Individual Behavior Research Articles

Who Gets Vaccinated? Cognitive and Non‐Cognitive Predictors of Individual Behaviour in Pandemics

AbstractThis study investigates different cognitive and non‐cognitive characteristics associated with individuals' willingness to get vaccinated against Covid‐19 and their actual vaccination status. Our empirical analysis is based on data obtained from three survey waves conducted in 2021 among about 2,000 individuals living in the German state of North Rhine‐Westphalia. We find that individuals with a high level of trait reactance – a personality characteristic that entails the personal tendency to perceive persuasion attempts as restricting one's freedom – display a significantly lower willingness to get vaccinated. They also tend to get inoculated later or never. Moreover, neuroticism, locus of control, and statistical numeracy appear to be associated with the willingness to get vaccinated, but these results are less pronounced and less robust. Our results indicate that vaccination campaigns and policies could be improved by specifically addressing those with a high level of trait reactance.

Does green imprinting affect green entrepreneurial behaviors? The application of imprinting theory and stimulus‐organism‐response theory

AbstractGreen entrepreneurship has become pivotal for mitigating resource wastage and safeguarding the ecological environment within the framework of green economic development. Scholars have paid scant attention to investigating the transformation and advancement of green imprinting in shaping individual green entrepreneurial behaviors. In this study, we address this gap by integrating imprinting theory and the stimulus‐organism‐response (SOR) theory, constructing a comprehensive mediating moderation model encompassing green imprinting, green entrepreneurial intentions, green entrepreneurial behaviors, and green self‐efficacy. Through an empirical examination of 331 valid questionnaire responses, we identify two distinct dimensions of green imprinting. Both positive and negative green imprinting exert a notable influence on green entrepreneurial behaviors, with green entrepreneurial intentions serving as a mediating factor between green imprinting and actual entrepreneurial behaviors. Our research carries substantial theoretical and practical implications, enriching our comprehension of the mechanisms underlying green imprinting and providing guidance for entrepreneurs engaged in green business ventures.

Development and validation of machine-learning models for monitoring individual behaviors in group-housed broiler chickens

Animals' individual behavior is commonly monitored by live or video observation by a person. This can be labor intensive and inconsistent. An alternative is the use of machine learning-based computer vision systems. The objectives of this study were to 1) develop and optimize machine learning model frameworks for detecting, tracking and classifying individual behaviors of group-housed broiler chickens in continuous video recordings; and 2) use an independent dataset to evaluate the performance of the developed machine leaning model framework for individual poultry behaviors differentiation. Forty-two video recordings from 4 different pens (total video duration = 1,620 min) were used to develop and train multiple models for detecting and tracking individual birds and classifying 4 behaviors: feeding, drinking, active, and inactive. The optimal model framework was used to continuously analyze an external set of 11 videos (duration = 326 min), and the second-by-second behavior of each individual broiler was extracted for the comparison of human observation. After comparison of model performance, the YOLOv5l, out of 5 detection models, was selected for detecting individual broilers in a pen; the osnet_x0_25_msmt17, out of 4 tracking algorithms, was selected to track each detected bird in continuous frames; and the Gradient Boosting Classifier, out of 12 machine learning classifiers, was selected to classify the 4 behaviors. Most of the models were able to keep previously assigned individual identifications of the chickens in limited amounts of time, but lost the identities throughout an examination period (≥4 min). The final framework was able to accurately predict feeding (accuracy = 0.895) and drinking time (accuracy = 0.9) but subpar for active (accuracy = 0.545) and inactive time (accuracy = 0.505). The algorithms employed by the machine learning models were able to accurately detect feeding and drinking behavior but still need to be improved for maintaining individual identities of the chickens and identifying active and inactive behaviors.

