Human Behavior Research Articles

Nudging visitors into pro-environmental behaviour: assessing the use of a tidal information pillar for effective dynamic zoning

In the past few years, more human-wildlife conflicts have occurred as a result of increased human visitations, particularly in areas where space is scarce and functions need to co-exist. Nature organisations are increasingly challenged to improve nature protection on the one hand, while offering visitors high quality nature experiences on the other hand. To encourage both go hand in hand, nudging has recently received more attention. Nudging is a tool to subtly change human behaviour without imposing strict rules. It is, however, hardly applied in nature areas. Currently, experiments are taking place in the Dutch part of the Wadden Sea with alternating signage (nudging message based on real-time data of the area) aided by a tidal information pillar to encourage dynamic zoning. At low tide the signage indicates: freely accessible, at high tide the advice: ‘do not enter’. The purpose is to address visitors’ sense of responsibility, nudge pro-environmental behaviour and reduce human-wildlife conflicts by limiting access. This article assesses the effectiveness of the alternating nudging signage, and especially the effectiveness of the signage ‘high tide – do not enter’. The results show that the signage on the pillar is most effective when visitors stop at the pillar and read the advice. Among these visitors, about half turn around. Among the visitors who do not encounter the signage and the pillarn, the majority goes on to access the area. With this study, we aim to contribute to the knowledge on nudging as a tool to promote pro-environmental behaviour in nature areas.

Dissecting of the two-stages object detection models architecture and performance

Artificial intelligence (AI) is the discipline focused on enabling computers to operate autonomously without explicit programming. Within AI, computer vision is an emerging field tasked with endowing machines with the ability to interpret visual data from images and videos. Over recent decades, computer vision has found applications in diverse fields such as autonomous vehicles, information retrieval, surveillance, and understanding human behavior. Object detection, a key aspect of computer vision, employs deep neural networks to continually advance detection accuracy and speed. Its goal is to precisely identify objects within images or videos and assign them to specific classes. Object detection models typically consist of three components: a backbone network for feature extraction, a neck model for feature aggregation, and a head for prediction. The focus of this study lies on two stage detectors. This study aims to provide a comprehensive review of two stage detectors in object detection, followed by benchmarking to offer insights for researchers and scientists. By analyzing and understanding the efficacy of these models, this research seeks to guide future developments in the field of object detection within computer vision.

Artificial Intelligence: A Quick Overview of Speech Recognition System

Abstract: The study of intelligent behaviour is known as artificial intelligence. Wagner said, "We build intelligent machines in science." By this, he implied that the primary goal is to teach these sophisticated devices, such as computers, to examine and comprehend human conduct. numerous believed that human intelligence might be understood through the construction of several programmes, while other researchers believed that numerous basics should be required in order to accomplish the intended objective. We can carry out or replicate any type of task we conduct using a computer. Therefore, computers are the ideal devices for developing artificial intelligence. In the hopes that they will outperform computers in several other areas, some researchers created additional computing devices. Billions of dollars were invested in creating new devices that surpassed the speed of the computer used to simulate software. However, the computers and the code both need to be extremely quick. As you learn about artificial intelligence, you may wonder, what really is intelligence? How is intelligence measured? Turn become something quite significant. In this case, the programme that evaluates its surroundings acts as the intelligent agent. Modern digital computers and human minds are comparable to one other in ways such as symbolic information processing systems. Both use symbolic data as input, change it in accordance with predetermined guidelines, and then use the results to solve issues. In order to mechanically replicate intelligent human activity, artificial intelligence researchers have programmed some algorithms to recognise intelligent human behaviour. Human conduct in language processing, chess, and other games, as well as medical diagnostics, may be used to monitor this activity. Voice recognition is a key component of AI. A certain voice may be recognised using voice recognition technology. The cornerstone for speaker identification is voice signals. Voice targeting is applicable to a wide range of applications, including voice mail, database access, phone banking, and phone purchasing. The ability to enter one's voice for verification is among the most potent uses of voice recognition for security. The fundamental means of interpersonal communication is speech. The technique of translating voice sounds into appropriate text is known as speech recognition. Over the past few years, speech recognition technology has advanced significantly. Nonetheless, there are other significant study obstacles, such as variations in speaker and language, ambient sound, word size, etc. This study aims to give a comprehensive overview of speech acceptance by summarising the several approaches utilised in the standard speech system and describing the numerous processes involved

Testing theory of mind in large language models and humans.

