On the use of the l(2)-norm for texture analysis of polarimetric SAR data

In this paper, the use of the l2-norm, or Span, of the scattering vectors is suggested for texture analysis of polarimetric synthetic aperture radar (SAR) data, with the benefits that we need neither an analysis of the polarimetric channels separately nor a filtering of the data to analyze the statistics. Based on the product model, the distribution of the l2-norm is studied. Closed expressions of the probability density functions under the assumptions of several texture distributions are provided. To utilize the statistical properties of the l2-norm, quantities including normalized moments and log-cumulants are derived, along with corresponding estimators and estimation variances. Results on both simulated and real SAR data show that the use of statistics based on the l2-norm brings advantages in several aspects with respect to the normalized intensity moments and matrix variate log-cumulants.Peer ReviewedPostprint (published version

Statistical modeling of polarimetric SAR data: a survey and challenges

Knowledge of the exact statistical properties of the signal plays an important role in the applications of Polarimetric Synthetic Aperture Radar (PolSAR) data. In the last three decades, a considerable research effort has been devoted to finding accurate statistical models for PolSAR data, and a number of distributions have been proposed. In order to see the differences of various models and to make a comparison among them, a survey is provided in this paper. Texture models, which could capture the non-Gaussian behavior observed in high resolution data, and yet keep a compact mathematical form, are mainly explained. Probability density functions for the single look data and the multilook data are reviewed, as well as the advantages and applicable context of those models. As a summary, challenges in the area of statistical analysis of PolSAR data are also discussed.Peer ReviewedPostprint (published version

Higher order statistics for texture analysis and physical interpretation of polarimetric SAR data

The logarithmic cumulants (log-cumulants for short) of the second and third orders are widely used in the statistical analysis of polarimetric synthetic aperture radar (PolSAR) data. However, both the product model and the finite mixture model may produce the same values of these statistics, which means that the use of these log-cumulants is not enough to determine the statistical model of the data. In this letter, it is demonstrated that the log-cumulants of higher orders can help to distinguish the concept of texture from that of mixture, providing a physical insight into the data statistics. A tool called log-cumulant cube, which helps to visualize this difference, is proposed by considering texture distributions from the Pearson's family. Results on both simulated and real SAR data show that the use of higher order statistics is useful when it comes to the texture analysis of PolSAR data.Peer ReviewedPostprint (author's final draft

Hydrogen Supply Infrastructure Network Planning Approach towards Chicken-egg Conundrum

In the early commercialization stage of hydrogen fuel cell vehicles (HFCVs), reasonable hydrogen supply infrastructure (HSI) planning decisions is a premise for promoting the popularization of HFCVs. However, there is a strong causality between HFCVs and hydrogen refueling stations (HRSs): the planning decisions of HRSs could affect the hydrogen refueling demand of HFCVs, and the growth of demand would in turn stimulate the further investment in HRSs, which is also known as the ``chicken and egg'' conundrum. Meanwhile, the hydrogen demand is uncertain with insufficient prior knowledge, and thus there is a decision-dependent uncertainty (DDU) in the planning issue. This poses great challenges to solving the optimization problem. To this end, this work establishes a multi-network HSI planning model coordinating hydrogen, power, and transportation networks. Then, to reflect the causal relationship between HFCVs and HRSs effectively without sufficient historical data, a distributionally robust optimization framework with decision-dependent uncertainty is developed. The uncertainty of hydrogen demand is modeled as a Wasserstein ambiguity set with a decision-dependent empirical probability distribution. Subsequently, to reduce the computational complexity caused by the introduction of a large number of scenarios and high-dimensional nonlinear constraints, we developed an improved distribution shaping method and techniques of scenario and variable reduction to derive the solvable form with less computing burden. Finally, the simulation results demonstrate that this method can reduce costs by at least 10.4% compared with traditional methods and will be more effective in large-scale HSI planning issues. Further, we put forward effective suggestions for the policymakers and investors to formulate relevant policies and decisions

Comparative genomics reveals intraspecific divergence of Acidithiobacillus ferrooxidans: insights from evolutionary adaptation

