Human Behavioral Responses Research Articles

Behavioral Data Analysis of Robot-Assisted Autism Spectrum Disorder (ASD) Interventions Based on Lattice Computing Techniques.

Recent years have witnessed the proliferation of social robots in various domains including special education. However, specialized tools to assess their effect on human behavior, as well as to holistically design social robot applications, are often missing. In response, this work presents novel tools for analysis of human behavior data regarding robot-assisted special education. The objectives include, first, an understanding of human behavior in response to an array of robot actions and, second, an improved intervention design based on suitable mathematical instruments. To achieve these objectives, Lattice Computing (LC) models in conjunction with machine learning techniques have been employed to construct a representation of a child’s behavioral state. Using data collected during real-world robot-assisted interventions with children diagnosed with Autism Spectrum Disorder (ASD) and the aforementioned behavioral state representation, time series of behavioral states were constructed. The paper then investigates the causal relationship between specific robot actions and the observed child behavioral states in order to determine how the different interaction modalities of the social robot affected the child’s behavior.

Covid-19 Pandemic and Human Behavioral Response

Covid-19 Pandemic and Human Behavioral Response

Reinventing the Relationship Between Architecture, Biology and Human Experience

The oblivious implementation of ‘biology’ or ‘study of life’ into architectural design has been shaping human experiences for centuries. The human body consciously or subconsciously accepts the constructed surroundings to design emotions, senses, behavior, and logical order of its own. Likewise, the identity of a group of individuals occupied by a built structure to a certain extent reflects the spatial experience outlined by the structure. The current gap in biological understanding in design often assists in resulting imbalance between the human body and the surrounding environment. With this in mind, the first phase involves an exploration of existing biological theories regarding user spatial experience. The second phase studies a complex range of human movements, sensory stimuli, and emotional and behavioral responses recommending probable approaches for assuring structural soundness, aesthetic pleasure, and functional accuracy of an architectural setting. This research finally opens an opportunity to re-evaluate design solutions based on the potential applications of bio-scientific research for future design development.

A Game-Theoretic Modeling Approach to Comprehend the Advantage of Dynamic Health Interventions in Limiting the Transmission of Multi-Strain Epidemics

In the situation of inadequate vaccines and rapid mutation of virulent strains, alternative health interventions play a crucial role in the containment of emerging epidemics. This study elucidates the critical aspects of health interventions to control epidemic resurgence. Besides, human behavioral response to epidemics plays an instrumental role in bringing the success of control efforts. The appearance of multi-strain epidemics has become a global health concern that requires special attention. Here, we introduce a novel mean-field epidemic game approach to predict the evolutionary dynamics of flu-like epidemics having multiple disease strains. Our model illustrates the importance of multiple provisions alongside their timely execution for better disease attenuation. In addition to vaccination, we introduce self-protection as a potential alternative that yields safeguard against either strain. Both these imperfect provisions render better efficacy against primary (resident) strain than secondary (mutant) to contain epidemic transmission. The simulation-backed model analysis further sheds some light on the crucial impacts of control interventions to limit the invasion of virulent strains from qualitative and quantitative viewpoints. It explicates how vaccination and self-protection complement each other as per situation demands. Our full-fledged theoretical approach further illustrates the dynamic trade-off between the cost and efficacy of a certain intervention. We confirm that the disease dies out when the basic reproduction number of individual strains is less than one and becomes endemic if it is greater than one. Finally, the model addresses the evolutionary consequences when mutation takes place from primary to secondary strain. Some impressive facts while employing dual provisions have been reinforced using a game-theoretic framework.

Noise increases the correspondence between artificial and human vision.

The best performing computer vision systems are based on deep neural networks (DNNs). A study in this issue of PLOS Biology shows that DNNs trained on noisy stimuli are better than standard DNNs at mirroring both human behavioral and neural visual responses.

Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images.

Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs provide a viable model of human vision when tested with challenging noisy images of objects, sometimes presented at the very limits of visibility. We show that popular state-of-the-art DNNs perform in a qualitatively different manner than humans—they are unusually susceptible to spatially uncorrelated white noise and less impaired by spatially correlated noise. We implemented a noise training procedure to determine whether noise-trained DNNs exhibit more robust responses that better match human behavioral and neural performance. We found that noise-trained DNNs provide a better qualitative match to human performance; moreover, they reliably predict human recognition thresholds on an image-by-image basis. Functional neuroimaging revealed that noise-trained DNNs provide a better correspondence to the pattern-specific neural representations found in both early visual areas and high-level object areas. A layer-specific analysis of the DNNs indicated that noise training led to broad-ranging modifications throughout the network, with greater benefits of noise robustness accruing in progressively higher layers. Our findings demonstrate that noise-trained DNNs provide a viable model to account for human behavioral and neural responses to objects in challenging noisy viewing conditions. Further, they suggest that robustness to noise may be acquired through a process of visual learning.

3D CNN to Estimate Reaction Time from Multi-Channel EEG.

The study of human reaction time (RT) is invaluable not only to understand the sensory-motor functions but also to translate brain signals into machine comprehensible commands that can facilitate augmentative and alternative communication using brain-computer interfaces (BCI). Recent developments in sensor technologies, hardware computational capabilities, and neural network models have significantly helped advance biomedical signal processing research. This study is an attempt to utilize state-of-the-art resources to explore the relationship between human behavioral responses during perceptual decision-making and corresponding brain signals in the form of electroencephalograms (EEG). In this paper, a generalized 3D convolutional neural network (CNN) architecture is introduced to estimate RT for a simple visual task using single-trial multi-channel EEG. Earlier comparable studies have also employed a number of machine learning and deep learning-based models, but none of them considered inter-channel relationships while estimating RT. On the contrary, the use of 3D convolutional layers enabled us to consider the spatial relationship among adjacent channels while simultaneously utilizing spectral information from individual channels. Our model can predict RT with a root mean square error of 91.5 ms and a correlation coefficient of 0.83. These results surpass all the previous results attained from different studies.Clinical relevance Novel approaches to decode brain signals can facilitate research on brain-computer interfaces (BCIs), psychology, and neuroscience, enabling people to utilize assistive devices by root-causing psychological or neuromuscular disorders.

Human Behavior in Response to Incentives and Opportunity Costs : Experimental Method

We use experimental methods in examining several aspects of psychology and economics to understand economic phenomena in simulation processes and behavior. We examine human behavior in response to incentives and opportunity costs. We recruited 80 participants by classifying them based on income level, debt owned, cost of living and family dependents. We use a game method where participants play a game in the form of choosing a box that has a cost per box and there is a mystery prize from each box or not choosing at all. each participant can get a prize money based on the decision he made. From the results of the study, almost all participants expected the same results, namely to be able to bring as much money as possible as research incentives. However, variations in decision making, readiness to take risks, and readiness to return home without getting any money can be seen to be influenced by income level, debt owned, cost of living, and family dependents.

Dengue and COVID-19 infections in the ASEAN region: a concurrent outbreak of viral diseases.

Member countries of the Association of Southeast Asian Nations (ASEAN) have faced dengue outbreaks for decades, and the region has one of the highest rates of dengue globally. Outbreaks continue to occur concurrently with the coronavirus disease 2019 (COVID-19) pandemic in the 10 ASEAN countries. Both infectious diseases pose a tremendous burden in these countries related to both infection control and the economy. Increases in the number of dengue cases occurred in part due to disruptions in the pathogen-host-vector relationship caused by changes in human behaviour in response to the COVID-19 pandemic. The spread of dengue was further aggravated by the implementation of lockdowns and social distancing policies. These measures limited the coverage of dengue preventive programs and delayed the medical management of both diseases due to co-infection and misdiagnosis. It is of the utmost importance for the population to remain aware of both diseases, and dengue vector control strategies must be devised to properly address outbreaks using digitalization and remote surveillance. Similarly, critical triage algorithms and further research are also needed to combat co-infection and misdiagnosis. Controlling the spread of COVID-19 though vaccination should also be undertaken to reduce the impact of the pandemic.

