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Background The rapid global spread of COVID-19 has seriously impacted people’s daily lives and the social economy while also posing a threat to their lives. The analysis of infectious disease transmission is of significant importance for the rational allocation of epidemic prevention and control resources, the management of public health emergencies, and the improvement of future public health systems. Methods We propose a spatiotemporal COVID-19 transmission model with a neighborhood as an agent unit and an urban spatial network with long and short edge connections. The spreading model includes a network of defined agent attributes, transformation rules, and social relations and a small world network representing agents’ social relations. Parameters for each stage are fitted by the Runge-Kutta method combined with the SEIR model. Using the NetLogo development platform, accurate dynamic simulations of the spatial and temporal evolution of the early epidemic were achieved. Results Experimental results demonstrate that the fitted curves from the four stages agree with actual data, with only a 12.27% difference between the average number of infected agents and the actual number of infected agents after simulating 1 hundred times. Additionally, the model simulates and compares different “city closure” scenarios. The results showed that implementing a ‘lockdown’ 10 days earlier would lead to the peak number of infections occurring 7 days earlier than in the normal scenario, with a reduction of 40.35% in the total number of infections. Discussion Our methodology emphasizes the crucial role of timely epidemic interventions in curbing the spread of infectious diseases, notably in the predictive assessment and evaluation of lockdown strategies. Furthermore, this approach adeptly forecasts the influence of varying intervention timings on peak infection rates and total case numbers, accurately reflecting real-world virus transmission patterns. This highlights the importance of proactive measures in diminishing epidemic impacts. It furnishes a robust framework, empowering policymakers to refine epidemic response strategies based on a synthesis of predictive modeling and empirical data.

A biomimetic cellular‐eating phenomenon in gallium‐based liquid metal to realize particle internalization in full‐pH‐range solutions is reported. The effect, which is called liquid metal phagocytosis, represents a wet‐processing strategy to prepare various metallic liquid metal‐particle mixtures through introducing excitations such as an electrical polarization, a dissolving medium, or a sacrificial metal. A nonwetting‐to‐wetting transition resulting from surface transition and the reactive nature of the intermetallic wetting between the two metallic phases are found to be primarily responsible for such particle‐eating behavior. Theoretical study brings forward a physical picture to the problem, together with a generalized interpretation. The model developed here, which uses the macroscopic contact angle between the two metallic phases as a criterion to predict the particle internalization behavior, shows good consistency with experimental results. A particle‐eating effect called liquid metal phagocytosis in gallium‐based liquid metals is realized in full‐pH‐range solutions through introducing three different kinds of excitations. Wettability alteration and intermetallic reaction are found to be primarily responsible for the particle‐eating behavior. In order to establish a generalized understanding of the underlying mechanisms, a theoretical model based on surface energy theory is built and validated.

The nascent field of nanotechnology-enabled metallurgy has great potential. However, the role of eutectic alloys and the nature of alloy solidification in this field are still largely unknown. To demonstrate one of the promises of liquid metals in the field, we explore a model system of catalytically active Bi-Sn nano-alloys produced using a liquid-phase ultrasonication technique and investigate their phase separation, surface oxidation, and nucleation. The Bi-Sn ratio determines the grain boundary properties and the emergence of dislocations within the nano-alloys. The eutectic system gives rise to the smallest grain dimensions among all Bi-Sn ratios along with more pronounced dislocation formation within the nano-alloys. Using electrochemical CO 2 reduction and photocatalysis, we demonstrate that the structural peculiarity of the eutectic nano-alloys offers the highest catalytic activity in comparison with their non-eutectic counterparts. The fundamentals of nano-alloy formation revealed here may establish the groundwork for creating bimetallic and multimetallic nano-alloys. The combination of metallurgy concepts and nanotechnology with liquid metal processing has been largely unexplored. Here the authors use liquid-phase ultrasonication to produce a model system of catalytically active nano-alloys, demonstrating electrocatalysis and photocatalysis.

