A Primer on the Human Readiness Level Scale (ANSI/HFES 400-2021)

The Human Readiness Level (HRL) Scale is a simple 9-level scale for evaluating, tracking, and communicating the readiness of a technology for safe and effective human use. It is modeled after the well-established Technology Readiness Level (TRL) framework that is used throughout the government and industry to communicate the maturity of a technology and to support decision making about technology acquisition. Here we (1) introduce the ANSI/HFES 400-2021 Standard that defines the HRL scale and (2) provide concrete examples of evaluation activities to support the application of HRLs in the development of automated driving systems

Adapting the Human Factors Analysis and Classification System for Commercial Fishing Vessel Accidents

The commercial fishing industry is frequently described as one of the most hazardous occupations in the United States. The objective, to maximize the catch, is routinely challenged by a variety of elements due to the environment, the vessel, the crew, and how they interact with each other. This study developed and evaluated a version of Wiegmann and Shappell’s (2003) Human Factors Analysis and Classification System (HFACS), specifically for commercial fishing industry vessels (HFACS-FV), using data from ten years of fatal fishing vessel accidents. For this study, the accident investigation information was converted into the HFACS-FV format by independent raters and measured for inter-rater reliability. The results were analyzed for the frequency of the causal factors and their relationship with vessel demographic information

Human System Engineering Applications from Distracted Driving Simulations

Most of the studies to explore the impact of distracted driving have been descriptive in nature; i.e. the research is conducted in naturalistic settings to evaluate the performance of the driver with and without distracters. However simulation models can also be used that predict the workload for driving tasks. Using concepts from process modeling, baseline models of driving tasks can be created for different driving sequences that include the associated fine motor, visual and cognitive human resources. These models can then be used to evaluate incidents of workload overload caused by different distracters, from both the internal and external vehicle environment. Identifying specific overloaded resources can lead to mitigation strategies to reduce workload and minimize distracted driving. Lessons learned from distracted driving research can then be applied to evaluation other types of manual, visual, and cognitive intensive tasks. Identifying combinations of tasks that contribute to peak workload of operators, and then simulating the impact of multi-tasking using personal devices (i.e. cell phones) can lead to management insights for other types of work environments. Additionally, iterative modeling can also include the impact of sensors and alerts, as well as enhanced workstation displays. Individual component overload can help understand causes for performance detriments during different task sequences, and the impact of additional types of technologies and activities. Using the simulation analysis, the impact on overall workload, identification of peak workload occurrences, and specific overloaded resources can lead to mitigation strategies to reduce workload and improve operator performance

The Impact of Human Assurance on Satellite Operations

Mission assurance is a method to guarantee mission success against a known set of risks; mission assurance is generally represented as a probability against a threshold of acceptable performance. Human assurance can be considered as the likelihood of acceptable operator performance given a set of conditions that include the operator, the system, and the environment. Standard mission assurance models tend to assume a qualified crew, but do not include other aspects of the internal or external environment that may impact the reliability of the human operator. A human assurance model can be created that allows the exploration of the variability in operator performance due to the likelihood of different risks. An example human assurance model has been created for the detection of adverse trending satellite data and the need to modify the existing mission schedule to address the satellite emergency. The model leverages the Human Viewpoint framework to capture the human-focused data within the mission context. From this data, sources of risk can be identified for the socio-technical system and a risk framework developed. The resulting risk model allows exploration of the characteristics of both the operator and the operating environment, as well as the impact of organizational mitigations, on the likelihood that the socio-technical system will meet mission assurance thresholds. The method provided can be used to identify the limitations of human system performance against the established criteria

Employee-Task Assignments for Organization Modeling: A Review of Models and Applications

In this study, we present a review of task assignment problems in organizations, an area that has become more important as tasks become more complex and personnel skills become more specialized. The challenge is to design task assignments that meet all requirements and result in the best organizational performance. The consequences of poor design include failed tasks, reduced efficiency, and inability to meet deadlines. Moreover, inequity of workload between employees can cause lack of job satisfaction, loss of motivation and also boredom. In general, work processes in organizations consist of different tasks, which require different expertise. Personnel usually have various degrees of qualifications and their performance may vary for different tasks. The outcome of the work process depends heavily on which tasks are assigned to which personnel. Performance of an organization can be increased by assigning the tasks to the most qualified available personnel. However, it could result in overloading some personnel while the others remain under-loaded. So, the even distribution of the workload between them also needs to be taken into consideration. In addition, it helps to increase organization\u27s productivity by distributing personnel\u27s knowledge, time, and attention more extensively. We review task-employee assignment problems in organization modeling with the computational models that have been reported in the literature with their applications. Human factors engineering, in terms of workload in organizational modeling is included as the work process performance is heavily dependent on the human (personnel). Based on the initial findings, we propose to investigate an improved workload model that allows the use of optimization of select constraints, such as balancing workload among team members. While current workload models allow the evaluation of workload among team members interacting in a work process, it is up to the analyst to suggest improvements. By providing an optimized solution, we present the Engineering Manager, that can then be adjusted to meet practical criteria

When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias.

Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was valid on half the trials or to decide whether the conclusion was believable on the other half. When belief and logic conflict, the default-interventionist view predicts that it should take less time to respond on the basis of belief than logic, and that the believability of a conclusion should interfere with judgments of validity, but not the reverse. The parallel-processing view predicts that beliefs should interfere with logic judgments only if the processing required to evaluate the logical structure exceeds that required to evaluate the knowledge necessary to make a belief-based judgment, and vice versa otherwise. Consistent with this latter view, for the simplest reasoning problems (modus ponens), judgments of belief resulted in lower accuracy than judgments of validity, and believability interfered more with judgments of validity than the converse. For problems of moderate complexity (modus tollens and single-model syllogisms), the interference was symmetrical, in that validity interfered with belief judgments to the same degree that believability interfered with validity judgments. For the most complex (three-term multiple-model syllogisms), conclusion believability interfered more with judgments of validity than vice versa, in spite of the significant interference from conclusion validity on judgments of belief

Spinal CX3CL1/CX3CR1 may not directly participate in the development of morphine tolerance in rats

CX3CL1 (fractalkine), the sole member of chemokine CX3C family, is implicated in inflammatory and neuropathic pain via activating its receptor CX3CR1 on neural cells in spinal cord. However, it has not been fully elucidated whether CX3CL1 or CX3CR1 contributes to the development of morphine tolerance. In this study, we found that chronic morphine exposure did not alter the expressions of CX3CL1 and CX3CR1 in spinal cord. And neither exogenous CX3CL1 nor CX3CR1 inhibitor could affect the development of morphine tolerance. The cellular localizations of spinal CX3CL1 and CX3CR1 changed from neuron and microglia, respectively, to all the neural cells during the development of morphine tolerance. A microarray profiling revealed that 15 members of chemokine family excluding CX3CL1 and CX3CR1 were up-regulated in morphine-treated rats. Our study provides evidence that spinal CX3CL1 and CX3CR1 may not be involved in the development of morphine tolerance directly

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy