Artificial Intelligence-Assisted Multiparameter Size Discrimination of Silver Nanoparticles through Electrochemical Collision.

Single particle collision is an important tool for size analysis at the individual particle level; however, due to complex dynamic behaviors of nanoparticles on the surface of an electrode, the accuracy of size discrimination is limited. A silver (Ag) nanoparticle (NP) was chosen as the research target, and the dynamic behavior of Ag NPs was simplified by enhancing adsorption between Ag NP and Au ultramicroelectrode (UME) in alkaline media. Immediately after, accurate dynamic and thermodynamic information on single Ag NP was accurately extracted from collision events, including current intensity, transferred charge, and duration time. On the basis that there were differences between parameters of different-sized Ag NPs, multiparameter size discrimination was proposed, which improved the accuracy compared to single-parameter discrimination. More intriguingly, multiparameter analysis was combined with artificial intelligence, a tool adept at processing multidimensional data, for the first time. Finally, artificial intelligence-assisted multiparameter size discrimination was successfully used to intelligently distinguish mixed Ag NPs, with an optimal accuracy of more than 95%. To sum up, the artificial intelligence-assisted multiparameter method showed an excellent ability to quickly achieve the most accurate size discrimination of nanoparticles at the level of individual particle and provide an effective guidance for the application of nanoparticles.

Zinc oxide nanoparticles enhanced rice yield, quality, and zinc content of edible grain fraction synergistically.

Zinc oxide nanoparticles (ZnO NPs) have been widely used in agriculture as a new type of Zn fertilizer, and many studies were conducted to evaluate the effect of ZnO NPs on plant growth. However, there are relatively few studies on the effects of application methods and appropriate dosages of ZnO NPs on rice yield, quality, grain Zn content, and distribution. Therefore, in the 2019 and 2020, field trials were conducted with six ZnO NPs basal application dosages of no ZnO NPs, 3.75 kg hm-2, 7.5 kg hm-2, 15 kg hm-2, 30 kg hm-2, and 60 kg hm-2, and the effects of ZnO NPs application on rice yield, quality, grain Zn content, and distribution were investigated. The results demonstrated that applying ZnO NPs in Zn-deficient soils (available Zn < 1.0 mg kg-1) increased rice grain yield by 3.24%-4.86% and 3.51%-5.12% in 2019 and 2020, respectively. In addition, ZnO NPs improved the quality of rice by increasing the head milling rate, reducing chalky grain percentage, and increasing the taste value and breakdown of rice. In terms of Zn accumulation in rice, ZnO NPs application significantly increased the Zn content in both milled rice and brown rice, compared with no Zn treatment, in 2019 and 2020, Zn content in milled rice significantly increased by 20.46%-41.09% and 18.11%-38.84%, respectively, and in brown rice significantly increased by 25.78%-48.30% and 20.86%-42.00%, respectively. However, the Zn fertilizer utilization gradually decreased with increasing ZnO NPs application dosage. From the perspective of yield, rice quality, Zn fertilizer utilization, and Zn accumulation, basal application of 7.5 kg-30 kg hm-2 ZnO NPs is beneficial for rice yield and quality improvement and rice Zn accumulation. This study effectively demonstrated that ZnO NPs could be a potential high-performed fertilizer for enhancing rice yield, quality, and zinc content of edible grain fraction synergistically.

Zinc Oxide Nanoparticles Foliar Application Effectively Enhanced Zinc and Aroma Content in Rice (Oryza sativa L.) Grains.

