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Cyber attacks are increasingly commonplace and cause significant disruption, and therefore, have been a focus of much research. The objective of this research was to understand the factors that might lead users to fail to recognize red flags and succumb to cyber events. We investigated users’ knowledge of cyber attacks, their propensity to trust technology, arousal, emotional valence, and situational trust in response to different types and severity of cyber attacks. Our findings suggest that high-risk attacks elicited more arousal and more negative emotional valence than low-risk attacks. The attack-type manipulation revealed that phishing scenarios yielded distinctive patterns, including weaker affective responses than ransomware and other malware. The authors further examined arousal, emotional valence, and situational trust patterns among the subset of high- knowledge participants who successfully identified all the attacks and compared these responses with those of less knowledgeable peers. Our findings suggest that the more knowledgeable the user, the higher was their general propensity to trust technology, the more sensitive were their emotional responses to the manipulation of risk, and the lower their situational trust when faced with cyber attack scenarios.

Previous research has not produced a satisfactory resource to study reflexive muscle activity for investigating potentially injurious whiplash motions. Various experimental and computational studies are available, but none provided a comprehensive biomechanical representation of human response during rear impacts. Three objectives were addressed in the current study to develop female and male finite element human body models with active reflexive neck muscles: 1) eliminate the buckling in the lower cervical spine of the model observed in earlier active muscle controller implementations, 2) evaluate and quantify the influence of the individual features of muscle activity, and 3) evaluate and select the best model configuration that can be used for whiplash injury predictions. The current study used an open-source finite element model of the human body for injury assessment representing an average 50th percentile female anthropometry, together with the derivative 50th percentile male morphed model. Based on the head-neck kinematics and CORelation and Analyis (CORA) tool for evaluation, models with active muscle controller and parallel damping elements showed improved head-neck kinematics agreement with the volunteers over the passive models. It was concluded that this model configuration would be the most suitable for gender-based whiplash injury prediction when different impact severities are to be studied.

Abstract COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) system where autonomous drones deliver supplies to field units in mountainous areas. The mission risks vary with topography, flight decisions, and mission goals. The missions engage a human plus AI team where users determine which of two AI‐controlled drones is better for each mission. This article reports on the technical approach and findings of the project and reflects on challenges that complex combinatorial problems present for users, machine learning, user studies, and the context of use for XAI systems. COGLE creates explanations in multiple modalities. Narrative “What” explanations compare what each drone does on a mission and “Why” based on drone competencies determined from experiments using counterfactuals. Visual “Where” explanations highlight risks on maps to help users to interpret flight plans. One branch of the research studied whether the explanations helped users to predict drone performance. In this branch, a model induction user study showed that post‐decision explanations had only a small effect in teaching users to determine by themselves which drone is better for a mission. Subsequent reflection suggests that supporting human plus AI decision making with pre‐decision explanations is a better context for benefiting from explanations on combinatorial tasks.

Explanations are central to understanding the causal relationships between entities within the environment. Instead of examining basic heuristics and schemata that inform the acceptance or rejection of scientific explanations, recent studies have predominantly examined complex explanatory models. In the present study, we examined which essential features of explanatory schemata can account for phenomena that are attributed to domain-specific knowledge. In two experiments, participants judged the validity of logical syllogisms and reported confidence in their response. In addition to validity of the explanations, we manipulated whether scientists or people explained an animate or inanimate phenomenon using mechanistic (e.g., force, cause) or intentional explanatory terms (e.g., believes, wants). Results indicate that intentional explanations were generally considered to be less valid than mechanistic explanations and that ‘scientists’ were relatively more reliable sources of information of inanimate phenomena whereas ‘people’ were relatively more reliable sources of information of animate phenomena. Moreover, after controlling for participants’ performance, we found that they expressed greater overconfidence for valid intentional and invalid mechanistic explanations suggesting that the effect of belief-bias is greater in these conditions.

Free-standing passengers on public transport are subjected to perturbations during non-collision incidents caused by driver maneuvers, increasing the risk of injury. In the literature, the step strategy is described as a recovery strategy during severe perturbations. However, stepping strategies increase body displacement, ultimately subjecting passengers to higher risk of impacts and falls on public transport. This study investigates the influence of different recovery strategies on the outcome of balance recovery of free-standing public transport passengers, challenged in postural balance by the non-uniform vehicle dynamics. From high-speed video recordings, a qualitative investigation of the balance responses of volunteer participants in a laboratory experiment was provided. On a linearly moving platform, 24 healthy volunteers (11 females and 13 males) were subjected to perturbation profiles of different magnitude, shape and direction, mimicking the typical acceleration and deceleration behavior of a bus. A methodology categorizing the balancing reaction to an initial strategy and a recovery strategy, was used to qualitatively identify, characterize and, evaluate the different balance strategies. The effectiveness of different strategies was assessed with a grading criterion. Statistical analysis based on these ordinal data was provided. The results show that the current definition in the literature of the step strategy is too primitive to describe the different identified recovery strategies. In the volunteers with the most successful balancing outcome, a particularly effective balance recovery strategy not yet described in the literature was identified, labeled the fighting stance. High jerk perturbations seemed to induce faster and more successful balance recovery, mainly for those adopting the fighting stance, compared to the high acceleration and braking perturbation profiles. Compared to the pure step strategy, the characteristics of the fighting stance seem to increase the ability to withstand higher perturbations by increasing postural stability to limit body displacement.

