Past Behavior Research Articles

Pedestrian behavior interacting with autonomous vehicles during unmarked midblock multilane crossings: Role of infrastructure design, AV operations and signaling

One of the main challenges autonomous vehicles (AVs) will face is interacting with pedestrians, especially at unmarked midblock locations where the right-of-way is unspecified. This study investigates pedestrians' crossing behavior given different roadway centerline features (i.e., undivided, two-way left-turn lane, and median) and various AV operational schemes portrayed to pedestrians through on-vehicle signals (i.e., no signal, yellow negotiating indication, and yellow/blue negotiating/no-yield indications). This study employs virtual reality (VR) to simulate an urban unmarked midblock environment where pedestrians interact with AVs as they cross a four-lane arterial roadway. Results demonstrate that both roadway centerline design features and AV operations and signaling significantly impact pedestrians' unmarked midblock crossing behavior, including the waiting time at the curb, waiting time in the middle of the road, and the total crossing time. But only the roadway centerline design features significantly impact the walking time. Participants in the undivided scene spent a longer time waiting at the curb and walking on the road than in the median and TWLTL scenes, but they spent a shorter time waiting in the middle of the road. Compared to the AV without a signal, the design of yellow signal significantly reduced pedestrian waiting time at the curb and in the middle. But yellow/blue signals significantly increased the pedestrian waiting time. Interaction effects between roadway centerline design features and AV operations and signaling are significant only for waiting time in the middle of the road. Other factors, such as demographics, past behaviors, and walking exposure of pedestrians, are also explored. Results indicate that older individuals tend to wait longer before making crossing decisions, and pedestrians’ past crossing behaviors and past walking exposures do not significantly impact pedestrian walking behavior interacting with AV.

The Rating of Basketball Players' Competitive Performance Based on RBF-EVA Method

Basketball, as an offensive and defensive game centered around high altitude, has become an international mass competitive sport. Traditional methods cannot comprehensively evaluate the future potential of players, nor can they simply add up individual competitive abilities to judge the overall competitive performance of a team. To address these issues, this article proposes a video-based RBF neural network competitive scoring method, which analyzes players' past sports behavior, captures every subtle difference in their abilities, and achieves objective evaluation of players' competitive performance. Through comparative experiments, the accuracy of the test results is improved by about 5% compared to conventional RBF methods. This indicates that the improved RBF neural network designed in this article has significantly better prediction performance than traditional convolutional neural networks. This study provides a new method for evaluating the competitive performance of basketball players and has important guiding significance for basketball training and skill enhancement.

Hydrothermal Treatment via Microwave Radiation Improves Viscoelastic Properties of Native Gluten-Free Flours for Extrusion 3D Printing

The market for gluten-free products is experiencing significant growth due to the increase in the number of gluten/wheat affected patients diagnosed, but largely as a result of the emergence of a new niche market dedicated for consumers who optionally avoid gluten. Native flours are perceived as viable alternative for industrially used starch and hydrocolloids blends, mainly due to their lack of vitamins and minerals, which are abundant in non-refined raw materials. Edible inks for on-demand printing are under significant consideration, while texture building capacity remains an issue. As heat-moisture treatment has proved to be useful for stabilizing the pasting and rheological behavior of various native flours, HMT supported by microwave heating was investigated as printable ink stabilizers. For Spanish and Polish buckwheat flours and two different varieties of teff (white and brown) flour pasting, structural and textural characteristics after the microwave supported heat moisture treatment in 30% of initial moisture content were evaluated. The peak viscosity was reduced by 54% and 60% for Polish and Spanish flour, respectively, while for teff, the reduction was 15% and 43% for the white and brown varieties, respectively. Significant improvement in viscoelastic modulus G’ (for Polish and Spanish buckwheat flour, 32% and 16%, respectively; for white and brown tef varieties, 14% and 18%, respectively) was observed for all the treated samples regardless of the species or variety; this resulted in better performance during 3D printing.

