Unique Dynamics Research Articles

Computational assessment of blood lipid influence on hemodynamics in human retinal vessels

The study of retinal hemodynamics is pivotal for understanding both physiological and pathological conditions affecting the eye. Microcirculation in the retina exhibits unique rheological properties and flow dynamics compared to larger vessels. This computational study investigates the possible impact of elevated blood lipids on retinal vascular flow characteristics, focusing on viscosity increases and potential blockage effects. We utilized computational fluid dynamics to solve the incompressible Navier-Stokes equations for an image-based retinal vessel network under healthy conditions. Our findings reveal that arterial vessels have a higher average mainstream flow velocity than venous vessels, however, the latter experience higher wall shear stress (WSS) in those fine branch vessels, which are far away from the optical disc. Notably, vessels with more branches in the venous network are subjected to greater WSS. Then, we simulated the effect of elevated blood lipids by increasing venous viscosity by about 10-20%, which led to a proportional rise in WSS. Furthermore, we explored the potential blockage that may caused by elevated blood lipids, leading to localized increases in velocity and WSS. This study provides insights into the hemodynamic alterations induced by hyperlipidemia, highlighting the importance of considering systemic health parameters in ocular disease research and treatment.

Implementasi Hukum Permintaan Minuman Es Teh Jumbo pada Pasar Malam Bunderan Jombang: Antara Teori dan Praktik

Demand for jumbo iced tea drinks at the Bunderan Jombang night market shows unique dynamics that cannot be fully explained by conventional demand laws. In addition to price, factors such as promotions, flavor innovation, social trends, and the influence of digital media play an important role in consumer purchasing decisions. This phenomenon is interesting to study because it reflects how consumer behavior in traditional markets is influenced by economic, social, and psychological aspects simultaneously. This study aims to analyze the application of the law of demand in the context of night markets and uncover the non-price factors that influence the demand for jumbo iced tea. Using a qualitative method with a phenomenological approach, this study collected data through direct observation, in-depth interviews with traders and consumers, and documentation of market activities. Data analysis was conducted by highlighting consumers' experiences and perceptions regarding the factors that drive their purchasing decisions. The results show that quantity-based promotions, such as “buy one get one free,” are more effective in increasing demand compared to direct price reductions. This strategy increased sales by 40%, while price discounts only resulted in a 12% increase in demand. In addition, flavor innovation, strategic location, and virality on social media play an important role in attracting consumers. Seasonal factors also come into play, with a spike in demand in the summer and a decline during the rainy season. This research confirms that the law of demand remains relevant but needs to be understood in a broader context, including social and psychological aspects. The findings provide insights for businesses in designing more innovative marketing strategies as well as for academics in understanding the complexities of consumer behavior in traditional markets.

Comparative analysis of thoracic structure and function using CT and dynamic MRI in pediatric thoracic insufficiency syndrome with and without neuromuscular disease.

Comparative analysis of thoracic structure and function using CT and dynamic MRI in pediatric thoracic insufficiency syndrome with and without neuromuscular disease.

The Multifaceted Role of Extrachromosomal DNA in Cancer: Functions and Clinical Implications

The Extrachromosomal DNA (ecDNA) in cancer biology has emerged as a critical driver, enhancing the knowledge about tumorigenesis, progression and treatment. The current review article explores the multifaceted role of Extrachromosomal DNA, focusing on its ability to amplify oncogenes, enhance tumor heterogenicity, and support cancer cell survival and understanding therapeutics pressure. Moreover, the unique transcriptional and replication dynamics of ecDNA with linking the uneven segregation during cell division, create a significant environment for the understanding of genetic diversity and adaptive evolution in tumors. In clinics the ecDNA holds significant potential as a biomarker for cancer, diagnosis, treatment, therapeutic monitoring and progenies. The higher level of ecDNA correlates with poor clinical outcomes and resistance to therapies, emphasizing its prognostic value. The current therapeutic techniques targeting ecDNA specific vulnerabilities, such as disrupting replication stress pathways or silencing the transcriptional activity, represents promising ways for cancer treatment This review also highlights the potential of circulating ecDNA in liquid biopsies as a non-invasive diagnostic and monitoring tool. Despite these advances, challenges such as standardizing detection methods and understanding ecDNA diverse roles across cancer types remain. Addressing these gaps will unlock new opportunities in precision oncology, making ecDNA a cornerstone of future cancer diagnostics and therapeutics. Bangladesh J Medicine 2025; 36(2): 82-91

