On the numerical solution and dynamical laws of nonlinear fractional Schrödinger/Gross-Pitaevskii equations

International audienceThe purpose of this paper is to discuss some recent developments concerning the numerical simulation of space and time fractional Schrödinger and Gross-Pitaevskii equations. In particular, we address some questions related to the discretization of the models (order of accuracy and fast implementation) and clarify some of their dynamical properties. Some numerical simulations illustrate these points

Balancing Reinforcement Learning Training Experiences in Interactive Information Retrieval

Interactive Information Retrieval (IIR) and Reinforcement Learning (RL) share many commonalities, including an agent who learns while interacts, a long-term and complex goal, and an algorithm that explores and adapts. To successfully apply RL methods to IIR, one challenge is to obtain sufficient relevance labels to train the RL agents, which are infamously known as sample inefficient. However, in a text corpus annotated for a given query, it is not the relevant documents but the irrelevant documents that predominate. This would cause very unbalanced training experiences for the agent and prevent it from learning any policy that is effective. Our paper addresses this issue by using domain randomization to synthesize more relevant documents for the training. Our experimental results on the Text REtrieval Conference (TREC) Dynamic Domain (DD) 2017 Track show that the proposed method is able to boost an RL agent's learning effectiveness by 22\% in dealing with unseen situations.Comment: Accepted by SIGIR 202

Substitution of manure for chemical fertilizer affects soil microbial community diversity, structure and function in greenhouse vegetable production systems

Soil microbial communities and enzyme activities together affect various ecosystem functions of soils. Fertilization, an important agricultural management practice, is known to modify soil microbial characteristics; however, inconsistent results have been reported. The aim of this research was to make a comparative study of the effects of different nitrogen (N) fertilizer rates and types (organic and inorganic) on soil physicochemical properties, enzyme activities and microbial attributes in a greenhouse vegetable production (GVP) system of Tianjin, China. Results showed that manure substitution of chemical fertilizer, especially at a higher substitution rate, improved soil physicochemical properties (higher soil organic C (SOC) and nutrient (available N and P) contents; lower bulk densities), promoted microbial growth (higher total phospholipid fatty acids and microbial biomass C contents) and activity (higher soil hydrolase activities). Manure application induced a higher fungi/bacteria ratio due to a lower response in bacterial than fungal growth. Also, manure application greatly increased bacterial stress indices, as well as microbial communities and functional diversity. The principal component analysis showed that the impact of manure on microbial communities and enzyme activities were more significant than those of chemical fertilizer. Furthermore, redundancy analysis indicated that SOC and total N strongly influenced the microbial composition, while SOC and ammonium-N strongly influenced the microbial activity. In conclusion, manure substitution of inorganic fertilizer, especially at a higher substitution rate, was more efficient for improving soil quality and biological functions.</p

Mapping of QTL for Grain Yield Components Based on a DH Population in Maize

The elite maize hybrid Zhengdan 958 (ZD958), which has high and stable yield and extensive adaptability, is widely grown in China. To elucidate the genetic basis of yield and its related traits in this elite hybrid, a set of doubled haploid (DH) lines derived from ZD958 were evaluated in four different environments at two locations over two years, and a total of 49 quantitative trait loci (QTL) and 24 pairs of epistatic interactions related to yield and yield components were detected. Furthermore, 21 QTL for six investigated phenotypic traits were detected across two different sites. Combining the results of these QTL in each environment and across both sites, three main QTL hotspots were found in chromosomal bins 2.02, 2.05–2.06, and 6.05 between the simple sequence repeat (SSR) markers umc1165-bnlg1017, umc1065-umc1637, and nc012-bnlg345, respectively. The existence of three QTL hotspots associated with various traits across multiple environments could be explained by pleiotropic QTL or multiple tightly linked QTL. These genetic regions could provide targets for genetic improvement, fine mapping, and marker-assisted selection in future studies

Effects of Montmorillonite on the Mineralization and Cementing Properties of Microbiologically Induced Calcium Carbonate

Carbonate mineralization microbe is a microorganism capable of decomposing the substrate in the metabolic process to produce the carbonate, which then forms calcium carbonate with calcium ions. By taking advantage of this process, contaminative uranium tailings can transform to solid cement, where calcium carbonate plays the role of a binder. In this paper, we have studied the morphology of mineralized crystals by controlling the mineralization time and adding different concentrations of montmorillonite (MMT). At the same time, we also studied the effect of carbonate mineralized cementation uranium tailings by controlling the amount of MMT. The results showed that MMT can regulate the crystal morphology of calcium carbonate. What is more, MMT can balance the acidity and ions in the uranium tailings; it also can reduce the toxicity of uranium ions on microorganisms. In addition, MMT filling in the gap between the uranium tailings made the cement body more stable. When the amount of MMT is 6%, the maximum strength of the cement body reached 2.18 MPa, which increased by 47.66% compared with that the sample without MMT. Therefore, it is reasonable and feasible to use the MMT to regulate the biocalcium carbonate cemented uranium tailings

Who can help me? Understanding the antecedent and consequence of medical information seeking behavior in the era of bigdata

IntroductionThe advent of bigdata era fundamentally transformed the nature of medical information seeking and the traditional binary medical relationship. Weaving stress coping theory and information processing theory, we developed an integrative perspective on information seeking behavior and explored the antecedent and consequence of such behavior.MethodsData were collected from 573 women suffering from infertility who was seeking assisted reproductive technology treatment in China. We used AMOS 22.0 and the PROCESS macro in SPSS 25.0 software to test our model.ResultsOur findings demonstrated that patients’ satisfaction with information received from the physicians negatively predicted their behavior involvement in information seeking, such behavior positively related to their perceived information overload, and the latter negatively related to patient-physician relationship quality. Further findings showed that medical information seeking behavior and perceived information overload would serially mediate the impacts of satisfaction with information received from physicians on patient-physician relationship quality.DiscussionThis study extends knowledge of information seeking behavior by proposing an integrative model and expands the application of stress coping theory and information processing theory. Additionally, it provides valuable implications for patients, physicians and public health information service providers

Carbon in Chinese grasslands : meta-analysis and theory of grazing effects

Unidad de excelencia María de Maeztu CEX2019-000940-MGlobally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha−1) and typical steppes (3 to 4 sheep ha−1), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha−1) and alpine steppes (7 to 8 sheep ha−1) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the 'intermediate disturbance hypothesis'. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha−1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks