Humidity, huddling & the hibernation energetics of big brown bats (Eptesicus fuscus)

During winter, many mammals hibernate and lower their body temperature and metabolic rate (MR) in prolonged periods of torpor. Hibernators will use energetically expensive arousals (i.e., restore body temperature and MR) presumably to re-establish water balance. Some hibernating mammals however will huddle in groups, possibly to decrease energetic costs and total evaporative water loss (EWL), although the benefit is not fully understood. Research on the relationship between behaviour, physiology, water loss, and energy expenditure of bats during hibernation is especially important because of a fungal disease called white-nose syndrome (WNS). To date, 12 North American bat species are affected by WNS, however big brown bats (Eptesicus fuscus) appear resistant, although the underlying mechanism is poorly understood. The overall objective of my thesis was to understand the influence of humidity and huddling on the behavioural and physiological responses of hibernating big brown bats. To test my hypotheses, I used a captive colony of hibernating big brown bats (n = 20). Specifically, for Chapter 2, I first tested the hypothesis that big brown bats adjust huddling and drinking behaviour depending on humidity, to maintain a consistent pattern of periodic arousals, and therefore energy balance during hibernation. I found that bats hibernating in a dry environment did not differ in arousal/torpor bout frequency, or torpor bout duration throughout hibernation but drank at twice the rate as bats in a humid environment. Bats in the dry treatment also had shorter arousals, and huddled in a denser huddle, potentially to reduce rates of total EWL. During late hibernation, for Chapter 3, I used open-flow respirometry to test two additional hypotheses, first that phenotypic flexibility in total EWL helps explain the tolerance of hibernating big brown bats for a wide range of humidity relative to other bat species. I found that dry-acclimated bats had lower rates of total EWL, compared to bats acclimated to humid conditions. I then tested the second hypothesis that big brown bats can use huddling to mitigate the challenge of dry conditions. I found that, for humid-acclimated bats, rates of total EWL were reduced with huddling bats but there was no effect of huddling on EWL for bats acclimated to dry conditions. These results suggest that the ability of big brown bats to reduce rates of total EWL through acclimation may reduce the need to huddle with conspecifics to avoid water loss and thus dehydration. Overall, my thesis suggests that big brown bats use both behavioural and physiological mechanisms to reduce water loss which could allow them to exploit habitats for hibernation that are unavailable to other bat species and could also help explain their apparent resistance to WNS.Natural Sciences and Engineering Research Council University of Winnipeg Graduate StudiesMaster of Science in Bioscience, Technology, and Public Polic

PRP Rebooted: Advancing the State of the Art in FOND Planning

Fully Observable Non-Deterministic (FOND) planning is a variant of classical symbolic planning in which actions are nondeterministic, with an action's outcome known only upon execution. It is a popular planning paradigm with applications ranging from robot planning to dialogue-agent design and reactive synthesis. Over the last 20 years, a number of approaches to FOND planning have emerged. In this work, we establish a new state of the art, following in the footsteps of some of the most powerful FOND planners to date. Our planner, PR2, decisively outperforms the four leading FOND planners, at times by a large margin, in 17 of 18 domains that represent a comprehensive benchmark suite. Ablation studies demonstrate the impact of various techniques we introduce, with the largest improvement coming from our novel FOND-aware heuristic.Comment: 13 pages, 4 figures, AAAI conference paper Update: Fixed abstract and typo

Parameterized Compilation Lower Bounds for Restricted CNF-formulas

We show unconditional parameterized lower bounds in the area of knowledge compilation, more specifically on the size of circuits in decomposable negation normal form (DNNF) that encode CNF-formulas restricted by several graph width measures. In particular, we show that - there are CNF formulas of size $n$ and modular incidence treewidth $k$ whose smallest DNNF-encoding has size $n^{\Omega(k)}$, and - there are CNF formulas of size $n$ and incidence neighborhood diversity $k$ whose smallest DNNF-encoding has size $n^{\Omega(\sqrt{k})}$. These results complement recent upper bounds for compiling CNF into DNNF and strengthen---quantitatively and qualitatively---known conditional low\-er bounds for cliquewidth. Moreover, they show that, unlike for many graph problems, the parameters considered here behave significantly differently from treewidth

Sexual Nostalgia as a Response to Unmet Sexual and Relational Needs: The Role of Attachment Avoidance

Romantic relationships help people meet needs for connection and emotional and sexual fulfillment. In the current research, we investigate an unexplored response to feeling sexually and relationally unfulfilled: reflecting on positive sexual experiences with past partners (or sexual nostalgia). Across three studies, people low in attachment avoidance (i.e., comfortable with closeness) who were (a) single or (b) sexually or relationally dissatisfied reported greater sexual nostalgia, whereas people high in attachment avoidance (i.e., value autonomy) did not calibrate their feelings of sexual nostalgia based on their current relationship status or satisfaction. Sexual fantasies about past partners (i.e., sexual nostalgia) were distinct from other types of sexual fantasies (Study 1) and the effects could not be attributed to general nostalgia (Study 2) or sexual desire (Study 3). Chronic sexual nostalgia detracted from satisfaction over time. The findings have implications for theories of nostalgia and attachment and for managing unfulfilled needs in relationships

Computing Contingent Plans via Fully Observable Non-Deterministic Planning

Planning with sensing actions under partial observability is a computationally challenging problem that is fundamental to the realization of AI tasks in areas as diverse as robotics, game playing, and diagnostic problem solving. Recent work on generating plans for partially observable domains has advocated for online planning, claiming that offline plans are often too large to generate. Here we push the envelope on this challenging problem, proposing a technique for generating conditional (aka contingent) plans offline. The key to our planner's success is the reliance on state-of-the-art techniques for fully observable non-deterministic (FOND) planning. In particular, we use an existing compilation for converting a planning problem under partial observability and sensing to a FOND planning problem. With a modified FOND planner in hand, we are able to scale beyond previous techniques for generating conditional plans with solutions that are orders of magnitude smaller than previously possible in some domains

Non-Deterministic Planning With Conditional Effects

Recent advances in fully observable non-deterministic (FOND) planning have enabled new techniques for various applications, such as behaviour composition, among others. One key limitation of modern FOND planners is their lack of native support for conditional effects. In this paper we describe an extension to PRP, the current state of the art in FOND planning, that supports the generation of policies for domains with conditional effects and non-determinism. We present core modifications to the PRP planner for this en-hanced functionality without sacrificing soundness and com-pleteness. Additionally, we demonstrate the planner’s capa-bilities on a variety of benchmarks that include actions with both conditional effects and non-deterministic outcomes. The resulting planner opens the door to models of greater expres-sivity, and does so without affecting PRP’s efficiency.