Time Series Clustering for Exploring Neighborhood Dynamics: The Case of U.S. Neighborhood Racial and Ethnic Trends, 1990–2020

ABSTRACTThis article introduces a time‐series clustering approach for classifying, visualizing, and exploring neighborhood dynamics. We illustrate the method for the case of racial and ethnic dynamics of neighborhoods in 64 U.S. metropolitan areas from 1990 to 2020. We establish typologies of continuous attribute trajectories for the share of Black, White, and Hispanic populations at the census tract level and explore generalizability versus specificity tradeoffs when varying the cluster analysis scale. Our results affirm a consistent decline in White population shares in neighborhoods across most metropolitan areas, accompanied by varied increases in Black and Hispanic populations. We also highlight the importance of metropolitan context in shaping neighborhood trends. While all cities show a trend towards increased diversity, the specific patterns and rates of change vary considerably, highlighting the unique demographic dynamics at play in each metropolitan area. The time‐series clustering approach offers some advantages over previously used methods for visualizing and classifying longitudinal neighborhood dynamics like sequence analysis or growth change modeling in that it clusters the full continuous time series and does assume a pre‐determined functional form.

Financial Distress Determinants in Emerging Markets: Evidence from Nepalese Financial Institutions

Background: Financial distress occurs when institutions fail to meet financial obligations, potentially leading to bankruptcy. While extensively studied in developed economies, research remains limited in developing nations like Nepal, where financial sector stability is crucial for economic growth. This study examines financial distress determinants in Nepalese financial institutions, focusing on liquidity, profitability, credit risk, firm size, operational efficiency (BOPO), and capital adequacy (CAR). Methods: A quantitative approach analyzed eight Nepalese financial institutions under regulatory scrutiny from 2018–2023. Panel data analysis, including unit root and Hausman tests, was conducted. The Fixed Effects Model (FEM) was selected, validated by a significant Hausman test (p = 0.0206). Altman’s Z-score measured distress, while regression analysis evaluated determinants. Results: Descriptive statistics revealed wide variations in financial health, with Altman’s Z-scores (0.1336–4.0317) indicating distress risks. Unit root analysis showed non-stationarity in liquidity, profitability, and credit risk, while firm size was stationary. CAR had a significant negative impact on distress (p = 0.011), whereas liquidity, profitability, and credit risk were insignificant. BOPO showed marginal significance (p < 0.1). The model exhibited strong explanatory power (R² = 0.9999) with no autocorrelation (Durbin-Watson = 2.2166). Conclusion: Capital adequacy is the most critical determinant of financial distress in Nepal, aligning with global findings but contrasting with studies emphasizing liquidity or profitability. The results underscore CAR’s role in mitigating distress, urging regulators to enforce robust capital standards. Novelty: This study fills a gap in Nepal-specific financial distress research, highlighting unique institutional dynamics. It challenges conventional liquidity-centric views, emphasizing CAR’s predictive superiority in emerging markets. Policymakers and managers can leverage these insights to enhance financial stability.

Carbonate chemistry and CO2 dynamics in the Persian Gulf.

Carbonate chemistry and CO2 dynamics in the Persian Gulf.

