Automated Detection and Characterization of Cracks on Concrete using Laser Scanning

Accurate crack detection and characterization on concrete are essential for the maintenance, safety, and serviceability of various infrastructures. In this paper, an innovative approach was developed to automatically measure the cracks from 3D point clouds collected by a phase-shift terrestrial laser scanner (TLS) (FARO Focus3D S120). The approach integrates several techniques to characterize the cracks, which include the deviation on point normal determined using k-nearest neighbor (kNN) and principal components analysis (PCA) algorithms to identify the cracks, and principal axes and curve skeletons of cracks to determine the projected and real dimensions of cracks, respectively. The coordinate transformation was then performed to estimate the projected dimensions of cracks. Curve skeletons and cross sections of cracks were extracted to represent the real dimensions. Two cases of surface cracks were used to validate the developed approach. Because of the differences in definitions of the crack dimension in the three methods and due to the curve shape of the crack, the width and depth of cracks obtained from the cross-section method and manual measurement were close but slightly smaller than those measured by the projection algorithm; whereas the length of cracks determined by the curve-skeletons method was slightly larger than those obtained by the manual measurement and projection method. The real dimension of a crack has good agreements with real situations when compared with the results of the manual measurement and projection method

Strain prioritization and genome mining for enediyne natural products

The enediyne family of natural products has had a profound impact on modern chemistry, biology, and medicine, and yet only 11 enediynes have been structurally characterized to date. Here we report a genome survey of 3,400 actinomycetes, identifying 81 strains that harbor genes encoding the enediyne polyketide synthase cassettes that could be grouped into 28 distinct clades based on phylogenetic analysis. Genome sequencing of 31 representative strains confirmed that each clade harbors a distinct enediyne biosynthetic gene cluster. A genome neighborhood network allows prediction of new structural features and biosynthetic insights that could be exploited for enediyne discovery. We confirmed one clade as new C-1027 producers, with a significantly higher C-1027 titer than the original producer, and discovered a new family of enediyne natural products, the tiancimycins (TNMs), that exhibit potent cytotoxicity against a broad spectrum of cancer cell lines. Our results demonstrate the feasibility of rapid discovery of new enediynes from a large strain collection. IMPORTANCE Recent advances in microbial genomics clearly revealed that the biosynthetic potential of soil actinomycetes to produce enediynes is underappreciated. A great challenge is to develop innovative methods to discover new enediynes and produce them in sufficient quantities for chemical, biological, and clinical investigations. This work demonstrated the feasibility of rapid discovery of new enediynes from a large strain collection. The new C-1027 producers, with a significantly higher C-1027 titer than the original producer, will impact the practical supply of this important drug lead. The TNMs, with their extremely potent cytotoxicity against various cancer cells and their rapid and complete cancer cell killing characteristics, in comparison with the payloads used in FDA-approved antibody-drug conjugates (ADCs), are poised to be exploited as payload candidates for the next generation of anticancer ADCs. Follow-up studies on the other identified hits promise the discovery of new enediynes, radically expanding the chemical space for the enediyne family

Methylation of CYP1A1 and VKORC1 promoter associated with stable dosage of warfarin in Chinese patients

Objective To investigate the association between DNA methylation and the stable warfarin dose through genome-wide DNA methylation analysis and pyrosequencing assay. Method This study included 161 patients and genome-wide DNA methylation analysis was used to screen potential warfarin dose-associated CpGs through Illumina Infinium HumanMethylation 450 K BeadChip; then, the pyrosequencing assay was used to further validate the association between the stable warfarin dose and alterations in the methylation of the screened CpGs. GenomeStudio Software and R were used to analyze the differentially methylated CpGs. Results The methylation levels of CpGs surrounding the xenobiotic response element (XRE) within the CYP1A1 promoter, differed significantly between the different dose groups (P  0, P < 0.05) with an increase in the stable dose of warfarin. At the VKORC1 promoter, two CpGs methylation levels were significantly different between the differential dose groups (P < 0.05), and one CpG (Chr16: 31106793) presented a significant negative correlation (r <  0, P <  0.05) among different dose (low, medium, and high) groups. Conclusion This is a novel report of the methylation levels of six CpGs surrounding the XRE within the CYP1A1 promoter and one differential CpG at the VKORC1 promoter associated with stable warfarin dosage; these methylation levels might be applied as molecular signatures for warfarin

Onset of Tethered Chain Overcrowding

We proposed an approach to precisely control the density of tethered chains on solid substrates using PEO-b-PS and PLLA-b-PS. As the crystallization temperature T-x increased, the PEO or PLLA lamellar crystal thickness d(L) increased as well as the reduced tethering density (σ) over tilde of the PS chains. The onset of tethered PS chains overcrowding in solution occurs at (σ) over tilde*similar to3.7-3.8 as evidenced by an abrupt change in the slope between (d(L))(-1) and T-x. This results from the extra surface free energy created by the tethered chain that starts to affect the growth barrier of the crystalline blocks

