Three-dimensional object recognition

In the development of an object pattern recognition system, feature construction is always the problem issue. Due to the large amount of information contained in three dimensional (3D) objects, features extracted to efficiently and sufficiently represent 3D objects are difficult to obtain. Thus, current commercially available object recognition systems mostly emphasize the classification of two dimensional objects or patterns. This work presents a paradigm to develop a complete 3D object recognition system that uses simple and efficient features, and supports the integration of CAD/CAM models;In this research, several proposed algorithm for extracting features representing 3D objects are constructed based on the properties of the Radon transform. Two of these algorithms have been successfully implemented for manufacturing applications. The implemented systems use the artificial neural network as the classifier to learn features and to identify 3D objects. A statistical model has also been established based on the output node values of a perceptron neural network to predict the future misclassifications of features which have not been learned by the neural network in the training stage

Current therapy option for necrotizing enterocolitis: Practicalities and challenge

Necrotizing enterocolitis (NEC) is one of the most prevalent neonatal gastrointestinal disorders. Despite ongoing breakthroughs in its treatment and prevention, the incidence and mortality associated with NEC remain high. New therapeutic approaches, such as breast milk composition administration, stem cell therapy, immunotherapy, and fecal microbiota transplantation (FMT) have recently evolved the prevention and the treatment of NEC. This study investigated the most recent advances in NEC therapeutic approaches and discussed their applicability to bring new insight to NEC treatment

Gateroad protection mechanism and surrounding rock control for gob-side entry with slender pillar in deep and inclined extra-thick coal seams

The depth of coal mining in the central and eastern China is increasing, the ground pressure is high, the roadway deformation and burst risk is great. Gob-side entry with slender gate pillar (GESGP) is constantly adopted to improve surrounding rock environment. In order to grasp ground pressure behavior of the gob-side entry and develop targeted surrounding rock control measures, field observation and numerical simulation have been carried out against a case of GESGP of 3 m pillar in a ultra thick coal seam of a 800 m cover depth. The results show that: ① Fragmentation and deformation of surrounding rock on the coal pillar side are larger than the other side. Fragmentation and deformation of pillar at the gob side is larger than the other; Although the buried depth is great, the gob is settled and a large amount of overburden load is sustained by it, so the stress is sufficiently transferred to the deep rocks; ② The deformation of the gob-side entry is asymmetrical, the roof sags more on the pillar side than the other, pillar rib top and solid coal side rid middle are greater with deformation occurring mostly at shallow part; ③ Gob is the “escape” passage for entry deformation which is good for slow release of deformation energy and reduction of burst; ④ The range of the pressure relief area is expanded from triangle before excavation to parallelogram after excavation, also the location of the stress concentration area is shifted to the upper right of the entry; ⑤ Interface of the first/second shear failure planes on the pillar and the high stress zone on the upper right of the entry are the key targeted control zones. The surrounding rock control system was put forward that coal pillar reinforcement based on multiple plastic zone development cycles and precise destress of high stress zone. The research can provide research foundation and scientific basis for the adjacent panels and other similar deep and inclined extra-thick coal seams

N-myristoylation of Antimicrobial Peptide CM4 Enhances Its Anticancer Activity by Interacting With Cell Membrane and Targeting Mitochondria in Breast Cancer Cells

Development of antimicrobial peptides (AMPs) as highly effective and selective anticancer agents would represent great progress in cancer treatment. Here we show that myristoyl-CM4, a new synthetic analog generated by N-myristoylation of AMPs CM4, had anticancer activity against MCF-7, MDA-MB-231, MX-1 breast cancer cells (IC50 of 3–6 μM) and MDA-MB-231 xenograft tumors. The improved activity was attributed to the effect of myristoyl on the cell membrane. Flow cytometry and confocal laser scanning microscopy results showed that N-myristoylation significantly increased the membrane affinity toward breast cancer cells and also effectively mediated cellular entry. Despite increasing cytotoxicity against HEK293 and NIH3T3 cells and erythrocytes associated with its anticancer activity, myristoyl-CM4 maintained a certain selectivity toward breast cancer cells. Accordingly, the membrane affinity toward breast cancer cells was two to threefold higher than that of normal cells. Glycosylation analysis showed that sialic acid-containing oligosaccharides (including O-mucin and gangliosides) were important targets for myristoyl-CM4 binding to breast cancer cells. After internalization, co-localization analysis revealed that myristoyl-CM4 targeted mitochondria and induced mitochondrial dysfunction, including alterations in mitochondrial transmembrane potential, reactive oxygen species (ROS) generation and cytochrome c release. Activation of caspase 9, caspase 3 and cleavage of PARP were observed in MX-1, MCF-7, and MDA-MB-231 cells after myristoyl-CM4 treatment. The current work indicates that increasing hydrophobicity by myristoylation to modulate peptide-membrane interactions and then target mitochondria is a good strategy to develop AMPs as anticancer agents in the future