At the core of what defines us as humans is the concept of theory of mind: the ability to track other people's mental states. The recent development of large language models (LLMs) such as ChatGPT has led to intense debate about the possibility that these models exhibit behaviour that is indistinguishable from human behaviour in theory of mind tasks. Here we compare human and LLM performance on a comprehensive battery of measurements that aim to measure different theory of mind abilities, from understanding false beliefs to interpreting indirect requests and recognizing irony and faux pas. We tested two families of LLMs (GPT and LLaMA2) repeatedly against these measures and compared their performance with those from a sample of 1,907 human participants. Across the battery of theory of mind tests, we found that GPT-4 models performed at, or even sometimes above, human levels at identifying indirect requests, false beliefs and misdirection, but struggled with detecting faux pas. Faux pas, however, was the only test where LLaMA2 outperformed humans. Follow-up manipulations of the belief likelihood revealed that the superiority of LLaMA2 was illusory, possibly reflecting a bias towards attributing ignorance. By contrast, the poor performance of GPT originated from a hyperconservative approach towards committing to conclusions rather than from a genuine failure of inference. These findings not only demonstrate that LLMs exhibit behaviour that is consistent with the outputs of mentalistic inference in humans but also highlight the importance of systematic testing to ensure a non-superficial comparison between human and artificial intelligences.

An Evolutionary Psychological Approach Toward BDSM Interest and Behavior.

Bondage/discipline, Dominance/submission, and Sadism/Masochism (BDSM) have gained increased attention and discussion in recent years. This prevalence is accompanied by a shift in perceptions of BDSM, including the declassification of sadomasochism as a paraphilic disorder. Evolutionary psychology offers a unique perspective of why some individuals are interested in BDSM and why some prefer certain elements of BDSM over others (e.g., dominance versus submission). In this paper, we examine BDSM from an evolutionary standpoint, examining biopsychosocial factors that underlie the BDSM interests and practice. We articulate this perspective via an exploration of: proximate processes, such as the role of childhood experiences, sexual conditioning, and physiological factors; as well as ultimate explanations for power play and pain play dimensions of BDSM, highlighting the potential adaptive advantages of each. While BDSM may not be adaptive in itself, we examine the literature of sex differences in BDSM role preferences and argue that these preferences may stem from the extreme forms of behaviors which enhance reproductive success. In the realm of pain play, we explore the intersection of pain and pleasure from both physiological and psychological perspectives, highlighting the crucial role of psychological and play partner factors in modulating the experience of pain. Finally, we encourage future research in social sciences to utilize evolutionary frameworks to further explore the subject and help alleviate the mystification surrounding BDSM. This multifaceted exploration of BDSM provides valuable insights for clinicians, kink-identified individuals, and scholars seeking to understand the evolutionary perspectives of human sexual behavior and preferences.

Movement trajectories as a window into the dynamics of emerging neural representations

The rapid transformation of sensory inputs into meaningful neural representations is critical to adaptive human behaviour. While non-invasive neuroimaging methods are the de-facto method for investigating neural representations, they remain expensive, not widely available, time-consuming, and restrictive. Here we show that movement trajectories can be used to measure emerging neural representations with fine temporal resolution. By combining online computer mouse-tracking and publicly available neuroimaging data via representational similarity analysis (RSA), we show that movement trajectories track the unfolding of stimulus- and category-wise neural representations along key dimensions of the human visual system. We demonstrate that time-resolved representational structures derived from movement trajectories overlap with those derived from M/EEG (albeit delayed) and those derived from fMRI in functionally-relevant brain areas. Our findings highlight the richness of movement trajectories and the power of the RSA framework to reveal and compare their information content, opening new avenues to better understand human perception.