Implicit Identification with Death, Clinician Evaluation and Suicide Ideation among Adolescent Psychiatric Outpatients-The Mediating Role of Depression

Implicit identification with death (i.e., subconsciously self-associating oneself with death), measured by the Death-Suicide Implicit Association Test (D/S-IAT), is associated with Suicide Ideation (SI). Our understanding of the mechanisms underlying this association is limited. The current study examined (1) the mediating role of depression between D/S-IAT and recent SI and (2) the association between SI, D/S-IAT, and clinician evaluation of SI among a clinical sample of adolescents. 148 adolescents aged 10–18 years (69.4% female) from two outpatient clinics were assessed at intake. Participants completed D/S-IAT and self-report measures for recent SI and depression during intake. Findings indicate that depression is a mediator between D/S-IAT and recent SI, controlling for gender, site differences, and past suicidal thoughts and behaviors. D/S-IAT and clinician evaluation were correlated with recent SI but not beyond depression. Our findings highlight the importance of examining the underlying psychological mechanisms regarding the association between D/S-IAT and suicide.

The Byzantine monastery as a commons

Although scholars have paid increased attention to commons, most studies explore modern cases, disregarding historical commons. The analysis of the latter can contribute to understanding the long-term effects of past behaviours on future generations and provide inspiration for solutions to contemporary problems arising from similar social dilemmas. One historical commons that still exists is the Byzantine monastic institution. Drawing on historical sources and contemporary studies, the paper uses (a) historical institutional analysis, to outline the structure of the institution, and (b) the community design principles of successful commons, to explore whether the Byzantine monastery can be classified as a commons. We find that the Byzantine monastery was a successful case of a historical commons, which developed a credible governance structure to sustainably manage and preserve their common goods, both intangible and tangible, despite the lack of direct democratic processes that characterize modern commons.

Effects of three different polysaccharides on the sol gel-behavior, rheological, and structural properties of tapioca starch

The sol-gel behavior of tapioca starch (TS) plays a crucial role in the processing and quality control of flour-based products. However, natural tapioca starch has low gel strength and poor viscosity, which tremendously limits its application. To solve this problem, this study investigated the effects of κ-carrageenan (KC), konjac gum (KGM), and Mesona chinensis Benth polysaccharide (MCP) on the pasting behavior, rheological, and structural properties of tapioca starch. KC, KGM, and MCP significantly increased the viscosity of TS. With the exception of high-concentration KGM (0.5 %), all other blending systems showed decrease in setback. This may be attributed to the stronger effect of the high-concentration KC (0.5 %) and MCP (0.5 %) functional groups interacting with starch. KC, KGM, and MCP effectively improved the dynamic modulus (G' and G") of TS gel and were effective in increasing the gel strength and hardness of TS. The FT-IR analysis indicated that the short-range order of TS was mainly influenced by polysaccharides through non-covalent bonding interactions. Furthermore, it was confirmed that three polysaccharides could form dense structures by hydrogen bonding with TS. Similarly, more stable structure and pore size were observed in the microstructure diagram.

How do explicit, implicit, and sociodemographic measures relate to concurrent suicidal ideation? A comparative machine learning approach.

Suicide is a leading cause of death, and decades of research have identified a range of risk factors, including demographics, past self-injury and suicide attempts, and explicit suicide cognitions. More recently, implicit self-harm and suicide cognitions have been proposed as risk factors for the prospective prediction of suicidal behavior. However, most studies have examined these implicit and explicit risk factors in isolation, and little is known about their combined effects and interactions in the prediction of concurrent suicidal ideation. In an online community sample of 6855 participants, we used different machine learning techniques to evaluate the utility of measuring implicit self-harm and suicide cognitions to predict concurrent desire to self-harm or die. Desire to self-harm was best predicted using gradient boosting, achieving 83% accuracy. However, the most important predictors were mood, explicit associations, and past suicidal thoughts and behaviors; implicit measures provided little to no gain in predictive accuracy. Considering our focus on the concurrent prediction of explicit suicidal ideation, we discuss the need for future studies to assess the utility of implicit suicide cognitions in the prospective prediction of suicidal behavior using machine learning approaches.

Is Deceitful Autobiographical Memory Really Forgotten?

