Functionalization of a gold surface with DNA is often complicated by kinetic traps from unintended DNA base adsorption. Herein, we communicate that Br serves as a robust backfilling agent displacing selected DNA bases on gold. Traditional thiol backfillers are too strong, while even 300 mM Br is well tolerated. Conjugates prepared with Br hybridize 10-fold faster and resist DNA release with better colloidal stability yielding highly sensitive probes. From colorimetric and Raman assays, adsorption affinity ranks as F < T ≈ Cl < C < G ≈ Br < A < I, allowing Br to displace nonpoly-A sequences from gold. This well-controlled biointerface will impact biosensing, drug delivery, and directed assembly of nanomaterials.
The mobile laser scanning (MLS) technique has attracted considerable attention for providing high-density, high-accuracy, unstructured, three-dimensional (3D) geo-referenced point-cloud coverage of the road environment. Recently, there has been an increasing number of applications of MLS in the detection and extraction of urban objects. This paper presents a systematic review of existing MLS related literature. This paper consists of three parts. Part 1 presents a brief overview of the state-of-the-art commercial MLS systems. Part 2 provides a detailed analysis of on-road and off-road information inventory methods, including the detection and extraction of on-road objects (e.g., road surface, road markings, driving lines, and road crack) and off-road objects (e.g., pole-like objects and power lines). Part 3 presents a refined integrated analysis of challenges and future trends. Our review shows that MLS technology is well proven in urban object detection and extraction, since the improvement of hardware and software accelerate the efficiency and accuracy of data collection and processing. When compared to other review papers focusing on MLS applications, we review the state-of-the-art road object detection and extraction methods using MLS data and discuss their performance and applicability. The main contribution of this review demonstrates that the MLS systems are suitable for supporting road asset inventory, ITS-related applications, high-definition maps, and other highly accurate localization services.
Recently, the advancement of deep learning in discriminative feature learning from 3D LiDAR data has led to rapid development in the field of autonomous driving. However, automated processing uneven, unstructured, noisy, and massive 3D point clouds is a challenging and tedious task. In this paper, we provide a systematic review of existing compelling deep learning architectures applied in LiDAR point clouds, detailing for specific tasks in autonomous driving such as segmentation, detection, and classification. Although several published research papers focus on specific topics in computer vision for autonomous vehicles, to date, no general survey on deep learning applied in LiDAR point clouds for autonomous vehicles exists. Thus, the goal of this paper is to narrow the gap in this topic. More than 140 key contributions in the recent five years are summarized in this survey, including the milestone 3D deep architectures, the remarkable deep learning applications in 3D semantic segmentation, object detection, and classification; specific datasets, evaluation metrics, and the state of the art performance. Finally, we conclude the remaining challenges and future researches.
Since the initial discovery of ribozymes in the early 1980s, catalytic nucleic acids have been used in different areas. Compared with protein enzymes, catalytic nucleic acids are programmable in structure, easy to modify, and more stable especially for DNA. We take a historic view to summarize a few main interdisciplinary areas of research on nucleic acid enzymes that may have broader impacts. Early efforts on ribozymes in the 1980s have broken the notion that all enzymes are proteins, supplying new evidence for the RNA world hypothesis. In 1994, the first catalytic DNA (DNAzyme) was reported. Since 2000, the biosensor applications of DNAzymes have emerged and DNAzymes are particularly useful for detecting metal ions, a challenging task for enzymes and antibodies. Combined with nanotechnology, DNAzymes are key building elements for switches allowing dynamic control of materials assembly. The search for new DNAzymes and ribozymes is facilitated by developments in DNA sequencing and computational algorithms, further broadening our fundamental understanding of their biochemistry.
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