The unique dynamics of water and polymer in polyethylene imine–water mixtures across the glass transition

The unique dynamics of water and polymer in polyethylene imine–water mixtures across the glass transition

A chip-integrated comb-based microwave oscillator

Low-noise microwave oscillators are cornerstones for wireless communication, radar and clocks. The employment and optimization of optical frequency combs have enabled photonic microwave synthesizers with unrivalled noise performance and bandwidth breaking the bottleneck of those electronic counterparts. Emerging interest is to use chip-based Kerr frequency combs, namely microcombs. Today microcombs built on photonic integrated circuits feature small size, weight and power consumption, and can be manufactured to oscillate at any frequency ranging from microwave to millimeter-wave band. A monolithic microcomb-based microwave oscillator requires integration of lasers, photodetectors and nonlinear microresonators on a common substrate, which however has still remained elusive. Here, we demonstrate the first, fully hybrid-integrated, microcomb-based microwave oscillator at 10.7 GHz. The chip device, powered by a customized microelectronic circuit, leverages hybrid integration of a high-power DFB laser, a silicon nitride microresonator of a quality factor exceeding 25 × 106, and a high-speed photodetector chip of 110 GHz bandwidth (3 dB) and 0.3 A/W responsivity. Each component represents the state of the art of its own class, yet also allows large-volume manufacturing with low cost using established CMOS and III-V foundries. The hybrid chip outputs an ultralow-noise laser of 6.9 Hz intrinsic linewidth, a coherent microcomb of 10.7 GHz repetition rate, and a 10.7 GHz microwave carrier of 6.3 mHz linewidth – all the three functions in one entity occupying a footprint of only 76 mm2. Furthermore, harnessing the nonlinear laser-microresonator interaction, we observe and maneuver a unique noise-quenching dynamics within discrete microcomb states, which offers immunity to laser current noise, suppression of microwave phase noise by more than 20 dB, and improvement of microwave power by up to 10 dB. The ultimate microwave phase noise reaches −75/−105/−130 dBc/Hz at 1/10/100 kHz Fourier offset frequency. Our results can reinvigorate our information society for communication, sensing, imaging, timing and precision measurement.

Determinants of Firm’s Capital Structure in Indonesia

The determination of capital structure has been a focal point of finance research for over six decades, yet it remains a complex and controversial topic, particularly in emerging markets like Indonesia. This study seeks to address a key gap in the literature by examining the firm-specific factors such as profitability, tangibility, growth opportunities, liquidity, and business risk that influence capital structure decisions among Indonesian firms. Despite existing knowledge, limited empirical research specifically addresses the unique financial dynamics of Indonesian firms, many of which rely heavily on debt due to restricted access to equity markets and the prevalence of family-owned enterprises. This reliance on debt raises concerns about financial stability, particularly in light of risks underscored by the Global Financial Crisis of 2008. Using data from public companies listed on the Indonesian Stock Exchange between 2014 and 2023, this study employs panel data regression and multiple regression analysis to investigate these factors. The significance of this study extends beyond academic contribution, offering valuable insights into financial management, policymaking, and investment strategies. By clarifying how firm-specific factors influence capital structure, this research provides practical guidance for financial managers to develop effective financing strategies. Furthermore, it assists policymakers in creating a supportive regulatory environment for businesses and helps investors make informed decisions. Ultimately, this study enhancing financial literacy and stability within Indonesia's growing economy.

Unique Dynamics and Challenges of the Oregon and Washington Hardwood Manufacturing Sector

Unique Dynamics and Challenges of the Oregon and Washington Hardwood Manufacturing Sector

Reciprocal relationships between social support and depression among military cadets in Taiwan: findings from a long-term cross-lagged panel analysis.

This study examines the reciprocal relationship between social support and depressive symptoms among military cadets in Taiwan, a population facing unique academic and military pressures. While emerging adults are prone to mental health challenges, they encounter additional stressors such as strict hierarchies and separation from family. Social support is known to be a protective factor, yet its long-term effects and bidirectional relationship with depression remain underexplored, particularly in collectivist military cultures where mental health may be stigmatised. Using a cross-lagged panel model with three waves of data, this study also explores whether this relationship varies by gender. A secondary analysis of longitudinal data was conducted from the "Career Development of Military Academy Students" project, which surveyed all Taiwanese military academy students from the 111th class across three waves (W1-W3). The final sample consisted of 898 students (73.2% male, average age=20.9) from six military academies. To analyse the bidirectional relationship between social support and depression, autoregressive cross-lagged panel analysis using structural equation modelling (SEM) was employed. Multigroup SEM was used to assess gender difference. The cross-lagged panel model revealed reciprocal effects between social support and depression in the overall sample, evident only between W1 and W2. From W2 to W3, depression influenced perceived social support, with a stronger effect observed in males than females. These results underscore the unique dynamics of social support and depression in military contexts, particularly for females, where the relationship appears more complex. The findings highlight the need for both systemic support structures and individualised interventions in military settings, considering gender differences and the evolving nature of mental health challenges. By addressing these factors, military leaders and mental health professionals can better support cadets in managing stress and depression, fostering a more resilient and mentally healthy military community.

