Reconciling Perspectives on Blame Avoidance Behaviour

Blame avoidance behaviour (BAB) has become an increasingly popular topic in political science. However, the preconditions of BAB, its presence and consequences in various areas and in different political systems largely remain a black box. In order to generate a better understanding of BAB and its importance for the workings of democratic political systems, the scattered literature on BAB needs to be assessed and structured. This article offers a comprehensive review of the literature on blame avoidance. It departs from Weaver’s concept of blame avoidance and subsequently differentiates between work on BAB in comparative welfare state research and work on BAB in public policy and administration. It is argued that between these two strands of literature a bifurcation exists since both perspectives rarely draw on each other to create a more general understanding of BAB. Advantages from existing approaches must be combined to assess the phenomenon of blame avoidance in a more comprehensive way.

Visual avoidance in phobia: particularities in neural activity, autonomic responding, and cognitive risk evaluations.

We investigated the neural mechanisms and the autonomic and cognitive responses associated with visual avoidance behavior in spider phobia. Spider phobic and control participants imagined visiting different forest locations with the possibility of encountering spiders, snakes, or birds (neutral reference category). In each experimental trial, participants saw a picture of a forest location followed by a picture of a spider, snake, or bird, and then rated their personal risk of encountering these animals in this context, as well as their fear. The greater the visual avoidance of spiders that a phobic participant demonstrated (as measured by eye tracking), the higher were her autonomic arousal and neural activity in the amygdala, orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and precuneus at picture onset. Visual avoidance of spiders in phobics also went hand in hand with subsequently reduced cognitive risk of encounters. Control participants, in contrast, displayed a positive relationship between gaze duration toward spiders, on the one hand, and autonomic responding, as well as OFC, ACC, and precuneus activity, on the other hand. In addition, they showed reduced encounter risk estimates when they looked longer at the animal pictures. Our data are consistent with the idea that one reason for phobics to avoid phobic information may be grounded in heightened activity in the fear circuit, which signals potential threat. Because of the absence of alternative efficient regulation strategies, visual avoidance may then function to down-regulate cognitive risk evaluations for threatening information about the phobic stimuli. Control participants, in contrast, may be characterized by a different coping style, whereby paying visual attention to potentially threatening information may help them to actively down-regulate cognitive evaluations of risk.

Anticipatory and reactive forms of blame avoidance: of foxes and lions

Blame avoidance behavior (BAB) encompasses all kinds of integrity-protecting activities by officeholders in the face of potentially blame-attracting events. Although considered essential for a realistic understanding of politics and policymaking, a general understanding of this multi-faceted behavioral phenomenon and its implications has been lacking to date. We argue that this is due to the lack of careful conceptualization of various forms of BAB. Crucially, the difference between anticipatory and reactive forms of BAB is largely neglected in the literature. This paper links anticipatory and reactive forms of BAB as two consecutive decision situations. It exposes dependence relationships between the situations that trigger BAB, the rationalities at work, the resources and strategies applied by blame-avoiding actors, and the various consequences thereof. The paper concludes that anticipatory and reactive BAB are distinct phenomena that require specific research approaches to assess their relevance for the workings of polities.

Corporate Tax Avoidance and High Powered Incentives

This paper analyzes the links between corporate tax avoidance, the growth of highpowered incentives for managers, and the structure of corporate governance. We develop and test a simple model that highlights the role of complementarities between tax sheltering and managerial diversion in determining how high-powered incentives influence tax sheltering decisions. The model generates the testable hypothesis that firm governance characteristics determine how incentive compensation changes sheltering decisions. In order to test the model, we construct an empirical measure of corporate tax avoidance - the component of the book-tax gap not attributable to accounting accruals - and investigate the link between this measure of tax avoidance and incentive compensation. We find that, for the full sample of firms, increases in incentive compensation tend to reduce the level of tax sheltering, suggesting a complementary relationship between diversion and sheltering. As predicted by the model, the relationship between incentive compensation and tax sheltering is a function of a firm.s corporate governance. Our results may help explain the growing cross-sectional variation among firms in their levels of tax avoidance, the .undersheltering puzzle,. and why large book-tax gaps are associated with subsequent negative abnormal returns.

