High-power mid-infrared femtosecond master oscillator power amplifier Er:ZBLAN fiber laser system

High-power femtosecond mid-infrared (MIR) lasers are of vast importance to both fundamental research and applications. We report a high-power femtosecond master oscillator power amplifier laser system consisting of a single-mode Er:ZBLAN fiber mode-locked oscillator and pre-amplifier followed by a large-mode-area Er:ZBLAN fiber main amplifier. The main amplifier is actively cooled and bidirectionally pumped at 976 nm, generating a slope efficiency of 26.9%. Pulses of 8.12 W, 148 fs at 2.8 μm with a repetition rate of 69.65 MHz are achieved. To the best of our knowledge, this is the highest average power ever achieved from a femtosecond MIR laser source. Such a compact ultrafast laser system is promising for a wide range of applications, such as medical surgery and material processing

Trichinella spiralis Infection Mitigates Collagen-Induced Arthritis via Programmed Death 1-Mediated Immunomodulation

Helminth infection induces Th2-biased immune responses and inhibitory/regulatory pathways that minimize excessive inflammation to facilitate the chronic infection of helminth in the host and in the meantime, prevent host hypersensitivity from autoimmune or atopic diseases. However, the detailed molecular mechanisms behind modulation on inflammatory diseases are yet to be clarified. Programmed death 1 (PD-1) is one of the important inhibitory receptors involved in the balance of host immune responses during chronic infection. Here, we used the murine model to examine the role of PD-1 in CD4+ T cells in the effects of Trichinella spiralis infection on collagen-induced arthritis (CIA). Mice infected with T. spiralis demonstrated higher expression of PD-1 in the spleen CD4+ T cells than those without infection. Mice infected with T. spiralis 2 weeks prior to being immunized with type II collagen displayed lower arthritis incidence and significantly attenuated pathology of CIA compared with those of uninfected mice. The therapeutic effect of T. spiralis infection on CIA was reversed by blocking PD-1 with anti-PD-1 antibody, associated with enhanced Th1/Th17 pro-inflammatory responses and reduced Th2 responses. The role of PD-1 in regulating CD4+ T cell differentiation and proliferation during T. spiralis infection was further examined in PD-1 knockout (PD-1−/−) C57BL/6 J mice. Interestingly, T. spiralis-induced alteration of attenuated Th1 and enhanced Th2/regulatory T cell differentiation in wild-type (WT) mice was effectively diminished in PD-1−/− mice characterized by recovered Th1 cytokine levels, reduced levels of Th2 and regulatory cytokines and CD4+CD25+Foxp3+ cells. Moreover, T. spiralis-induced CD4+ T cell proliferation suppression in WT mice was partially restored in PD-1−/− mice. This study introduces the first evidence that PD-1 plays a critical role in helminth infection-attenuated CIA in a mouse model by regulating the CD4+ T cell function, which may provide the new insights into the mechanisms of helminth-induced immunomodulation of host autoimmunity

Wet and Dry Atmospheric Depositions of Inorganic Nitrogen during Plant Growing Season in the Coastal Zone of Yellow River Delta

The ecological problems caused by dry and wet deposition of atmospheric nitrogen have been widespread concern in the world. In this study, wet and dry atmospheric depositions were monitored in plant growing season in the coastal zone of the Yellow River Delta (YRD) using automatic sampling equipment. The results showed that SO42- and Na+ were the predominant anion and cation, respectively, in both wet and dry atmospheric depositions. The total atmospheric nitrogen deposition was ~2264.24 mg m−2, in which dry atmospheric nitrogen deposition was about 32.02%. The highest values of dry and wet atmospheric nitrogen deposition appeared in May and August, respectively. In the studied area, NO3-–N was the main nitrogen form in dry deposition, while the predominant nitrogen in wet atmospheric deposition was NH4+–N with ~56.51% of total wet atmospheric nitrogen deposition. The average monthly attribution rate of atmospheric deposition of NO3-–N and NH4+–N was ~31.38% and ~20.50% for the contents of NO3-–N and NH4+–N in 0–10 cm soil layer, respectively, suggested that the atmospheric nitrogen was one of main sources for soil nitrogen in coastal zone of the YRD

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

Simulation and verification for seed-filling performance of cell wheel precision seed metering device based on discrete element method

The cell wheel seed metering device was improved and a stirring seed-filling device was added to improve the seed-filling performance of cell wheel pseudo-ginseng precision seed metering devices. Using pseudo-ginseng seeds in Wenshan Prefecture, Yunnan Province as the objects for seed metering, the software application EDEM was adopted based on the discrete element method for the simulation calculation and analysis of the seed-filling performance of the seed metering device under 4 rotational speeds of the cell wheel and 6 rotational speeds of the stir wheel. The simulation results indicate that the filling ratio increases as the rotational speed of the stir wheel increases under a constant rotational speed of the cell wheel. Test verification of the simulation analysis results was conducted on the test bed of the seed metering device. The results indicate that increasing the rotational speed of the stir wheel can obtain a filling ratio of over 90%. The test results display a similar variation trend to that of the simulation analysis with an error of average filling ratio less than 5%. Therefore, it is feasible to analyze the seed-filling performance of the stirring and seed-filling device of the seed metering device with the discrete element method

Simulation and verification for seed-filling performance of cell wheel precision seed metering device based on discrete element method

