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In the low-lying, river-rich Pearl River Delta in South China, an extensive network of flood defense levees, spanning over 4400 km, plays a crucial role in urban flood management. These levees are designed to withstand floods and storm surges, yet their failure can lead to significant human and economic losses, highlighting the need for robust urban flood defense strategies. This necessitates the development of a sophisticated geographic information system for the levee network and rapid, accurate assessment methods for levee conditions to support water management and flood mitigation efforts. This study focuses on the levees along the Hengmen waterway in the Pearl River Delta, utilizing airborne Light Detection and Ranging (LiDAR) technology to gather 3D spatial data of the levees. Employing the Cloth Simulation Filter (CSF) algorithm, non-ground point cloud data were extracted. The study improved upon the region-growing algorithm, using a seed point set approach for the automatic extraction of levee point cloud data. The accuracy and completeness of levee extraction were evaluated using the quality index. This method achieved effective extraction of four levee types, showing significant improvements over traditional algorithms, with extraction quality ranging from 72% to 83%. Key research outcomes include the development of a novel method for detecting localized levee depressions based on the computation of the variance of angles between normal vectors in single-phase levee point cloud data. An adaptive optimal neighborhood approach was utilized to accurately determine the normal vectors, effectively representing the local morphology of the levee point clouds. Applied in three levee depression detection experiments, this method proved effective, demonstrating the capability of single-phase data in identifying regions of levee depression deformation. This advancement in levee monitoring technology marks a significant step forward in enhancing urban flood defense capabilities in regions such as the cities of the Pearl River Delta in China. [ABSTRACT FROM AUTHOR]

Laser scanning, along with its resultant 3D point clouds, constitutes a prevalent method for the documentation of cultural heritage. This paper introduces a novel workflow for the structural analysis of glazed tubular tiles that adorn the roofs of historical buildings in the Orient, utilizing 3D point clouds. The workflow integrates a robust segmentation algorithm utilizing the maximum principal curvature and normal vectors. Moreover, clustering algorithms, including DBSCAN, are incorporated to refine the clusters and thus increase segmentation accuracy. Structural analysis is enabled by cylindrical model fitting, which allows for the estimation of parameters and residuals. While the results exhibit commendable performance in individual tile segmentation, it is imperative to address the impact of substantial variations in scanning range and incident angles before engaging in the structural analysis fitting process. The results of experiment demonstrate that under conditions of significantly large scanning angles, the root mean square error (RMSE) for inadequately fitted tiles can extend to 0.066 m, surpassing twice the RMSE observed for well-fitted tiles. The proposed workflow proves to be applicable and exhibits significant potential to advance practices in cultural heritage documentation. [ABSTRACT FROM AUTHOR]

Planar feature segmentation is an essential task for 3D point cloud processing, finding many applications in various fields such as robotics and computer vision. The Random Sample Consensus (RANSAC) is one of the most common algorithms for the segmentation, but its performance, as given by the original form, is usually limited due to the use of a single threshold and interruption of similar planar features presented close to each other. To address these issues, we present a novel point cloud processing workflow which aims at developing an initial segmentation stage before the basic RANSAC is performed. Initially, normal vectors and maximum principal curvatures for each point of a given point cloud are analyzed and integrated. Subsequently, a subset of normal vectors and curvature is utilized to cluster planes with similar geometry based on the region growing algorithm, serving as a coarse but fast segmentation process. The segmentation is therefore refined with the RANSAC algorithm which can be now performed with higher accuracy and speed due to the reduced interference. After the RANSAC process is applied, resultant planar point clouds are built from the sparse ones via a point aggregation process based on geometric constraints. Four datasets (three real and one simulated) were used to verify the method. Compared to the classic segmentation method, our method achieves higher accuracy, with an RMSE from fitting equal to 0.0521 m, along with a higher recall of 93.31% and a higher F1-score of 95.38%. [ABSTRACT FROM AUTHOR]