Understanding the relationship between brain function and behavior remains a major challenge in neuroscience. Photoacoustic tomography (PAT) is an emerging technique that allows for noninvasive in vivo brain imaging at micrometer-millisecond spatiotemporal resolution. In this article, a novel, miniaturized 3D wearable PAT (3D-wPAT) technique is described for brain imaging in behaving rats. 3D-wPAT has three layers of fully functional acoustic transducer arrays. Phantom imaging experiments revealed that the in-plane X-Y spatial resolutions were ~200 μm for each acoustic detection layer. The functional imaging capacity of 3D-wPAT was demonstrated by mapping the cerebral oxygen saturation via multi-wavelength irradiation in behaving hyperoxic rats. In addition, we demonstrated that 3D-wPAT could be used for monitoring sensory stimulus-evoked responses in behaving rats by measuring hemodynamic responses in the primary visual cortex during visual stimulation. Together, these results show the potential of 3D-wPAT for brain study in behaving rodents.

Regulating favorable assemblies of metallic atoms in the liquid state provides promise for catalyzing various chemical reactions. Expanding the selection of metallic solvents, especially those with unique properties and low cost, enables access to distinctive fluidic atomic structures on the surface of liquid alloys and offers economic feasibility. Here, Sn solvent, as a low-cost commodity, supports unique atomic assemblies at the interface of molten SnIn 0.1034 Cu 0.0094 , which are highly selective for H 2 synthesis from hydrocarbons. Atomistic simulations reveal that distinctive adsorption patterns with hexadecane can be established with Cu transiently reaching the interfacial layer, ensuring an energy-favorable route for H 2 generation. Experiments with a natural oil as feedstock underscore this approach’s performance, producing 1.2 × 10 − 4  mol/min of H 2 with 5.0 g of catalyst at ~93.0% selectivity while offering reliable scalability and durability at 260 °C. This work presents an alternative avenue of tuning fluidic atomic structures, broadening the applications of liquid metals. Molten Sn as a metallic solvent presents economic feasibility and offers unique surface atomic structures, expanding the concept of liquid metal catalysis. As a demonstration, SnIn 0.1034 Cu 0.0094 enables selective H 2 production from hydrocarbons.

Energy can exist in nature in a wide range of forms. Energy conversion refers to the process in which energy is converted from one form to another, and this process will be greatly enhanced by energy conversion sensitizers. Recently, an emerging class of new materials, namely liquid metals (LMs), shows excellent prospects as highly versatile materials. Notably, in terms of energy delivery and conversion, LMs functional materials are chemical responsive, heat‐responsive, photo‐responsive, magnetic‐responsive, microwave‐responsive, and medical imaging responsive. All these intrinsic virtues enabled promising applications in energy conversion, which means LMs can act as energy sensitizers for enhancing energy conversion and transport. Herein, first the unique properties of the light, heat, magnetic and microwave converting capacity of gallium‐based LMs materials are summarized. Then platforms and applications of LM‐based energy conversion sensitizers are highlighted. Finally, some of the potential applications and opportunities of LMs are prospected as energy conversion sensitizers in the future, as well as unresolved challenges. Collectively, it is believed that this review provides a clear perspective for LMs mediated energy conversion, and this topic will help deepen knowledge of the physical chemistry properties of LMs functional materials. Liquid Metals (LMs) featuring both fluidic and metallic properties, are capable of responding to external energy stimuli, which are particularly suitable for energy conversion in many impactful applications. This review systematically summarized and discussed representative platforms and applications of the LMs‐based energy conversion sensitizers, with an emphasis on the intrinsic energy‐responsive virtues and the involved mechanism for specific energy conversion.

We present a noninvasive method of photoacoustic tomography (PAT) for imaging cerebral hemodynamics in awake-moving rats. The wearable PAT (wPAT) system has a size of 15 mm in height and 33 mm in diameter, and a weight of ~ 8 g (excluding cabling). The wPAT achieved an imaging rate of 3.33 frames/s with a lateral resolution of 243 μm. Animal experiments were designed to show wPAT feasibility for imaging cerebral hemodynamics on awake-moving animals. Results showed that the cerebral oxy-hemoglobin and deoxy-hemoglobin changed significantly in response to hyperoxia; and, after the injection of pentylenetetrazol (PTZ), cerebral blood volume changed faster over time and larger in amplitude for rats in awake-moving state compared with rats under anesthesia. By providing a light-weight, high-resolution technology for in vivo monitoring of cerebral hemodynamics in awake-behaving animals, it will be possible to develop a comprehensive understanding on how activity alters hemodynamics in normal and diseased states.

