Tag: nevin manimala

Chaos. 2025 Jan 1;35(1):013155. doi: 10.1063/5.0240447.

ABSTRACT

The differential equations involving two discrete delays are helpful in modeling two different processes in one model. We provide the stability and bifurcation analysis in the fractional order delay differential equation Dαx(t)=ax(t)+bx(t-τ)-bx(t-2τ) in the ab-plane. Various regions of stability include stable, unstable, single stable region (SSR), and stability switch (SS). In the stable region, the system is stable for all the delay values. The region SSR has a critical value of delay that bifurcates the stable and unstable behavior. Switching of stable and unstable behaviors is observed in the SS region.

PMID:39869928 | DOI:10.1063/5.0240447

Chaos. 2025 Jan 1;35(1):013152. doi: 10.1063/5.0231457.

ABSTRACT

Synaptic plasticity plays a fundamental role in neuronal dynamics, governing how connections between neurons evolve in response to experience. In this study, we extend a network model of θ-neuron oscillators to include a realistic form of adaptive plasticity. In place of the less tractable spike-timing-dependent plasticity, we employ recently validated phase-difference-dependent plasticity rules, which adjust coupling strengths based on the relative phases of θ-neuron oscillators. We explore two distinct implementations of this plasticity: pairwise updates to individual coupling strengths and global updates applied to the mean coupling strength. We derive a mean-field approximation and assess its accuracy by comparing it to θ-neuron simulations across various stability regimes. The synchrony of the system is quantified using the Kuramoto order parameter. Through bifurcation analysis and the calculation of maximal Lyapunov exponents, we uncover interesting phenomena such as bistability and chaotic dynamics via period-doubling and boundary crisis bifurcations. These behaviors emerge as a direct result of adaptive coupling and are absent in systems without such plasticity.

PMID:39869927 | DOI:10.1063/5.0231457

Chaos. 2025 Jan 1;35(1):013156. doi: 10.1063/5.0250482.

ABSTRACT

Investment in resources is essential for facilitating information dissemination in real-world contexts, and comprehending the influence of resource allocation on information dissemination is, thus, crucial for the efficacy of collaborative networks. Nonetheless, current studies on information dissemination frequently fail to clarify the complex interplay between information distribution and resources in network contexts. In this work, we establish a resource-based information dissemination model to identify the complex interplay by examining the propagation threshold and equilibriums. We assess the model’s efficacy by juxtaposing the mean-field method with Monte Carlo simulations across three author collaboration networks. In addition, we define the function of resources in information dissemination and evaluate the model’s applicability using propagating threshold, time evolution, and parametric analyses. Our findings indicate that an increase in available resources accelerates and expands the distribution of information. Notably, we identify abrupt transition phenomena concerning available resources and demonstrate that the information self-learning rate and the information review rate hasten this transition, while information decline and re-diffusion rates decelerate it.

PMID:39869926 | DOI:10.1063/5.0250482

Chaos. 2025 Jan 1;35(1):013153. doi: 10.1063/5.0248723.

ABSTRACT

Generosity through donation plays a crucial role in reducing inequality and influencing human behavior. However, previous research on donation has overlooked individuals’ acceptance of the extent of inequality, which acts as a trigger for donation. To address this gap, this paper systematically explores the impact of donation based on inequality tolerance on the evolution of cooperation in spatial public goods game. Specifically, donation occurs only when an individual’s payoff advantage exceeds her inequality tolerance. The results show that donation patterns are crucial for the emergence and stability of cooperation. In the enduring period, the defector-to-cooperator donation pattern helps to form cooperative clusters. In the expanding period, cooperator-to-cooperator, defector-to-defector, and defector-to-cooperator donation patterns create a stable three-layer structure through self-organization, providing a payoff advantage to boundary cooperators. As donation ratio increases, the three-layer structure provides a greater payoff advantage to boundary cooperators, leading to an increase in cooperation. As inequality tolerance increases, changes in donation patterns weaken the three-layer structure, causing cooperation to decrease or disappear through discontinuous phase transitions. Subsequently, all critical points of discontinuous phase transitions are identified by specific spatial configurations. In addition, the influence of donation patterns on the evolution of cooperation is robust, even in heterogeneous small-world networks. This paper offers valuable insights into the dynamics of cooperation evolution and the role of donation in shaping behavior.

PMID:39869925 | DOI:10.1063/5.0248723

Chaos. 2025 Jan 1;35(1):013149. doi: 10.1063/5.0241236.