Human behaviour in informal settlement fires in Costa Rica

Globally, 1 billion people live in informal settlements, which are typically highly susceptible to fire. Small fires can quickly evolve into large conflagrations causing significant losses of life and property, injuries, and subsequent exacerbation of residents’ existing vulnerabilities. Informal settlement fires are a complex socio-technical phenomenon which involve a combination of fire dynamics, structural and behavioural response. These fires are not broadly researched nor are they well understood. In this paper, the authors attempt to illustrate this multi-faceted issue and provide recommendations to help guide future research.Emphasis is placed on human behaviour in response to fires, including fire response activities by residents and city fire brigades. The case study presented in this paper is a 2019 fire which occurred in El Pochote, an informal settlement located in San José, the capital of Costa Rica. Through the Costa Rican Fire Corps, video footage recorded live and in-situ (70 min) of the brigades’ and residents’ actions in this event was obtained. This video shows real-time human behaviour and fire response activities, as well as complex fire dynamics and resulting structural reactions. It is clear from this footage that human behaviour responses to informal settlement fires are highly coupled with local context and specific situations, demonstrating limitations with extending observations from a specific case study to informal settlements more broadly.This paper introduces a methodology for situational analysis and documentation of human behaviour responses based on video footage of informal settlement fires. It provides key insights to how key stakeholders such as the Costa Rican Fire Corps, the police and informal settlement dwellers interact with each other and respond to fires in informal settlements in Costa Rica. These results form a first-stage contextualization of informal settlement fires in Costa Rica, which can be used to inform the Costa Rican Fire Corps, non-governmental organizations and other stakeholders that may be able to support fire safety improvements in Costa Rican informal settlements. Despite the challenging nature of studying human behaviour from real-life footage, the authors aim to establish a foundation for future research in compiling evidence of human behaviour in informal settlement fires across different countries.

Sex differences shape zebrafish performance in a battery of anxiety tests and in response to acute scopolamine treatment

Sex differences influence human and animal behavioral and pharmacological responses. The zebrafish (Danio rerio) is a powerful, popular model system in neuroscience and drug screening. However, the impact of zebrafish sex differences on their behavior and drug responses remains poorly understood. Here, we evaluate baseline anxiety-like behavior in adult male and female zebrafish, and its changes following an acute 30-min exposure to 800-μM scopolamine, a common psychoactive anticholinergic drug. Overall, we report high baseline anxiety-like behavior and more individual variability in locomotion in female zebrafish, as well as distinct, sex-specific (anxiolytic-like in females and anxiogenic-like in males) effects of scopolamine. Collectively, these findings reinforce the growing importance of zebrafish models for studying how both individual and sex differences shape behavioral and pharmacological responses.

Predictive performance of international COVID-19 mortality forecasting models

Forecasts and alternative scenarios of COVID-19 mortality have been critical inputs for pandemic response efforts, and decision-makers need information about predictive performance. We screen n = 386 public COVID-19 forecasting models, identifying n = 7 that are global in scope and provide public, date-versioned forecasts. We examine their predictive performance for mortality by weeks of extrapolation, world region, and estimation month. We additionally assess prediction of the timing of peak daily mortality. Globally, models released in October show a median absolute percent error (MAPE) of 7 to 13% at six weeks, reflecting surprisingly good performance despite the complexities of modelling human behavioural responses and government interventions. Median absolute error for peak timing increased from 8 days at one week of forecasting to 29 days at eight weeks and is similar for first and subsequent peaks. The framework and public codebase (https://github.com/pyliu47/covidcompare) can be used to compare predictions and evaluate predictive performance going forward.

Artificial Emotional Intelligence and the Intimate Politics of Robotic Sociality

ABSTRACT This article examines Artificial Emotion Intelligence (AEI) and its application in social robots. It argues that AEI and social robotics intensify practices of data-capture and algorithmic governance by extending the spatial reach of digital surveillance deeper into intimate spaces and individual psyches, with the goal of manipulating human emotional and behavioural responses. The analysis demonstrates the need to more thoroughly engage the multiplicity of theoretical and applied approaches to building artificial intelligence, to question assumptions as to the kinds of intelligence being created, and to consider how a diversity of AI systems infiltrate and reshape the spaces of everyday life.