Autobiographical memory for deceitful events is said to be forgotten over time to reduce guilt and stress. People who engage in deceitful behavior continue to do so because they are able to stretch their memories to match their moral outlook. In this study, the authors wanted to see if participants who engage in deceitful behavior will change their behavior if they are reminded of their previous misdeeds and compare it with reminding them of past moral behavior and any neutral event. We also studied how the experience, or phenomenology of remembering, differs between immoral and moral memories. In Experiment 1, we found evidence to suggest that reminding deceptive autobiographical memory does not reduce deceptive behavior. In Experiment 2, we found evidence to suggest phenomenological characteristics of Immoral and moral memories are not significantly different from each other but they are both significantly different from that of neutral memory. This contradicts established results in the field. It is interesting to note that only emotional valence is significantly different between immoral and moral memory.

Investigating residents’ willingness to participate in urban edible landscaping: Perspectives from China

In the context of the persistent food crisis and shifting societal dynamics, the concept of ‘edible landscaping’ has garnered increasing attention. Edible landscaping entails integrating food production into urban green spaces, offering a novel approach to address both food security and environmental sustainability. However, in China, conflicts regarding urban green spaces have arisen due to inadequate legal framework and management strategies. Gaining a better understanding of residents’ behavioral intention and willingness to participate will provide support for future intervention measures by decision-makers. This study proposes an extended model based on the Theory of Planned Behavior to investigate the effects of individual attributes on behavioral intentions. An online questionnaire survey was conducted in Hefei, China for hypotheses verification. The findings indicate that residents’ intention to participate in edible landscaping is influenced by perceived benefits and costs, attitudes, perceived behavioral control, and subjective norm. Multi-group analyses reveal the moderating effects of past behavior, age, and gender on the proposed models. This study underscores the significance of promoting the benefits of edible landscaping while mitigating unfavorable factors. Additionally, it is important to consider the specific needs of different population groups. These findings have practical implications for future planning, implementation, and management of edible landscaping initiatives.

The Stickiness of Category Labels: Audience Perception and Evaluation of Producer Repositioning in Creative Markets

Market producers often seek to position themselves in different categories over time. Successful repositioning is difficult, however, as audiences often devalue offerings that depart from a producer’s past creations. Prior research suggests that this penalty arises as evaluators withhold opportunities for producers to reposition because of presumptions of a lack of competence in different categories. In this paper, we develop understanding of a novel evaluator-driven challenge to producers’ repositioning efforts: evaluators are prone to “categorical stickiness,” by which the categories they have come to associate with a producer through its prior offerings shape their perceptions of the producer’s subsequent offerings. The result is a systematic mismatch between what producers claim and what evaluators perceive when a producer repositions. We further propose that audience members who have the greatest prior experience with a producer are the least likely to recognize its repositioning efforts. We examine evidence for our theory using data from Goodreads.com on authors within the book publishing industry, 2007–2017. We first build a novel deep-learning framework to predict categorization of a given book based solely on an author’s description of its content. We then use data on how Goodreads users categorize and evaluate books as well as their past reading behavior to test for evidence of our proposed mechanism. Overall, our results extend understanding of the evaluative processes that generate categorical constraints and how these may differ among various types of audience members. This paper was accepted by Isabel Fernandez-Mateo, organizations. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2021.02070 .

Never miss a beep: Using mobile sensing to investigate (non-)compliance in experience sampling studies

Given the increasing number of studies in various disciplines using experience sampling methods, it is important to examine compliance biases because related patterns of missing data could affect the validity of research findings. In the present study, a sample of 592 participants and more than 25,000 observations were used to examine whether participants responded to each specific questionnaire within an experience sampling framework. More than 400 variables from the three categories of person, behavior, and context, collected multi-methodologically via traditional surveys, experience sampling, and mobile sensing, served as predictors. When comparing different linear (logistic and elastic net regression) and non-linear (random forest) machine learning models, we found indication for compliance bias: response behavior was successfully predicted. Follow-up analyses revealed that study-related past behavior, such as previous average experience sampling questionnaire response rate, was most informative for predicting compliance, followed by physical context variables, such as being at home or at work. Based on our findings, we discuss implications for the design of experience sampling studies in applied research and future directions in methodological research addressing experience sampling methodology and missing data.

