Water quality's responses to water energy variability of the Yangtze River.

River energy serves as an indicator of pollutant-carrying capacity (PCC), influencing regional water quality dynamics. In this study, MIKE21 hydrodynamics-water quality models were developed for two scenarios, and grid-by-grid numerical integration of energy was conducted for the Yangtze River's mainstream. Comparison of predicted and measured values at monitoring points revealed a close fit, with average relative errors ranging from 5.17 to 8.37%. The concept of PCC was introduced to assess water flow's ability to transport pollutants during its course, elucidating the relationship between river energy and water quality. A relationship model between Unit Area Energy (UAE) and PCC was fitted (R2 = 0.8184). Temporally, reservoir construction enhanced the smoothness of UAE distribution by 74.47%, attributable to peak shaving and flow regulation. While this flood-drought season energy transfer reduced PCC differences, it concurrently amplified pollutant retention by 40.95%. Spatially, energy distribution fine-tuned PCC values, showcasing binary variation with energy changes and a critical threshold. Peak PCC values for TP, NH3-N, and COD were 2.46, 2.26, and 54.09 t/(km·a), respectively. These insights support local utility regulators and decision-makers in navigating low-carrying capacity, sensitive areas, enhancing targeted water protection measures for increased effectiveness and specificity.

Achieving consistency of flexible surface acoustic wave sensors with artificial intelligence.

Flexible surface acoustic wave technology has garnered significant attention for wearable electronics and sensing applications. However, the mechanical strains induced by random deformation of these flexible SAWs during sensing often significantly alter the specific sensing signals, causing critical issues such as inconsistency of the sensing results on a curved/flexible surface. To address this challenge, we first developed high-performance AlScN piezoelectric film-based flexible SAW sensors, investigated their response characteristics both theoretically and experimentally under various bending strains and UV illumination conditions, and achieved a high UV sensitivity of 1.71 KHz/(mW/cm²). To ensure reliable and consistent UV detection and eliminate the interference of bending strain on SAW sensors, we proposed using key features within the response signals of a single flexible SAW device to establish a regression model based on machine learning algorithms for precise UV detection under dynamic strain disturbances, successfully decoupling the interference of bending strain from target UV detection. The results indicate that under strain interferences from 0 to 1160 µÎµ the model based on the extreme gradient boosting algorithm exhibits optimal UV prediction performance. As a demonstration for practical applications, flexible SAW sensors were adhered to four different locations on spacecraft model surfaces, including flat and three curved surfaces with radii of curvature of 14.5, 11.5, and 5.8 cm. These flexible SAW sensors demonstrated high reliability and consistency in terms of UV sensing performance under random bending conditions, with results consistent with those on a flat surface.

Navigating the difference of riverine microplastic movement footprint into the sea: Particle properties influence.

As a critical source of marine microplastics (MPs), estuarine MPs community varied in movement due to particle diversity, while tide and runoff further complicated their transport. In this study, a particle mass gradient that represents MPs in the surface layer of the Yangtze River estuary was established. This was done by calculating the masses of 16 particle types using the particle size probability density function (PDF), with typical shapes and polymers as classifiers. Further, Aschenbrenner shape factor and polymer density were embedded into drag coefficients to categorically trace MP movement footprints. Results revealed that the MPs in North Branch moved northward and the MPs in South Branch moved southeastward in a spiral oscillation until they left the model boundary under Changjiang Diluted Water front and the northward coastal currents. Low-density fibrous MPs are more likely to move into the open ocean and oscillate more than films, with a single PE fiber trajectory that reached a maximum oscillatory width of 16.7 km. Over 95 % of the PVC fiber particles settled in nearshore waters west of 122.5°E. Elucidating the aggregation and retention of different MPs types can provide more accurate environmental baseline reference for more precise MP exposure levels and risk dose of ingestion for marine organisms.

Universal Murray's law for optimised fluid transport in synthetic structures.

Materials following Murray's law are of significant interest due to their unique porous structure and optimal mass transfer ability. However, it is challenging to construct such biomimetic hierarchical channels with perfectly cylindrical pores in synthetic systems following the existing theory. Achieving superior mass transport capacity revealed by Murray's law in nanostructured materials has thus far remained out of reach. We propose a Universal Murray's law applicable to a wide range of hierarchical structures, shapes and generalised transfer processes. We experimentally demonstrate optimal flow of various fluids in hierarchically planar and tubular graphene aerogel structures to validate the proposed law. By adjusting the macroscopic pores in such aerogel-based gas sensors, we also show a significantly improved sensor response dynamics. In this work, we provide a solid framework for designing synthetic Murray materials with arbitrarily shaped channels for superior mass transfer capabilities, with future implications in catalysis, sensing and energy applications.

Surface Acoustic Wave-Enhanced Multi-View Acoustofluidic Rotation Cytometry (MARC) for Pre-Cytopathological Screening.

Cytopathology, crucial in disease diagnosis, commonly uses microscopic slides to scrutinize cellular abnormalities. However, processing high volumes of samples often results in numerous negative diagnoses, consuming significant time and resources in healthcare. To address this challenge, a surface acoustic wave-enhanced multi-view acoustofluidic rotation cytometry (MARC) technique is developed for pre-cytopathological screening. MARC enhances cellular morphology analysis through comprehensive and multi-angle observations and amplifies subtle cell differences, particularly in the nuclear-to-cytoplasmic ratio, across various cell types and between cancerous and normal tissue cells. By prioritizing MARC-screened positive cases, this approach can potentially streamline traditional cytopathology, reducing the workload and resources spent on negative diagnoses. This significant advancement enhances overall diagnostic efficiency, offering a transformative vision for cytopathological screening.