The search for an effective zinc fertilizer and its application method to effectively increase zinc content and enhance aroma in rice grains is a crucial objective. In this study, a 2-year field plot experiment was conducted to investigate the influence of ZnO NPs foliar spraying on rice quality, grain zinc and aroma content, along with exploring the physiological mechanisms underlying these effects. Our results demonstrated that the rice breakdown value and taste value of foliar spraying zinc oxide nanoparticles were improved by 31.0-41.7% and 8.2-13.0% compared with CK (control treatment involved spraying water), improving the tasting and steaming quality of rice. While Fe and Cu content in grains decreased for the application of zinc oxide nanoparticles, zinc oxide nanoparticles foliar spraying significantly increased the zinc content and accumulation of grains by 33.6-65.1% and 37.8-74.7%, respectively. Further analysis showed that the sprayed zinc oxide nanoparticles achieved effective enrichment of zinc in edible parts and increased the final bioavailability of Zn. In addition, foliar spraying of zinc oxide nanoparticles significantly increased activities of nitrate reductase and glutamine synthetase in leaves, which elevated nitrogen content in leaves and grains, and ultimately enhanced 2-acetyl-1-pyrroline (2-AP) content in grains at maturity by 6.1-21.4% compared to CK. Our findings indicated that zinc oxide nanoparticles can be practically applied as a foliar fertilizer at the gestation for quality improvement, zinc enrichment and aroma enhancement of rice grains.

Current Lifetime of Single-Nanoparticle Electrochemical Collision for In Situ Monitoring Nanoparticles Agglomeration and Aggregation.

In situ monitoring of the agglomeration/aggregation process of nanoparticles (NPs) is crucial because it seriously affects cell entry, biosafety, catalytic performance of NPs, and so on. Nevertheless, it remains hard to monitor the solution phase agglomeration/aggregation of NPs via conventional techniques such as electron microscopy, which requires sample pretreatment and cannot represent native state NPs in solution. Considering that single-nanoparticle electrochemical collision (SNEC) is powerful to detect NPs in solution at the single-particle level, and the current lifetime, which refers to the time that current intensity decays to 1/e of the original value, is skilled in distinguishing different sized NPs, herein, a current lifetime-based SNEC has been developed to distinguish a single Au NP (d = 18 nm) from its agglomeration/aggregation. Based on this, the agglomeration/aggregation process of small-sized NPs and the discrimination of agglomeration vs aggregation have been carefully investigated at the single-particle level. Results showed that the agglomeration/aggregation of Au NPs (d = 18 nm) in 0.8 mM HClO4 climbed from 19% to 69% over two hours, whereas there was no visible granular sediment, and Au NPs tended to agglomerate rather than aggregate irreversibly under normal conditions. Hence, the proposed current lifetime-based SNEC could serve as a complementary method to in situ monitor the agglomeration/aggregation of small-sized NPs in solution at the single-particle level and provide effective guidance for the practical application of NPs.

Single-Nanoparticle Collision Electrochemistry Biosensor Based on an Electrocatalytic Strategy for Highly Sensitive and Specific Detection of H7N9 Avian Influenza Virus.

Single-nanoparticle collision electrochemistry (SNCE) has gradually become an attractive analytical method due to its advantages in analytical detection, such as a fast response, low cost, low sample consumption, and in situ real-time detection of analytes. However, the biological analyte's direct detection based on the SNCE blocking mode has the problems of low sensitivity and specificity. In this work, an SNCE biosensor based on SNCE electrocatalytic strategy was used for the detection of H7N9 AIV. Nucleic acid aptamers were introduced to recognize the target virus (H7N9 AIV). After the recognition event, ssDNA1 was released and hybridized with another ssDNA2. Owing to the nicking endonuclease Nt.AlwI-mediated target nucleic acid cyclic amplification, one virus particle can indirectly induce the release of 4.2 × 106 Au NPs that can be counted by the SNCE electrocatalytic strategy. The high conversion efficiency greatly improved the detection sensitivity, and the detection limit was as low as 24.3 fg/mL. Therefore, the constructed biosensor can achieve a highly sensitive and specific detection of H7N9 AIV and show a great potential in bioanalytical application.

Interactions of Vallisneria natans and Iron-Oxidizing Bacteria Enhance Iron-Bound Phosphorus Formation in Eutrophic Lake Sediments.