Ion Gel-Modulated Low-Temperature Field-Effect Phototransistors with Multispectral Responsivity for Artificial Synapses.

We report an ion-gel-gated amorphous indium gallium zinc oxide (a-IGZO) optoelectronic neuromorphic transistors capable of synaptic emulation in both photoelectric dual modes. The ion-gel dielectric in the coplanar-structured transistor, fabricated via ink-jet printing, exhibits excellent double-layer capacitance (>1 μF/cm2) and supports low-voltage operation through lateral gate coupling. The integration of ink-jet printing technology enables scalable and large-area fabrication, highlighting its industrial feasibility. Electrical stimulation-induced artificial synaptic behaviors were successfully demonstrated through ion migration in the gel matrix. Through a simple and controllable oxygen vacancy engineering process involving low-temperature oxygen-free growth and post-annealing process, a sufficient density of stable subgap states was generated in IGZO, extending its responsivity spectrum to the visible-red region and enabling wavelength-discriminative photoresponses to 450/532/638 nm visible light. Notably, the subgap states exhibited unique interaction dynamics with low-energy photons in optically triggered pulse responses. Critical synaptic functionalities-including short-term plasticity (STP), long-term plasticity (LTP), and paired-pulse facilitation (PPF)-were successfully simulated under both optical and electrical stimulations. The device achieves low energy consumption while maintaining compatibility with flexible substrates through low-temperature processing (≤150 °C). This study establishes a scalable platform for multimodal neuromorphic systems utilizing printed iontronic architectures.

Exploring the Relationship between Generational Diversity, Employee Engagement, and Turnover Intention: Evidence from Manufacturing Workers

Generational diversity is a challenge as well as an opportunity to increase employee engagement, which can affect turnover intention. This study analyzes the influence of these two factors on manufacturing companies in Cikarang. With a quantitative approach, this study uses a purposive sampling method with a total of 73 respondents. Data was collected through questionnaires and analyzed using the Structural Equation Modeling technique based on Partial Least Squares (PLS). The results show that both generational diversity and employee engagement have a negative influence on turnover intention, but the influence is not significant. These findings indicate that while generational diversity can create unique work dynamics and employee engagement increases employee emotional engagement, these factors are not the main determinants of turnover intention in the manufacturing sector. Job stability, compensation, and a structured work culture play a greater role in influencing employees' intentions to stay in the company. This study provides important insights for management to develop human resource management strategies that focus on strengthening job stability, providing competitive incentives, and creating a cross-generational inclusive work environment. The novelty of this study lies in its focus on the manufacturing industry context in Cikarang, where generational diversity is high yet rarely studied in relation to turnover intention. By integrating generational differences and employee engagement in a single empirical model, this research offers a new perspective that can guide more targeted HR interventions in multi-generational workplace settings.

Pulse-driven MEMS gas sensor combined with machine learning for selective gas identification

The sensing and identification of trace gases are essential for ensuring chemical safety and protecting human health. This study introduces a low-power electronic nose system that utilizes a single sensor driven by repeated pulsed power inputs, offering a viable alternative to conventional sensor array-based methods. The sensor’s compact design and suspended architecture facilitate a rapid thermal response, effectively decoupling the influences of temperature, physisorption, and charge exchange on the conductivity of the sensing material. This mechanism generates distinct gas sensing responses, characterized by alternating dual responses within a single time period. The unique dynamics of the dual signals, which vary with gas type and concentration, enable precise identification of multiple gas species using machine learning (ML) algorithms. Microfabricated through wafer-level batch processing, our innovative electronic nose system holds significant potential for battery-powered mobile devices and IoT-based monitoring applications.