Flexible Nanofiber Pressure Sensors with Hydrophobic Properties for Wearable Electronics

In recent years, flexible pressure sensors have received considerable attention for their potential applications in health monitoring and human–machine interfaces. However, the development of flexible pressure sensors with excellent sensitivity performance and a variety of advantageous characteristics remains a significant challenge. In this paper, a high-performance flexible piezoresistive pressure sensor, BC/ZnO, is developed with a sensitive element consisting of bacterial cellulose (BC) nanofibrous aerogel modified by ZnO nanorods. The BC/ZnO pressure sensor exhibits excellent mechanical and hydrophobic properties, as well as a high sensitivity of −15.93 kPa−1 and a wide range of detection pressure (0.3–20 kPa), fast response (300 ms), and good cyclic durability (>1000). Furthermore, the sensor exhibits excellent sensing performance in real-time monitoring of a wide range of human behaviors, including mass movements and subtle physiological signals.

Relationship between Socioeconomic Status and Pro-Environmental Behavior: The Role of Efficacy Beliefs

Efficacy beliefs are important determinants of human behavior. In the context of social cognitive theory, the perception of collective efficacy is closely related to the individual perception of self-efficacy, which is influenced by socio-structural factors such as socioeconomic status (SES). Surprisingly, the relationship between these variables has received little attention in the literature on environmental issues. Within the framework of social cognitive theory, the aim of this study was to investigate whether SES has a direct effect on pro-environmental behavior and whether it has an indirect effect via perceptions of self-efficacy and collective efficacy, in relation to climate change mitigation behavior. An online cross-sectional study was conducted using a quota sample of 1075 participants (51.9% women) aged 18–79 years. Participants reported their SES using objective and subjective measures, perceptions of their own and collective efficacy in mitigating climate change, and the frequency of their pro-environmental behaviors. Structural equation modeling revealed that the model with serial mediation effects of self-efficacy and collective efficacy between SES (both objective and subjective) and pro-environmental behaviors showed a good model fit. As expected, both objective and subjective SES had no direct effect on pro-environmental behavior. Surprisingly, neither objective nor subjective SES had an indirect effect (via efficacy beliefs) on pro-environmental behavior. However, both self-efficacy and collective efficacy were associated with pro-environmental behavior. These findings have practical implications for the development of strategies aimed at enhancing pro-environmental behavior.

Ethical Considerations in AI Simulations for Designing Assistive Technologies

Current ethical debates on the use of artificial intelligence (AI) in healthcare approach AI technology in three primary ways. First, they assess the risks and potential benefits of current AI-enabled products using ethical checklists. Second, they propose ex ante lists of ethical values relevant to the design and development of assistive technologies. Third, they advocate for incorporating moral reasoning into AI's automation processes. These three perspectives dominate the discourse, as evidenced by a brief literature summary. We propose a fourth approach: viewing AI as a methodological tool to aid ethical reflection. This involves an AI simulation concept informed by three elements: 1) stochastic human behavior models based on behavioral data for simulating realistic scenarios, 2) qualitative empirical data on value statements regarding internal policy, and 3) visualization components to illustrate the impact of variable changes. This approach aims to inform an interdisciplinary field about anticipated ethical challenges or trade-offs in specific settings, prompting a re-evaluation of design and implementation plans. This is particularly useful for applications involving complex values and behaviors or limited communication resources, such as dementia care or care for individuals with cognitive impairments. While simulation does not replace ethical reflection, it allows for detailed, context-sensitive analysis during the design process and before implementation.Finally, we discuss the quantitative analysis methods enabled by stochastic simulations and the potential for these simulations to enhance traditional thought experiments and future-oriented technology assessments.

