Estimation of net primary productivity of forests by modified CASA models and remotely sensed data

To increase the accuracy of predicting net primary productivity (NPP), in this study, Carnegie–Ames–Stanford Approach (CASA) model was modified by developing new methods to estimate absorbed photosynthetically active radiation or fraction of photosynthetically active radiation (FPAR) and water stress coefficient (WSC). In the modified model, FPAR was derived based on its non-linear relationship with leaf area index. Moreover, WSC was estimated using leaf water potential from soil moisture instead of a traditional evapotranspiration-based method. This study was conducted in Baiyun District area of Guangzhou, China, using Gaofen-1 (GF-1), Landsat 7, and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The predictions from the original and three modified CASA models and MODIS NPP product MOD17A3 were compared with field observations. The results showed that all the CASA-based models led to similar spatial distributions of forest aboveground NPP estimates. Overall, the estimates increased with elevation because the valley bottoms were dominated by developed or urbanized areas whereas the hillslopes and hilltops were largely vegetated. Based on root mean square error (RMSE) and relative RMSE between the observed and predicted values, the CASA model that integrated the modifications of both FPAR and WSC increased the estimation accuracy of NPP by 8.1% over the original one. The increase in accuracy was mainly contributed by the modification of FPAR. This suggested that the modification of FPAR provided greater potential than that of WSC for improving the predictions of CASA model. Compared to the CASA models, MOD17A3 had lower accuracy of aboveground NPP estimates. This study also showed that the fine spatial resolution GF-1 image provided a new source of data used to estimate NPP of forest ecosystems.     

SWATShare – A web platform for collaborative research and education through online sharing,simulation and visualization of SWAT models

Hydrologic models for a particular watershed or a region are created for addressing a specific research or management problem, and most of the models do not get reused after the project is completed. Similarly, multiple models may exist for a particular geographic location from different researchers or organizations. To avoid the duplication of efforts, and enable model reuse and enhancement through collaborative efforts, a prototype cyberinfrastructure, called SWATShare, is developed for sharing, execution and visualization of Soil and Water Assessment Tool (SWAT). The objective of this paper is to present the software architecture, functional capabilities and implementation of SWATShare as a collaborative environment for hydrology research and education using the models published and shared in the system. Besides the capability of publishing, sharing, discovery and downloading of SWAT models, some of the functions in SWATShare such as model calibration are supported by providing access to high performance computing resources including the XSEDE and cloud. Additionally, SWATShare can create dynamic spatial and temporal plots of model outputs at different scales. SWATShare can also be used as an educational tool within a classroom setting for comparing the hydrologic processes under different geographic and climatic settings. The utility of SWATShare for collaborative research and education is demonstrated by using three case studies. Even though this paper focuses on the SWAT model, the system’s architecture can be replicated for other models as well.     

Evaluation of two empirical wind erosion models in arid and semi-arid regions of China and the USA

Wind erosion models are important tools for assessing soil erodibility and identifying management practices to control erosion. The Agricultural Policy/Environmental eXtender (APEX) model and Revised Wind Erosion Equation (RWEQ) were tested using data collected from the Tarim Basin of China and Columbia Plateau of the United States of America. Adequate performance in simulating soil loss was achieved using the original APEX model and RWEQ in respectively a cotton field and desert-oasis ecotone in the Tarim Basin and winter wheat - summer fallow (WW-SF) field in the Columbia Plateau. We calibrated the APEX model and RWEQ to improve performance because both models have many empirical parameters. After calibration, both models adequately simulated soil loss from all land use types except the RWEQ from the red date orchard in the Tarim Basin. Inadequate performance of the calibrated RWEQ in the red date orchard was likely due to underestimating maximum mass transport.     