Quercetin ameliorates depressive-like phenotypes and memory deficits in hypoxia-induced murine model of stress

BackgroundHypoxia is believed to induce a form of stress that contributes to the exacerbation of certain disease conditions such as heart diseases. Most of these conditions revolve around the central nervous system (CNS) since the brain consumes a significant percentage of oxygen. PurposeThis study aims to determine the specific effect of hypoxia on mood and cognitive behaviours using behavioural assessment and histological methods in mice. Additionally, this study investigated the counter effect of quercetin (QCN) on the hypoxia-induced changes. MethodsA total of thirty (30) mice were equally divided into five (5) groups. Group 1 and 2 received 5 % DMSO while only the latter was subjected to the hypoxia protocol. Groups 3–5 received graded doses of quercetin (10, 20 and 40 mg/kg), respectively. Approximately 24 h after a consecutive seven-day treatment, the mice were tested for depressive-like symptoms as well as dysfunctional memory function using recognized pharmacological tests. Afterwards, histology of specific brain regions was conducted. Finally, the data were analysed by one-way ANOVA and statistical significance was set at p<0.05. ResultsIn comparison with the normal control, mice of the model control group scored significantly (p<0.05) higher in the tests that assess depression and significantly (p<0.05) lower in the tests that assessed memory function, both indicators of adverse effects of hypoxia. Also, the contributing brain regions were also negatively affected by hypoxia. However, a significant attenuation of these effects was observed in the groups that received quercetin. ConclusionIn conclusion, quercetin is a nutritional flavonoid that possesses the ability to improve behaviour and cognition in individuals regularly exposed to hypoxia or suffering from conditions that affect oxygen delivery within the body.

How Individual Factors Shape Innovative Work Behavior in Malaysian HEIs: The Role of Innovation Capability, Knowledge Sharing and Psychological Empowerment

This study investigates the factors driving academics' innovative work behavior (IWB) in Malaysian Higher Education Institutions (HEIs), focusing on individual innovation capability, psychological empowerment, and knowledge sharing. The respondents comprised 382 academics from 24 Malaysian universities listed in the QS World Ranking 2023, selected through convenience sampling. Data were collected via a Google Form questionnaire distributed by email. The descriptive analysis assessed individual innovation capabilities, psychological empowerment, and knowledge-sharing levels, and their impact on IWB. The findings indicate high engagement in innovative activities, with academics demonstrating strong innovative capabilities, a sense of empowerment, and active knowledge-sharing practices. These individual factors significantly contribute to fostering IWB, highlighting the importance of continuous professional development, supportive institutional environments, and collaborative cultures in promoting innovation within HEIs. This study provides valuable insights for policymakers and university administrators to enhance the innovative potential of academics, ultimately contributing to the advancement of knowledge and improvement of educational practices in Malaysian HEIs. Future research should explore longitudinal effects and potential moderating factors to further understand innovative work behavior dynamics in academic settings.

“All you’ve got to do is stop”: A Qualitative Examination of Gambling Stigma and Discrimination from the Perspective of Lived Experience

People with lived experience have drawn attention to gambling stigma as a harm in itself, justifying discrimination and exacerbating other harms. The gambling establishment’s response has reproduced individual responsibility by reducing stigma to a barrier to help-seeking. More recently, adapting to critiques of individual responsibility, the gambling establishment has expanded the issue to one of services and society. This paper identifies the structural dynamics that drive gambling stigma and discrimination from the perspective of lived experience. Semi-structured interviews were conducted with adults in Great Britain who had experienced gambling harm (n = 40). Several key themes were identified: (1) Harmless fun and individual responsibility; (2) Comparison with substance use; (3) The role of money; (4) Lack of parity in government policy; (5) Stereotypes of “typical” gamblers. The findings show the fundamental driver of stigma is the way commercial gambling functions and is enabled to function by the state, thus perpetuating the very conditions producing stigma in the first place. Stigma-reduction strategies that focus on changing individual behaviour or public information campaigns that tell people to get help early are insufficient: they are just another version of “responsible gambling,” where the individual is expected to do everything. Change requires addressing the unique features of gambling harm, stigma and discrimination, and the position the U.K. government allows commercial gambling to occupy.