Submerged macrophyte restoration and in situ phosphorus (P) passivation are effective methods for the control of internal P loading from sediments. This study explored the synergistic effects of Vallisneria natans and iron (Fe)-oxidizing bacteria (IOB) on internal P loading from eutrophic freshwater lake sediments by taking into account Fe-bound P (FeP) formation and associated bacterial community structures. Sediment samples were prepared in glass tanks under four treatments, namely no V. natans planting or IOB inoculation (control), planting V. natans without IOB inoculation (Va), planting V. natans with IOB inoculation (Va-IOB), and planting V. natans with autoclaved IOB inoculation (Va-IOB[A]). Compared with the control, all three treatments with V. natans (Va, Va-IOB, and Va-IOB[A]) had significantly decreased organic matter contents and increased redox potential in sediments (p < 0.05), at the rapid growth and mature stages of V. natans. Planting V. natans with and without IOB inoculation also decreased the total P (TP) and Fe-P concentrations in sediments. Conversely, Fe3+ concentrations, Fe3+/Fe2+ ratios, and the proportions of Fe-P in TP all increased in sediments planted with V. natans, especially under the Va-IOB treatment (p < 0.05). Furthermore, bacterial community diversity increased in sediments due to the presence of V. natans. The relative abundances of IOB (including Acidovorax and Chlorobium) increased from the transplanting to the rapid growth stage of V. natans and then decreased afterwards. In the later stages, the relative abundances of IOB and their ratios to Fe-reducing bacteria were the highest under the Va-IOB treatment. Accordingly, synergistic interactions between V. natans and IOB could enhance Fe-P formation and reduce TP concentrations in eutrophic lake sediments by altering sediment physicochemical properties and Fe oxidation-related bacterial community structures.

Current Lifetime of Single-Nanoparticle Collision for Sizing Nanoparticles.

Accurate size analysis of nanoparticles (NPs) is vital for nanotechnology. However, this cannot be realized based on conventional single-nanoparticle collision (SNC) because the current intensity, a thermodynamic parameter of SNC for sizing NPs, is always smaller than the theoretical value due to the effect of NP movements on the electrode surface. Herein, a size-dependent dynamic parameter of SNC, current lifetime, which refers to the time that the current intensity decays to 1/e of the original value, was originally utilized to distinguish differently sized NPs. Results showed that the current lifetime increased with NP size. After taking the current lifetime into account rather than the current intensity, the overlap rates for the peak-type current transients of differently sized Pt NPs (10 and 15 nm) and Au NPs (18 and 35 nm) reduced from 73 and 7% to 45 and 0%, respectively, which were closer to the theoretical values (29 and 0%). Hence, the proposed SNC dynamics-based method holds great potential for developing reliable electrochemical approaches to evaluate NP sizes accurately.

High atmospheric wet nitrogen deposition and major sources in two cities of Yangtze River Delta: Combustion-related NH3 and non-fossil fuel NOx.

High ammonia (NH3) and nitrogen oxide (NOx) emissions are related to serious air pollution in urban areas and the negative impacts of excessive reactive nitrogen (N) deposition on many ecosystems. However, whether there is a relationship between N deposition rates and their sources with urbanization or not remains unclear in many areas. Here, we investigated the deposition rates of ammonium (NH4+), nitrate (NO3-), dissolved organic N, and water-insoluble particular N from July 2017 to June 2018 at two urban and two suburban sites in the Yangtze River Delta (YRD). The δ15N values of precipitation NH4+ and NO3- were measured, and major sources were analyzed using a Bayesian isotope mixing model. Wet N deposition rates were higher in Yangzhou (developing city, 20.3-22.7 kg N ha-1 yr-1) than those in Nanjing (developed city, 19.4-20.5 kg N ha-1 yr-1), and were higher at urban sites (20.4-22.5 kg N ha-1 yr-1) than those at suburban sites (18.7-20.3 kg N ha-1 yr-1). δ15N values of precipitation NH4+ increased with an increase in precipitation pH because ambient acidity affects the equilibrium isotope fractionation between NH3 and NH4+ and wet scavenging coefficients of NH3 and particulate NH4+. For NH4+, combustion-related NH3 sources (62%-65% with 5.5-6.4 kg N ha-1 yr-1, including coal combustion, vehicle exhaust, and biomass burning) contributed more than volatilization NH3 sources (35%-38% with 2.9-3.9 kg N ha-1 yr-1, including fertilizer application and waste volatilization). For NO3-, non-fossil fuel NOx sources (50%-63% with 3.4-4.1 kg N ha-1 yr-1, including biomass burning and microbial N cycle) were comparable to fossil fuel NOx sources (37%-50% with 2.4-3.4 kg N ha-1 yr-1, including coal combustion and vehicle exhaust). This study evidenced high N deposition rates and the importance of combustion-related NH3 emissions and non-fossil fuel NOx emissions in city areas of the YRD.

