Efficient surface water flow simulation on static Cartesian grid with local refinement according to key topographic features

Aiming at improving the computational efficiency without accuracy losses for surface water flow simulation, this paper presents a structured but non-uniform grid system incorporated into a Godunov-type finite volume scheme. The proposed grid system can detect the key topographic features in the computational domain where high-resolution mesh is in need for reliably solving the shallow water equations. The mesh refinement is automatically carried out in these areas while the mesh in the rest of the domain remains coarse. The criterion determining the refinement is suggested by a dimensionless number with a fixed value of 0.2 after sensitivity analysis. Three laboratory and field-scale test cases are employed to demonstrate the performance of the model for flow simulations on the new non-uniform grids. In all of the tests, the grid system is shown to successfully generate high-resolution mesh only in those areas with abruptly changing topographic features that dominate the flooding processes. To produce numerical solutions of similar accuracy, the non-uniform grid based model is able to accelerate by about two times comparing with the fine uniform grid based counterpart

Organoaqueous calcium chloride electrolytes for capacitive charge storage in carbon nanotubes at sub-zero-temperatures

© The Royal Society of Chemistry. Solutions of calcium chloride in mixed water and formamide are excellent electrolytes for capacitive charge storage in partially oxidised carbon nanotubes at unprecedented sub-zero-temperatures (e.g. 67% capacitance retention at -60 °C)

Dietary Supplementation With Chinese Herbal Residues or Their Fermented Products Modifies the Colonic Microbiota, Bacterial Metabolites, and Expression of Genes Related to Colon Barrier Function in Weaned Piglets

To explore the feasibility of dietary Chinese herbal residue (CHR) supplementation in swine production with the objective of valorization, we examined the effects of dietary supplementation with CHR or fermented CHR products on the colonic ecosystem (i.e., microbiota composition, luminal bacterial metabolites, and expression of genes related to the intestinal barrier function in weaned piglets). We randomly assigned 120 piglets to one of four dietary treatment groups: a blank control group, CHR group (dose of supplement 4 kg/t), fermented CHR group (dose of supplement 4 kg/t), and a positive control group (supplemented with 0.04 kg/t virginiamycin, 0.2 kg/t colistin, and 3000 mg/kg zinc 0.04 kg/t virginiamycin, 0.2 kg/t colistin, and 3000 mg/kg zinc oxide). Our results indicate that dietary supplementation with CHR increased (P < 0.05) the mRNA level corresponding to E-cadherin compared with that observed in the other three groups, increased (P < 0.05) the mRNA level corresponding to zonula occludens-1, and decreased (P < 0.05) the quantity of Bifidobacterium spp. When compared with the blank control group. Dietary supplementation with fermented CHR decreased (P < 0.05) the concentration of indole when compared to the positive control group; increased (P < 0.05) the concentrations of short-chain fatty acids compared with the values measured in the CHR group, as well as the mRNA levels corresponding to interleukin 1 alpha, interleukin 2, and tumor necrosis factor alpha. However, supplementation with fermented CHR decreased (P < 0.05) interleukin 12 levels when compared with the blank control group. Collectively, these findings suggest that dietary supplementation with CHR or fermented CHR modifies the gut environment of weaned piglets

B, N Dual Doped Coral-Like Carbon Framework With Superior Pseudocapacitance and Surface Wettability

Carbon-based materials are usually considered as conventional electrode materials for supercapacitors (SCs), therefore it is meaningful to enhance supercapacitive capacity and cycling stability via rational surface structure design of carbon-based materials. The bio-inspired coral-like porous carbon structure has attracted much attention recently in that it can offer large surface area for ion accommodation and favor ions-diffusion, promoting its energy storage capacity. Herein, we designed a superiorly hydrophilic B, N dual doped coral-like carbon framework (BN-CCF) and studied its surface wettability via low-field nuclear magnetic resonance relaxation technique. The unique coral-like micro-nano structure and B, N dual doping in carbon framework can enhance its pseudocapacitance and improve surface wettability. Therefore, when used as electrodes of SCs, the BN-CCF displays 457.5 F g−1 at 0.5 A g−1, even when current density increases 20 folds, it still exhibits high capacitance retention of 66.1% and superior cycling stability. The symmetrical SCs assembled by BN-CCF electrodes show a high energy density of 14.92 Wh kg−1 (600 W kg−1). In this work, simple structural regulation with B, N dual doping and surface wettability should be considered as effective strategy to enhance energy storage capacity of carbon-based SCs

Distribution characteristics of available trace elements in soil from a reclaimed land in a mining area of north Shaanxi, China