Understanding the Role of Visitor Behavior in Soundscape Restorative Experiences in Urban Parks

The restorative effects of soundscapes on human physical and mental well-being are widely recognized, but their effectiveness is influenced by various factors, including external environments and individual characteristics. Despite being a crucial element in environmental experience, the role of individual behavior in the restorative effects of soundscapes has been insufficiently studied. To address this research gap, we conducted a survey in five parks in Fuzhou, China, using questionnaires to assess visitors’ evaluations of soundscape characteristics, their soundscape restorative experiences, and behavioral characteristics. A total of 419 valid responses were collected. Using these data, we employed a structural equation model and conditional process analysis to explore the interaction between visitor behavior and soundscape experiences. The results show that soundscapes with pleasantness and eventfulness promote static behaviors to a certain degree, while dynamic behaviors are influenced solely by eventfulness soundscapes. In the process by which soundscape characteristics influence restorative experiences, static behavior is the only mediating factor, accounting for 8% of the total effect. Additionally, increased visit intensity enhances the impact of pleasantness soundscape on restorative experiences while weakening the mediating effect of static behavior. These findings provide strong support for relevant design considerations.

Analisis Psikospiritual Fenomena Relapse Bagi Kelompok ODGPZ di Loka Rehabilitasi BNN Deli Serdang Tahun 2024

Relapse is a relapse behavior that repeatedly occurs after undergoing rehabilitation characterized by the emergence of addictive mindsets, behaviors and actions after the withdrawal period. Drug cases create a sense of dependence caused by several factors, namely family factors, social factors, employment factors, psychological factors and spiritual factors. That's why the case causes uncontrolled emotions of wanting to collect. The focus of the research is to analyze in depth the psychospiritual of ODGPZ who experience continuous relapse in the Rehabilitation Workshop. The term psychospiritual refers to psychology and spirituality where the psychological dimension affects the spiritual experience and the spiritual dimension can affect psychology. Spirituality and psychology include the search for identity which raises various questions that can cause problems in oneself that make oneself anxious, depressed, unstable mood and feeling like they have no purpose in life. Psychospirituality is used as a tool or analytical knife for counselors to dismantle spiritual problems experienced by counselors and see patterns of relapsed behavior. The purpose of the study was to determine the pattern of relapse behavior for the ODGPZ group and analyze the pattern of relapse behavior using a psychospiritual perspective at the BNN Deli Serdang Rehabilitation Workshop. This study uses a qualitative research methodology with a case study method to clients who have experienced relapse. Data collection techniques were obtained by initial observation, interviews and documentation. The results of the analysis showed that the pattern of relapse behavior by ODGPZ was extraordinary enjoyment, suggestions from ODGPZ friends, increasing the spirit of activity, escaping from problems, and pressure and stigma from society. After the pattern was analyzed using a psychospiritual lens, the author found that there were clients who still found it difficult to refuse offers from ODGPZ friends, there were errors in interpreting the theological message of the Bible text, all problems were solved with drugs, finding meaning and purpose in life and social change. Therefore, psychospirituality is closely related to the intellectual and emotional of the individual which affects the mindset and behavior of individuals, especially drug user.

Pain Resilience and Coping Behaviors in Individuals in a Collectivist Social Context.

Pain resilience (PR) may be associated with different coping skills, resulting in differences in pain outcomes. This study aimed to understand the role of PR in dictating the choice of coping methods. This study completed a preliminary validation of the Mandarin Chinese version of the Pain Resilience Scale (PRS-C) with online survey data (n = 46). Further, we conducted interviews with individuals with chronic low back pain (n = 24). The PRS-C psychometric properties were assessed using a confirmatory factor analysis. The interviews explored pain history, treatment experiences, and coping strategies and were analyzed thematically. The validated PRS-C (10 items) demonstrated satisfactory psychometric properties. The interview results showed that participants who scored lower were more likely to adopt disengagement rather than engagement coping strategies. Qualitative data revealed three themes explaining why and how participants in this collectivist social framework chose their coping methods. The findings suggest that while participants tried to understand their pain and treatment experiences, the cognitive appraisal construct in PR influenced some of the coping experiences. However, deeply influenced by Confucianism and Buddhism, participants also expressed factors beyond the scope of individual fortitudes, such as the relationship with a higher power that significantly influenced their coping behaviors.