Microscale fracture and creep analysis of 3D porous graphene-based cementitious material by nanoindentation test and energy-based method

As an exceptional nanomaterial, three-dimensional (3D) porous graphene possesses a promising capacity to enhance the performance of cementitious materials and reduce the usage of cement. However, the microscopic understanding of the fracture and creep behaviors of 3D porous graphene-based cementitious materials remains unclear. Here, we combine nanoindentation experiments and the energy-based method to investigate the microscale fracture and creep behaviors of both mortars and cement pastes. Specifically, we use the energy-based method to assess elastic modulus, hardness, fracture toughness, energy releasing rate, creep modulus, and creep characteristic time of cementitious materials containing 3D porous graphene. Our outcomes indicate that the additions of 3D porous graphene to both the mortar and cement paste improve their elastic behaviors. The fracture toughness and energy releasing rate reach the optimal values at 3D porous graphene content of 0.05 wt%. In addition, the presence of 3D porous graphene promotes the formation of high-density calcium silicate hydrate (C-S-H) and reduces the creeps in cementitious materials. Our findings provide insights into the performance of graphene-cementitious composites and represent a step forward toward the practical application of 3D porous graphene in concrete.

Movie recommendation system using taymon optimized deep learning network

The increased usage of the internet and social networks generates a large volume of information. Exploring through the large collection is time-consuming and hard to find the required one, so there is a serious need for a recommendation system. Based on this context several movie recommendation (MR) systems have been recently established. In addition, they have poor data analytics capability and cannot handle changing user preferences. As a result, there are many movies listed on the recommendation page, which provides for a poor user experience is the major issue. Therefore, in this work, a novel Taymon Optimized Deep Learning network (TODL net) for recommending top best movies based on their past choices, behaviour and movie contents. The deep neural network is a combination of Dilated CNN with Bi-directional LSTM. The DiCNN-BiLSTM model eliminates the functionality pooling operations and uses a dilated convolution layer to address the issue of information loss. The DiCNN is employed to learn the movie contents by mining user behavioral pattern attributes. The BiLSTM is applied to recommend the best movies on basis of the extracted features of the movie rating sequences of users in other social mediums. Moreover, for providing better results the DiCNN-BiLSTM is optimized with Taymon optimization algorithm to recommend best movies for the users. The proposed TODL net obtains the overall accuracy of 97.24% for best movies recommendation by using TMDB and MovieLens datasets.

Moderating effect of country-level health determinants on the association between hobby engagement and mental health: cross-cohort multi-level models, meta-analyses, and meta-regressions

BackgroundTheories from anthropology, evolutionary psychology, and sociology have focused on the potential adaptive benefits of hobby engagement for mental health in older adults. However, previous studies have used data from single countries, potentially biased by specific measurement and methodological approaches, cohort effects, or cultural specificities. Whether there are genuine benefits for mental health in older adults cross-culturally remains unknown. This study explored the consistency of this association across 16 different nations. MethodsFor this epidemiological study, we used data from adults aged 65 years or older across 16 countries in the USA, Europe, and Asia, represented in five longitudinal studies (ELSA, JAGES, HRS, SHARE and CHARLS; N=93 263, 45–62% female, mean age 72–76 years, data collected 2008–20). We harmonised measures of self-reported engagement in hobbies and past-times, depressive symptoms (validated scales), and Likert scale responses for self-reported health, happiness, and life satisfaction. We conducted fixed-effects models and longitudinal regression models of hobbies and mental health for each country and then pooled in multinational meta-analyses. We accounted for all time-constant factors including those unobserved (eg, genetics, past leisure behaviour, medical history, psychological traits) and identified time-varying factors (eg, sociodemographic background, clinical conditions, daily functioning). We tested the potential moderating effects of country-level determinants of health in meta-regressions and multilevel models. FindingsMeta-analytic fixed-effects findings showed that having a hobby was associated with fewer depressive symptoms (pooled coefficient –0·10, 95% CI –0·13 to –0·07, I2=69·5%, H2=3·28), and higher levels of self-reported health (0·06, 0·03 to 0·08, I2=48·1%, H2=1·93), happiness (0·09, 0·06 to 0·13, I2=67·0%, H2=3·03), and life satisfaction (0·10, 0·08 to 0·12, I2=33·6%, H2=1·51). Results were consistent in meta-analyses of longitudinal regression models testing directionality of findings. Macro-level factors such as life expectancy, world happiness index, country wealth, and income inequality predicted prevalence of hobby engagement, but they showed only marginal moderating effects on the association between hobbies and mental health. InterpretationDespite some heterogeneity in measurement between the cohorts, the apparent universality of the health benefits of hobbies internationally suggests that facilitating greater opportunities for engagement across demographic groups and between countries could be an important part of multidisciplinary care. Findings have implications for social prescribing schemes (currently in trial in many countries) and multidisciplinary work on origins and human behavioural patterns of hobby engagement. FundingNational Endowment for the Arts, Wellcome Trust, Belgian Nnational Scientific Fund (FNRS).

