Description: Accessing information efficiently is vital for animals to make the optimal decisions, and it is particularly important when they are facing predators. Yet until now, very few quantitative conclusions have been drawn about the information dynamics in the interaction between animals due to the lack of appropriate theoretic measures. Here, we employ transfer entropy (TE), a new information-theoretic and model-free measure, to explore the information dynamics in the interaction between a predator and a prey fish. We conduct experiments in which a predator and a prey fish are confined in separate parts of an arena, but can communicate with each other visually and tactilely. TE is calculated on the pair’s coarse-grained state of the trajectories. We find that the prey’s TE is generally significantly bigger than the predator’s during trials, which indicates that the dominant information is transmitted from predator to prey. We then demonstrate that the direction of information flow is irrelevant to the parameters used in the coarse-grained procedures. We further calculate the prey’s TE at different distances between it and the predator. The resulted figure shows that there is a high plateau in the mid-range of the distance and that drops quickly at both the near and the far ends. This result reflects that there is a sensitive space zone where the prey is highly vigilant of the predator’s position.

Description: Nitrogen is an essential nutrient element in crop photosynthesis and yield improvement. Thus, it is urgent and important to accurately estimate the leaf nitrogen contents (LNC) of crops for precision nitrogen management. Based on the correlation between LNC and reflectance spectra, the hyperspectral LiDAR (HSL) system can determine three-dimensional structural parameters and biochemical changes of crops. Thereby, HSL technology has been widely used to monitor the LNC of crops at leaf and canopy levels. In addition, the laser-induced fluorescence (LIF) of chlorophyll, related to the histological structure and physiological conditions of green plants, can also be utilized to detect nutrient stress in crops. In this study, four regression algorithms, support vector machines (SVMs), partial least squares (PLS) and two artificial neural networks (ANNs), back propagation NNs (BP-NNs) and radial basic function NNs (RBF-NNs), were selected to estimate rice LNC in booting and heading stages based on reflectance and LIF spectra. These four regression algorithms were used for 36 input variables, including the reflectance spectral variables on 32 wavelengths and four peaks of the LIF spectra. A feature weight algorithm was proposed to select different band combinations for the LNC retrieval models. The determination coefficient (R2) and the root mean square error (RMSE) of the retrieval models were utilized to compare their abilities of estimating the rice LNC. The experimental results demonstrate that (I) these four regression methods are useful for estimating rice LNC in the order of RBF-NNs > SVMs > BP-NNs > PLS; (II) The LIF data in two forms, including peaks and indices, display potential in rice LNC retrieval, especially when using the PLS regression (PLSR) model for the relationship of rice LNC with spectral variables. The feature weighting algorithm is an effective and necessary method to determine appropriate band combinations for rice LNC estimation.

Description: The effects of the liquid water content (LWC) and mixing ratio of hydrometeors in the simulation of convective precipitation in Wuhan, Hubei Province, China, are investigated using a three-dimensional convective rainstorm model. The microphysical processes of warm and cold clouds are considered into microphysical parameterization. The warm-cloud process is dominated by the combined effects of condensation and drop coalescence. The cold-cloud process is initiated mainly by production of graupel, and the microphysical parameterizations are used to predict the mixing ratio of cloud droplets, rain, ice crystals, snow, and graupel. The simulations results show that 80% rainfall is derived from warm cloud microphysical processes, and the rest is produced by cold cloud microphysical processes. The mixed phase microphysical process can invigorate the production of convective rainfall and enhance the liquid water content (LWC). In addition, the vertical distribution of LWC is mainly concentrated at the height isotherms of −10 to −20 °C in precipitation and the concentration area of LWC matches the distribution range of graupel particles. However, the growth of graupel particles depend on the microphysical processes of nucleation and propagation between rain and graupel particles (NUrg) and collision and coalescence between cloud droplets and graupel (CLcg), in which NUrg is a major source of graupel particles and the contribution of the process accounts for 77% of the amount of graupel particles.