The influences of soil sulfate content on the transformations of nitrate and sulfate during the reductive soil disinfestation (RSD) process.

The transformations and products of sulfate (SO42-) and nitrate (NO3-), especially the influences of SO42- content on the transformations during RSD process, are unclear. In this study, a series of soil SO42- contents (from 333 to 3000 mg S kg-1) were prepared before RSD treatment. The results indicated that nearly all the cumulative NO3- (>98.6%) was removed and not affected by the soil SO42- content. The 15N recovery results showed that 0.57-1.24% and 2.94-4.59% of NO3- translated into ammonium (NH4+) and organic N, respectively, and high SO42- contents stimulated the processes of NO3- dissimilatory reduction and NO3- immobilization. The soluble SO42- contents decreased by 397-922 mg S kg-1, but the contents of total sulfur, sulfide, and sulfate precipitation varied slightly after RSD, indicating that the decreased SO42- was mainly immobilized into organic sulfur in all soils. In addition, a fraction of decreased SO42- was adsorbed to the soil with a relatively high SO42- content. The leaching of SO42- was high (42.9-602 mg S kg-1) during the RSD process, and the leaching amounts increased with increasing soil SO42- content. In terms of the gases emitted from the transformations of NO3- and SO42-, the cumulative emissions of nitrous oxide (N2O) and six sulfurous gases (hydrogen sulfide, carbonyl sulfide, carbon disulfide, methyl mercaptan, dimethyl sulfide, and dimethyl disulfide) were in the ranges of 17.1-21.2 mg N kg-1 and 7.78-23.5 µg S kg-1, respectively, during the whole RSD process. The emissions of sulfurous gases were inhibited by high soil SO42- content, but the N2O emissions were unaffected. In conclusion, the soil SO42- content influenced the transformations of NO3- and SO42- during RSD process, and the SO42- leaching and N2O emissions might threaten the environment which should be concerned.

Clinical Implementation of Automated Treatment Planning for Rectum Intensity-Modulated Radiotherapy Using Voxel-Based Dose Prediction and Post-Optimization Strategies.

PURPOSE: This study aims to demonstrate the feasibility of clinical implementation of automated treatment planning (ATP) using voxel-based dose prediction and post-optimization strategies for rectal cancer on uRT (United Imaging Healthcare, Shanghai, China) treatment planning system. METHODS: A total of 180 previously treated rectal cancer cases were enrolled in this study, including 160 cases for training, 10 for validation and 10 for testing. Using CT image data, planning target volumes (PTVs) and contour delineation of the organs at risk (OARs) as input and three-dimensional (3D) dose distribution as output, a 3D-Uet DL model was developed. Based on the voxel-wise prediction dose distribution, intensity-modulated radiation therapy (IMRT) plans were then generated automatedly using post-optimization strategies, including a complex clinical dose target metrics homogeneity index (HI) and conformation index (CI). To evaluate the performance of the proposed ATP approach, the dose-volume histogram (DVH) parameters of OARs and PTV and the 3D dose distributions of the plan were compared with those of manual plans. RESULTS: By combining clinical post-optimization strategies, the automatically generated treatment plan can achieve better homogeneous PTV coverage and dose sparing for OARs except the mean dose for femoral-head compared with the use of the mean square error objective function alone. Compared with the manual plan, no statistically significant differences in HI, CI or global maximum dose were found. The manual plans perform slightly better than plans with post-optimization strategies in other dosimetric indexes, but these plans are still within clinical requirements. CONCLUSIONS: With the help of clinical post-optimization strategies, the proposed new ATP solution can generate IMRT plans that are within clinically acceptable levels and comparable to plans manually generated by dosimetrists.