Understanding Tsunami Evacuation via a Social Force Model While Considering Stress Levels Using Agent-Based Modelling

Given massive events, such as demonstrations in coastal cities exposed to tsunamigenic earthquakes, it is essential to explore pedestrian motion methods to help at-risk coastal communities and stakeholders understand the current issues they face to enhance disaster preparedness. This research targets SDG 11 Sustainable Cities and Communities. It strengthens resilience in coastal areas by implementing a social force model using a microscopic agent-based model to assess the impact of human behaviour on evacuation performance by introducing evacuation stress levels due to a tsunami triggered in central Chile. Two scenarios with two environments and three crowd sizes are implemented in NetLogo. In Scenario 1, pedestrians walk at a relaxed velocity. In Scenario 2, tsunami evacuation stress is incorporated, resulting in pedestrians walking at a running velocity, taking, on average, four times less time to evacuate. We explored more realistic settings by considering the internal susceptibility of each agent to spread tsunami evacuation stress among other evacuees. Results from Scenario 2 show that internal susceptibility effects almost double the mean evacuation time for 200 agents. Findings suggest a trade-off between realism and the minimization of evacuation time. This research is considered a first step toward including stress in tsunami evacuations for sustainable evacuation planning.

Computational reconstruction of mental representations using human behavior

Revealing how the mind represents information is a longstanding goal of cognitive science. However, there is currently no framework for reconstructing the broad range of mental representations that humans possess. Here, we ask participants to indicate what they perceive in images made of random visual features in a deep neural network. We then infer associations between the semantic features of their responses and the visual features of the images. This allows us to reconstruct the mental representations of multiple visual concepts, both those supplied by participants and other concepts extrapolated from the same semantic space. We validate these reconstructions in separate participants and further generalize our approach to predict behavior for new stimuli and in a new task. Finally, we reconstruct the mental representations of individual observers and of a neural network. This framework enables a large-scale investigation of conceptual representations.

A Study on Behavioural Finance

This research paper delves into the intriguing field of behavioral finance, exploring how psychological factors influence financial decision-making processes. Behavioral finance seeks to understand why people make irrational financial decisions despite being aware of the consequences. It bridges the gap between economics and psychology, offering insights into human behavior that traditional finance models often overlook. The study examines various aspects of behavioral finance, including cognitive biases, market anomalies, and investor behavior under different market conditions. Through a comprehensive review of existing literature and empirical studies, this paper aims to shed light on the complex interplay between human emotions, cognitive limitations, and financial markets. The findings contribute to a deeper understanding of investor behavior, potentially informing strategies for financial advisors and investors alike. This research underscores the importance of incorporating psychological principles into financial analysis, highlighting the potential for improved investment outcomes through a more nuanced understanding of human behavior.

Exploring the Influence of Emotional Competence on Humor Styles and Personality Traits

This research aims to uncover the complexities of the dynamics that regulate human behavior and connection with others by investigating the relationships between humor styles, emotional competence, and personality factors. Using a wide range of literature review and empirical research, this study examines how individuals' humor styles, defined by their tendency to affiliate, self-enhance, be aggressive, or dislike themselves, interact with emotional competence and personality characteristics. As a transdisciplinary construct, humor provides various psychological functions and shapes people's emotional experiences and social relationships. The affiliative style, which uses humor to strengthen social ties and relieve tension, has been linked to increased emotional intelligence and extraversion. Conversely, aggressive humor, which includes sarcasm and derision, is associated with weaker emotional competence and greater degrees of neuroticism. Emotional competence, which provides for emotional awareness, management, and expression, is critical in balancing the impacts of various humor styles on psychological well-being and interpersonal interactions. Individuals with greater emotional competence prefer to use adaptive humor styles, which promote good emotions and social cohesiveness. In contrast, individuals with lower emotional competence may use maladaptive methods, such as self-defeating humor, as a coping strategy. Furthermore, psychological qualities like extraversion, neuroticism, and openness to experience influence people's humor preferences and usage habits. Extraverts, for example, are likelier to engage in affiliative humor, whereas neurotic persons may use self-defeating humor as a defense strategy. This study adds to a better understanding of human behavior by illuminating the interaction between humor styles, emotional competence, and personality factors. It also gives insights into how to promote psychological well-being and efficient interpersonal communication.”

