Abstract In structured light three-dimensional (3D) measurement, the high dynamic range (HDR) imaging for varying reflectivity objects with snapshot and with high accuracy is still a great challenge. This paper proposes a snapshot HDR structured light method based on polarizer modulated polarization imaging technology. In our snapshot HDR 3D reconstruction method, a linear polarizer is placed in front of the four channels polarization camera, which allows the polarization camera to capture four images with different brightness levels in a single exposure for both metal and non-metallic objects in our developed structured light system. The optimal rotation angle is investigated and determined to maximize the accuracy of the polarization structured light 3D measurement system for complex varying reflectivity objects. Experimental results demonstrate that our proposed method can perform snapshot HDR imaging for fringe projection structured light 3D measurement and outperform four-exposure HDR fusion method, which requires less acquisition times, making it more suitable for dynamic measurements.

Abstract A second-order memristor itself is a complex nonlinear dynamical system. The core advantage of second-order memristors over the classic first-order model lies in their introduction of multiple coupled internal state variables, which enables far more complex dynamical behaviors and information processing capabilities than the latter. In this work, a discrete secondorder memristor is designed and coupled with a one-dimensional sine map to construct a threedimensional hyper-chaotic system. Dynamical analysis reveals that the system exhibits a wide range of behaviors, including period, quasi-period, chaos, and hyperchaos states. Moreover, complexity analysis shows that smaller coupling parameters and larger nonlinear parameters tend to promote the emergence of chaotic dynamics. The system also displays multistability in the form of attractor coexistence, such as between chaos states and fixed points, as well as between chaos and period states. Finally, digital circuit implementations are performed to validate typical attractor phase trajectories observed in the system.

ABSTRACT Legacy has become a common feature across multiple mega sporting events, with organisers and invested stakeholders touting the positive impacts such tournaments can have on the host nation. While common across both popular and academic discourse, the term is used in varying and multiple ways, with many frameworks proposed to help conceptualise, implement, and measure event legacy. Here we expand upon such scholarship to offer a complex systems approach for conceptualising and thinking about the gender legacies associated with the 2023 FIFA Women’s World Cup (FWWC23). To accomplish this, we look specifically at the enactment of gender legacy within New Zealand during the tournament. Drawing on interviews conducted with staff from legacy-related organisations (e.g. New Zealand Football, Oceania Football Confederation), we explore the multiple stakeholders that were part of the New Zealand gendered legacy complex system. Offering a multi-scalar approach to mega-event legacy, we argue that complex systems thinking is useful for understanding the challenges associated with gender legacy policies, particularly in terms of operationalising change through local, national, and international gender legacy interventions.

In this work, the trans-[Pt(L)2(PPh3)2] complex (L: 5-heptyl-1,3,4-oxadiazole-2-(3H)-thione) was associated with a microemulsion (ME/PtII complex). The microemulsified system underwent physicochemical characterization, including pH, conductivity, rheology, zeta potential, and dynamic light scattering (DLS) measurements. The microemulsion system remained stable at a pH near 6.0, indicating biocompatibility, while the conductivity was between 7 and 8 μS cm-1 , with a hysteresis area of −0.06 Pas-1 for the ME/PtII complex. The DLS technique confirmed the presence of a microemulsion with particle sizes ranging from 10 to 200 nm. The polydispersity index for the ME/PtII complex system was close to 0.3, indicating a monodisperse system, with a zeta potential of −19.2 ± 4.49 mV. These results showed that the system containing the PtII complex and the microemulsion is thermodynamically stable. Subsequently, cell viability studies demonstrated that the ME/PtII complex system is not toxic to peripheral blood mononuclear cells (PBMCs). In the phagocytosis activity assay, the complex associated with the microemulsion showed an increase in the phagocytosis index, suggesting that the microemulsion (ME/PtII complex) has potential for new biological assays, such as antitumor and antibacterial.

Neural plasticity, heterochrony, and the onto-phylogeny of consciousness.

Development of a multifunctional, injectable biomaterial using hyaluronan as a bioactive nanocarrier.

Development of a new fluorescent probe for methylglyoxal determination in foods and living zebrafish.

Optimal decision support of irrigation drainage combination schemes in lakefront agriculture-wetland systems.

