Spatio-temporal characteristics and determinants of anthropogenic nitrogen and phosphorus inputs in an ecologically fragile karst basin: Environmental responses and management strategies

Excessive nitrogen and phosphorus inputs to land and subsequent export to water via runoff leads to aquatic ecosystem deterioration. The WRB is the world’s largest karst basin which is characterized by a fragile ecosystem coupling with high population pressure, and the transformation of intensive agriculture. Quantifying different sources of pollution in karst regions is challenging due to the complexity of landscape topography and geology coupled with high transmissivity and connectivity of subsurface hydrological systems. This results in large uncertainty associated with nitrogen (N) and phosphorus (P) flow pathways. This combination of factors contributes to the WRB being a high priority for quantitatively understanding the contribution of regional nutrient inputs and those of other major water quality determinants. Here we applied the latest statistical data (2000–2018) and simple quasi-mass-balance methods of net anthropogenic nitrogen and phosphorus inputs (NANI and NAPI) to estimate spatio-temporal heterogeneity of N and P inputs. The results show that while NANI and NAPI are first decreasing, this is followed by an increasing trend during 2000–2018, with average values of 11262.06 ± 2732 kg N km− 2 yr−1 and 2653.91 ± 863 kg P km−2 yr−1 respectively. High N and P concentrations in the river drainage network are related to the spatial distribution of excessive inputs of N and P. Rapid urbanization, livestock farming and the conflicts between economic development and lagged-environmental management are the main reasons for the incremental regional N and P inputs. Management decisions on nutrient pollution in karst regions need careful consideration to reduce ecological impacts and contamination of karst aquifers. This study provides new insight for policy and decision making in the WRB, highlighting policy options for managing nutrient inputs and providing recommendations for closing the science-policy divide

The Ratio and Concentration of Two Monoterpenes Mediate Fecundity of the Pinewood Nematode and Growth of Its Associated Fungi

The pinewood nematode (PWN) Bursaphelenchus xylophilus, vectored primarily by the sawyer beetle, Monochamus alternatus, is an important invasive pest and causal agent of pine wilt disease of Chinese Masson pine, Pinus massoniana. Previous work demonstrated that the ratios and concentrations of α-pinene∶β-pinene differed between healthy trees and those trees containing blue-stain fungus (and M. alternatus pupae). However, the potential influence of the altered monoterpene ratios and concentrations on PWN and associated fungi remained unknown. Our current results show that low concentrations of the monoterpenes within petri dishes reduced PWN propagation, whereas the highest concentration of the monoterpenes increased PWN propagation. The propagation rate of PWN treated with the monoterpene ratio representative of blue-stain infected pine (α-pinene∶β-pinene = 1∶0.8, 137.6 mg/ml) was significantly higher than that (α-pinene∶β-pinene = 1∶0.1, 137.6 mg/ml) representative of healthy pines or those damaged by M. alternatus feeding, but without blue stain. Furthermore, inhibition of mycelial growth of associated fungi increased with the concentration of the monoterpenes α-pinene and β-pinene. Additionally, higher levels of β-pinene (α-pinene∶β-pinene = 1∶0.8) resulted in greater inhibition of the growth of the associated fungi Sporothrix sp.2 and Ophiostoma ips strains, but had no significant effects on the growth of Sporothrix sp.1, which is the best food resource for PWN. These results suggest that host monoterpenes generally reduce the reproduction of PWN. However, PWN utilizes high monoterpene concentrations and native blue-stain fungus Sporothrix sp.1 to improve its own propagation and overcome host resistance, which may provide clues to understanding the ecological mechanisms of PWN's successful invasion

Unsupervised Anomaly Detection for Intermittent Sequences Based on Multi-Granularity Abnormal Pattern Mining

In the actual maintenance of manufacturing enterprises, abnormal changes in after-sale parts demand data often make the inventory strategies unreasonable. Due to the intermittent and small-scale characteristics of demand sequences, it is difficult to accurately identify the anomalies in such sequences using current anomaly detection algorithms. To solve this problem, this paper proposes an unsupervised anomaly detection method for intermittent time series. First, a new abnormal fluctuation similarity matrix is built by calculating the squared coefficient of variation and the maximum information coefficient from the macroscopic granularity. The abnormal fluctuation sequence can then be adaptively screened by using agglomerative hierarchical clustering. Second, the demand change feature and interval feature of the abnormal sequence are constructed and fed into the support vector data description model to perform hypersphere training. Then, the unsupervised abnormal point location detection is realized at the micro-granularity level from the abnormal sequence. Comparative experiments are carried out on the actual demand data of after-sale parts of two large manufacturing enterprises. The results show that, compared with the current representative anomaly detection methods, the proposed approach can effectively identify the abnormal fluctuation position in the intermittent sequence of small samples, and also obtain better detection results

Approximate message passing detector based upon probability sorting for large-scale GSM systems

Large-scale generalized spatialmodulation(GSM) technology has great potential in constructing low-complexity massive multiple-input multiple-output wireless systems, with a simplified structure which employs only a fewradio frequency (RF) chains. However, detection is a very complex problem for large-scale GSM systems. In this correspondence paper, we have proposed an innovative probability sorting based approximate message passing (PS-AMP) detector. Specifically, in the proposed scheme, an approximate message passing method is used to obtain the probability for activation of each transmit antenna, and a method based upon probability sorting is developed to ascertain the signal search space. Simulation results demonstrate that the proposed PS-AMP detector exhibits a better bit error rate performance with a reduced complexity compared to its conventional counterparts