The Health Cost of College Expectations: Adolescent Educational Expectations and Obesity

Although previous studies have identified the effect of social environment and individual behavior on adolescent obesity in the field of social science, much less is known about the association between adolescent educational expectations and obesity. This article draws on China Education Panel Survey (CEPS) 2013 to 2014 to examine the relationship between adolescent educational expectations and BMI/obesity. Results show that adolescents with college expectations have higher BMI and higher risk of obesity. Learning time partially mediates the relationship between adolescent college expectations and obesity. Additionally, the association between adolescent college expectations and BMI/obesity is stronger for males and urban students. The findings indicate that higher educational expectations may lead to health problems. School and family should perceive the health cost of high educational expectations to promote adolescent all-around development.

Droughts reshape apex predator space use and intraguild overlap.

Droughts are increasing in frequency and severity globally due to climate change, leading to changes in resource availability that may have cascading effects on animal ecology. Resource availability is a key driver of animal space use, which in turn influences interspecific interactions like intraguild competition. Understanding how climate-induced changes in resource availability influence animal space use, and how species-specific responses scale up to affect intraguild dynamics, is necessary for predicting broader community-level responses to climatic changes. Although several studies have demonstrated the ecological impacts of drought, the behavioural responses of individuals that scale up to these broader-scale effects are not well known, particularly among animals in top trophic levels like large carnivores. Furthermore, we currently lack understanding of how the impacts of climate variability on individual carnivore behaviour are linked to intraguild dynamics, in part because multi-species datasets collected at timescales relevant to climatic changes are rare. Using 11 years of GPS data from four sympatric large carnivore species in southern Africa-lions (Panthera leo), leopards (Panthera pardus), African wild dogs (Lycaon pictus) and cheetahs (Acinonyx jubatus)-spanning 4 severe drought events, we test whether drought conditions impact (1) large carnivore space use, (2) broad-scale intraguild spatial overlap and (3) fine-scale intraguild interactions. Drought conditions expanded space use across species, with carnivores increasing their monthly home range sizes by 35% (wild dogs) to 66% (leopards). Drought conditions increased the amount of spatial overlap between lions and subordinate felids (cheetahs and leopards) by up to 119%, but only lion-cheetah encounter rates were affected by these changes, declining in response to drought. Our findings reveal that drought has a clear signature on the space use of multiple sympatric large carnivore species, which can alter spatiotemporal partitioning between competing species. Our study thereby illuminates the links between environmental change, animal behaviour and intraguild dynamics. While fine-scale avoidance strategies may facilitate intraguild coexistence during periodic droughts, large carnivore conservation may require considerable expansion of protected areas or revised human-carnivore coexistence strategies to accommodate the likely long-term increased space demands of large carnivores under projected increases in drought intensity.

National biodiversity strategies under-utilize the potential for individual behavior change

Biodiversity conservation is increasingly recognized as a main challenge for the sustainability agenda. With humans at the epicenter of the biodiversity crisis, conserving nature requires changes in individual behavior. This study reveals gaps regarding the incorporation of behavior change into national biodiversity policy. A total of 1306 policy actions proposed by ten National Biodiversity Strategies and Action Plans (NBSAPs) from all world regions were coded for target actors, target behavior and responsible agents as well as the policy options, intervention types and behavioral determinants listed in the Behavior Change Wheel (BCW) framework. Results show that only 11 % (n=148) of the policy actions specified individual behaviors and 10 % mentioned individual actors to be targeted. Only 3 % (n=36) of the policy actions were specific about how interventions and policies could enable individual behavior change. Policy actions targeting individual behavior change were aimed mostly at increasing people’s capabilities (i.e., providing information) or providing opportunities (i.e., resources), and rarely addressed the motivation of individuals. More attention and specificity regarding behavior change and better incorporation of the behavioral sciences can improve the effectiveness of national biodiversity strategies.

Exploring pathogen population density as a metric for understanding post-COVID infectious disease surges.

After the easing of COVID-19 restrictions, peaks of common infectious diseases surpassed pre-pandemic levels, raising questions about causes and ways to monitor these changes. A proposed measure, the Pathogen Population Density (PPD) score, could help track these shifts. PPD refers to the concentration of infectious agents within a population at a given time and location, serving as a potential indicator of infection levels in susceptible individuals at the population level. It is likely that PPD remains relatively stable within a specific community, as an equilibrium forms between infections and susceptibility. During the pandemic, nonpharmaceutical interventions (NPIs) led to a reduction in infectious diseases, possibly lowering population immunity and decreasing the PPD score. Once NPIs were lifted, the PPD score likely increased sharply due to a larger pool of susceptible individuals, causing more primary infections and stronger recurrent infections, faster transmission, and more severe pathogenic outcomes at the individual level. Monitoring the PPD score over time could help predict when infection peaks will occur. PPD is influenced by factors such as public health strategies, vaccination programs, and the behavior of high-risk individuals. As a quantitative measure, PPD has the potential to serve as a valuable predictive and monitoring tool, helping public health officials anticipate and track changes in infectious disease dynamics. It could be an effective tool for managing future outbreaks or pandemics and serve as a communication tool between scientists and the public to understand the emergence of new disease peaks.

The Evolution of Illicit-Drug Detection: From Conventional Approaches to Cutting-Edge Immunosensors-A Comprehensive Review.

The increasing use of illicit drugs has become a major global concern. Illicit drugs interact with the brain and the body altering an individual's mood and behavior. As the substance-of-abuse (SOA) crisis continues to spread across the world, in order to reduce trafficking and unlawful activity, it is important to use point-of-care devices like biosensors. Currently, there are certain conventional detection methods, which include gas chromatography (GC), mass spectrometry (MS), surface ionization, surface-enhanced Raman spectroscopy (SERS), surface plasmon resonance (SPR), electrochemiluminescence (ECL), high-performance liquid chromatography (HPLC), etc., for the detection of abused drugs. These methods have the advantage of high accuracy and sensitivity but are generally laborious, expensive, and require trained operators, along with high sample requirements, and they are not suitable for on-site drug detection scenarios. As a result, there is an urgent need for point-of-care technologies for a variety of drugs that can replace conventional techniques, such as a biosensor, specifically an immunosensor. An immunosensor is an analytical device that integrates an antibody-based recognition element with a transducer to detect specific molecules (antigens). In an immunosensor, the highly selective antigen-antibody interaction is used to identify and quantify the target analyte. The binding event between the antibody and antigen is converted by the transducer into a measurable signal, such as electrical, optical, or electrochemical, which corresponds to the presence and concentration of the analyte in the sample. This paper provides a comprehensive overview of various illicit drugs, the conventional methods employed for their detection, and the advantages of immunosensors over conventional techniques. It highlights the critical need for on-site detection and explores emerging point-of-care testing methods. The paper also outlines future research goals in this field, emphasizing the potential of advanced technologies to enhance the accuracy, efficiency, and convenience of drug detection.

Association of genomically enhanced residual feed intake with performance, feed efficiency, feeding behavior, gas flux, and nutrient digestibility in growing Holstein heifers.