Description: In this paper, we propose a new ground penetrating radar (GPR) imaging technique based on multi-scale weighted back projection (BP) processing. Firstly, the whole imaging region is discretized by large scale and low-resolution imaging result is obtained by using traditional BP imaging technique. Secondly, the potential targets regions (PTR) are delineated from low-resolution imaging result by using intensity detection method. In the PTR, small scale discretization is implemented and higher resolution imaging result is obtained by using weighted BP imaging technique. A weight factor is designed by analyzing the statistical characteristics of scattering data on the time-delay curve. The above “discretization-imaging-PTR delineation” processing continues until the imaging resolution reaches the specified requirement. In the multi-scale imaging result, the resolution in other regions is not as high as that in PTR. This algorithm can get higher resolution imaging results with much lower computation compared with traditional BP imaging algorithm. The simulation of this algorithm is processed and experimental results validate the feasibility of this method.

Description: The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

Description: Large amounts of leaching residue are released into tailings dams from mines, and their acid content can cause environmental pollution. The aim of this study was to research the feasibility and value of a leaching residue backfill recycling method. The combination of property detection, laboratory tests (the neutralization method, strength test and diffusivity test) and numerical simulation methods (3D computational fluid dynamics (CFD) simulations of pipeline transportation properties) were used to assess the performance of the leaching residue backfill. The results show that backfill body with the cement:sand mass ratio of 1:3, the leaching residue:classified tailings ratio of 1:6, and slurry mass concentration of 71 wt % can meet the strength and pipeline self-flowing transportation requirements of mine backfill. The leaching residue is a good backfill aggregate, and its recovery ratio can reach 19.5 wt %. In addition, the recycling of leaching residue effectively alleviates the problem of mine waste emissions and protects the ecological environment surrounding the mining area. This study serves as a guide for the recycling of fine tailings and the environmental governance of the mining area.

Description: Deep underground mines are highly energy consuming due to the need to overcome the growing airflow resistance. The multi-fan station ventilation system (MFSVS), formed by several parallel fans at different locations in an underground mine generally, has greatly reduced energy costs by using high-quantity and low-pressure energy-saving fans. However, experimental data still indicates that 30–70% of the fan pressure is used to overcome the severe shock losses in a parallel fan station (PFS), in spite of more than 80% operating efficiency, and the shock losses greatly weaken the superiority and the service capacity of PFS. Based on the investigation and measured data of several PFSs in a MFSVS in an underground mine, a three-dimensional PFS model was developed by computational fluid dynamics (CFD) to demonstrate airflow performance and variation characteristics of velocity, pressure and turbulence. First, the fan characteristic in the PFS was discussed and compared with the fan operating performance under standard conditions; the shock losses were then presented from both sides of the inlet shock losses and the outlet shock losses in the PFS; meanwhile, the effects of blade angle variation and airflow mutual interference were conducted to determine whether they exert a significant influence on the shock losses. The results show that the shock losses are primarily generated in the range of 0 to 3.0 m from the fans’ exits, due to the intensely change in air velocity in the PFS. The study also provides several directions and references for recovering air pressure and reducing energy consumption in the parallel fans’ structure.

Description: Sustainability, Vol. 10, Pages 1402: Collection and Remanufacturing of Waste Products under Patent Protection and Government Regulation Sustainability doi: 10.3390/su10051402 Authors: Dingyue Zhang Xuemei Zhang Bin Shi Jian Cao Gengui Zhou There is increasing academic and pragmatic interest in leveraging patent rights to invigorate remanufacturing for waste products under governmental interventions via regulations and reward–penalty instruments. In practice, many original manufacturers that are possessed with intellectual property rights allow third-party remanufacturers to implement reproducing operations through authorization and charging licensing fees. The general purpose of this paper is to explore favorable strategies for a closed-loop supply chain (CLSC) system of waste product collection and remanufacturing, in the context of either manufacturer-remanufacturing or remanufacturer-remanufacturing. To achieve such an objective, game theory is adopted to establish models of three collection and remanufacturing modes among channel members involving a manufacturer, a seller, and a remanufacturer. In so doing, the results show that a government’s allocations of elementary remanufacturing ratio and the unit amount of reward–penalty count significantly in CLSC operations, especially for the manufacturer, who acts as the leader in the system and makes mode selections.