This study investigates the response of standing passengers on public transport who experience balance perturbations during non-collision incidents. The objective of the study was to analyse the effects of the perturbation characteristics on the initial responses of the passengers and their ability to maintain their balance. Sled tests were conducted on healthy volunteers aged 33.8 ± 9.2 years (13 males, 11 females) standing on a moving platform, facilitating measurements of the initial muscle activity and stepping response of the volunteers. The volunteers were exposed to five different perturbation profiles representing typical braking and accelerating manoeuvres of a public transport bus in the forward and backward direction. The sequence of muscle activations in lower-extremity muscles was consistent for the perturbation pulses applied. For the three acceleration pulses combining two magnitudes for acceleration (1.5 and 3.0 m/s2) and jerk (5.6 and 11.3 m/s3), the shortest muscle onset and stepping times for the passengers to recover their balance were observed with the higher jerk value, while the profile with the higher acceleration magnitude and longer duration induced more recovery steps and a higher rate of safety-harness deployment. The tendency for a shorter response time was observed for the female volunteers. For the two braking pulses (1.0 and 2.5 m/s2), only the lower magnitude pulse allowed balance recovery without compensatory stepping. The results obtained provide a reference dataset for human body modelling, the development of virtual test protocols, and operational limits for improving the safety of public transportation vehicles and users.

Compared with the young, the elderly (age greater than or equal to 60 years old) vulnerable road users (VRUs) face a greater risk of injury or death in a traffic accident. A contributing vulnerability is the aging processes that affect their brain structure. The purpose of this study was to investigate the injury mechanisms and establish head AIS 4+ injury tolerances for the elderly VRUs based on various head injury criteria. A total of 30 elderly VRUs accidents with detailed injury records and video information were selected and the VRUs’ kinematics and head injuries were reconstructed by combining a multi-body system model (PC-Crash and MADYMO) and the THUMS (Ver. 4.0.2) FE models. Four head kinematic-based injury predictors (linear acceleration, angular velocity, angular acceleration, and head injury criteria) and three brain tissue injury criteria (coup pressure, maximum principal strain, and cumulative strain damage measure) were studied. The correlation between injury predictors and injury risk was developed using logistical regression models for each criterion. The results show that the calculated thresholds for head injury for the kinematic criteria were lower than those reported in previous literature studies. For the brain tissue level criteria, the thresholds calculated in this study were generally similar to those of previous studies except for the coup pressure. The models had higher (>0.8) area under curve values for receiver operator characteristics, indicating good predictive power. This study could provide additional support for understanding brain injury thresholds in elderly people.

The spatial and temporal reach of contemporary environmental problems are unparalleled. Collective efforts to address global environmental problems are required but actions to tackle these problems demand initial recognition of their seriousness. Cross-cultural research has shown a reliable bias in comparative judgements about the severity of environmental problems for geographically distant places, with environmental issues perceived to be more severe “there” than “here.” The robustness of this effect may have unwarranted consequences since perceiving environmental problems as being worse elsewhere might lead individuals to not take actions in their locality. We conducted a within-country study to test whether this spatial bias would emerge for samples from all Brazilian states (k = 27, N = 4,265; 85% female; Age M = 24; Age SD = 9.67). Providing further support for a biased comparative judgement, we observed that the severity of environmental problems was judged as worse at the country level than at the state level (mean spatial bias score among Brazilian states = 0.54). Only 2% of the variation in spatial bias was attributable to across-state differences. By replicating cross-cultural findings within a single nation, our findings provide further support for the prevalence and generalizability of biased comparative judgements about the severity of environmental problems. We discuss critical future directions for spatial bias research.

PURPOSE:1) To compare levels of emotional symptoms and health-related quality of life between patients with heart failure and their family caregivers; and 2) to examine whether patients' and caregivers' emotional symptoms were associated with their own, as well as their partner's health-related quality of life. METHOD:In this cross-sectional study, 41 patients-caregiver dyads (78% male patients, aged 68.6 years; and 83% female caregivers, aged 65.8 years) completed all nine dimensions of the Brief Symptom Inventory and the Minnesota Living with Heart failure Questionnaire. Dyadic data were analysed for 6 sub-scales of the Brief Symptom Inventory, using the Actor-Partner Interdependence Model. RESULTS:There were no statistically significant differences in emotional symptoms and health-related quality of life between patients with heart failure and their caregivers. Patients' and caregivers' emotional symptoms were associated with their own health-related quality of life. Caregivers' anxiety, phobic anxiety, obsession-compulsion, depression and hostility negatively influenced their partner's (i.e. the patient's) health-related quality of life. There were no partner effects of patients' emotional symptoms on the health-related quality of life of caregivers. CONCLUSIONS:The results of this study suggest that patients may be particularly vulnerable to the emotional distress, i.e. thoughts, impulses and actions of their caregivers. It may be possible to improve patients' health-related quality of life by targeting specific detrimental emotional symptoms of caregivers.