ABSTRACT

Experimental observations and field data demonstrated that predators adapt their hunting strategies in response to prey abundance. While previous studies explored the impact of predation risk on predator-prey interactions, the impact of symbiotic relationships between fear-affected prey and non-prey species on system dynamics remains unexplored. This study uses a mathematical approach to investigate how different symbiotic relationships govern system dynamics when predators adapt to prey availability. Our study illustrates that the mutualistic relationship between prey and partners extends predator survivability. However, the fear-affected symbiotic system may undergo regime shifts, which can be catastrophic or non-catastrophic, depending on symbiotic interaction patterns. The study demonstrates a hump-shaped relationship between the predator’s optimal search rate and biomass and identifies an intermediate range of search rates where the system exhibits a “bubbling”phenomenon. Overall, our findings provide new insights into symbiotic relationships in community ecology, highlighting the complex interplay among predators, prey, and non-prey species.

PMID:39869923 | DOI:10.1063/5.0241236

Ann Intern Med. 2025 Jan 28. doi: 10.7326/ANNALS-24-00165. Online ahead of print.

ABSTRACT

BACKGROUND: Prior studies indicate that 1% to 4% of Epstein-Barr virus (EBV)-seronegative recipients of EBV-seropositive donor (EBV D+/R-) kidneys develop posttransplant lymphoproliferative disorder (PTLD). However, these estimates are based on limited data that lack granularity.

OBJECTIVE: To determine the associations between pretransplant EBV D+/R- and recipient EBV-seropositive status (R+) and the outcomes of PTLD and graft and patient survival among adult kidney transplant recipients.

DESIGN: Retrospective cohort study.

SETTING: Two large U.S. transplant centers.

PARTICIPANTS: Epstein-Barr virus D+/R- and EBV R+ recipients matched 1:3 on donor, recipient, and transplant characteristics between 1 January 2010 and 30 June 2022.

MEASUREMENTS: Exposure was pretransplant donor and recipient EBV serostatus. The primary outcome was biopsy-proven PTLD. Secondary outcomes were all-cause graft loss (death, retransplant, or graft failure) and death. Follow-up was truncated to 3 years after transplant.

RESULTS: The final cohort comprised 104 EBV D+/R- recipients matched to 312 EBV R+ recipients. The mean age was 42 years (SD, 17.1), 59% were living donor transplants, and 95% received thymoglobulin induction. Among EBV D+/R- recipients, 50 (48.1%) developed EBV DNAemia, with a median time of 198 days (IQR, 110 to 282 days) after transplantation. Posttransplant lymphoproliferative disorder occurred in 23 (22.1%) EBV D+/R- recipients at a median of 202 days (IQR, 118 to 317 days) after transplantation. Epstein-Barr virus D+/R- recipients had higher all-cause graft failure (hazard ratio, 2.21 [95% CI, 1.06 to 4.63]); mortality was higher but not statistically significant (hazard ratio, 2.19 [CI, 0.94 to 5.13]).

LIMITATION: Two-center study.

CONCLUSION: Compared with previous studies, this study showed that EBV D+/R- kidney recipients face a 5- to 10-fold higher cumulative incidence of PTLD. Strategies to mitigate the PTLD risk are urgently needed.

PRIMARY FUNDING SOURCE: National Institutes of Health.

PMID:39869913 | DOI:10.7326/ANNALS-24-00165

J Med Internet Res. 2025 Jan 27;27:e69080. doi: 10.2196/69080.

ABSTRACT

BACKGROUND: Digital gaming has become increasingly popular among older adults, potentially offering cognitive, social, and physical benefits. However, its broader impact on health and well-being, particularly in real-world settings, remains unclear.

OBJECTIVE: This study aimed to evaluate the multidimensional effects of digital gaming on health and well-being among older adults, using data from the Japan Gerontological Evaluation Study conducted in Matsudo City, Chiba, Japan.

METHODS: Data were drawn from 3 survey waves (2020 prebaseline, 2021 baseline, and 2022 follow-up) of the Japan Gerontological Evaluation Study, which targets functionally independent older adults. The exposure variable, digital gaming, was defined as regular video game play and was assessed in 2021. In total, 18 outcomes across 6 domains were evaluated in 2022; domain 1-happiness and life satisfaction, domain 2-physical and mental health, domain 3-meaning and purpose, domain 4-character and virtue, domain 5-close social relationships, and domain 6-health behavior. Furthermore, 10 items from the Human Flourishing Index were included in domains 1-5, with 2 items for each domain. Overall flourishing was defined as the average of the means across these 5 domains. In addition, 7 items related to domains 2, 5, and 6 were assessed. The final sample consisted of 2504 participants aged 65 years or older, with questionnaires containing the Human Flourishing Index randomly distributed to approximately half of the respondents (submodule: n=1243). Consequently, we used 2 datasets for analysis. We applied targeted maximum likelihood estimation to estimate the population average treatment effects, with Bonferroni correction used to adjust for multiple testing.