The cell wheel seed metering device was improved and a stirring seed-filling device was added to improve the seed-filling performance of cell wheel pseudo-ginseng precision seed metering devices. Using pseudo-ginseng seeds in Wenshan Prefecture, Yunnan Province as the objects for seed metering, the software application EDEM was adopted based on the discrete element method for the simulation calculation and analysis of the seed-filling performance of the seed metering device under 4 rotational speeds of the cell wheel and 6 rotational speeds of the stir wheel. The simulation results indicate that the filling ratio increases as the rotational speed of the stir wheel increases under a constant rotational speed of the cell wheel. Test verification of the simulation analysis results was conducted on the test bed of the seed metering device. The results indicate that increasing the rotational speed of the stir wheel can obtain a filling ratio of over 90%. The test results display a similar variation trend to that of the simulation analysis with an error of average filling ratio less than 5%. Therefore, it is feasible to analyze the seed-filling performance of the stirring and seed-filling device of the seed metering device with the discrete element method

Ecosystem photosynthesis regulates soil respiration on a diurnal scale with a short-term time lag in a coastal wetland

Although increasing evidence has provided that soil respiration is strongly related to recent canopy photosynthesis, doubts remain as to the extent to which primary productivity controls soil respiratory and the speed of the link between soil respiration and photosynthesis. Based on the automated measurements of soil respiration and eddy covariance measurements of ecosystem photosynthesis (i.e. gross primary production, GPP) in a coastal wetland, we assessed the speed of link between ecosystem photosynthesis and soil respiration on the diurnal scale, and quantified the control of the ecosystem primary production on diurnal soil respiration. On the diurnal scale, the time of daily peak soil respiration lagged GPP but preceded soil temperature on both sunny and cloudy days. Daytime soil respiration was significantly linearly correlated with GPP with a lag of 1.5 h on sunny days and 1 h on cloudy days, respectively. By taking advantage of the natural shift of sunny and cloudy days without disturbance to the plant-soil system, our results also indicated that the changes in soil temperature and GPP together explained 53% of the changes in daytime soil respiration rates between sunny days and adjacent cloudy days. Under the same soil temperature, changes in soil respiration rates were strongly correlated with changes in GPP between sunny days and adjacent cloudy days. We therefore conclude that recent canopy photosynthesis regulates soil respiration on a diurnal scale with a short-term time lag. Thus, it is necessary to take into account the influence of photosynthesis on soil respiration in order to accurately simulate the magnitude and variation of soil respiration, especially at short and medium temporal scales. (C) 2013 Elsevier Ltd. All rights reserved.Although increasing evidence has provided that soil respiration is strongly related to recent canopy photosynthesis, doubts remain as to the extent to which primary productivity controls soil respiratory and the speed of the link between soil respiration and photosynthesis. Based on the automated measurements of soil respiration and eddy covariance measurements of ecosystem photosynthesis (i.e. gross primary production, GPP) in a coastal wetland, we assessed the speed of link between ecosystem photosynthesis and soil respiration on the diurnal scale, and quantified the control of the ecosystem primary production on diurnal soil respiration. On the diurnal scale, the time of daily peak soil respiration lagged GPP but preceded soil temperature on both sunny and cloudy days. Daytime soil respiration was significantly linearly correlated with GPP with a lag of 1.5 h on sunny days and 1 h on cloudy days, respectively. By taking advantage of the natural shift of sunny and cloudy days without disturbance to the plant-soil system, our results also indicated that the changes in soil temperature and GPP together explained 53% of the changes in daytime soil respiration rates between sunny days and adjacent cloudy days. Under the same soil temperature, changes in soil respiration rates were strongly correlated with changes in GPP between sunny days and adjacent cloudy days. We therefore conclude that recent canopy photosynthesis regulates soil respiration on a diurnal scale with a short-term time lag. Thus, it is necessary to take into account the influence of photosynthesis on soil respiration in order to accurately simulate the magnitude and variation of soil respiration, especially at short and medium temporal scales. (C) 2013 Elsevier Ltd. All rights reserved

Numerical Investigation on Infiltration and Runoff in Unsaturated Soils with Unsteady Rainfall Intensity

Modeling infiltration into soil and runoff quantitative evaluations is very significant for hydrological applications. In this paper, a flow model of unsaturated soils was established. A computational process of soil water content and runoff prediction was presented that combines an analytical solution with numerical approaches. The solutions have good agreements with the experimental results and other infiltration solutions (Richards numerical solution and classical Green–Ampt solution). We analyzed the effects on cumulative infiltration and runoff under three conditions of rainfall intensity with same average magnitude. These rainfall conditions were (Case 1) decreasing rainfall, (Case 2) steady rainfall, and (Case 3) increasing rainfall, respectively. The results show that the cumulative infiltration in Case 1 is the highest among the three cases. The cumulative runoff under condition of Case 3 is smaller than that of decreasing rainfall at the initial stage, which then becomes larger at the later stage. The time of runoff under the conditions of Case 1 is earliest among the three rainfall conditions, which is about 50% earlier than Case 3. Therefore, project construction for urban flood control should pay more attention to urban flood defense in increasing rainfall weather than other rainfall intensities under the same average magnitude. The approaches presented can be utilized to easily and effectively evaluate infiltration and runoff as a theoretical foundation

Study on Multiobjective Modeling and Optimization of Offshore Micro Integrated Energy System considering Uncertainty of Load and Wind Power

Offshore micro integrated energy systems (OMIESs) are the basis of offshore oil and gas engineering and play an important role in developing and utilizing marine resources. By introducing offshore wind power generation, the carbon emissions of offshore micro integrated energy systems can be effectively reduced; however, greater challenges have been posted to the reliable operation due to the uncertainty. To reduce the influence brought by the uncertainty, a multiobjective optimization model was proposed based on the chance-constrained programming (CCP); the operating cost and penalty cost of natural gas emission were selected as objectives. Then, the improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the model efficiently. Finally, the numerical studies verified the efficiency of the proposed algorithm, as well as the validity and feasibility of the proposed model in improving the economy of OMIES under uncertainty