A deep-neural-network-based hybrid method for semi-supervised classification of polarimetric SAR data

This paper proposes a deep-neural-network-based semi-supervised method for polarimetric synthetic aperture radar (PolSAR) data classification. The proposed method focuses on achieving a well-trained deep neural network (DNN) when the amount of the labeled samples is limited. In the proposed method, the probability vectors, where each entry indicates the probability of a sample associated with a category, are first evaluated for the unlabeled samples, leading to an augmented training set. With this augmented training set, the parameters in the DNN are learned by solving the optimization problem, where the log-likelihood cost function and the class probability vectors are used. To alleviate the “salt-and-pepper” appearance in the classification results of PolSAR images, the spatial interdependencies are incorporated by introducing a Markov random field (MRF) prior in the prediction step. The experimental results on two realistic PolSAR images demonstrate that the proposed method effectively incorporates the spatial interdependencies and achieves the good classification accuracy with a limited number of labeled samples

Pumping tests in nonuniform aquifers: The radially asymmetric case

This is the published version. Copyright American Geophysical UnionAn analytical solution for the case of transient, pumping-induced drawdown in a nonuniform aquifer is presented. The nonuniform aquifer is conceptualized as a uniform matrix into which a disk of anomalous properties has been placed. The disk can be arbitrarily located with respect to the pumping well. This solution can be used to develop considerable insight concerning the nature of drawdown in nonuniform systems. Changes in drawdown are sensitive to the hydraulic properties of a discrete portion of an aquifer for a time of limited duration. After that time, it is virtually impossible to gain further information about those properties. The volume of the aquifer controlling a given increment of drawdown at an observation well increases greatly as the distance between the pumping and observation well increases. At observation wells located at moderate to large distances from the pumping well, this volume is so large that the effect of spatial variations in flow properties may be negligible. In general, drawdown data from wells located at a distance from the pumping well should nicely fit the ideal models of the well hydraulics literature. When combined with previous work, these results demonstrate that constant rate pumping tests are not an effective tool for characterizing lateral variations in flow properties

The roles of environmental variation and spatial distance in explaining diversity and biogeography of soil denitrifying communities in remote Tibetan wetlands

The relative importance of local environments and dispersal limitation in shaping denitrifier community structure remains elusive. Here, we collected soils from 36 riverine, lacustrine and palustrine wetland sites on the remote Tibetan Plateau and characterized the soil denitrifier communities using high-throughput amplicon sequencing of the nirS and nirK genes. Results showed that the richness of nirS-type denitrifiers in riverine wetlands was significantly higher than that in lacustrine wetlands but not significantly different from that in palustrine wetlands. There was no clear distinction in nir community composition among the three kinds of wetlands. Irrespective of wetland type, the soil denitrification rate was positively related to the abundance, but not the α-diversity, of denitrifying communities. Soil moisture, carbon availability and soil temperature were the main determinants of diversity [operational taxonomic unit (OTU) number] and abundance of thenirS-type denitrifier community, while water total organic carbon, soil NO3- and soil moisture were important in controlling nirK-type denitrifier diversity and abundance. The nirS community composition was influenced by water electrical conductivity, soil temperature and water depth, while the nirK community composition was affected by soil electrical conductivity. Spatial distance explained more variation in the nirS community composition than in the nirK community composition. Our findings highlight the importance of both environmental filtering and spatial distance in explaining diversity and biogeography of soil nir communities in remote and relatively undisturbed wetlands.</p

Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment

As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches

Gastroprotective and ulcer healing properties of ethanol extract of Alpinia conchigera rhizome in experimentally induced gastric ulcer in rats

Purpose: To investigate the gastroprotective effect of Alpinia conchigera rhizome in an ulcer rat model. Method: Sprague-Dawley rats were treated with ethanol extract of Alpinia conchigera at doses of 75 and 150 mg/kg body weight. After 28 days, the rats were sacrificed. Ulcer index, total acidity, pH, hemoglobin levels, and hemorrhagic lesions were determined through macroscopic assessment and histopathological examination. The levels of lipid peroxidation (LPO), superoxide dismutase (SOD), and catalase (CAT), and inflammatory markers (TNF-α, IL-1β, and IL-6) were also determined. Results: Alpinia conchigera significantly reduced ulcer index, total acidity, pH and hemoglobin levels (p &lt; 0.05). Results from histology revealed that the extract protected the mucosa from lesions. Moreover, the extract significantly enhanced gastric mucosal activities of SOD and CAT, and decreased LPO levels and plasma concentrations of TNF-α, IL-1β, and IL-6 (p &lt; 0.05). Conclusion: These results validate the traditional claims on the gastroprotective effects of Alpinia conchigera as revealed through its antioxidant and ulcer-healing properties by stimulation of important cellular mechanisms

Semi-supervised classification of polarimetric SAR images using Markov random field and two-level Wishart mixture model

In this work, we propose a semi-supervised method for classification of polarimetric synthetic aperture radar (PolSAR) images. In the proposed method, a 2-level mixture model is constructed by associating each component density with a unique Wishart mixture model (instead of a single Wishart distribution as that in the conventional Wishart mixture model). This modeling scheme facilitates the accurate description of data for the categories, each of which includes multiple subcategories. The learning algorithm for the proposed model is developed based on variational inference and all the update equations are obtained in closed form. In the learning algorithm, the spatial interdependencies are incorporated by imposing a Markov random field prior on the indicator variable to alleviate the speckle effect on the classification results. The experimental results demonstrate the improved performance of the proposed method compared with the unsupervised version and supervised version of the proposed model as well as an existing method for semi-supervised classification

Slug tests in partially penetrating wells

This is the published version. Copyright American Geophysical UnionA semianalytical solution is presented to a mathematical model describing the flow of groundwater in response to a slug test in a confined or unconfined porous formation. The model incorporates the effects of partial penetration, anisotropy, finiteradius well skins, and upper and lower boundaries of either a constant-head or an impermeable form. This model is employed to investigate the error that is introduced into hydraulic conductivity estimates through use of currently accepted practices (i.e., Hvorslev, 1951; Cooper et al., 1967) for the analysis of slug-test response data. The magnitude of the error arising in a variety of commonly faced field configurations is the basis for practical guidelines for the analysis of slug-test data that can be utilized by field practitioners