RESULTS: Digital gaming was not significantly associated with overall flourishing or with any of the 5 domains from the Human Flourishing Index. Although initial analyses indicated associations between digital gaming and participation in hobby groups (mean difference=0.12, P=.005) as well as meeting with friends (mean difference=0.076, P=.02), these associations did not remain significant after applying the Bonferroni correction for multiple testing. In addition, digital gaming was not associated with increased sedentary behavior or reduced outdoor activities.

CONCLUSIONS: This study provides valuable insights into the impact of digital gaming on the health and well-being of older adults in a real-world context. Although digital gaming did not show a significant association with improvements in flourishing or in the individual items across the 5 domains, it was also not associated with increased sedentary behavior or reduced outdoor activities. These findings suggest that digital gaming can be part of a balanced lifestyle for older adults, offering opportunities for social engagement, particularly through hobby groups. Considering the solitary nature of gaming, promoting social gaming opportunities may be a promising approach to enhance the positive effects of digital gaming on well-being.

PMID:39869904 | DOI:10.2196/69080

JMIR Ment Health. 2025 Jan 27;12:e67478. doi: 10.2196/67478.

ABSTRACT

BACKGROUND: Insomnia is a prevalent sleep disorder affecting millions worldwide, with significant impacts on daily functioning and quality of life. While traditionally assessed through subjective measures such as the Insomnia Severity Index (ISI), the advent of wearable technology has enabled continuous, objective sleep monitoring in natural environments. However, the relationship between subjective insomnia severity and objective sleep parameters remains unclear.

OBJECTIVE: This study aims to (1) explore the relationship between subjective insomnia severity, as measured by ISI scores, and activity-based objective sleep parameters obtained through wearable devices; (2) determine whether subjective perceptions of insomnia align with objective measures of sleep; and (3) identify key psychological and physiological factors contributing to the severity of subjective insomnia complaints.

METHODS: A total of 250 participants, including both individuals with and without insomnia aged 19-70 years, were recruited from March 2023 to November 2023. Participants were grouped based on ISI scores: no insomnia, mild, moderate, and severe insomnia. Data collection involved subjective assessments through self-reported questionnaires and objective measurements using wearable devices (Fitbit Inspire 3) that monitored sleep parameters, physical activity, and heart rate. The participants also used a smartphone app for ecological momentary assessment, recording daily alcohol consumption, caffeine intake, exercise, and stress. Statistical analyses were used to compare groups on subjective and objective measures.

RESULTS: Results indicated no significant differences in general sleep structure (eg, total sleep time, rapid eye movement sleep time, and light sleep time) among the insomnia groups (mild, moderate, and severe) as classified by ISI scores (all P>.05). Interestingly, the no insomnia group had longer total awake times and lower sleep quality compared with the insomnia groups. Among the insomnia groups, no significant differences were observed regarding sleep structure (all P>.05), suggesting similar sleep patterns regardless of subjective insomnia severity. There were significant differences among the insomnia groups in stress levels, dysfunctional beliefs about sleep, and symptoms of restless leg syndrome (all P≤.001), with higher severity associated with higher scores in these factors. Contrary to expectations, no significant differences were observed in caffeine intake (P=.42) and alcohol consumption (P=.07) between the groups.

CONCLUSIONS: The findings demonstrate a discrepancy between subjective perceptions of insomnia severity and activity-based objective sleep parameters, suggesting that factors beyond sleep duration and quality may contribute to subjective sleep complaints. Psychological factors, such as stress, dysfunctional sleep beliefs, and symptoms of restless legs syndrome, appear to play significant roles in the perception of insomnia severity. These results highlight the importance of considering both subjective and objective assessments in the evaluation and treatment of insomnia and suggest potential avenues for personalized treatment strategies that address both psychological and physiological aspects of sleep disturbances.

TRIAL REGISTRATION: Clinical Research Information Service KCT0009175; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=26133.

PMID:39869900 | DOI:10.2196/67478

J Med Internet Res. 2025 Jan 27;27:e58656. doi: 10.2196/58656.

ABSTRACT

BACKGROUND: The COVID-19 pandemic reshaped social dynamics, fostering reliance on social media for information, connection, and collective sense-making. Understanding how citizens navigate a global health crisis in varying cultural and economic contexts is crucial for effective crisis communication.

OBJECTIVE: This study examines the evolution of citizen collective sense-making during the COVID-19 pandemic by analyzing social media discourse across Italy, the United Kingdom, and Egypt, representing diverse economic and cultural contexts.

METHODS: A total of 755,215 social media posts from X (formerly Twitter) were collected across 3 time periods: the virus’ emergence (February 15 to March 31, 2020), strict lockdown (April 1 to May 30, 2020), and the vaccine rollout (December 1, 2020 to January 15, 2021). In total, 284,512 posts from Italy, 261,978 posts from the United Kingdom, and 209,725 posts from Egypt were analyzed using the latent Dirichlet allocation algorithm to identify key thematic topics and track shifts in discourse across time and regions.

RESULTS: The analysis revealed significant regional and temporal differences in collective sense-making during the pandemic. In Italy and the United Kingdom, public discourse prominently addressed pragmatic health care measures and government interventions, reflecting higher institutional trust. By contrast, discussions in Egypt were more focused on religious and political themes, highlighting skepticism toward governmental capacity and reliance on alternative frameworks for understanding the crisis. Over time, all 3 countries displayed a shift in discourse toward vaccine-related topics during the later phase of the pandemic, highlighting its global significance. Misinformation emerged as a recurrent theme across regions, demonstrating the need for proactive measures to ensure accurate information dissemination. These findings emphasize the role of cultural, economic, and institutional factors in shaping public responses during health crises.

CONCLUSIONS: Crisis communication is influenced by cultural, economic, and institutional contexts, as evidenced by regional variations in citizen engagement. Transparent and culturally adaptive communication strategies are essential to combat misinformation and build public trust. This study highlights the importance of tailoring crisis responses to local contexts to improve compliance and collective resilience.

PMID:39869893 | DOI:10.2196/58656

J Med Internet Res. 2025 Jan 27;27:e64649. doi: 10.2196/64649.

ABSTRACT

BACKGROUND: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.

OBJECTIVE: This study aimed to evaluate the impact of an AI-assisted diagnostic system on the diagnostic efficiency of radiologists. It specifically examined the report modification rates and missed and misdiagnosed rates of junior radiologists with and without AI assistance.

METHODS: We obtained effective data from 12,889 patients in 2 tertiary hospitals in Beijing before and after the implementation of the AI system, covering the period from April 2018 to March 2022. Diagnostic reports written by both junior and senior radiologists were included in each case. Using reports by senior radiologists as a reference, we compared the modification rates of reports written by junior radiologists with and without AI assistance. We further evaluated alterations in lung nodule detection capability over 3 years after the integration of the AI system. Evaluation metrics of this study include lung nodule detection rate, accuracy, false negative rate, false positive rate, and positive predictive value. The statistical analyses included descriptive statistics and chi-square, Cochran-Armitage, and Mann-Kendall tests.

RESULTS: The AI system was implemented in Beijing Anzhen Hospital (Hospital A) in January 2019 and Tsinghua Changgung Hospital (Hospital C) in June 2021. The modification rate of diagnostic reports in the detection of lung nodules increased from 4.73% to 7.23% (χ²₁=12.15; P<.001) at Hospital A. In terms of lung nodule detection rates postimplementation, Hospital C increased from 46.19% to 53.45% (χ²₁=25.48; P<.001) and Hospital A increased from 39.29% to 55.22% (χ²₁=122.55; P<.001). At Hospital A, the false negative rate decreased from 8.4% to 5.16% (χ²₁=9.85; P=.002), while the false positive rate increased from 2.36% to 9.77% (χ²₁=53.48; P<.001). The detection accuracy demonstrated a decrease from 93.33% to 92.23% for Hospital A and from 95.27% to 92.77% for Hospital C. Regarding the changes in lung nodule detection capability over a 3-year period following the integration of the AI system, the detection rates for lung nodules exhibited a modest increase from 54.6% to 55.84%, while the overall accuracy demonstrated a slight improvement from 92.79% to 93.92%.

CONCLUSIONS: The AI system enhanced lung nodule detection, offering the possibility of earlier disease identification and timely intervention. Nevertheless, the initial reduction in accuracy underscores the need for standardized diagnostic criteria and comprehensive training for radiologists to maximize the effectiveness of AI-enabled diagnostic systems.

PMID:39869890 | DOI:10.2196/64649