How Parenting Style Varies Between the Sexualities and Cultures in the Aspects of Evolutionary Psychology

From the perspective of evolutionary psychology, the evolution of human parenting styles is delved into, considering various mechanisms and factors influencing it. The primary focus is placed on how these parenting styles have been changed over time and influenced by different cultures.The paper analyzes five key evolutionary mechanisms and their impact on parenting styles.The first mechanism explores how the transition from polygamous mating to normative monogamy in history increased paternal investment in offspring. The second mechanism delves into how cultural differences between Eastern and Western societies have shaped distinct parenting styles. The third evolutionary mechanism examines how different family structures have led to variations in child-rearing approaches.The fourth point discusses how the progress of women's status in society has brought about shifts in marital dynamics and parenting practices. Lastly, building upon the fourth evolutionary mechanism, the paper analyzes the relationship between the advancement of women's status, increased divorce rates, and the consequent influence on parenting styles within single-parent families.The overarching conclusion drawn from this paper is that human parenting styles, from ancient nomadic periods to contemporary societies, have evolved in response to various evolutionary mechanisms and changing environmental factors. Parenting decisions are intricately tied to specific temporal, spatial, and environmental contexts, ultimately serving the goals of reproduction and survival. Valuable insights into the evolution of parenting styles have been provided, emphasizing the importance of considering a variety of influences when studying human behavior.

Framed or Freedom? Emotional Discourse of Individuals to the Overturned of Roe V. Wade

The Roe V. Wade case has long been a noteworthy issue in the United States. According to research Basel 2022, approximately 504, 803 tweets have been filtered based on terms related to abortion. By collecting information and posts on Twitter, this study hopes to demonstrate how attitudes have changed in response to the adoption of abortion regulations. Its interesting to learn how the attitudes of various local residents toward this new law relate to one another. Sentiment analysis is applied to 200 postings with typical features in order to accomplish this goal. In order to complete and build a more distinct future trend, data are compared and evaluated with historical abstracts. The findings imply that people have a moderate tendency to take an optimistic perspective. Having stated that, this conclusion offers a projection of potential human behavior and the underlying rationale determining various perceptions. This study also seeks to understand the social repercussions and intimate relationship between abortion and conception. Which introduces feminism, gender equality, teen problems, and self-induced abortion by addressing potential results and possible conflicts. To sum up, this study uses emotional analysis and additional academic approaches to investigate the relationship between various demographic, and socioeconomic groups and their attitudes beforehand and following Roe v. Wade. Understanding how people feel is of utmost importance as abortion continues to be discussed incessantly online.

The Jojosi Dongas: An interdisciplinary project to study the evolution of human behaviour and landscapes in open-air contexts

Hunter-gatherer groups conduct most of their activities in open landscapes as they provide drinking water, food, and raw materials, and offer spaces for social gatherings. The remains left behind at such sites allow for unique archaeological insights into the spatial patterning of prehistoric behaviour. The Stone Age record in southern Africa remains best-known from sheltered sites. A paucity of stratified open-air localities precludes understanding the full spectrum of past hominin activities. Here we introduce an interdisciplinary project in KwaZulu-Natal to study the evolution of human behaviour and landscape dynamics during the Pleistocene in the open-air context of a stratified hillslope with sediments exposed in so-called dongas, a landform created by gully erosion. The project encompasses field and laboratory approaches, combining archaeological, geographical, geological, chronometric, and palaeoenvironmental data. After reviewing relevant open-air research in archaeology and geography, we identify the Jojosi Dongas as a promising research area. Our fieldwork results from 2022-2023 demonstrate the high archaeological, geographical, and geological potential of this landscape. Foot surveys found abundant MSA artefacts spread throughout the dongas, one area with ESA tools, but little to no traces of LSA or later material. Most finds lie on the surface with rarer stratified material occurring in exposed profiles. The surface MSA material is characterised by almost exclusive hornfels use, frequent cortical pieces, many large blanks and cores, and rare retouched tools. These features differ markedly from lithic trends observed in well-known shelter sites, likely the result of differences in site function. Based on the nature of the surface assemblages and the presence of a large outcrop of high-quality hornfels, we hypothesise that the Jojosi Dongas may have been a specialised quarry and workshop area. The stratified MSA occupations are the focus of ongoing excavations and further studies will aim to test our preliminary interpretations provided here.