Emotional and behavioural responses to the 19 September 2017 earthquake: the case of the occupants of three multi-storey buildings

PurposeStudies on human behaviour during a seismic emergency in tall buildings are scant. During such emergencies, occupants need to reach a safe place. The purpose of this paper is to address some of the emotional and behavioural responses of the occupants of three multi-storey buildings during the 19 September earthquake that hit Mexico City in 2017.Design/methodology/approachA cross-sectional and non-probability study was conducted using a questionnaire-based survey; the sample size was n = 352, and the study was conducted from 4 October to 20 November 2017.Findings(1) In the 11 storey-building, women, age (18–49 years old [yo]) and participants with higher education exhibited flight behaviour, and those of the six storey-building within the age category 18–49 yo also exhibited a similar behaviour; (2) Women and age (18–49 yo) in the six and 11-storey buildings were significantly associated with fear of the earthquake; (3) Women were significantly more fearful and felt more intense the tremors than men in the 11-storey building; (4) Women were significantly more fearful of the 11-storey building collapsing; (5) The taller the building, the more fearful were the occupants of the building collapsing.Research limitations/implicationsFirst, the sample considered in the study was no probability; consequently, the results should not be generalised to the existing high-rising buildings in Mexico City. Second, some of the variables considered herein were of the Likert-type scale but have been assumed as continuous; in fact, some future work could be the design of a valid and reliable questionnaire to address human behaviour during earthquakes in tall buildings.Practical implicationsThe presented results may be the great value to key decision-makers on how to address the lack of earthquake preparedness during a seismic emergency. Further, the results have shed light on the negative emotions (fear) experienced by the occupants of tall buildings.Social implicationsGaining a better understanding of human behavioural in tall buildings is essential in devising measures to mitigate the impact of earthquake disasters.Originality/valueResearch on human behaviour during a seismic emergency in high-rise buildings is scant. To gain a better understanding of human emotional and behavioural response to earthquakes in tall buildings, it becomes necessary to conduct research such as the present case study. This may help decision-makers to devise measures so that the impact of earthquake disasters may be limited.

Capacity Building Indicators for Faculty Development Programs

Capacity development targets the changes occurs in human behavior in response to learn any new skills, knowledge, behavior and values overtime within complex organization setting. This development process indicates the progressive readiness of human resource to perform in complex environment. Similarly, this growth process of individual would reflect when dealing with others

Human movement influenced by perceived risk of wildlife encounters at fine scales: Evidence from central India

Most research applying the ‘landscape of fear’ concept to human-wildlife interactions explores wildlife responses to anthropogenic risks, such as altered movement patterns. Here, we explored people's landscapes of fear by investigating their perceptions of spatio-temporal variation in the risk of encountering wildlife, and how those perceptions influence their movement. We conducted a participatory risk mapping exercise with people living in the buffer zones of two protected areas in central India, which provide habitat to tigers, leopards, sloth bears, and numerous crop-raiding herbivores. We then tracked people's movement using GPS devices and explored how their movement related to their risk maps. Results of integrated step selection functions show that perceived risk influenced the speed and directedness with which people move, mixed evidence that perceived risk influenced where people went (habitat selection), and variation in how individuals responded to risks from different species. Future research on how humans and wildlife adapt to each other should investigate (1) human behavioral responses to wildlife over longer periods of time, (2) how movement affects the spatial patterns of human-wildlife conflict, and (3) the cultural and cognitive dimensions of how risk and emotions influence people's movement decisions.

COVID-19 Pandemic and Human Behavioral Response

Global human population are perhaps at the face of unprecedented challenge due to most devastative infection of a new virus, severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). A number of important research findings have been published in a very brief period in addition to discovery of vaccines against the target virus. The present communication attempts to brief the reasons behind the deadly nature of COVID-19, its evolutionary history, pathogenic damage to humans and even death. Since first report of COVID-19 in 1960s, the emergence the current pandemic requires more investigations. The use of host cell machinery by the virus for its propagation through respiratory droplet of the infected persons and frequent alterations of its structure, virulence, interactions with the human cell have also been considered. At the same time, the history of pandemics since 430BC as well as the sudden disappearance of SARS-CoV-1 has been discussed to enhance our preparedness to combat such pandemics in future. I also like to remind that adoption of some measures could ensure our win in the battle against the COVID-19 with emphasis on bringing some behavioral change among us at individual level, societal level and in relation to governance and policy.

