Assessing soil nitrous oxide emission as affected by phosphorus and nitrogen addition under two moisture levels

Agricultural soils are deficient of phosphorus （P） worldwide. Phosphatic fertilizers are therefore applied to agricultural soils to improve the fertility and to increase the crop yield. However, the effect of phosphorus application on soil N2O emissions has rarety been studied. Therefore, we conducted a laboratory study to investigate the effects P addition on soil N2O emissions from P deficient alluvial soil under two levels of nitrogen （N） fertilizer and soil moisture. Treatments were arranged as follows： P （0 and 20 mg P kg-1） was applied to soil under two moisture levels of 60 and 90% water filled pore space （WFPS）. Each P and moisture treatment was further treated with two levels of N fertilizer （0 and 200 mg N kg-1 as urea）. Soil variables including mineral nitrogen （NH4＋-N and NO3--N）, available P, dissolved organic carbon （DOC）, and soil N2O emissions were measured throughout the study period of 50 days. Results showed that addition of P increased N2O emis- sions either under 60% WFPS or 90% WFPS conditions. Higher N2O emissions were observed under 90% WFPS when compared to 60% WFPS. Application of N fertilizer also enhanced N2O emissions and the highest emissions were 141 μg N2O kg-1 h-1 in P＋N treatment under 90% WFPS. The results of the present study suggest that P application markedly increases soil N2O emissions under both low and high soil moisture levels, and either with or without N fertilizer application.

Analysis of erbium doped holey fiber using fundamental space filling mode

Erbium-doped holey fiber with hexagonal lattice was modeled by using effective index method. In order to calculate the equivalent step index of the periodic structure of the cladding holey optical fiber, all-vectorial fundamental space filling mode approach was utilized. By using EHll mode, we have numerically solved the rate equations of a three-level pumping scheme for a fiber laser. The obtained results have shown a good agreement with the other experimental results, recently. The results have predicted amplifiers with gain efficiencies as high as 10 dB/mW.

A Knowledge Graph-Based Deep Learning Framework for Efficient Content Similarity Search of Sustainable Development Goals Data

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'resources.Sustainable Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future generations.Scholars can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this work.We propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph store.First,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is described.Then,a thorough case study in a distributed knowledge graph environment experimentally evaluates our framework.The results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare organizations.Our approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval times.It facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

Design of a modified circular-cut multiband fractal antenna

This paper presents a modified circular-cut multiband fractal antenna with good radiation patterns designed for digital cellular system（DCS）, personal communication system（PCS）, 2.4/5.2/5.8 GHz wireless local area networks（WLAN） and 2.5/3.5/5.5 GHz worldwide interoperability for microwave access（WiMAX） applications simultaneously. Originally, the modified circular monopole antenna is designed to resonate at around 2.1 GHz and 3.6 GHz. After subtracting the circular iterative tree fractal structure, it can produce three other resonances at around 5.6 GHz, 6.47 GHz and 7.89 GHz. Besides, as the number of iterations increases, not only do the new frequency bands appear（it demonstrates the good self-similarity property of the proposed antenna）, but also the operating bands shift from high frequency to low frequency（it shows the well space filling property）. Furthermore, the proposed antenna owns a compact structure, which can achieve the 5.28 dBi of relative high gain. And the measured results are basically accordant to simulated results, which proves the effectiveness of the proposed antenna.