Relational mobility is a socio-ecological construct quantifying how much freedom and opportunity a society affords individuals to choose and dispose of interpersonal relationships. Past research has confirmed that relational mobility varies across nations, but no large-scale study has examined the degree to which relational mobility may vary within a single nation. We report two studies (Study 1, N = 647; Study 2, N = 7343) exploring within-country similarity or variability in relational mobility across all 27 states and five geo-socio-political regions in the continent-size country of Brazil. Results confirmed the measurement equivalence of the Relational Mobility Scale across respondents from all Brazilian states. Notably, relational mobility scores were uniform across Brazilian regions and states, indicating a common national culture regarding the amount of opportunities Brazilians have in selecting new relationship partners within their social context. Replicating existing findings, relational mobility was positively associated with pro-active tendencies that help people retain relationships-levels of intimacy and self-disclosure toward a close friend-indicating that friends tend to feel closer intimacy to their close friends, and reveal serious personal information to a larger degree in social contexts where opportunities to find and retain relationships with like-minded others are greater.

We report the first cross-cultural and cross-organizational evidence for an evolved hazing motivation. Using experiments performed in the United States, Japan, and among members of a hazing and a nonhazing organization, we demonstrate an invariant set of core hazing predictors. In particular, we show that the perception of near-term group benefits, which would have been ancestrally exploitable by new group members, substantially increases desired hazing severity in all samples. Results are discussed in light of human organizational psychology and the difficulty of reliably suppressing hazing behavior.

Objectives Head injuries are the leading cause of death in horse-related injury events and, even since the introduction of helmets, represent a sizeable proportion of all horse-related injuries. Falls from horseback and kicks to the head are the most frequent type of incident causing head injuries, but it is unknown whether these incidents are predictors of head injury. This study aimed to investigate head injuries and the association between incident type and head injury.Method Retrospective review of 7815 horse-related injury events was conducted. Data were gathered from hospitals, local healthcare centres and public dental services in Skaraborg, Sweden. Binary logistic regression was used to analyse the association between the incident type and occurrence of head injury while controlling for risk factors.Results Approximately 20% of riders sustained a head injury, mostly soft tissue injuries (56.3%) and concussions (33.4%). A fall from or with the horse was the primary cause of head injury (63.9%). Those who fell from a carriage or other height or who were injured through contact with the horse had no difference in the likelihood of head injury when compared with those that fell from or with the horse. However, those who sustained an injury without any horse contact had lower odd of head injury (OR: 0.640, p

We examine the negotiations held under the auspices of the United Nations Framework Convention of Climate Change in Paris, December 2015. Prior to these negotiations, there was considerable uncertainty about whether an agreement would be reached, particularly given that the world’s leaders failed to do so in the 2009 negotiations held in Copenhagen. Amid this uncertainty, we applied three different methods to predict the outcomes: an expert survey and two negotiation simulation models, namely the Exchange Model and the Predictioneer’s Game. After the event, these predictions were assessed against the coded texts that were agreed in Paris. The evidence suggests that combining experts’ predictions to reach a collective expert prediction makes for significantly more accurate predictions than individual experts’ predictions. The differences in the performance between the two different negotiation simulation models were not statistically significant.

One of the challenges in writing an article reviewing the current state of cyber education and workforce development is that there is a paucity of quantitative assessment regarding the cognitive aptitudes, work roles, or team organization required by cybersecurity professionals to be successful. In this review, we argue that the people who operate within the cyber domain need a combination of technical skills, domain specific knowledge, and social intelligence to be successful. They, like the networks they operate, must also be reliable, trustworthy, and resilient. Defining the knowledge, skills, attributes, and other characteristics is not as simple as defining a group of technical skills that people can be trained on; the complexity of the cyber domain makes this a unique challenge. There has been little research devoted to exactly what attributes individuals in the cyber domain need. What research does exist places an emphasis on technical and engineering skills while discounting the important social and organizational influences that dictate success or failure in everyday settings. This paper reviews the literature on cyber expertise and cyber workforce development to identify gaps and then argues for the important contribution of social fit in the highly complex and heterogenous cyber workforce. We then identify six assumptions for the future of cybersecurity workforce development, including the requirement for systemic thinkers, team players, a love for continued learning, strong communication ability, a sense of civic duty, and a blend of technical and social skill. Finally, we make recommendations for social and cognitive metrics which may be indicative of future performance in cyber work roles to provide a roadmap for future scholars.