3 X 3 BASKETBALL

This dataset encompasses match sheet data from the FIBA 3x3 World Tour (only teams data), aimed at supporting quantitative research in the field of sports analytics.</p

Three-dimensional object recognition

In the development of an object pattern recognition system, feature construction is always the problem issue. Due to the large amount of information contained in three dimensional (3D) objects, features extracted to efficiently and sufficiently represent 3D objects are difficult to obtain. Thus, current commercially available object recognition systems mostly emphasize the classification of two dimensional objects or patterns. This work presents a paradigm to develop a complete 3D object recognition system that uses simple and efficient features, and supports the integration of CAD/CAM models;In this research, several proposed algorithm for extracting features representing 3D objects are constructed based on the properties of the Radon transform. Two of these algorithms have been successfully implemented for manufacturing applications. The implemented systems use the artificial neural network as the classifier to learn features and to identify 3D objects. A statistical model has also been established based on the output node values of a perceptron neural network to predict the future misclassifications of features which have not been learned by the neural network in the training stage.</p

Research and application of anchor cable support technology for whole coal roadway in isolated working face of extra-thick coal seam

It is the first time for Hebi No.9 mine to use the whole coal anchor cable support in 3204 upper coal roadway. However, the original support condition has large deformation, insufficient support strength and poor effect. Therefore, the roof support mode of 3204 lower coal roadway is studied and optimized. The plastic zone development, surrounding rock stress distribution and roof subsidence law of 3204 coal roadway under different roof anchor cable support are analyzed. After comprehensive on-site construction and support cost, it is determined that the anchor cable support is changed from “3-0-3” to “4-3-4”. After optimization, the deformation of 3204 lower coal roadway is significantly reduced. The optimization scheme is applied to the 4101 coal roadway on the working face of Hebi No. 3 mine. The field monitoring data shows that the maximum displacement of roof and floor is 129 mm, the maximum displacement of two sides is 140 mm, and the maximum displacement of roof separation is 20 mm

Structured SWNTs and Graphene for Solar Cells

We propose the concept of structured single-walled carbon nanotubes (SWNTs) for the applications of heterojunction solar cells and dye-sensitized solar cells (DSSCs). The structure of SWNTs was controlled and modified by a simple water vapor treatment, which was originally developed by our group. Compared with the graphene-Si solar cell and the SWNT-Si solar cell using the random-oriented SWNT film, the pristine micro-honeycomb structured SWNT-Si solar cell shows a significant improvement in terms of fill factor and the greater potential to obtain high power conversion efficiency (PCE). Moreover, the performance of the pristine micro-honeycomb structured SWNT-Si solar cells is stable in ambient condition. In addition, the PCE and fill factor of the DSSC with the micro-honeycomb structured SWNT counter electrode are 3.90 % and 0.61, respectively, which are comparable to those of the DSSC with Pt as the counter electrode. This result shows that the micro-honeycomb networked SWNTs provide a low-cost alternative to replace Pt in DSSCs

Bi-Kronecker Functional Decision Diagrams: A Novel Canonical Representation of Boolean Functions

In this paper, we present a novel data structure for compact representation and effective manipulations of Boolean functions, called Bi-Kronecker Functional Decision Diagrams (BKFDDs). BKFDDs integrate the classical expansions (the Shannon and Davio expansions) and their bi-versions. Thus, BKFDDs are the generalizations of existing decision diagrams: BDDs, FDDs, KFDDs and BBDDs. Interestingly, under certain conditions, it is sufficient to consider the above expansions (the classical expansions and their bi-versions). By imposing reduction and ordering rules, BKFDDs are compact and canonical forms of Boolean functions. The experimental results demonstrate that BKFDDs outperform other existing decision diagrams in terms of sizes