Acoustic behaviour of Portland cement paste with sodium gluconate additive during hydration

The ultrasonic pitch–catch method was used to study the hydration behaviour of Portland cement paste with sodium gluconate (SG) additive using a tailor-made piezoelectric transducer. X-ray diffraction analysis showed that the intensity of the diffraction peak of calcium hydroxide decreased with increasing SG content (CSG), especially for CSG > 0.10 wt%. The compressive strength of the hardening cement pastes decreased remarkably for the pastes with CSG > 0.05 wt%. Ultrasonic waveforms appeared after 2 h of hydration and the waveform amplitudes of cement pastes with SG contents of 0.15 wt% and 0.20 wt% were obviously larger than those of cement pastes with CSG = 0.05 wt% in the early hydration stage. The hydration process of the cement paste over 300 h was classified into three stages based on the head wave amplitude variation – the fluctuation period, the rapidly increasing period and the smoothly increasing period. The acoustic propagation time changed greatly with hydration before a hydration age of 48 h, indicating that the hydration and hardening process of the cement paste was intense in the first 48 h. The proposed ultrasonic monitoring method opens a new perspective for studying the hydration behaviour of SG-blended cement paste.

'It's kind of like weaning. I had to wean myself off of wine': Navigating no- and low-alcohol drinks as potential harm reduction tools and relapse triggers by women in recovery in the UK.

Concerns have been raised that consumption of no- and low-alcohol drinks by those who are in recovery could lead to a relapse to past drinking behaviours. However, little is known regarding how individuals use these products to substitute alcohol and support their sobriety. This article draws on an ethnographic study of women's experiences of recovery within online sobriety communities in which semi-structured interviews were conducted with 25 UK-based women. The dataset was analysed and coded from a pragmatist feminist standpoint using a grounded theoretical approach to specifically address the research question: 'How do women in recovery navigate the protective and risk factors associated with no- and low-alcohol drinks through practices of consumption?' Women in recovery navigate no- and low-alcohol drinks as potential harm-reduction tools and relapse triggers by engaging in nuanced practices of substitution. Contrasting examples include direct substitution and temporary avoidance in early recovery. Substitution practices are informed by the temporality of participants' recovery journeys, the social situation, and the products. Participants selectively replicate and resist their former drinking practices to balance their perceived harm-reduction benefits and relapse triggers of no- and low-alcohol drinks. Important considerations are raised for those in recovery who may want to use no- and low-alcohol drinks as a harm reduction tool, and for recovery modalities that promote them. It concludes with calls for more clarity regarding the definition and labelling of no- and low-alcohol drinks, and for a greater understanding of their use across different recovery cultures.

Does Intention Strength Moderate the Intention-Health Behavior Relationship for Covid-19 Protection Behaviors?

The present research tests whether intention strength moderates intention-health behavior relations and the extent to which this is accounted for by the moderating effects of intention stability, goal priority, and goal conflict. In a prospective multi-behavior study, a representative sample of UK adults (N = 503) completed measures of past behavior, intention, intention strength, goal priority, and goal conflict in relation to eight Covid-19 protection behaviors at time 1. Intention and self-reported behavior were assessed at time 2 (2 months later). Intention stability was assessed over 2 months. Intention strength was a significant moderator of the intention-behavior relationship (controlling for past behavior). Controlling for the moderating effects of intention stability attenuated the moderating effect of intention strength, while also controlling for the moderating effects of goal priority and goal conflict reduced the moderating effects of intention strength to nonsignificance. The present findings indicate that intention strength is a significant moderator of the intention-health behavior relationship. They also suggest that the moderating effect of intention strength is explained by effects on intention stability, goal priority, and goal conflict. Tests of interventions to manipulate intention strength as a means to strengthen intention stability and intention-behavior relations are warranted.

