The improvement of digital image classification over an urban area: A probabilistic relaxation approach

Digital image classification is a technique to extract land cover information from imagery using certain classification schemes. Additional information, either in a map, digital or verbal format, from multi-sources other than satellite imagery can be integrated into a classification scheme to improve its performance. The research in this field is essential because data interpretation has long been a weak link between the functions of two powerful systems: data acquisition by the remote sensing system and data storage, renewal and retrieval by the geographic information system - that has been more and more involved in the geographical research with the development of new concepts and technology. Statistical models are flexible in incorporating information from multi-sources into a classification procedure to extract land cover information from satellite data. When a statistical model is applied to the urban scene, however, it is difficult to incorporate any spatial and ancillary information into the classification procedure because of their unpredictable nature in an urban scene and the difficulty in defining them into a meaningful format for a machine. In this thesis, the probabilistic relaxation model is used with Landsat TM data of the Omaha metropolitan area. The purpose of this approach is to improve the overall classification accuracy from a Gaussian Maximum Likelihood (GML) classifier by incorporating the contextual information contained in the neighborhood of a central pixel into the classification procedure. Prior to classification, ten land cover types determined visually from the image were combined into six classes by comparing their relative positions in a 6-dimensional classification space. After the the completion of GML classification on the original image data, the relaxation model is applied to adjust the class membership probabilities; after each adjustment, the classified map is compared with the reference map to assess the improvement of overall classification accuracy. This process is continued until the maximum accuracy is obtained. The error pattern during the iteration is analyzed and it is found that most error pixels occur at the boundaries between classes or they are located inside the dominant classes as individual parcels. Part of these errors have been corrected through the continuous adjustment of probabilities by iteration. The rationale of all statistical models used in this study and their mathematical meanings are reviewed in this thesis. It is concluded from the actual operation of the relaxation procedure on the Landsat TM imagery of the Omaha metropolitan area that the spectral separability checking has minimized the spectral ambiguity and the relaxation model has reduced much of the identity ambiguity. The result from this combined effort is the increase of overall classification accuracy from 77.01% of the original GML classification to 88.49% after the 13th relaxation iteration. The successful operation of the procedure has shown that it has a potential to be used in a computer-assisted land use monitoring system for the purpose of resource management

Polymorphisms of STAT-6, STAT-4 and IFN-γ genes and the risk of asthma in Chinese population

SummaryBackgroundAsthma is a complex disease resulting from multiple gene–gene and gene–environment interactions. Study on gene–gene interactions could provide insight into the pathophysiologic mechanisms of the disease.ObjectivesWe investigated the single nucleotide polymorphisms and interactions among three different loci in three candidate genes (STAT-6 G2964A, STAT-4 T90089C and IFN-γ T874A) in 95 Chinese asthmatic subjects and 95 matched controls to determine the possible associations with asthma.MethodsGenotyping of the gene polymorphisms was performed by means of PCR-SSCP analysis. Genotype–phenotype associations were examined in dominant and recessive genetic models using logistic regression. The method of multifactor dimensionality reduction was used to analyze gene–gene interactions.ResultsNo statistically significant difference was found in the distribution of the STAT-6 G2964A polymorphisms between asthmatic patients and controls in this case–control study. The STAT-4 T90089C polymorphisms were significantly associated with asthma in the dominant model (p=0.007). As for the IFN-γ T874A, the significant associations were found in both dominant model (p=0.004) and recessive model (p=0.006). A significant gene–gene interaction was found among STAT-6, STAT-4 and IFN-γ on the risk of asthma. In the best 3-locus model, the odds ratio for the high-risk to the low-risk group was 6.9 (95% CI, 3.5–13.7; p<0.0001).ConclusionsOur findings suggest that STAT-4 T90089C and IFN-γ T874A polymorphisms might be the genetic factors for the risk of asthma in the Chinese population. In addition, the significant interactions among STAT-6 G2964A, STAT-4 T90089C and IFN-γ T874A may increase an individual's susceptibility and contribute to the pathogenesis of asthma

Limit Equilibrium Method-Based Shear Strength Prediction for Corroded Reinforced Concrete Beam with Inclined Bars

Shear strength is a widely investigated parameter for reinforced concrete structures. The corrosion of reinforcement results in shear strength reduction. Corrosion has become one of the main deterioration factors in reinforced concrete beam. This paper proposes a shear strength model for beams with inclined bars based on a limit equilibrium method. The proposed model can be applied to both corroded and uncorroded reinforced concrete beams. Besides the tensile strength of longitudinal steel bars, the shear capacity provided by the concrete on the top of the diagonal crack, the tensile force of the shear steel at the diagonal crack, the degradation of the cross-sectional area and strength of the reinforcements induced by corrosion are all considered. An experimental work on two groups accelerated corroded beams was performed. Good agreements were found between the proposed theoretical predictions and experimental observations

Limit Equilibrium Method-Based Shear Strength Prediction for Corroded Reinforced Concrete Beam with Inclined Bars

Shear strength is a widely investigated parameter for reinforced concrete structures. The corrosion of reinforcement results in shear strength reduction. Corrosion has become one of the main deterioration factors in reinforced concrete beam. This paper proposes a shear strength model for beams with inclined bars based on a limit equilibrium method. The proposed model can be applied to both corroded and uncorroded reinforced concrete beams. Besides the tensile strength of longitudinal steel bars, the shear capacity provided by the concrete on the top of the diagonal crack, the tensile force of the shear steel at the diagonal crack, the degradation of the cross-sectional area and strength of the reinforcements induced by corrosion are all considered. An experimental work on two groups accelerated corroded beams was performed. Good agreements were found between the proposed theoretical predictions and experimental observations

3D Printing of Auxetic Shape-Memory Metamaterial Towards Designable Buckling

Poisson’s ratios of shape-memory auxetic metamaterial was experimentally investigated. Based on the generalized Maxwell model and finite-element method, the buckling behaviors and their main influence factors were studied. The analytical results and experimental ones showed a good agreement. Thermomechanical properties of the printed metamaterials govern the temperature and strain rate-dependent buckling, and a controllable transition from the negative to positive Poisson’s ratio in the metamaterials can be achieved. Based on the shape memory effect, the buckled state and the Poisson’s ratio of the metamaterials can be tuned by programmed thermomechanical processes. This study provides a simple and efficient way to generate morphing structures using the designable buckling effect

Identification of the Conformational transition pathway in PIP2 Opening Kir Channels

The gating of Kir channels depends critically on phosphatidylinositol 4,5-bisphosphate (PIP2), but the detailed mechanism by which PIP2 regulates Kir channels remains obscure. Here, we performed a series of Targeted molecular dynamics simulations on the full-length Kir2.1 channel and, for the first time, were able to achieve the transition from the closed to the open state. Our data show that with the upward motion of the cytoplasmic domain (CTD) the structure of the C-Linker changes from a loop to a helix. The twisting of the C-linker triggers the rotation of the CTD, which induces a small downward movement of the CTD and an upward motion of the slide helix toward the membrane that pulls the inner helix gate open. At the same time, the rotation of the CTD breaks the interaction between the CD- and G-loops thus releasing the G-loop. The G-loop then bounces away from the CD-loop, which leads to the opening of the G-loop gate and the full opening of the pore. We identified a series of interaction networks, between the N-terminus, CD loop, C linker and G loop one by one, which exquisitely regulates the global conformational changes during the opening of Kir channels by PIP2