Residual feed intake (RFI), a metric of feed efficiency, is moderately heritable and independent of body size and productivity, making it an ideal trait for investigation as a selection criterion to improve feed efficiency of growing cattle. The objective of this study was to examine the differences in performance, feed efficiency, feeding behavior, gas flux, and nutrient digestibility in Holstein heifers with divergent genomically enhanced breeding values for RFI (RFIg). Holstein heifers (n = 55; BW = 352 ± 64kg) with low (n = 29) or high (n = 26) RFIg were selected from a contemporary group of 453 commercial Holstein heifers. Heifers were rotated between 1 of 2 pens, each equipped with four electronic feed bunks and one pen with a GreenFeed gaseous exchange monitoring (GEM) system. Individual dry matter intake (DMI) and feeding behavior data were collected for 84-d. Body weight (BW) was measured weekly and spot fecal samples collected at weighing. Phenotypic RFI (RFIp) was calculated as the residual from regression of DMI on average daily gain (ADG) and mid-test metabolic BW (BW0.75). A mixed model including the fixed effect of RFIg classification and random effect of group was used to evaluate the effect of RFIg classification on response variables. There were no differences (P > 0.05) in BW and ADG for heifers with divergent RFIg; however, low RFIg heifers consumed 7.5% less (P < 0.05) feed per day. Consequently, low RFIg heifers exhibited a more favorable (P < 0.05) RFIp (-0.196 vs 0.222kg/d, respectively). Low RFIg heifers had 8.7% fewer (P < 0.05) bunk visit (BV) events per day and tended to have a 11.2% slower (P < 0.10) eating rate. Low RFIg heifers had 7.7% lower (P < 0.05) methane (CH4) emissions (g/d), 6.1% lower (P ≤ 0.05) carbon dioxide (CO2) production (g/d), and 5.6% lower (P ≤ 0.05) heat production (Mcal/d) than high RFIg heifers. However, CH4 yield and CO2 yield (g/kg DMI), and heat production per unit DMI (Mcal/kg DMI) did not differ (P > 0.05) between heifers with divergent RFIg. Dry matter and nutrient digestibility did not differ (P > 0.05) between heifers with divergent RFIg. Overall, heifers selected to be more feed efficient exhibited more favorable energy efficiencies and feed efficiency phenotypes. Results suggest that selection based on RFIg provides opportunities to select cattle with favorable feed efficiency phenotypes to increase the economic and environmental sustainability of the cattle industry.

Intelligent monitoring of marine vessel dynamics based on data mining

This study explores vessel navigation's universal characteristics and individual anomaly behavior from dispatch to destination. With the help of information technology, it introduces big data and machine learning technologies into the work of vessel traffic management and conducts statistical analysis and monitoring studies of vessel behavior from a data-driven perspective. The study was conducted by modeling vessel speed, position, course, and other navigational characteristics behavior through comprehensive statistical analysis of vessel AIS, radar, and VTS data. The study was based on the monitoring methods for anomalous behavior of vessel speed, position, and heading inconsistencies with the expected behavior identified by the model.

Self-Stigma vs. Perceived Public Stigma Toward Mental Illness in Rural Adults

Introduction: Mental illness is a clinically significant disturbance in an individual's cognition, emotion regulation, or behavior. Stigma toward mental health comes in two primary forms: Self-stigma and perceived public stigma. Purpose: The objective of this study is to quantify the amount of stigma toward mental illness in rural adults and analyze differences in stigma across demographic groups. Methods: Adults were offered a 14-item questionnaire at five different sites from January 2023 to April 2023. Rural distinctions were made based on participants' reported county of residence following the Indiana Office of Community and Rural Affairs (OCRA) definition of rurality. Demographic information such as age, gender, marital status, total household income, and highest level of education were also obtained. Results: Rural adults experience mild amounts of self-stigma (14.52 +/- 5.0) and moderate amounts of perceived public stigma (18.4 +/- 4.3). Adults aged 46-65 experience more significant levels of perceived public stigma when compared to those of younger participants. An inverse relationship exists between the highest level of education and self-stigma towards mental illness. Seventy two percent of respondents agreed or strongly agreed with the statement, “In general, others believe that having a mental illness is a sign of personal weakness or inadequacy.” Conclusions: This study demonstrates that perceived public stigma toward mental illness presents a significant barrier to care for mental illness. Adults aged 46-65 are especially vulnerable to the perceived public stigma toward mental illness. To provide the largest benefit to rural populations, anti-stigma campaigns should focus on perceived public stigma among adults aged 46-65.