Acidithiobacillus ferrooxidans serves as a model chemolithoautotrophic organism in extremely acidic environments, which has attracted much attention due to its unique metabolism and strong adaptability. However, little was known about the divergences along the evolutionary process based on whole genomes. Herein, we isolated six strains of A. ferrooxidans from mining areas in China and Zambia, and used comparative genomics to investigate the intra-species divergences. The results indicated that A. ferrooxidans diverged into three groups from a common ancestor, and the pan-genome is ‘open’. The ancestral reconstruction of A. ferrooxidans indicated that genome sizes experienced a trend of increase in the very earliest days before a decreasing tendency during the evolutionary process, suggesting that both gene gain and gene loss played crucial roles in A. ferrooxidans genome flexibility. Meanwhile, 23 single-copy orthologous groups (OGs) were under positive selection. The differences of rusticyanin (Rus) sequences (the key protein in the iron oxidation pathway) and type IV secretion system (T4SS) composition in the A. ferrooxidans were both related to their group divergences, which contributed to their intraspecific diversity. This study improved our understanding of the divergent evolution and environmental adaptation of A. ferrooxidans at the genome level in extreme conditions, which provided theoretical support for the survival mechanism of living creatures at the extreme

Serum CHI3L1 as a biomarker of interstitial lung disease in rheumatoid arthritis

BackgroundInterstitial lung disease (ILD) is a relatively prevalent extra-articular manifestation of rheumatoid arthritis (RA) and contributes to significant morbidity and mortality. This study aimed to analyze the association between chitinase-3 like-protein-1(CHI3L1) and the presence of RA-ILD.MethodsA total of 239 RA patients fulfilling the American Rheumatism Association (ACR) 1987 revised criteria were enrolled and subclassified as RA-ILD and RA-nILD based on the results of high-resolution computed tomography scans (HRCT) of the chest. The disease activity of RA was assessed by Disease Activity Score for 28 joints (DAS28) and categorized as high, moderate, low, and remission. Chemiluminescence immunoassays were applied to determine the serum levels of CHI3L1. Univariate analysis was performed and the receiver operating characteristics (ROC) curves were plotted to evaluate the correlation between RA-ILD and CHI3L1.ResultsAmong the eligible RA patients studied, 60 (25.1%) patients were diagnosed with RA-ILD. Compared with RA-nILD, RA patients with ILD had significantly higher median age (median [IQR], 68.00 [62.00-71.75] vs 53.00 [40.00-63.00], p<0.001) and a higher proportion of males (21 (35.0%) vs 30 (16.8%), p=0.003). Notably, differences in DAS28 scores between the two groups were not observed. The serum level of CHI3L1 was significantly higher in RA-ILD patients (median [IQR], 69.69 [44.51-128.66] ng/ml vs 32.19 [21.63-56.99] ng/ml, p<0.001). Furthermore, the areas under the curve (AUC) of CHI3L1 attained 0.74 (95% confidence interval [CI], 0.68-0.81, p<0.001) in terms of identifying patients with RA-ILD from those without ILD. Similar trends were seen across the spectrum of disease activity based on DAS28-ESR.ConclusionOur findings of elevated serum CHI3L1 levels in RA-ILD patients suggest its possible role as a biomarker to detect RA-ILD noninvasively

Reduced expression of N-Myc downstream-regulated gene 2 in human thyroid cancer

<p>Abstract</p> <p>Background</p> <p><it>NDRG</it>2 (N-Myc downstream-regulated gene 2) was initially cloned in our laboratory. Previous results have shown that <it>NDRG</it>2 expressed differentially in normal and cancer tissues. Specifically, <it>NDRG</it>2 mRNA was down-regulated or undetectable in several human cancers, and over-expression of <it>NDRG</it>2 inhibited the proliferation of cancer cells. <it>NDRG</it>2 also exerts important functions in cell differentiation and tumor suppression. However, it remains unclear whether <it>NDRG</it>2 participates in carcinogenesis of the thyroid.</p> <p>Methods</p> <p>In this study, we investigated the expression profile of human <it>NDRG</it>2 in thyroid adenomas and carcinomas, by examining tissues from individuals with thyroid adenomas (n = 40) and carcinomas (n = 35), along with corresponding normal tissues. Immunohistochemistry, quantitative RT-PCR and western blot methods were utilized to determine both the protein and mRNA expression status of Ndrg2 and c-Myc.</p> <p>Results</p> <p>The immunostaining analysis revealed a decrease of Ndrg2 expression in thyroid carcinomas. When comparing adenomas or carcinomas with adjacent normal tissue from the same individual, the mRNA expression level of <it>NDRG</it>2 was significantly decreased in thyroid carcinoma tissues, while there was little difference in adenoma tissues. This differential expression was confirmed at the protein level by western blotting. However, there were no significant correlations of <it>NDRG</it>2 expression with gender, age, different histotypes of thyroid cancers or distant metastases.</p> <p>Conclusion</p> <p>Our data indicates that <it>NDRG</it>2 may participate in thyroid carcinogenesis. This finding provides novel insight into the important role of <it>NDRG2 </it>in the development of thyroid carcinomas. Future studies are needed to address whether the down-regulation of <it>NDRG</it>2 is a cause or a consequence of the progression from a normal thyroid to a carcinoma.</p