Concentration-dependent rheological characteristics of chickpea (Cicer arietinum L.) flour dispersion in steady and dynamic shear

Chickpea (Cicer arietinum L.) flour (CF) is the basic raw material used in the form of dispersion in varied concentrations for making promising oriental sweets and snacks in the Asian subcontinent. The finished product quality of these fried food items thus mainly depends on the consistency of flour dispersions. Therefore, a concentration-dependent steady-state and dynamic rheological study, along with the pasting behaviour, was carried out. Steady shear rheology exhibited concentration-dependent pseudoplastic behaviour with significantly higher apparent viscosity for 40 - 45% CF dispersions, and a desirable consistency to be used in making fried sweets and snacks. The Herschel-Bulkley model described dispersions better at 5 - 20%, while Mizrahi-Berk at 25 - 50%. Hahn Ree-Erying's model described thixotropic behaviours for time-dependent flow; increasing CF concentration from 30 - 50% and increasing storage (G') and loss (G'') modulus in the linear viscoelastic region. However, G' values were dominant over G'' values in the small amplitude region, showing elastic behaviour, whereas viscous behaviour was exhibited in the higher amplitude region. During heating (30 - 80°C) in the temperature sweep test, concentrated samples (30 - 50%) showed a drastic increase in G' and complex viscosity (η*), while in cooling stages (95 - 25°C), a 25% concentration sample resulted in the highest values of G', G'', and η*.

Artificial intelligence extracts key insights from legal documents to predict intimate partner femicide

Legal documents serve as valuable repositories of information pertaining to crimes, encompassing not only legal aspects but also relevant details about criminal behaviors. To date and the best of our knowledge, no studies in the field examine legal documents for crime understanding using an Artificial Intelligence (AI) approach. The present study aims to fill this research gap by identifying relevant information available in legal documents for crime prediction using Artificial Intelligence (AI). This innovative approach will be applied to the specific crime of Intimate Partner Femicide (IPF). A total of 491 legal documents related to lethal and non-lethal violence by male-to-female intimate partners were extracted from the Vlex legal database. The information included in these documents was analyzed using AI algorithms belonging to Bayesian, functions-based, instance-based, tree-based, and rule-based classifiers. The findings demonstrate that specific information from legal documents, such as past criminal behaviors, imposed sanctions, characteristics of violence severity and frequency, as well as the environment and situation in which this crime occurs, enable the correct detection of more than three-quarters of both lethal and non-lethal violence within male-to-female intimate partner relationships. The obtained knowledge is crucial for professionals who have access to legal documents, as it can help identify high-risk IPF cases and shape strategies for preventing crime. While this study focuses on IPF, this innovative approach has the potential to be extended to other types of crimes, making it applicable and beneficial in a broader context.

Do cosmopolitans care about the world? The effect of cosmopolitanism on the consumption of sustainable apparel

PurposeThe purpose of this study is to empirically examine the impact of cosmopolitan consumer orientation (CCO) on sustainable apparel consumer behavior.Design/methodology/approachA total of 469 US responses collected using MTurk were retained for the analysis after screening for unengaged responses. Structural equation modeling was used to confirm the factor structure of the measurement model and to analyze the structural model. A two-step cluster analysis using log-likelihood distance measure and Akaike's Information Criterion was conducted to explore consumer profiles and past behavior.FindingsBased on the model results, CCO positively impacts apparel sustainability knowledge, attitude toward purchasing sustainable apparel, perceived norm and sustainable apparel purchase intention. Attitude and perceived norm also impact sustainable purchase intention. The two-step cluster analysis, based mainly on sustainable past behavior, reveals that the group of sustainability engaged consumers knows more about apparel sustainability, has a stronger intention to purchase sustainable apparel, is more cosmopolitan and shows a higher tendency to follow social norms. Consumers in this group also tend to live in metropolitan areas and are slightly younger than unengaged consumers.Originality/valueThis study expands CCO research linking two major trends in society and industry: cosmopolitanism and sustainable apparel consumer behavior. The study reveals that CCO uplifts consumers' sustainable behavior and provides evidence in support of CCO as a driver of sustainable consumer behavior. Moreover, results imply a positive future outlook for the diffusion of sustainable apparel, as well as a much-needed mainstream consumer adhesion to more sustainable lifestyles. Given the repercussions of the findings, this research has numerous theoretical as well practical implications.