Abstract 3242: DNA methylation profiling of Epstein-Barr virus (EBV) in lymphoproliferative disease reveals diagnostic and therapeutic applications

Abstract Introduction: Epstein-Barr Virus (EBV) is an oncogenic herpesvirus linked to hematologic malignancies. EBV enters latency within host cells and can undergo lytic activation, resulting in release of infectious virions. Latent EBV mediates malignant transformation, while lytic EBV is a frequent complication in immune suppression settings like post-transplant lymphoproliferative disease (PTLD). Current clinical assays detect only the presence of EBV via qPCR, limiting their diagnostic use. DNA methylation on EBV genomes is essential for interconversion of lytic/latent states, making it a promising virology biomarker. Methods: We have developed a high-throughput multiplex PCR profiling assay (iPLEX) to assess quantitative EBV DNA methylation at n=35 CpG dinucleotide sites in liquid biopsies (plasma/serum). We applied this assay to a cohort of n=246 plasma samples collected at the OSU Wexner Medical Center via the Leukemia Tissue Bank Shared Resource. Our cohort consisted of viremic patients with EBV-associated lymphoma or non-malignant EBV activation, including n=118 organ transplant recipients. We complemented our analysis with single molecule readout of EBV plasma methylomes (n=27) using Nanopore sequencing of native DNA methylation. Results: Low EBV methylation distinguished lytic from latent EBV (sensitivity: 93.3%, specificity: 97.2%), outperforming clinical EBV qPCR. We revealed distinct EBV methylation in lymphoma subtypes, ranging from intermediate (Hodgkin lymphoma, polymorphic PTLD) to high (Burkitt-, NK/T-cell lymphoma, monomorphic PTLD). Assessment of EBV methylation in treatment follow-up (n=55) highlighted malleable EBV methylation was associated with improved survival under treatment (p=0.0005). We further identified unique EBV methylation dynamics under epigenetic therapies, including DNA methyltransferase (DNMT) inhibitor decitabine. DNA methylation in the EBV protein kinase gene BGLF4 was further associated with response to antiviral ganciclovir (GCV) use. Lastly, assessment of overall methylation patterns revealed four EBV methylation groups. Single molecule methylome analysis via Nanopore sequencing validated our data and identified distinct states of molecular epigenetic heterogeneity in EBV lymphoma and PTLDs. Methylation groups showed highly significant association with overall survival in multiple disease entities, including Hodgkin- and diffuse large B-cell lymphoma (DLBCL). Conclusion: Our data reveal the epigenetic EBV landscape in lymphoma and non-malignant viremic conditions. EBV methylation can identify lymphoma through a minimally invasive plasma test for earlier and more reliable diagnosis of EBV-driven malignancy. EBV methylation could guide informed treatment decisions, especially with regard to epigenetic- and antiviral drug use, and aid in personalized care in the future. Citation Format: Christoph Weigel, Haley L. Klimaszewski, Cara Noel, Ada C. Sher, Kurtis M. Host, Yue-Zhong Wu, Sarah Y. Schlotter, Eric Brooks, Charles T. Gregory, Esko Kautto, Elshafa H. Ahmed, Rosemary Rochford, James S. Blachly, Mark Lustberg, Timothy Voorhees, Christopher C. Oakes, Robert A. Baiocchi. DNA methylation profiling of Epstein-Barr virus (EBV) in lymphoproliferative disease reveals diagnostic and therapeutic applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3242.

Contextualizing relationship quality between pregnant Black women and the fathers of their babies: A latent class analysis.