Texture analysis and physical interpretation of polarimetric SAR data

This thesis is dedicated to the study of texture analysis and physical interpretation of PolSAR data. As the starting point, a complete survey of the statistical models for PolSAR data is conducted. All the models are classified into three categories: Gaussian distributions, texture models, and finite mixture models. The texture models, which assume that the randomness of the SAR data is due to two unrelated factors, texture and speckle, are the main subject of this study. The PDFs of the scattering vector and the sample covariance matrix in different models are reviewed. Since many models have been proposed, how to choose the most accurate one for a test data is a big challenge. Methods which analyze different polarimetric channels separately or require a filtering of the data are limited in many cases, especially when it comes to high resolution data. In this thesis, the L2-norms of the scattering vectors are studied, and they are found to be advantageous to extract statistical information from PolSAR data. Statistics based on the L2-norms can be utilized to determine what distribution the data actually follow. A number of models are suggested to model the texture of PolSAR data, and some are very complex. But most of them lack a physical explanation. The random walk model, which can be interpreted as a discrete analog of the SAR data focusing process, is studied with the objective to understand the data statistics from the point of view of scattering process. A simulator based on the random walk model is developed, where different variations in the scatterer types and scatterer numbers are considered. It builds a bridge between the mathematical models and underlying physical mechanisms. It is found that both the mixture and the texture could give the same statistics such as log-cumulants of the second order and the third order. The two concepts, texture and mixture, represent two quite different scenarios. A further study was carried on to see if it is possible to distinguish them. And higher order statistics are demonstrated to be favorable in this task. They can be physically interpreted to distinguish the scattering from a single type of target from a mixture of targets.Esta tesis está dedicada al estudio del análisis de texturas y de la interpretación física de datos PolSAR. Como punto de partida, se ha llevado a cabo un estudio completo de los modelos estadísticos para datos PolSAR. Todos los modelos se han clasificado en tres categorías: distribuciónes gaussianas, modelos de textura y modelos de mezcla finita. Los modelos de textura, que asumen que la aleatoriedad de los datos SAR se debe a dos factores no relacionados, la textura y el speckle, son el tema principal de este estudio. Las distribuciones del vector de dispersión y de la matriz de covarianza en diferentes modelos son revisados. Debido a que se han propuesto muchos modelos, cómo elegir el más preciso para unos datos en particular es un gran reto. Los métodos que analizan diferentes canales polarimétricos por separado o requieren de un filtrado de los datos presentan limitacions en muchos casos, especialmente cuando se trata de datos de alta resolución. En esta tesis, la norma L2 de los vectores de dispersión se estudian, demostrando su utilidad para extraer información estadística de los datos PolSAR. Las estadísticas basadas en la norma L2 se pueden utilizar para determinar la distribución de los datos. En la literatura, se sugieren una serie de modelos para modelar la textura de los datos PolSAR, siendo alguno de ellos muy complejos. Sin embargo, la mayoría de ellos carecen de una explicación física. El modelo de random walk, que se puede interpretar como un análogo discreto del proceso de enfocado de los datos SAR, se estudia con el objetivo de comprender las estadísticas de los datos desde el punto de vista de proceso de dispersión. Se desarrolla un simulador basado en el modelo de random walk, donde se consideran diversas variaciones en los tipos de dispersores y número de dispersores. Se construye un puente entre los modelos matemáticos y mecanismos físicos subyacentes. Se encontró que tanto la mezcla como la textura podrían dar las mismas estadísticas, tales como log-cumulantes de segundo orden y tercer orden. Los dos conceptos, la textura y la mezcla, representan dos escenarios muy diferentes. Se realizó un estudio adicional para ver si es posible distinguirlos, demostrando que las estadísticas de orden superior son favorables en esta tarea. Pueden interpretarse físicamente para distinguir la dispersión a partir de un solo tipo de blanco de una mezcla de blancos