An initial ‘snapshot’ of sensory information biases the likelihood and speed of subsequent changes of mind

We often need to rapidly change our mind about perceptual decisions in order to account for new information and correct mistakes. One fundamental, unresolved question is whether information processed prior to a decision being made (‘pre-decisional information’) has any influence on the likelihood and speed with which that decision is reversed. We investigated this using a luminance discrimination task in which participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli briefly remained on screen, and participants could change their response. Using psychophysical reverse correlation, we examined how moment-to-moment fluctuations in stimulus luminance affected participants’ decisions. This revealed that the strength of even the very earliest (pre-decisional) evidence was associated with the likelihood and speed of later changes of mind. To account for this effect, we propose an extended diffusion model in which an initial ‘snapshot’ of sensory information biases ongoing evidence accumulation.

Color multi-focus image fusion based on transfer learning

Multi-focus image fusion is a technique that integrates the focused areas in a pair or set of source images with the same scene into a fully focused image. Inspired by transfer learning, this paper proposes a novel color multi-focus image fusion method based on deep learning. First, color multi-focus source images are fed into VGG-19 network, and the parameters of convolutional layer of the VGG-19 network are then migrated to a neural network containing multilayer convolutional layers and multilayer skip-connection structures for feature extraction. Second, the initial decision maps are generated using the reconstructed feature maps of a deconvolution module. Third, the initial decision maps are refined and processed to obtain the second decision maps, and then the source images are fused to obtain the initial fused images based on the second decision maps. Finally, the final fused image is produced by comparing the Q ABF metrics of the initial fused images. The experimental results show that the proposed method can effectively improve the segmentation performance of the focused and unfocused areas in the source images, and the generated fused images are superior in both subjective and objective metrics compared with most contrast methods.

Fathers on Leave: Experiences of Middle-Class Fathers on Parental Leave in the City of Zagreb

Parental leave reforms that aimed at higher father’s involvement in childcare began in the 1970s. However, the number of fathers who took parental leave increased only in the 1990s when Scandinavian countries began introducing father’s quotas or paternity leaves, that is, earmarked leave periods to be used by fathers or otherwise lost. Croatia introduced the two-month father’s quota as late as in 2013. Although the reform did not contribute to a sudden increase in the number of fathers on parental leave, there is always a steady, albeit small, number of fathers taking up leave. This article aims to provide an insight into fathers’ experiences on parental leave in Croatia. Relying on interviews with 11 middle-class fathers in the City of Zagreb, the article explores father’s motives for taking leave, their experience regarding the initial decision and the procedure of exercising their right to leave and their experience of being on leave. Results suggest that the fathers were very eager to use their right to leave and spend time with their children. They mostly used longer leaves (more than 3 months) and the experience of being home alone with the child made the fathers learn new skills in relation to childcare and housework, but also rethink their relation to work and family. Key words: parental leave policy, parental leave, father’s quotas, fathers’ experiences, Croatia

The dynamics of decision-making and action during active sampling

Embodied Cognition Theories (ECTs) of decision-making propose that the decision process pervades the execution of choice actions and manifests itself in these actions. Decision-making scenarios where actions not only express the choice but also help sample information can provide a valuable, ecologically relevant model for this framework. We present a study to address this paradigmatic situation in humans. Subjects categorized (2AFC task) a central object image, blurred to different extents, by moving a cursor toward the left or right of the display. Upward cursor movements reduced the image blur and could be used to sample information. Thus, actions for decision and actions for sampling were orthogonal to each other. We analyzed response trajectories to test whether information-sampling movements co-occurred with the ongoing decision process. Trajectories were bimodally distributed, with one kind being direct towards one response option (non-sampling), and the other kind containing an initial upward component before veering off towards an option (sampling). This implies that there was an initial decision at the early stage of a trial, whether to sample information or not. Importantly, in sampling trials trajectories were not purely upward, but rather had a significant horizontal deviation early on. This result suggests that movements to sample information exhibit an online interaction with the decision process, therefore supporting the prediction of the ECTs under ecologically relevant constrains.

Decision Premises, Learning and Organizational Resilience Addressing Novel Adversities

Organizational resilience is traditionally associated with the ability to understand and to respond to the ongoing situation, even under unusual conditions. The capability to detect novel and unexpected situations plays a fundamental role in this process. Following (Simon‚ 1991), we believe that decision premises affect the problem representation and, ultimately, the possibility to detect, interpret and respond to novel situations, thus enhancing resilience. From this perspective, the ability to expand the perceptual limits of observation and to conceive a novel representation of the problem requires revising the initial decision premises. This theory of how organizations learn how to solve novel problems provides the foundation to introduce a role designed to legitimately challenge the decision premises and, ultimately, the spectrum of alternatives that are taken into consideration as possible solutions. To illustrate our proposal to increase organizational resilience, we introduce an exemplary real case stemming from the practice of the emergency management organizations under scrutiny of our research team; this case is reconstructed as a conversational narrative of the two key participants.

Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary

Multi-focus image fusion is an important method used to combine the focused parts from source multi-focus images into a single full-focus image. Currently, to address the problem of multi-focus image fusion, the key is on how to accurately detect the focus regions, especially when the source images captured by cameras produce anisotropic blur and unregistration. This paper proposes a new multi-focus image fusion method based on the multi-scale decomposition of complementary information. Firstly, this method uses two groups of large-scale and small-scale decomposition schemes that are structurally complementary, to perform two-scale double-layer singular value decomposition of the image separately and obtain low-frequency and high-frequency components. Then, the low-frequency components are fused by a rule that integrates image local energy with edge energy. The high-frequency components are fused by the parameter-adaptive pulse-coupled neural network model (PA-PCNN), and according to the feature information contained in each decomposition layer of the high-frequency components, different detailed features are selected as the external stimulus input of the PA-PCNN. Finally, according to the two-scale decomposition of the source image that is structure complementary, and the fusion of high and low frequency components, two initial decision maps with complementary information are obtained. By refining the initial decision graph, the final fusion decision map is obtained to complete the image fusion. In addition, the proposed method is compared with 10 state-of-the-art approaches to verify its effectiveness. The experimental results show that the proposed method can more accurately distinguish the focused and non-focused areas in the case of image pre-registration and unregistration, and the subjective and objective evaluation indicators are slightly better than those of the existing methods.

The Carolinas Campaign

This chapter examines the destructive Carolinas Campaign of 1864–1865 as a strategic culmination of the war by means of the transferal to the eastern theater of hard-war tactics that had long characterized the American Civil War’s western theaters. Infliction of property damage and psychological warfare expanded to wholesale destruction of towns and cities, widespread targeting of White civilians, male and female, summary punishment for irregular warfare, and the liberation of slaves in South Carolina as retribution for that state’s overwhelming and initial decision to secede. Federal commanders and soldiers alike, most from the West, were eager to implement this harder form of warfare in a theater known for a more traditional, limited mode of war making. The use of Black troops was most fully employed in the eastern theater in the Carolinas, much as it had been in the West in the Lower Mississippi Valley. As the war neared its end, the desperate Confederate commander in North Carolina, Gen. Joseph E. Johnston, unsuccessfully sought to prevent Maj. Gen. William T. Sherman’s troops from accomplishing destructive warfare, and thus victory, there. Sherman’s conciliatory surrender terms for Johnston’s army, which occurred days after Pres. Abraham Lincoln’s assassination, were rebuffed by angry Republicans in the cabinet, the War Department, and Congress, for whom leniency was now furthest from their minds.

Public attitudes to COVID-19 ‘booster vaccinations and influenza vaccines: A qualitative focus group study

Objectives This study explored public attitudes to COVID-19 ‘booster’ vaccines and influenza vaccines, including participants intentions to have them or not, and their preferences on how and when they should be administered. Study design. Qualitative study using online focus groups and interviews.Methods Group and individual online interviews were conducted with a diverse sample of 21 adults in the United Kingdom to explore their views on the issue of COVID-19 booster and influenza vaccination. Data were analysed using a framework approach.Results Three themes emerged to unpack participants views on COVID-19 booster and flu vaccinations: (1) Booster intentions correspond with decisions around initial vaccination (2) Mixed views on booster and flu vaccines (3) Mixed views on whether to get COVID-19 booster and flu vaccines together or separately. Those who had been more willing to accept their initial COVID-19 vaccine were more willing to accept a booster and a flu vaccine, whereas those who had been more hesitant about their initial COVID-19 vaccine were more hesitant about getting a booster and a flu vaccine – including the idea of getting them together.Conclusions Public health messaging related to COVID-19 boosters might emphasise that they can be seen as: an extension of their initial decision to get vaccination; a way to maintain population immunity over the longer term; a collective act (to protect others); a way to maintain freedoms or ‘normality’. Messaging around boosters and influenza vaccines needs to emphasise they are safe and convenient to be taken together and that both are important, especially for those clinically vulnerable

Artificial Intelligence Applications in the Auditing Profession: A Literature Review

This paper investigates some essential questions that might interest auditors regarding the impact of artificial intelligence (AI) applications on the auditing profession by reviewing a selective bibliography of papers published mainly between 2016 and 2020. It discusses the major AI applications in the auditing field and explores the associated benefits in increasing auditing work’s effectiveness, efficiency, and quality. It further illustrates the major internal critical considerations that should be taken into account before AI application adoption in auditing practices, from initial decision-making to the use of proper countermeasures, to ensure the successful and effective implementation of AI applications. The extent to which AI applications in the accounting and auditing field might affect current hiring practices and threaten an auditor’s job, as performed today, is discussed and various debates and contradictory opinions are presented. The major AI applications adopted by the Big Four accounting firms are also discussed.

Divergent effects of absolute evidence magnitude on decision accuracy and confidence in perceptual judgements

Whether people change their mind after making a perceptual judgement may depend on how confident they are in their initial decision. Recently, it was shown that, when making perceptual judgements about stimuli containing high levels of 'absolute evidence' (i.e., the overall magnitude of sensory evidence across choice options), people make less accurate initial decisions and are also slower to change their mind and correct their mistakes. Here we report two studies that investigated whether high levels of absolute evidence also lead to increased decision confidence. We used a luminance judgment task in which participants decided which of two dynamic, flickering stimuli was brighter. After making a decision, participants rated their confidence. We manipulated relative evidence (i.e., the mean luminance difference between the two stimuli) and absolute evidence (i.e., the summed luminance of the two stimuli). In the first experiment, we found that higher absolute evidence was associated with decreased decision accuracy but increased decision confidence. In the second experiment, we additionally manipulated the degree of luminance variability to assess whether the observed effects were due to differences in perceived evidence variability. We replicated the results of the first experiment but did not find substantial effects of luminance variability on confidence ratings. Our findings support the view that decisions and confidence judgments are based on partly dissociable sources of information, and suggest that decisions initially made with higher confidence may be more resistant to subsequent changes of mind.