Parallel compressive sampling matching pursuit algorithm for compressed sensing signal reconstruction with OpenCL

Compressive sensing (CS) is a new signal processing method, which was developed recent years. CS can sample signals with a frequency far below the Nyquist frequency. CS can also compress the signals while sampling, which can reduce the usage of resources for signal transmission and storage. However, the reconstruction algorithm used in the corresponding decoder is highly complex and computationally expensive. Thus, in some specific applications, e.g., remote sensing image processing for disaster monitoring, the CS algorithm usually cannot satisfy the time requirements on traditional computing platforms. Various studies have shown that many-core computing platforms such as OpenCL are among the most promising platforms that are available for real-time processing because of their powerful floating-point computing capabilities. In this study, we present the design and implementation of parallel compressive sampling matching pursuit (CoSaMP), which is an OpenCL-based parallel CS reconstruction algorithm, as well as some optimization strategies, such as access efficiency, numerical merge, and instruction optimization. Based on experiments using remote sensing images with different sizes, we demonstrated that the proposed parallel algorithm can achieve speedups of about 41 times and 58 times on AMD HD7350 and NVIDIA K20Xm platforms, respectively, without modifying the application code.     

The new extension of TOPSIS method for multiple criteria decision making with hesitant Pythagorean fuzzy sets

Pythagorean fuzzy sets (PFSs) as a new generalization of fuzzy sets (FSs) can handle uncertain information more flexibly in the process of decision making. In our real life, we also may encounter a hesitant fuzzy environment. In view of the effective tool of hesitant fuzzy sets (HFSs) for expressing the hesitant situation, we introduce HFSs into PFSs and extend the existing research work of PFSs. Concretely speaking, this paper considers that the membership degree and the non-membership degree of PFSs are expressed as hesitant fuzzy elements. First, we propose a new concept of hesitant Pythagorean fuzzy sets (HPFSs) by combining PFSs with HFSs. It provides a new semantic interpretation for our evaluation. Meanwhile, the properties and the operators of HPFSs are studied in detail. For the sake of application, we focus on investigating the normalization method and the distance measures of HPFSs in advance. Then, we explore the application of HPFSs to multi-criteria decision making (MCDM) by employing the technique for order preference by similarity to ideal solution (TOPSIS) method. A new extension of TOPSIS method is further designed in the context of MCDM with HPFSs. Finally, an example of the energy project selection is presented to elaborate on the performance of our approach.     

Use of a sulfur waste for biosynthesis of cadmium sulfide quantum dots with Fusarium oxysporum f. sp. lycopersici

After hydrodesulfurization of Mexican oil's sour acid gases, a sulfur toxic waste is recovered, we used it to synthesize cadmium sulfide quantum dots, which have been recently studied due to their optical (high photostability, high quantum yield and fluorescence) and catalytic properties. Increased demand of cadmium sulfide quantum dots has led to research of new synthesis methods that with higher yields, increased control over particle diameter, that produce hydrophilic quantum dots -as most of them are obtained in organic solvents- and that are environmentally friendly because most methods employ toxic materials or involve a high energy consumption. This study attempted to synthesize hydrophilic cadmium sulfide quantum dots using an environmentally friendly method with a fungus capable of transforming a dangerous waste into a high-value-added product. Mycelia of Fusarium oxysporum f. sp. lycopersici were incubated with 1 mM cadmium nitrate and 1% (w/v) sulfur waste at 30 °C for 24 h, then the biomass was separated through paper filtration. The filtrate became yellow indicating presence of extracellular cadmium sulfide quantum dots, as was confirmed by increased UV–vis absorption around 300 nm and fluorescence at 510 nm. The biomass of Fusarium oxysporum f. sp. lycopersici produced after 24 h, extracellular stable, hydrophilic and biocompatible cadmium sulfide quantum dots from a sulfur dangerous waste. Biosynthesized quantum dots were circular with diameter of 6.116±2.111 nm and had a wurtzite crystalline structure.     

Unsteady velocity profiling in bores and positive surges

In an open channel, steady flow conditions may be achieved when the discharge and boundary conditions remain constant for a reasonable period of time. The operation of any regulation device (e.g. gate) is associated with some unsteady surge motion. In the present study, new velocity profiling measurements were performed systematically under controlled flow conditions. Both steady and unsteady measurements were conducted in a relatively large laboratory facility. An ensemble-averaged technique was applied in unsteady flows to investigate positive surges. The experiments were repeated 25 (or 50) times for each controlled flow condition and the results were ensemble-averaged. The quality and accuracy of the Profiler data set were validated against data collected with an acoustic Doppler velocimeter, in both steady and unsteady rapidly-varied flows. A careful sensitivity analysis was conducted to test the appropriate number of runs. The results indicated that the selection of 25 runs was suitable for ensemble-averaging in rapidly-varied unsteady flows. Some instrumental error was observed however with the velocity profiler. Outside the boundary layer, the Profiler tended to produce errors in terms time-averaged velocity data and velocity fluctuations for a number of points in a profile. Overall, the study demonstrated that the propagation of positive surges is a highly unsteady turbulent process, and the performance of ADV Vectrino II Profiler in such an unsteady turbulent flow was satisfactory, provided that a careful validation was undertaken for all Profiler outputs.     

