Military mimicry:the art of concealment, deception, and imitation

Three dominant thematics emerge from the biological mimicry and camouflage literature, namely, concealment, deception, and imitation. These phenomena are interesting in their own right, but conceptually have similar analogs in the military context that have attracted only minimal intellectual curiosity. Accordingly, the purpose of this paper is to apply biological mimicry and camouflage concepts to the military environment. Concealment in the form of camouflage is traced from its nineteenth century origins to the military's imminent twenty-first century perfection of an “invisibility cloak”. Military deception is the art of duping enemies with fakes and dummies. Finally, imitation is examined from three perspectives: firstly, replacement of military personnel with animals; secondly, exploration of bioengineering, including exploitation of avian aerodynamics, insect biophysical structures, and mammal sonar attributes; and, thirdly, Artificial Intelligence that is driving military mimicry along an evolutionary path towards robots, swarms, and avatars in an emerging and novel military technology revolutio

Glacier-climate interactions: a synoptic approach

The reliance on freshwater released by mountain glaciers and ice caps demands that the effects of climate change on these thermally-sensitive systems are evaluated thoroughly. Coupling climate variability to processes of mass and energy exchange at the glacier scale is challenged, however, by a lack of climate data at an appropriately fine spatial resolution. The thesis addresses this challenge through attempting to reconcile this scale mismatch: glacier boundary-layer observations of meteorology and ablation at Vestari Hagafellsjökull, Iceland, and Storglaciären, Sweden, are related to synoptic-scale meteorological variability recorded in gridded, reanalysis data. Specific attention is directed toward synoptic controls on: i) near-surface air temperature lapse rates; ii) stationarity of temperature-index melt model parameters; and iii) glacier-surface ablation. A synoptic weather-typing procedure, which groups days of similar reanalysis meteorology into weather categories , forms the basis of the analytical approach adopted to achieve these aims. Lapse rates at Vestari Hagafellsjökull were found to be shallowest during weather categories characterised by warm, cloud-free weather that encouraged katabatic drainage; steep lapse rates were encountered in weather categories associated with strong synoptic winds. Quantitatively, 26% to 38% of the daily lapse-rate variability could be explained by weather-category and regression-based models utilizing the reanalysis data: a level of skill sufficient to effect appreciable improvements in the accuracy of air temperatures extrapolated vertically over Vestari Hagafellsjökull. Weather categories also highlighted the dynamic nature of the temperature-ablation relationship. Notably, the sensitivity of ablation to changes in air temperature was observed to be non-stationary between weather categories, highlighting vulnerabilities of temperature-index models. An innovative solution to this limitation is suggested: the relationship between temperature and ablation can be varied as a function of weather-category membership. This flexibility leads to an overall improvement in the simulation of daily ablation compared to traditional temperature-index formulations (up to a 14% improvement in the amount of variance explained), without the need for additional meteorological data recorded in-situ. It is concluded that weather categories are highly appropriate for evaluating synoptic controls on glacier meteorology and surface energetics; significant improvements in the parameterization of boundary-layer meteorology and ablation rates are realised through their application

Complex responses to movement-based disease control: when livestock trading helps

Livestock disease controls are often linked to movements between farms, for example, via quarantine and pre- or post-movement testing. Designing effective controls, therefore, benefits from accurate assessment of herd-to-herd transmission. Household models of human infections make use of R*, the number of groups infected by an initial infected group, which is a metapopulation level analogue of the basic reproduction number R0 that provides a better characterization of disease spread in a metapopulation. However, existing approaches to calculate R* do not account for individual movements between locations which means we lack suitable tools for livestock systems. We address this gap using next-generation matrix approaches to capture movements explicitly and introduce novel tools to calculate R* in any populations coupled by individual movements. We show that depletion of infectives in the source group, which hastens its recovery, is a phenomenon with important implications for design and efficacy of movement-based controls. Underpinning our results is the observation that R* peaks at intermediate livestock movement rates. Consequently, under movement-based controls, infection could be controlled at high movement rates but persist at intermediate rates. Thus, once control schemes are present in a livestock system, a reduction in movements can counterintuitively lead to increased disease prevalence. We illustrate our results using four important livestock diseases (bovine viral diarrhoea, bovine herpes virus, Johne's disease and Escherichia coli O157) that each persist across different movement rate ranges with the consequence that a change in livestock movements could help control one disease, but exacerbate another