How health care delay and avoidance decisions are affected by finances and health insurance

Objective. To identify how an individual's finances and health insurance coverage affects their decision whether to avoid or delay medical care. Methods. Secondary data analysis of The Effects of Financial and Insurance Considerations on Health Care Utilization 2007 telephone survey data. Study inclusion criteria. 18 years old, Harris County resident, and had a need for medical care within the past year. Post weighing was done to correct for non-response bias. Results. Survey decision makers were predominately minorities (60%), Female (70%), and insured (71%). Ninety-two percent of participants sought care when needed, however, of this population 39% delayed medical care. Fifty-six percent of participants who delayed medical care sought care in the Doctor's office. For those who replied "Yes" to considering health insurance and finances in deciding to avoid medical care, 61% stated that they were confused about their insurance coverage as the explanation why. Fifty-five percent of Respondents indicated that delaying medical care was due to not knowing whether medical care was necessary. Conclusion. Additional research needs to be conducted to examine the relationship between onset of medical symptoms and final medical diagnosis to identify whether survey participants who delayed or avoided medical care actions were appropriate responses to their initial medical symptoms and final diagnosis. ^

9-28 d of exposure to elevated pCO2 reduces avoidance of predator odour but had no effect on behavioural lateralization or swimming activity in a temperate wrasse(Ctenolabrus rupestris)

Most studies on the impact of near-future levels of carbon dioxide on fish behaviour report behavioural alterations, wherefore abnormal behaviour has been suggested to be a potential consequence of future ocean acidification and therefore a threat to ocean ecosystems. However, an increasing number of studies show tolerance of fish to increased levels of carbon dioxide. This variation among studies in susceptibility highlights the importance of continued investigation of the possible effects of elevated pCO2. Here, we investigated the impacts of increased levels of carbon dioxide on behaviour using the goldsinny wrasse (Ctenolabrus rupestris), which is a common species in European coastal waters and widely used as cleaner fish to control sea lice infestation in commercial fish farming in Europe. The wrasses were exposed to control water conditions (370 µatm) or elevated pCO2 (995 µatm) for 1 month, during which time behavioural trials were performed. We investigated the possible effects of CO2 on behavioural lateralization, swimming activity, and prey and predator olfactory preferences, all behaviours where disturbances have previously been reported in other fish species after exposure to elevated CO2. Interestingly, we failed to detect effects of carbon dioxide for most behaviours investigated, excluding predator olfactory cue avoidance, where control fish initially avoided predator cue while the high CO2 group was indifferent. The present study therefore shows behavioural tolerance to increased levels of carbon dioxide in the goldsinny wrasse. We also highlight that individual fish can show disturbance in specific behaviours while being apparently unaffected by elevated pCO2 in other behavioural tests. However, using experiments with exposure times measured in weeks to predict possible effects of long-term drivers, such as ocean acidification, has limitations, and the behavioural effects from elevated pCO2 in this experiment cannot be viewed as proof that these fish would show the same reaction after decades of evolution.

AUTOFLY-Aid: Flight Deck Automation Support with Dynamic 4D Trajectory Management for Responsive and Adaptive Airborne Collision Avoidance

AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.

Traffic jam driving with NMV avoidance

n recent years, the development of advanced driver assistance systems (ADAS) – mainly based on lidar and cameras – has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators – brake and throttle pedals – were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Optimal Impulsive Collision Avoidance

The problem of optimal impulsive collision avoidance between two colliding objects in 3-dimensional elliptical Keplerian orbits is investigated with the purpose of establishing the optimal impulse direction and orbit location that give rise to the maximum miss distance following the maneuver. Closed-form analytical expressions are provided that predicts such distance and can be employed to perform a full optimization analysis. After verifying the accuracy of the expression for any orbital eccentricity and encounter geometry the optimum maneuver direction is derived as a function of the arc length separation between the maneuver point and the predicted collision point. The provided formulas can be used for high accuracy instantaneous estimation of the outcome of a generic impulsive collision avoidance maneuver and its optimization

Collision avoidance maneuver optimization

The paper presents a high accuracy fully analytical formulation to compute the miss distance and collision probability of two approaching objects following an impulsive collision avoidance maneuver. The formulation hinges on a linear relation between the applied impulse and the objects relative motion in the b-plane, which allows to formulate the maneuver optimization problem as an eigenvalue problem. The optimization criterion consists of minimizing the maneuver cost in terms of delta-V magnitude in order to either maximize collision miss distance or to minimize Gaussian collision probability. The algorithm, whose accuracy is verified in representative mission scenarios, can be employed for collision avoidance maneuver planning with reduced computational cost when compared to fully numerical algorithms.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Embodied Religion and Liberal Society: The Obstacle of De Facto Established Religion

Recent scholarship suggests that religion should be conceived in terms of embodied social practices as much as (if not more than) a set of systematic beliefs. Such accounts of religion, I will argue, raise problems that have not been adequately treated in current discussion of the role of religion in liberal society.

Sorting by diffusion: An asymmetric obstacle course for continuous molecular separation

A separation technique employing a microfabricated sieve has been demonstrated by observing the motion of DNA molecules of different size. The sieve consists of a two-dimensional lattice of obstacles whose asymmetric disposition rectifies the Brownian motion of molecules driven through the device, causing them to follow paths that depend on their diffusion coefficient. A nominal 6% resolution by length of DNA molecules in the size range 15–30 kbp may be achieved in a 4-inch (10-cm) silicon wafer. The advantage of this method is that samples can be loaded and sorted continuously, in contrast to the batch mode commonly used in gel electrophoresis.