Improving Cycling Stability of the Lithium Anode by a Spin-Coated High-Purity Li(3)PS(4) Artificial SEI Layer

International audienceControlling the composition and microstructure of the solid electrolyte interphase (SEI) layer is critical to improving the cycling stability of the high-energy-density lithium-metal electrode. It is a quite tricky task to control the properties of the SEI layer which is conventionally formed by the chemical reactions between a Li metal and the additives. Herein, we develop a new route to synthesize a lithium-compatible sol of the sulfide electrolyte Li(3)PS(4), so that a Li(3)PS(4) artificial SEI layer with a controllable nanoscale thickness and high phase purity can be prepared by spin-coating. The layer stabilizes the lithium/electrolyte interface by homogenizing the Li-ion flux, preventing the parasitic reactions, and alleviating concentration polarization. Consequently, a symmetrical cell with the Li(3)PS(4)-modified lithium electrodes can achieve stable lithium plating/stripping for 800 h at a current density of 1 mA cm(-2). The Li-S batteries assembled with the Li(3)PS(4)-protected Li anodes show better capacity retention than their bare Li counterparts, whose average decay rate from the 240th cycle to the 800th cycle is only 0.004%/cycle. In addition, the Li(3)PS(4) layer improves the rate capacity of the batteries, significantly enhancing the capacity from 175 to 682 mA h g(-1) at a 2 C rate. The spin-coated Li(3)PS(4) artificial SEI layer provides a new strategy to develop high-performance Li metal batteries

AI-Based Modeling and Monitoring Techniques for Future Intelligent Elastic Optical Networks

With the development of 5G technology, high definition video and internet of things, the capacity demand for optical networks has been increasing dramatically. To fulfill the capacity demand, low-margin optical network is attracting attentions. Therefore, planning tools with higher accuracy are needed and accurate models for quality of transmission (QoT) and impairments are the key elements to achieve this. Moreover, since the margin is low, maintaining the reliability of the optical network is also essential and optical performance monitoring (OPM) is desired. With OPM, controllers can adapt the configuration of the physical layer and detect anomalies. However, considering the heterogeneity of the modern optical network, it is difficult to build such accurate modeling and monitoring tools using traditional analytical methods. Fortunately, data-driven artificial intelligence (AI) provides a promising path. In this paper, we firstly discuss the requirements for adopting AI approaches in optical networks. Then, we review various recent progress of AI-based QoT/impairments modeling and monitoring schemes. We categorize these proposed methods by their functions and summarize advantages and challenges of adopting AI methods for these tasks. We discuss the problems remained for deploying AI-based methods to a practical system and present some possible directions for future investigation

Electrochemical processes in all-solid-state Li-S batteries studied by electrochemical impedance spectroscopy

International audienceUnderstanding the electrochemical processes in all-solid-state lithium‑sulfur batteries is essential for designing high-performance devices. Here, the evolution of the electrochemical impedance spectra of an all-solid-state lithium‑sulfur battery during one charge/discharge cycle was quantitatively investigated with a reasonably established equivalent circuit. The impedance spectra could be decomposed into several parts as follows: the bulk resistance of solid electrolyte and current collector at highest frequency, three semicircles from high to low frequency corresponding to the dynamic processes at different interfaces and a 45° straight line followed by an inclined small tail at low frequency. It is found that the middle frequency semicircle, corresponding to charge transfer at the cathode, varied obviously during the charge/discharge cycle. Moreover, the 45° straight line, which is attributed to the Li diffusion in the cathode material LixS based on qualitative analysis, dominates the impedance spectra, revealing that the main kinetics-limiting factor is the Li diffusion in the active materials. Finally, an electrochemical model of the battery is proposed which provides insight for the designing of high-performance all-solid-state lithium‑sulfur batteries

A stable electrolyte interface with Li3PS4@Li7P3S11 for high-performance solid/liquid Li-S battery

International audienceThe solid/liquid Li-S battery shows promise in solving both the polysulfide "shuttle effect" in liquid batteries and the interfacial contact in all-solid-state batteries. However, increasing the interfacial stability of the electrolyte and the solid electrolyte remains a challenge in the solid/liquid batteries. In this work, a high ionic conductivity Li3PS4 solution is synthesized using a nano-Li2S precursor, which is then utilized to form a solid electrolyte Li3PS4@Li7P3S11 via dip-coating. The Li3PS4@Li7P3S11 can form a dense protective interface Li3PS4-DME with the DOL/DME and DME electrolyte. This interface can prevent direct contact between the solid electrolyte and the electrolytes, efficiently inhibiting further solid electrolyte decomposition. The lithium symmetric battery with the solid electrolyte Li3PS4@Li7P3S11 is cycled stably for 1000 h, at a current density of 0.38 mA cm-2 and a capacity of 1.51 mA h cm-2. The Li-S battery with the solid electrolyte Li3PS4@Li7P3S11 can cycle stably for 300 cycles at 0.2C with a capacity of 600 mA h g- 1 remaining