Through field and laboratory tests we studied the temporal and spatial variation in the soil content of four available trace elements :copper(Cu), iron(Fe), manganese(Mn) and zinc (Zn), to analyze their distribution characteristics in reclaimed mining land under different reclamation conditions. The available trace elements content varied considerably with different land reclamation patterns. Extended reclamation time was helpful for the recovery of the available trace element content in the soil, and after more than eight years of soil reclamation, the content of available trace elements was closer to or greater than that in soil under natural conditions. Various treatment measures significantly influenced the content and distribution of available trace elements in the soil, and reasonable artificial treatments, including covering the soil and growing shrubs and herbaceous plants, increased the content of available trace elements

An Index System and Method for Soil Productivity Evaluation on the Hillside

Abstract: For a long time, soil productivity evaluation has been one of the hotspots in soil science. In this article, research conducted to investigate vertical root distribution characters, root drought-resistance ability, the soil physical and chemical properties and the local scioeconomical conditions is reported. Based on the principle of the AHP (Analytical Hierarchy Process), a new method is proposed to evaluate the Current Soil Productivity(CSP) and Natural Soil Productivity(NSP). Calculated results indicated that the NSP of Robinia pseudoacacia in two villages was above the middle level, while the NSP of Prunus armeniacia var. ansu Pinus tabulaeformis Platycladus orientalis was low. CSP of the Robinia pseudoacacia and Prunus armeniacia var. ansu was higher than the other two tree species. Although the NSP of the 4 tree species in the two villages was similar, the CSP results of the 4 tree species showed a remarkable change in the two villages studied. Further analysis indicated that the attitude and the recognition of the local people concerning problem associated with hillside development play an important role for the success of the hillside development program

How Will Rwandan Land Use/Land Cover Change under High Population Pressure and Changing Climate?

In recent decades, population growth and economic development have greatly influenced the pattern of land use/land cover (LULC) in Rwanda. Nevertheless, LULC patterns and their underlying change mechanisms under future climate conditions are not well known. Therefore, it is particularly important to explore the direction of LULC transfer in the study area, identify the factors driving the transfer of different types of LULC and their changes, and simulate future LULC patterns under future climate conditions. Based on LULC analyses of Rwanda in 1990, 2000, 2010, and 2015, the LULC pattern of Rwanda in the next 30 years was simulated using an LULC transition matrix, random forest sampling, the Markov chain model, and the PLUS model. The results showed that LULC change in the study area primarily comprised a decrease in forest area and expansion of cropland area, accompanied by a small increase in grassland area and an annual increase in urban land area. Prior to 2000, the LULC in Rwanda was mainly converted from forest and grassland to cropland, with the ratio being 0.72:0.28. After 2010, the LULC was mainly converted from forest to grassland and cropland, with the ratio being 0.83:0.17. Changes in forests, grasslands, and cropland are driven by multiple factors, whereas changes in wetlands, water, urban land, and unused land are more likely to be driven by a single factor. The existing trend of LULC change will continue for the next 30 years, and the future LULC pattern will exhibit a trend in which cropland area will increase in the west and grassland area will decrease, whereas grassland area will increase in the east and cropland area will decrease

Perspective and Development of Brain-Inspired Swarm Navigation

In recent years, intelligent unmanned systems such as drones, autonomous vehicles, and unmanned boats have played a significant role in various fields, including military, industrial and agricultural production, and logistics transportation. However, due to the limitations in resources and capabilities of individual intelligent unmanned systems, they are unable to meet the increasingly complex demands of real-world applications. it has become a trend to organize multiple intelligent unmanned systems into clusters to achieve collaborative work and swarm intelligence, of which swarm navigation and positioning is an important basis for swarm intelligence.Traditional satellite navigation systems are inadequate to meet the application requirements of intelligent unmanned systems in complex environments. Therefore, autonomous navigation of intelligent unmanned swarm systems has become an urgent problem to solve. Inspired by the neural mechanisms and principles of animal navigation systems and collective coordination, brain-inspired swarm navigation has emerged as a promising research field. It aims to achieve efficient and intelligent navigation in complex and unknown environments, fulfilling the navigation needs of intelligent unmanned systems operating in groups. This article provides an overview of the concept and mechanisms of brain-inspired swarm navigation. It explores the spatial neural mechanisms involved in brain-inspired swarm navigation, relevant simulation models, and swarm intelligence algorithms for brain-inspired swarm decision-making. Finally, the future directions of brain-inspired swarm navigation are discussed