804 research outputs found
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Estimating global cropland production from 1961 to 2010
Global cropland net primary production (NPP) has tripled over the last 50 years, contributing 17–45 % to the increase in global atmospheric CO2 seasonal amplitude. Although many regional-scale comparisons have been made between statistical data and modeling results, long-term national comparisons across global croplands are scarce due to the lack of detailed spatiotemporal management data. Here, we conducted a simulation study of global cropland NPP from 1961 to 2010 using a process-based model called Vegetation–Global Atmosphere–Soil (VEGAS) and compared the results with Food and Agriculture Organization of the United Nations (FAO) statistical data on both continental and country scales. According to the FAO data, the global cropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr−1 in the 1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model captured these major trends on global and continental scales. The NPP increased most notably in the US Midwest, western Europe, and the North China Plain and increased modestly in Africa and Oceania. However, significant biases remained in some regions such as Africa and Oceania, especially in temporal evolution. This finding is not surprising as VEGAS is the first global carbon cycle model with full parameterization representing the Green Revolution. To improve model performance for different major regions, we modified the default values of management intensity associated with the agricultural Green Revolution differences across various regions to better match the FAO statistical data at the continental level and for selected countries. Across all the selected countries, the updated results reduced the RMSE from 19.0 to 10.5 TgC yr−1 (∼ 45 % decrease). The results suggest that these regional differences in model parameterization are due to differences in socioeconomic development. To better explain the past changes and predict the future trends, it is important to calibrate key parameters on regional scales and develop data sets for land management history
Deep Drawing of Cylindrical Cup Using Incremental Electromagnetic Assisted Stamping with Radial Magnetic Pressure
AbstractA new forming method named incremental electromagnetic assisted stamping with radial magnetic pressure is proposed to draw a deep cylindrical cup. The method combines with traditional stamping, electromagnetic sheet forming and electromagnetic launch technology. Three types of discharge coils are imbedded in die and blank holder, respectively. The 3D finite element model is set up to predict the complex deformation process. The forming process and principle of the new method are discussed. The values of material flow, stress and thickness in different forming processes are compared. In comparison with traditional stamping, incremental electromagnetic assisted stamping with radial magnetic pressure can significantly increase the value of material at sheet end flow inward, decrease the tensile stress and thickness reduction at the easily broken position, and obtain uniform stress distribution. Therefore, deeper cylindrical cup could be manufactured by incremental electromagnetic assisted stamping with radial magnetic pressure
Domain-Agnostic Molecular Generation with Self-feedback
The generation of molecules with desired properties has gained tremendous
popularity, revolutionizing the way scientists design molecular structures and
providing valuable support for chemical and drug design. However, despite the
potential of language models in molecule generation, they face numerous
challenges such as the generation of syntactically or chemically flawed
molecules, narrow domain focus, and limitations in creating diverse and
directionally feasible molecules due to a dearth of annotated data or external
molecular databases. To this end, we introduce MolGen, a pre-trained molecular
language model tailored specifically for molecule generation. MolGen acquires
intrinsic structural and grammatical insights by reconstructing over 100
million molecular SELFIES, while facilitating knowledge transfer between
different domains through domain-agnostic molecular prefix tuning. Moreover, we
present a self-feedback paradigm that inspires the pre-trained model to align
with the ultimate goal of producing molecules with desirable properties.
Extensive experiments on well-known benchmarks confirm MolGen's optimization
capabilities, encompassing penalized logP, QED, and molecular docking
properties. Further analysis shows that MolGen can accurately capture molecule
distributions, implicitly learn their structural characteristics, and
efficiently explore chemical space. The pre-trained model, codes, and datasets
are publicly available for future research at https://github.com/zjunlp/MolGen.Comment: Work in progress. Add results of binding affinit
De novo transcriptome analysis of the sandworm (Sipunculus nudus) and identification of differentially expressed genes associated with body size
The sandworm (Sipunculus nudus) is an aquatic species of economic importance because of its high nutritional and medicinal value. Under the same culture conditions, substantial individual growth variation is often found in populations of sandworms. However, the genetic mechanisms of individual growth variation are poorly understood. In this study, the transcriptome of the body wall muscle of the sandworm at different growth rates was analyzed by Illumina sequencing and bioinformatics analysis. A total of 185 181 unigenes were obtained after processing raw reads and about 96,824 (47.72%) of them were annotated. Among the annotated transcripts, 418 differentially expressed genes were identified, of which 207 were upregulated and 211 were downregulated in large worms relative to small worms. We identified several genes that had a possible association with individual growth variation. These results will provide insight into the growth mechanism of sandworm, and will further assist in the selective breeding of improved strains of this species
Expatriates, subsidiary autonomy and the overseas subsidiary performance of MNEs from an emerging economy
Despite a growing body of research on the role of expatriates in subsidiary performance, the mechanisms through which expatriates affect subsidiary performance are still the subject of debate. Drawing on the resource dependence theory, we examine the indirect effect of expatriates on subsidiary performance via subsidiary autonomy based on a sample of Chinese multinational enterprises (MNEs). The findings show that an increase in expatriates reduces the level of subsidiary autonomy and thus negatively affects subsidiary performance. We also find that the institutional quality of host countries reinforces the negative impact of expatriates on subsidiary autonomy, but reduces the importance of the latter on subsidiary performance
Ammonia Oxidizing Bacteria Community Dynamics in a Pilot-Scale Wastewater Treatment Plant
Background: Chemoautotrophic ammonia oxidizing bacteria (AOB) have the metabolic ability to oxidize ammonia to nitrite aerobically. This metabolic feature has been widely used, in combination with denitrification, to remove nitrogen from wastewater in wastewater treatment plants (WWTPs). However, the relative influence of specific deterministic environmental factors to AOB community dynamics in WWTP is uncertain. The ecological principles underlying AOB community dynamics and nitrification stability and how they are related are also poorly understood. Methodology/Principal Findings: The community dynamics of ammonia oxidizing bacteria (AOB) in a pilot-scale WWTP were monitored over a one-year period by Terminal Restriction Fragment Length Polymorphism (T-RFLP). During the study period, the effluent ammonia concentrations were almost below 2 mg/L, except for the first 60 days, indicting stable nitrification. T-RFLP results showed that, during the test period with stable nitrification, the AOB community structures were not stable, and the average change rate (every 15 days) of AOB community structures was 10%68%. The correlations between T-RFLP profiles and 10 operational and environmental parameters were tested by Canonical Correlation Analysis (CCA) and Mantel test. The results indicated that the dynamics of AOB community correlated most strongly with Dissolved Oxygen (DO), effluent ammonia, effluent Biochemical Oxygen Demand (BOD) and temperature. Conclusions/Significance: This study suggests that nitrification stability is not necessarily accompanied by a stable AO
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