COVID-19: Early Evening Curfews are Not Effective and May Backfire

Background: During the COVID-19 pandemic, some countries have introduced early evening curfews. Several studies try measure the effectiveness of such measures across different countries, but clear identification of effects is elusive.Methods: We took advantage of a natural experiment in Greece, where curfews shifted from 9pm to 6pm in one region, but not in another. We followed a difference-in-difference econometric approach, where we compared trends in mobility in groceries and pharmacies as well as residential spaces before and after the introduction of the 6pm curfew, in the two regions.Findings: We find that the 6pm instead of 9pm curfew in Athens led to a 4·63 percentage point relative increase in time spent at home and had no effect on time spent in groceries and pharmacies. Considering that this was a result of a 18·75% reduction in hours where people were allowed to leave home, it seems that the early evening curfew led to more crowding in indoor spaces – which may facilitate the spread of disease.Interpretation: We demonstrate that non-pharmaceutical interventions against the Covid-19 pandemic - such as curfews - may lead to an increase in crowding, rather than the intended decrease of it. Policy must take into account the human behavioural response in substitution of activities to prevent harmful consequences of such interventions.Funding: None.Conflict of Interest: The authors have nothing to disclose.Ethical Approval: We did not use any individual-level data, so ethics approval was not required.

Psychological Safety in Aviation New Product Development Teams: Case Study of 737 MAX Airplane

The goal of current study is to discern the antecedents of two airplane accidents involving the Boeing MAX 737. The theory of normal accidents serves as a lens to comprehend the hazard stemming from MAX design with dissonance between two critical systems: engine propulsion and flight control. Cooper’s framework further delineates lack of psychological safety during prototype development from the project’s inception along six dimensions: management/supervision, safety systems, risk, work pressure, competence, and procedures/rules. The analysis indicates dearth of leadership commitment for a safety culture under time pressure and budget constraint. Our results corroborate the paramount importance of the pilot’s extensive simulator training in order to test the interaction between the innovative Maneuvering Characteristics Augmentation System and human behavior response time. Lessons gleaned from the study include three insights. First, the importance of meticulously testing a prototype during the new product development stage and the hazard stemming from improvisation to extend the life of outdated engineering design. Second, the necessity of regulatory authorities, such as the Federal Aviation Administration, undergoing a modernization process by invigorating their ranks with data scientists attuned to 21st century skills in big data analytics. Third, FAA should diminish the delegation of self-certified permits to manufacturers.

Using perceptions to examine human responses to blanket bans: The case of the thresher shark landing-ban in Sri Lanka

Species-specific bans are increasingly being implemented to stem loss of vulnerable marine species, but there is a paucity of evaluative research into resulting socio-economic and ecological consequences. In 2012, a blanket ban on landing Alopiidae (thresher) sharks was introduced in Sri Lanka. We used fisher perceptions, shown to influence support and compliance with conservation policies, to examine human responses. Data, gathered over a ten-month period in 2019 from focus groups and informal engagement during site visits, suggest support for the ban was lowest amongst fishers who perceived negative social consequences to be higher. Perceptions were also undermined by feelings of poor engagement from institutions and a lack of ecological necessity. The ban appears effective in halting targeted fisheries; however, persistent bycatch was reported by fishers. Further, bycatch appears to be widely unrecorded partly owing to mistrust and confusion amongst fishers. Occasional illegal landings were reported, seemingly motivated by interlinked factors such as good economic returns for thresher meat and high vessel running costs. The potential severity and inequity in social consequences stemming from blanket bans was highlighted, particularly when bycatch and targeted fisheries co-exist. Case study lessons are translated into a checklist containing key questions, designed to aid policy-makers to assess data provision and needs prior to introducing bans. Increasing data provision could enhance the capability of policies to predict and adapt to human behavioural responses, a key requirement considering continuing global declines in sharks despite increasing conservation effort.