fraction of these populations to levels of lead higher than the recommended exposure limits. Similarly, mercury exposure was predicted to be higher than the recommended limits when the meat was served as steaks. This information about concentrations of contaminants of concern in goose meat and potential exposures associated with meat consumption based on probabilistic models will enable others to make informed decisions about the risks associated with the consumption of wild meat

A probablistic analysis of the Game of the Goose

We analyse the traditional board game the Game of the Goose. We are particularly interested in the probability of the different players to win. We show that we can determine these probabilities for up to six players. Our original motivation to investigate this game came from progress in stochastic process theories which prompted us to ask ourselves whether those methods are capable of dealing with well known probabilistic games. As these games have large state spaces, this is not trivial. As a side effect we found that common wisdom about this game is not true

Environmental Contaminant Concentrations in Canada Goose (\u3ci\u3eBranta canadensis\u3c/i\u3e) Muscle: Probabilistic Risk Assessment for Human Consumers

The issue of food insecurity affects millions of people in the United States every year. Often these people rely on soup kitchens, food banks, and shelters for proper meals, and these organizations often depend on donations to meet needs. One of the most limited food resources is meat. To help alleviate this problem, the U.S. Department of Agriculture Wildlife Services donates more than 60 tons of wild game (deer, moose, feral hogs, goats, geese, and ducks) to a variety of charitable organizations each year. Although commercially produced meat routinely undergoes screening for contaminants, potential exposure to environmental contaminants from eating wild game is not well characterized. In this study, the concentration of 17 contaminants of concern in the breast meat of wild geese was examined. These concentrations were then used in a probabilistic model to estimate potential risk associated with consumption of this meat. Based on model predictions, more than 99% of all adults were below exposure limits for all of the compounds tested. For all consumer age classes modeled, consumption of wild goose meat may expose a small fraction of these populations to levels of lead higher than the recommended exposure limits. Similarly, mercury exposure was predicted to be higher than the recommended limits when the meat was served as steaks. This information about concentrations of contaminants of concern in goose meat and potential exposures associated with meat consumption based on probabilistic models will enable others to make informed decisions about the risks associated with the consumption of wild meat

Caching-based Multicast Message Authentication in Time-critical Industrial Control Systems

Attacks against industrial control systems (ICSs) often exploit the insufficiency of authentication mechanisms. Verifying whether the received messages are intact and issued by legitimate sources can prevent malicious data/command injection by illegitimate or compromised devices. However, the key challenge is to introduce message authentication for various ICS communication models, including multicast or broadcast, with a messaging rate that can be as high as thousands of messages per second, within very stringent latency constraints. For example, certain commands for protection in smart grids must be delivered within 2 milliseconds, ruling out public-key cryptography. This paper proposes two lightweight message authentication schemes, named CMA and its multicast variant CMMA, that perform precomputation and caching to authenticate future messages. With minimal precomputation and communication overhead, C(M)MA eliminates all cryptographic operations for the source after the message is given, and all expensive cryptographic operations for the destinations after the message is received. C(M)MA considers the urgency profile (or likelihood) of a set of future messages for even faster verification of the most time-critical (or likely) messages. We demonstrate the feasibility of C(M)MA in an ICS setting based on a substation automation system in smart grids.Comment: For viewing INFOCOM proceedings in IEEE Xplore see https://ieeexplore.ieee.org/abstract/document/979676

A multi-isotope (δ13C, δ15N, δ34S, δ2H) approach to establishing migratory connectivity in lesser snow geese: Tracking an overabundant species

Expanding populations of North American midcontinent lesser snow geese (Anser caerulescens caerulescens) have potential to alter ecosystems throughout the Arctic and subarctic where they breed. Efforts to understand origins of harvested lesser snow geese to better inform management decisions have traditionally required mark-recapture approaches, while aerial photographic surveys have typically been used to identify breeding distributions. As a potential alternative, isotopic patterns that are metabolically fixed within newly grown flight feathers following summer molting could provide inferences regarding geographic breeding origin of individuals, without the need for prior capture. Our objective was to assess potential to use four stable isotopes (δ13C, δ15N, δ34S, δ2H) from feather material to determine breeding origins. We obtained newly grown flight feathers from individuals during summer banding at three Arctic and two subarctic breeding colonies in 2014 (n = 56) and 2016 (n = 45). We used linear discriminant analyses to predict breeding origins from models using combinations of stable isotopes as predictors and evaluated model accuracy when predicting colony, subregion, or subpopulation levels. We found a strong inverse relationship between δ2H values and increasing latitude (R2 = 0.83), resulting in differences (F4, 51 = 90.41, P \u3c 0.0001) among sampled colonies. No differences in δ13C or δ15N were detected among colonies, although δ34S in Akimiski Island, Baffin Island, and Karrak Lake were more enriched (F4, 51 = 11.25, P \u3c 0.0001). Using δ2H values as a predictor, discriminant analyses improved accuracy in classification level as precision decreased [model accuracy = 67% (colony), 88% (subregion), 94% (subpopulation)]. Application of the isotopic methods we describe could be used to provide an alternative monitoring method of population metrics, such as overall breeding population distribution, region-specific productivity and migratory connectivity that are informative to management decision makers and provide insight into cross-seasonal effects that may influence migratory behavior

Securing Restricted Publisher-Subscriber Communications in Smart Grid Substations

Smart Grid applications require accurate and correct data transmission from publisher to subscribers with critical communication latency requirements. Since the smart grid is being supported by distributed communication networks, deployed using various wired and wireless technologies, including IP-based networks, securing the communication infrastructure is both critically important and challenging. In this paper, we propose a secure and efficient data delivery scheme, based on a restricted yet dynamic publisher-subscriber architecture, for the published messages from a publisher to the subscribers distributed in the smart grid network. The scheme ensures that the published message is delivered from an authentic publisher to only those authorized subscribers by verifying publisher's signature and access structure of all subscribers. Operation overheads are reduced by performing only one encryption and decryption or hashing per subscriber location using a proxy node as a remote terminal unit. Our analysis shows that the scheme is resistant against replay, man-in-the-middle, and impersonation attacks. Performance evaluation shows that the scheme can support 600 subscribers given the communication latency requirement of 3 ms. We provide the performance of the scheme under different scenarios, and observe that the efficiency of our scheme increases as the ratio of the geographical locations within a substation to the number of subscribers increases