Structural connectivity between olfactory tubercle and ventrolateral periaqueductal gray implicated in human feeding behavior.

The olfactory tubercle (TUB), also called the tubular striatum, receives direct input from the olfactory bulb, and along with the nucleus accumbens, is one of the two principal components of the ventral striatum. As a key component of the reward system, the ventral striatum is involved in feeding behavior, but the vast majority of research on this structure has focused on the nucleus accumbens, leaving the TUB's role in feeding behavior understudied. Given the importance of olfaction in food seeking and consumption, olfactory input to the striatum should be an important contributor to motivated feeding behavior. Yet the TUB is vastly understudied in humans, with very little understanding of its structural organization and connectivity. In this study, we analyzed macrostructural variations between the TUB and the whole brain, and explored the relationship between TUB structural pathways and feeding behavior, using body mass index (BMI) as a proxy in females and males. We identified a unique structural covariance between the TUB and the periaqueductal gray (PAG), which has recently been implicated in the suppression of feeding. We further show that the integrity of the white matter tract between the two regions is negatively correlated with BMI. Our findings highlight a potential role for the TUB-PAG pathway in the regulation of feeding behavior in humans.Significance Statement Increasing evidence suggests that olfaction plays an important role in human feeding behavior. However, the neural underpinnings of this role remain relatively unexplored. Here, we examined the structural connectivity of the olfactory tubercle, which has been implicated in both olfaction and reward, using magnetic resonance imaging. We found that a unique connectivity of the olfactory tubercle with the periaqueductal gray was correlated with body mass index. Our findings highlight a potential role for this pathway in the regulation of human feeding behavior.

Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics.

Individuals' socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies.

Advocating for a behavioural science approach to inclusion and diversity

In recent years the benefits of inclusion and diversity have become increasingly clear. Australian and international studies have demonstrated the significant improvements in innovation, productivity and growth that can be achieved when teams are both inclusive and diverse. However, meaningful progress requires moving beyond traditional diversity initiatives. This paper highlights the potential use of behavioural science to design successful implementation strategies to improve diversity and inclusion in the upstream energy industry. This paper will also provide guidance on how scientific methodologies can be applied to measure impact and return on investment (ROI), aligning the business case for diversity and inclusion with individual interventions. Behavioural science involves the observation, hypothesis, experiment and analysis of human behaviour to draw conclusions. It is now a leading school of thought at the world’s top research and learning organisations. This paper argues that by measuring outcomes of diversity and inclusion interventions through a behavioural science approach, organisations can make informed decisions, identify areas of improvement, and refine their strategies to improve ROI. This approach not only ensures that resources are invested effectively but also fosters a culture of continuous learning and adaptation, leading to sustainable and meaningful progress for all employees and stakeholders. Drawing on international research and local case studies, this paper showcases successful applications of behavioural science in transforming organisational cultures, creating safer and more inclusive workplaces. Ideas for quantitative and qualitative measurements are proposed for application in the upstream energy industry, with a particular focus on operational people and performance.

A system mapping activity to visualize lithium’s interconnectedness to societal and environmental aspects of the green energy transition

Abstract Lithium’s role in the global green energy transition provides an engaging context to visualize the interconnectedness of chemistry to seismic shifts taking place in society. Lithium has seen a dramatic increase in utilization, but given lithium’s current low rates of recyclability, this development is exacerbating the e-waste problem. Equally important, we posit that lithium extraction, from either brine or ore, and the associated impacts on the environment and local communities should not be so easily decoupled from the shift in human behaviors causing its demand. Presented here is a mapping activity that was trialed in professional learning workshops organized in New Zealand for secondary/high school chemistry teachers. In their mapping activity response, the teachers were able to connect typical school chemistry content (batteries, chemical processes) with environmental (planetary systems) and social, economic, and ethical considerations (useful products, unintended consequences, inequity in access to water) of the ongoing electrification of society. The teachers indicated a positive intention to utilize the activity, or one similar with a different chemical process or product, in their own classrooms. A school-ready version of the activity is provided in the supplementary information, which was revised based on feedback from the teachers attending the workshops.