Tailoring the grain size of zirconia polycrystalline fibers by cetyltrimethyl ammonium bromide

In the study, cetyltrimethyl ammonium bromide (CTAB) has been found to have a significant effect on the grain size of zirconia (ZrO₂) polycrystalline fibers from a precursor of polyacetylacetonatozirconium (PAZ). A relation between the variation in the grain size of the fibers sintered at 1000 °C for 1 h and CTAB addition has been established by scanning electron microscopy (SEM) and matching the results by a Gaussian Function. The grain size increased firstly and then decreased at an elevated weight percent of CTAB with respect to PAZ. ZrO₂ nucleation at 500 °C and grain growth during thermal treatment between 500 and 1000 °C were investigated by thermal analysis (TG-DTA), X-ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD). The results indicate that the addition of CTAB accelerated the decomposition of PAZ. The enhanced decomposition promoted ZrO₂ nucleation and the removal of residual carbon. While excess CTAB resulted in the increase of residual carbon on grain surface. The general kinetics of the grain growth was evaluated by Arrhenius equation and the results did matched well with the variation in grain size.     

Rheological behavior of aqueous mullite-albumin-methylcellulose systems

In this work, the thermogelling behavior of aqueous mullite-bovine serum albumin (BSA) suspensions was studied by dynamic rheology in order to determine the experimental conditions that must be used to form mullite green bodies by thermal consolidation. Viscoelastic properties (G′ and G′′) as a function of temperature (30–95 °C) and time were determined by temperature sweep tests and time sweep tests, respectively. On the other hand, the influence of methylcellulose (MC) (2 wt%) as a binder on the viscoelastic properties of the aqueous mullite-protein system as a function of both experimental parameters (temperature and time) was also studied. In addition, shear flow properties of aqueous mullite (40 vol%; 0.45 wt% of polyacrylic polyelectrolyte as a dispersant)–BSA (10 and 15 vol%)-MC (2 wt%) suspensions were analyzed to obtain information on the rheological behavior of the suspensions at room temperature. The results obtained showed that the presence of mullite particles and MC changed the onset temperature of gelation of the protein and increased the gelation time. Thus, both the mullite particles and methylcellulose intervened in the formation of the developed protein gel.     

Improvement the electrochemical performance of Cr doped layered-spinel composite cathode material Li1.1Ni0.235Mn0.735Cr0.03O2.3 with Li4Ti5O12 coating

The Cr doped layered-spinel composite cathode material Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3 was synthesized and coated with different content of Li₄Ti₅O₁₂ by a sol–gel method. The materials were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The effect of Li₄Ti₅O₁₂ coatings on the electrochemical performance of the pristine material was evaluated from charge/discharge cycles, rate performance, and electrochemical impedance spectroscopy (EIS). The XRD results show that the lattice crystal and the content of spinel phase have been increased in the Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3 materials after Li₄Ti₅O₁₂ coating. The results from TEM and selected area electron diffraction (SAED) indicate that the Li₄Ti₅O₁₂ coating assumes a spinel structure on the Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3. The discharge capacities, cycling and rate performances of the Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3 materials in the first cycle are improved with the addition of Li₄Ti₅O₁₂. Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3 coated with 3 wt% Li₄Ti₅O₁₂ shows the highest discharge capacity (271.7 mA h g⁻¹), highest capacity retention (99.4% for 100 cycles), and best rate capability (132 mA h g⁻¹ at 10 C). EIS result indicates that the resistance of Li_1.1Ni_0.235Mn_0.735Cr_0.03O_2.3 electrode decreases with the addition of Li₄Ti₅O₁₂. The enhanced electrochemical performance can be ascribed to the increased spinel content, lower resistance and the enhanced lithium-ion diffusion kinetics.