Ultrafast and Sensitive Self-Powered Photodetector Featuring Self-Limited Depletion Region and Fully Depleted Channel with van der Waals Contacts

Self-powered photodetectors with great potential for implanted medical diagnosis and smart communications have been severely hindered by the difficulty of simultaneously achieving high sensitivity and fast response speed. Here, we report an ultrafast and highly sensitive self-powered photodetector based on two-dimensional (2D) InSe, which is achieved by applying a device architecture design and generating ideal Schottky or ohmic contacts on 2D layered semiconductors, which are difficult to realize in the conventional semiconductors owing to their surface Fermi-level pinning. The as-fabricated InSe photodiode features a maximal lateral self-limited depletion region and a vertical fully depleted channel. It exhibits a high detectivity of 1.26 × 1013 Jones and an ultrafast response speed of ∼200 ns, which breaks the response speed limit of reported self-powered photodetectors based on 2D semiconductors. The high sensitivity is achieved by an ultralow dark current noise generated from the robust van der Waals (vdW) Schottky junction and a high photoresponsivity due to the formation of a maximal lateral self-limited depletion region. The ultrafast response time is dominated by the fast carrier drift driven by a strong built-in electric field in the vertical fully depleted channel. This device architecture can help us to design high-performance photodetectors utilizing vdW layered semiconductors

Onset of tethered chain overcrowding

Physical Review Letters, 93(2): pp. 028301-1 -- 028301-4. Retrieved September 19, 2006 from http://www.materials.drexel.edu/SRG/chrisli.html. DOI: http://dx.doi.org/10.1103/PhysRevLett.93.028301We proposed an approach to precisely control the density of tethered chains on solid substrates using PEO-b-PS and PLLA-b-PS. As the crystallization temperature T-x increased, the PEO or PLLA lamellar crystal thickness d(L) increased as well as the reduced tethering density (σ) over tilde of the PS chains. The onset of tethered PS chains overcrowding in solution occurs at (σ) over tilde*similar to3.7-3.8 as evidenced by an abrupt change in the slope between (d(L))(-1) and T-x. This results from the extra surface free energy created by the tethered chain that starts to affect the growth barrier of the crystalline blocks

A Finite Element Variational Multiscale Method Based on Two Local Gauss Integrations for Stationary Conduction-Convection Problems

A new finite element variational multiscale (VMS) method based on two local Gauss integrations is proposed and analyzed for the stationary conduction-convection problems. The valuable feature of our method is that the action of stabilization operators can be performed locally at the element level with minimal additional cost. The theory analysis shows that our method is stable and has a good precision. Finally, the numerical test agrees completely with the theoretical expectations and the “ exact solution,” which show that our method is highly efficient for the stationary conduction-convection problems

Investigation of the Temperature Actions of Bridge Cables Based on Long-Term Measurement and the Gradient Boosted Regression Trees Method

Cable-stayed bridges have been commonly used on high-speed railways. The design, construction, and maintenance of cable-stayed bridges necessitate an accurate assessment of the cable temperature field. However, the temperature fields of cables have not been well established. Therefore, this research aims to investigate the distribution of the temperature field, the time variability of temperatures, and the representative value of temperature actions in stayed cables. A cable segment experiment, spanning over one year, is conducted near the bridge site. Based on the monitoring temperatures and meteorological data, the distribution of the temperature field is studied, and the time variability of cable temperatures is investigated. The findings show that the temperature distribution is generally uniform along the cross-section without a significant temperature gradient, while the amplitudes of the annual cycle variation and daily cycle variation in temperatures are significant. To accurately determine the temperature deformation of a cable, it is necessary to consider both the daily temperature fluctuations and the annual cycle of uniform temperatures. Then, using the gradient boosted regression trees method, the relationship between the cable temperature and multiple environmental variables is explored, and representative cable uniform temperatures for design are obtained by the extreme value analysis. The presented data and results provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges

Patent Automatic Classification Based on Symmetric Hierarchical Convolution Neural Network

With the rapid growth of patent applications, it has become an urgent problem to automatically classify the accepted patent application documents accurately and quickly. Most previous patent automatic classification studies are based on feature engineering and traditional machine learning methods like SVM, and some even rely on the knowledge of domain experts, hence they suffer from low accuracy problem and have poor generalization ability. In this paper, we propose a patent automatic classification method via the symmetric hierarchical convolution neural network (CNN) named PAC-HCNN. We use the title and abstract of the patent as the input data, and then apply the word embedding technique to segment and vectorize the input data. Then we design a symmetric hierarchical CNN framework to classify the patents based on the word embeddings, which is much more efficient than traditional RNN models dealing with texts, meanwhile keeping the history and future information of the input sequence. We also add gated linear units (GLUs) and residual connection to help realize the deep CNN. Additionally, we equip our model with a self attention mechanism to address the long-term dependency problem. Experiments are performed on large-scale datasets for Chinese short text patent classification. Experimental results prove our proposed model&rsquo;s effectiveness, and it performs better than other state-of-the-art models significantly and consistently on both fine-grained and coarse-grained classification