Unveiling the Significance of Individual Level Predictions: A Comparative Analysis of GRU and LSTM Models for Enhanced Digital Behavior Prediction

The widespread use of technology has led to a transformation of human behaviors and habits into the digital space; and generating extensive data plays a crucial role when coupled with forecasting techniques in guiding marketing decision-makers and shaping strategic choices. Traditional methods like autoregressive moving average (ARMA) can-not be used at predicting individual behaviors because we can-not create models for each individual and buy till you die (BTYD) models have limitations in capturing the trends accurately. Recognizing the paramount importance of individual-level predictions, this study proposes a deep learning framework, specifically uses gated recurrent unit (GRU), for enhanced behavior analysis. This article discusses the performance of GRU and long short-term memory (LSTM) models in this framework for forecasting future individual behaviors and presenting a comparative analysis against benchmark BTYD models. GRU and LSTM yielded the best results in capturing the trends, with GRU demonstrating a slightly superior performance compared to LSTM. However, there is still significant room for improvement at the individual level. The findings not only demonstrate the performance of GRU and LSTM models but also provide valuable insights into the potential of new techniques or approaches for understanding and predicting individual behaviors.

Adapting International Business Models for EU Projects: Macro- and Micro-Foundations of the Uppsala Model in Multinational Collaborations

This study examines the adaptation of the Uppsala Model to enhance the management of European Union (EU)-funded projects, particularly focusing on the macro- and micro-foundational elements of the model. The Uppsala Model, originally developed for firm-level internationalization, provides a valuable framework for addressing the complex challenges of EU project implementation, which include bureaucratic hurdles, diverse stakeholder management, and the intricacies of European integration. This paper highlights the persistent issues faced by project managers despite improved application processes and skilled beneficiaries. By applying the Uppsala Model, which emphasizes incremental knowledge development and resource commitment, this study aims to bridge the gap between fund acquisition and project delivery. The integration of both macro- (broad external factors) and micro- (individual and organizational behaviors) perspectives of the Uppsala Model offers a comprehensive approach to managing international, multi-stakeholder EU initiatives. This approach is exemplified through the SuMaNu project, which addresses nutrient recycling and sustainable manure management in the Baltic Sea Region. The findings suggest that the Uppsala Model’s principles can be effectively applied to enhance the execution of complex EU projects by fostering better stakeholder relationships, incremental learning, and adaptive strategies. This study underscores the relevance of experiential learning and network perspectives in achieving successful project outcomes in the EU context.

Inertial effect of cell state velocity on the quiescence-proliferation fate decision

Energy landscapes can provide intuitive depictions of population heterogeneity and dynamics. However, it is unclear whether individual cell behavior, hypothesized to be determined by initial position and noise, is faithfully recapitulated. Using the p21-/Cdk2-dependent quiescence-proliferation decision in breast cancer dormancy as a testbed, we examined single-cell dynamics on the landscape when perturbed by hypoxia, a dormancy-inducing stress. Combining trajectory-based energy landscape generation with single-cell time-lapse microscopy, we found that a combination of initial position and velocity on a p21/Cdk2 landscape, but not position alone, was required to explain the observed cell fate heterogeneity under hypoxia. This is likely due to additional cell state information such as epigenetic features and/or other species encoded in velocity but missing in instantaneous position determined by p21 and Cdk2 levels alone. Here, velocity dependence manifested as inertia: cells with higher cell cycle velocities prior to hypoxia continued progressing along the cell cycle under hypoxia, resisting the change in landscape towards cell cycle exit. Such inertial effects may markedly influence cell fate trajectories in tumors and other dynamically changing microenvironments where cell state transitions are governed by coordination across several biochemical species.