Ephedra sinica Stapf is an important traditional medicinal plant. However, in recent years, due to climate change and human activities, its habitat area and distribution area have been decreasing sharply. In order to provide better protection for E. sinica, it is necessary to study the historical and future potential zoning of E. sinica. The maximum entropy model (MaxEnt) was used to simulate the potential geographical distribution patterns of E. sinica under historical and future climatic conditions simulated using two Shared Socio-economic Pathways. The main results were also analyzed using the jackknife method and ArcGIS. The results showed that: (1) the potential suitable distribution area of E. sinica in China is about 29.18 × 105 km2—high-suitable areas, medium-suitable areas, and low-suitable areas cover 6.38 × 105 km2, 8.62 × 105 km2, 14.18 × 105 km2, respectively—and E. sinica is mainly distributed in Inner Mongolia; (2) precipitation and temperature contribute more to the distribution of E. sinica; (3) under two kinds of SSPs, the total suitable area of E. sinica increased significantly, but the differences between 2021–2040, 2041–2060, 2061–2080, and 2081–2100 are not obvious; (4) the barycentre of E. sinica moves from the historical position to its southwest. The results show that E. sinica can easily adapt to future climates well, and its ecological value will become more important. This study provides scientific guidance for the protection, management, renewal and maintenance of E. sinica. [ABSTRACT FROM AUTHOR]

This paper describes a simple microfluidic sorting system that can perform size profiling and continuous mass-dependent separation of particles through combined use of gravity (1 g) and hydrodynamic flows capable of rapidly amplifying sedimentation-based separation between particles. Operation of the device relies on two microfluidic transport processes: (i) initial hydrodynamic focusing of particles in a microchannel oriented parallel to gravity and (ii) subsequent sample separation where positional difference between particles with different mass generated by sedimentation is further amplified by hydrodynamic flows whose streamlines gradually widen out due to the geometry of a widening microchannel oriented perpendicular to gravity. The microfluidic sorting device was fabricated in poly(dimethylsiloxane), and hydrodynamic flows in microchannels were driven by gravity without using external pumps. We conducted theoretical and experimental studies on fluid dynamic characteristics of laminar flows in widening microchannels and hydrodynamic amplification of particle separation. Direct trajectory monitoring, collection, and postanalysis of separated particles were performed using polystyrene microbeads with different sizes to demonstrate rapid (< 1 min) and high-purity (>99.9%) separation. Finally, we demonstrated biomedical applications of our system by isolating small-sized (diameter

Molecular biomarkers can be used as objective indicators of pathologic processes. Although their levels often change over time, their measurement is often constrained to a single time point. Cumulative biomarker exposure would provide a fundamentally different kind of measurement to what is available in the clinic. Magnetic resonance relaxometry can be used to noninvasively monitor changes in the relaxation properties of antibody-coated magnetic particles when they aggregate upon exposure to a biomarker of interest. We used implantable devices containing such sensors to continuously profile changes in three clinically relevant cardiac biomarkers at physiological levels for up to 72 h. Sensor response differed between experimental and control groups in a mouse model of myocardial infarction and correlated with infarct size. Our prototype for a biomarker monitoring device also detected doxorubicin-induced cardiotoxicity and can be adapted to detect other molecular biomarkers with a sensitivity as low as the pg/ml range. [ABSTRACT FROM AUTHOR]

We explore the use of magnetic relaxation sensors as an in vitroassay platform. Functionalized magnetic nanoparticles that exhibit transverse relaxation time (T2) changes with the introduction of an analyte have previously been used to detect proteins, antibodies, receptor ligands, peptides, nucleic acids, oligonucleotides, and other small molecules. The standard procedure for sensitizing particles towards specific targets is, however, time-consuming and cumbersome. We report here a new approach that exploits primary–secondary antibody binding for easily derivatizing particles against specific targets. The assay is shown to be quantitative and a multiplexed assay against three target analytes is demonstrated. [ABSTRACT FROM AUTHOR]

Micro-scale technologies have already dramatically changed our society through their use in the microelectronics and telecommunications industries. Today these engineering tools are also useful for many biological applications ranging from drug delivery to DNA sequencing, since they can be used to fabricate small features at a low cost and in a reproducible manner. The discovery and development of new biomaterials aid in the advancement of these micro-scale technologies, which in turn contribute to the engineering and generation of new, custom-designed biomaterials with desired properties. This review aims to present an overview of the merger of micro-scale technologies and biomaterials in two-dimensional (2D) surface patterning, device fabrication and three-dimensional (3D) tissue-engineering applications. [ABSTRACT FROM AUTHOR]