Precision medicine is aimed at achieving a more personalized approach tailored to individual characteristics and urgently requires the development of precise diagnostic and therapeutic methods. Small-molecule dyes play indispensable roles in medical imaging and surgery procedures, attracting significant attention regarding disease diagnosis and therapy. However, their widespread utilization for accurate tumor localization and long-term intraoperative imaging remains hindered by their inherent limitations, including tedious synthesis protocols, poor photostability, susceptibility to fluorescence quenching in physiological environments, and rapid systemic clearance. Supramolecular dyes, defined as small-molecule dye-based assemblies, usually present unique and superior photophysical properties, including tunable optical properties, enhanced photodynamic and photothermal performance, improved photostability and optimized anti-quenching capability, collectively enabling high-precision optical diagnosis and therapy. Despite remarkable progress in supramolecular dyes, a systemic review summarizing their applications in precision biomedicine remains lacking. In this review, we systematically summarize the recent advances on the development of supramolecular dyes across three key self-assembly systems: supramolecular coordination complexes (SCCs) systems, host-guest systems (including cyclodextrin, cucurbit[n]urils (CB [n]s), calixarenes and pillararenes), and enzyme instructed self-assembly (EISA) systems. Moreover, we highlight current challenges and future perspectives to accelerate their translation from fundamental research to clinical applications.

As typical and complex mechatronic system, health state of the wind turbine (WT) is of significant importance to the sustained and reliable service. However, it is noted that influenced by the seasonal or fitful wind, WTs unavoidably serve in the dynamically varying environment. In this event, most of the currently available indicators expose deficiency in regard of the false or missed alarms due to the coupled condition interference. To address this issue and improve the reliability of the mechatronic system, a novel statistic discrepancy oriented cyclo-non-stationary (CNS) indicator is developed in this article. First, characteristics of the recorded degradation samples are revealed by a multiparametric model, during which the consistency is verified and improved by the hypothesis test. Second, a specific speed-dependent slicing (SDS) operator is then designed, aiming to alleviate the varying-speed-induced modulation interference at the different degradation stages. With this developed SDS operator, a CNS indicator, which can well adapt to the dynamically varying environment during the operating process, is subsequently developed by incorporating the resampling-based statistic discrepancy evaluating mechanism. Experiments indicate that the proposed method can effectively characterize the health state of the transmission parts of the industrial WT under varying speed conditions.

Optimal operation and marginal costs in a complex polygeneration system including thermal energy storage and DHCN pipelines

Leveraging large language models for automating water distribution network optimization.

Industrial IoT-driven condition-based maintenance plus for complex system with multiple dependencies

Pre-classification based stochastic reduced-order model for time-dependent complex system

PGVAE-VBAKF: A robust strategy for complex system response prediction and noise variance estimation considering modeling errors and nonstationary noises

Least ranked human individuals exhibit scale free behavioral responses in hierarchical social systems.

Insurance interference in electrophysiology: Reclaiming control for timely cardiac care.

Cerebral glymphatic system: Structure, regulation, ageing, and mechanisms of encephalopathy.

Rapid industrial growth in developing countries requires robust maintenance, and predictive maintenance (PdM) is a key solution to minimize downtime and costs. However, complex industrial systems and the acute scarcity of tagged data, particularly in African contexts, pose significant implementation challenges for traditional PdM approaches. This research proposes a novel predictive maintenance approach using a Variational Autoencoder (VAE) specifically designed to address data scarcity and improve interpretability in complex industrial systems in developing countries. The VAE is trained on real operational data and learns complex system patterns. Its interpretability is a key feature, achieved through visualization and analysis of latent space, providing deeper insight into system behavior. The VAE model demonstrates strong and consistent performance in anomaly detection and data reconstruction, as evidenced by low Mean Squared Error (MSE) and favorable R² values, and is rigorously validated through cross-validation, confirming its robustness and generalizability. This underscores its ability to accurately model complex system dynamics across diverse data subsets. This interpretable VAE model offers a powerful and promising predictive maintenance solution for improving the reliability of complex industrial systems in developing countries. By enabling early anomaly detection, synthetic data generation, and improved decision making, this approach has the potential to significantly contribute to the growth and sustainability of industries in these regions through reduced downtime and optimized resource utilization.

The U.S. college admissions process is a uniquely complex and decentralized system that poses significant challenges for both students and their parents. With over 4,000 institutions offering varied application platforms, deadlines, and requirements, navigating this process demands a highly personalized approach. While students juggle academic, extracurricular, and application-related responsibilities, effective time management becomes a critical factor in securing both admission and financial aid opportunities. Parents, ideally positioned to support their children through this journey, however they often find themselves overwhelmed due to a lack of clear and accessible information. The increasing dependance on expert guidance highlights the limitations of generic online resources in addressing the individualized needs of applicants. Furthermore, emotional involvement and limited knowledge can hinder parents' ability to provide objective and strategic support. This paper examines the multifaceted challenges parents face in the college admissions process and discusses potential strategies to bridge the information and support gap, ultimately aiming to enhance student outcomes during this pivotal life transition.