Inter-decadal variability of degree-day factors on Vestari Hagafellsjökull (Langjökull, Iceland) and the importance of threshold air temperatures

The skill of degree-day glacier melt models is highly dependent on the choice of degree-dayfactor (), which is often assumed to remain constant in time. Here we explore the validity of this assumption in a changing climate for two locations on Vestari Hagafellsjökull (1979-2012) using a Surface Energy Balance (SEB) approach that isolates the effect of changes in theprevailing weather on the . At lower-elevation, we observe stable during the period 10 of study; however, at higher elevation, is noted to be more variable and a statistically- significant downward trend is observed. This is found to result from an inappropriate threshold air temperature ( 12 ) from which to initiate the positive-degree-day sum, and is removed by setting to -1.83°C, rather than the usual value of 0°C used in degree-day melt models. The stationarity of once is adjusted contradicts previous research and lends support to the use of constant for projecting future glacier melt. Optimizing also improves the skill of melt simulations at our study sites. This research thus highlights the importance of for both melt model performance and the evaluation of stationarity in a changing climate

Exploring Psychological Reactions to Social Media Logos

Modern social media platforms offer myriad benefits to individuals, organizations, and societies; yet, social media also has a potential “dark side”, including, among other elements, the potential negative consequences of social media overuse. We explore whether mere exposure to social media cues can induce subconscious pleasurable reactions, particularly among those who report high levels of social media craving and use. We report the results of an online experiment (n=201) that used the Affect Misattribution Procedure (AMP) to elicit pleasantness ratings of target stimuli associated with social media logos and other types of control and comparison images. Results demonstrate that participants who report high levels of social media craving and use subconsciously attribute greater favorability to target stimuli associated with social media logos vs. (a) non-social media stimuli and (b) low craving/use participants, suggesting a spontaneous hedonic reaction to social media cues that may reinforce overuse behavior

Experimental testing and predictive machine learning to determine the mechanical characteristics of corroded reinforcing steel

Chloride-induced deterioration of reinforcing steel bars has become a densely researched topic over the past several decades because of the severe ramifications to the structural reliability of aging infrastructure. The ever-growing volume of experimental and field data continually enables advances in the field through deeper micro-macro analyses and various modeling applications. The purpose of this paper is twofold. First, an experimental program is introduced, describing the tensile testing of 284 artificially corroded, 25 mm diameter deformed Grade500E reinforcing bars. Secondly, the mechanical characteristics of corroded bars are predicted through a collection of regression-based machine learning algorithms. Models are trained and tested on a database of 1387 tensile tests compiled from 25 other experimental programs available in the literature. The complete database includes 19 input parameters used to predict nine key mechanical properties of the corroded steel bars. Nine machine learning models were selected from a balanced assortment of algorithm typologies to determine the most appropriate methodology for each response variable. The adaptive-neuro fuzzy inference system (ANFIS) model was found to have the strongest individual predictive ability across all models. Meanwhile, ensemble tree-based learning algorithms categorically provided the most consistently high-performing models over the selected response variables

An Empirical Examination of Peer vs. Expert Advice in Online Forums

Online discussion forums sponsored by electronic networks of practice offer a popular platform for a variety of participants to share their knowledge and provide feedback, including subject matter experts and a larger body of “peer” forum users with no particular expertise. Although prior research suggests that both expert and peer forum contributions can influence information seekers, current literature offers little guidance that explains how and when one is more influential than the other. This paper reports the results of two studies, a structured survey and a choice-based conjoint study, conducted to empirically validate a previously derived conceptual framework of 16 situational characteristics related to peer and expert advice seeking on forums. The results of our work offer theoretical and practical guidance for ongoing work in this area

An emerging tropical cyclone-deadly heat compound hazard

Climate change may bring new hazards through novel combinations of extreme weather (compound events). Here we evaluate the possibility of dangerous heat following major tropical cyclones (TCs) – a combination with serious potential consequences given that mega-blackouts may follow powerful TCs2, and the heavy reliance on air conditioning. We show that “TC-heat” events are already possible along densely populated coastlines globally but, so far, only an estimated 1,000 people have been impacted. However, this number could rise markedly, with over two million at risk under a storyline of the observed TCs recurring in a 2°C warmer world than preindustrial. Using analogues as focussing events we show, for example, that if the catastrophic 1991 Bangladesh Cyclone occurred with 2°C global warming, there would be >70% chance of subsequent dangerous heat. This research highlights a gap in adaptation planning and a need to prepare for an emerging TC-heat compound hazard