Ultrasound velocimetry has been widely used for blood flow imaging. However, the flow measurements are constrained to resolve the in‐plane 2D flow components when using a 1D transducer array. In this work, an ultrasound speckle decorrelation analysis‐based velocimetry (3C‐vUS) is proposed for 3D velocity components measurement using a 1D transducer array. The 3C‐vUS theory is first derived and validated with numerical simulations and phantom experiments. The in vivo testing results show that 3C‐vUS can accurately measure the blood flow 3D‐velocity‐components of the human carotid artery at arbitrary probe‐to‐vessel angles throughout the cardiac cycle. With such capability, the 3C‐vUS will alleviate the requirement of operators and promote disease screening for blood flow‐related disorders. The proposed ultrasound speckle decorrelation analysis‐based velocimetry (3C‐vUS) technique enables accurate measurement of the 3D velocity components and total flow speed of blood flow at arbitrary probe‐to‐vessel angles. This capability helps to alleviate the requirement of precise alignment and interpretation of operator, potentially mitigating the lack of skilled sonographers and facilitating large‐scale cardiovascular disease‐related screening at the community level.

Liquid metals are promising unconventional solvents for dissolving metals and growing their crystals. However, how the crystals grow within these metallic solvents cannot be observed easily due to the opacity of liquid metals. Using X-ray micro-computed tomography, the three-dimensional formations of crystals inside liquid metal solvents, under different conditions, are presented. In this work, we explore the use of different liquid metals solvents for growing metallic crystals, while imaging the crystals shape and sizes inside liquid metals. We use gallium-based solvents and platinum, as the solutes and demonstrate the use of liquid metals for forming metallic crystals through modulating environmental boundary effects, controlled cooling rates, and solvent selection. It is observed that the cooling rate and composition of the reaction media will influence crystals morphologies and intermetallic phases. As a proof-of-concept, we perform hydrogen evolution reaction using metallic crystals extracted from the solvents, showcasing the potential of liquid metal-based synthesis in tailoring metallic crystals properties for enhancing catalytic activity demonstrating a strategy for engineering metallic crystals in liquid metal solvents. Crystal growth is visualized inside non-transparent liquid metals, while preserving their original state, using X-ray micro-computed tomography to reveal how liquid metal solvent composition and cooling conditions influence crystal formation.

To ensure sustainable marine resource utilization, advanced monitoring methods are urgently needed to mitigate overfishing and ecological imbalances. Conventional fishing activity detection methods, including speed threshold-based approaches and Gaussian Mixture Models, often fail to accurately handle complex vessel trajectories, resulting in imprecise quantification of fishing effort and hindering effective monitoring of illegal, unreported, and unregulated (IUU) fishing activities. To address these limitations, we propose a spatiotemporal adaptive clustering and segmentation (STACS) framework for recognizing fishing activities. First, ST-DBSCAN clustering distinguishes concentrated fishing operations from transit movements. Second, an adaptive segmentation algorithm that incorporates heading stability and local density dynamically partitions trajectories into coherent segments, using spatiotemporal clusters as the basic units. Third, multiple features capturing temporal dynamics and spatial patterns are extracted to characterize fishing behaviors. Finally, an XGBoost classifier with run-length encoding post-processing converts point-level predictions to continuous fishing episodes. Experiments on fishing vessel trajectory datasets demonstrate that STACS outperforms conventional methods and advanced segmentation approaches, improving both point-level classification and segment-level coherence across diverse fishing scenarios. By enhancing IUU fishing detection and reducing classification inconsistencies, STACS provides valuable insights for marine conservation, policymaking, and fisheries management, bridging local behavioral dynamics with global trajectory analysis.