Black women in the United States experience higher rates of adverse maternal and birth outcomes (e.g., depressive symptoms and preterm birth), influenced by social and psychosocial factors including mother-father relationship quality. Existing measures of relationship quality often overlook the unique dynamics within Black families, requiring a more nuanced approach. This study aims to contextualize the multidimensional nature of relationship quality between pregnant Black women and the fathers of their babies. Using a cross-sectional design, we analyzed data from 405 women enrolled in the Biosocial Impacts on Black Births study. Participants completed questionnaires at 19-29 weeks gestation on six indicators of relationship quality: frequency of contact, frequency of father's involvement during pregnancy, relationship before and during pregnancy, support, and conflict. Latent class analysis was used to identify a construct of relationship quality. Three distinct classes of relationship quality were identified: "no relationship," "conflictual relationship," and "good relationship." Sensitivity analyses showed that while marital or cohabitation status was highly correlated with both the relationship indicators and identified classes, its inclusion as an additional indicator did not alter classification in the latent class model. These classes highlight the intricacies of relationship dynamics, which may be specific to Black families. This study underscores the importance of considering the multifaceted context of relationship quality, which is essential for designing culturally informed public health strategies or interventions. The implications of our findings are significant for both research and clinical interventions aimed at improving birth outcomes for diverse populations. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Profiling antivaccination channels in Telegram: early efforts in detecting misinformation

IntroductionTelegram’s privacy-focused architecture has made it a fertile ground for the spread of misinformation, yet its closed nature poses challenges for researchers. This study addresses the methodological gap in capturing and analysing misinformation on Telegram, with a particular focus on the anti-vaccination community.MethodsThe research was conducted in three phases: (1) a structured review of literature on misinformation dissemination via Telegram, (2) development of a conceptual framework incorporating features of message creators, message content, intended targets and broader social context, and (3) application of this framework to anti-vaccination Telegram channels using latent profile analysis (LPA). A dataset comprising 7,550 messages from 151 Telegram channels was manually annotated and analysed.ResultsLPA identified distinct profiles among the channels. Malicious and non-malicious channels showed significant differences in their communication patterns, particularly in the use of crisis framing, discursive manipulation, and thematic orientation. T-tests confirmed these distinctions.DiscussionThe findings highlight Telegram’s unique dynamics in misinformation spread and support the utility of the proposed framework in isolating harmful content. The study underscores the need for tailored analytical strategies for platforms with non-standard affordances and suggests that content-based profiling may assist in proactive moderation.

Modulation transfer function degradation of thermal imaging systems due to platform-induced blurs

The resolution of an infrared system is described by its modulation transfer function (MTF). This metric is traditionally measured in the lab but can also be measured in the field. For sensor systems designed for deployment in the field, it is best to measure the MTF in the field under the conditions it is expected to perform. As it becomes more common to mount infrared sensors on aerial platforms, assessing performance becomes a more complex problem. When the sensor is mounted on a moving airborne platform, the performance of the system is expected to change and degrade. Factors such as mechanical vibrations, flight dynamics, and flight path motions contribute to this degradation. Each platform type, whether a single-rotor helicopter or a multi-rotor UAV, exhibits unique dynamics influencing MTF degradation differently. Special attention must also be placed on the mounting technique to avoid introducing additional vibrations and to dampen vibrations when necessary. The comparison of static and dynamic MTFs aids in the optimization of system design for specific aerial platforms and direct-mounted sensors, ensuring peak performance in operational settings.

Robust and High Temperature Spin Crossover Controlled via the Self-Assembly of Chiral and Racemic Polymorphs in Triazolylimine [Fe2L3](BF4)4 Helicates.

Three new chiral spin crossover (SCO) dinuclear triple helicates of type [Fe2L3](BF4)4 are reported exhibiting a robust magnetic behavior that is resistant to rapid changes in temperature, moisture and light. The selective formation of racemic aggregates upon crystallization of a solution of the respective racemic complexes was found to be associated with the helical torsion, intermetallic distance as well as the spatial arrangement of the enantiomers and anions. Torsional stress and particular hydrogen bonding interactions were related to the potential coiling and uncoiling mechanisms inherent to some helically chiral systems as well as to the efficacy of cooperativity transmission within the crystal lattice. These unique structural dynamics were correlated with the display of a chirality-dependent semiabrupt SCO profile observed for each enantiopure aggregate. This study highlights how the molecular shape as well as the crystal packing of helically chiral compounds can be altered to modulate the magnetic behavior toward a robust and high temperature SCO system.