A Preliminary Experience of Implementing Deep-Learning Based Auto-Segmentation in Head and Neck Cancer: A Study on Real-World Clinical Cases.

PURPOSE: While artificial intelligence has shown great promise in organs-at-risk (OARs) auto segmentation for head and neck cancer (HNC) radiotherapy, to reach the level of clinical acceptance of this technology in real-world routine practice is still a challenge. The purpose of this study was to validate a U-net-based full convolutional neural network (CNN) for the automatic delineation of OARs of HNC, focusing on clinical implementation and evaluation. METHODS: In the first phase, the CNN was trained on 364 clinical HNC patients' CT images with annotated contouring from routine clinical cases by different oncologists. The automated delineation accuracy was quantified using the Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD). To assess efficiency, the time required to edit the auto-contours to a clinically acceptable standard was evaluated by a questionnaire. For subjective evaluation, expert oncologists (more than 10 years' experience) were randomly presented with automated delineations or manual contours of 15 OARs for 30 patient cases. In the second phase, the network was retrained with an additional 300 patients, which were generated by pre-trained CNN and edited by oncologists until to meet clinical acceptance. RESULTS: Based on DSC, the CNN performed best for the spinal cord, brainstem, temporal lobe, eyes, optic nerve, parotid glands and larynx (DSC >0.7). Higher conformity for the OARs delineation was achieved by retraining our architecture, largest DSC improvement on oral cavity (0.53 to 0.93). Compared with the manual delineation time, after using auto-contouring, this duration was significantly shortened from hours to minutes. In the subjective evaluation, two observes showed an apparent inclination on automatic OARs contouring, even for relatively low DSC values. Most of the automated OARs segmentation can reach the clinical acceptance level compared to manual delineations. CONCLUSIONS: After retraining, the CNN developed for OARs automated delineation in HNC was proved to be more robust, efficiency and consistency in clinical practice. Deep learning-based auto-segmentation shows great potential to alleviate the labor-intensive contouring of OAR for radiotherapy treatment planning.

Size-Resolved Single Entity Collision Biosensing for Dual Quantification of MicroRNAs in a Single Run.

Limited to the accuracy of size resolution, single entity collision biosensing (SECBS) for multiplex immunoassays remains challenging, because it is difficult to get the true value of nanoparticle (NP) sizes based on the current intensity due to the complex movement of NPs on the electrode surface. Considering that the size-dependent movement of NPs meanwhile will generate a characteristic current shape, in this work, the huge difference in the current rise time of 5 and 15 nm Pt NPs colliding on an Au ultramicroelectrode (d = 30 µm) was originally used to develop a size-resolved SECBS for multiplex immunoassays of miRNAs. The limit concentration that can be detected was 0.5 fM. Compared with conventional electrochemical biosensors for multiplex immunoassays, for the size-resolved SECBS, one does not need to worry about potential overlapping. Therefore, the proposed method demonstrates a promising potential for the application of SECBS in multiplex immunoassays.

Ultrasensitive Electrochemiluminescence Biosensor Based on Closed Bipolar Electrode for Alkaline Phosphatase Detection in Single Liver Cancer Cell.

An ultrasensitive electrochemiluminescence (ECL) biosensor was proposed based on a closed bipolar electrode (BPE) for the detection of alkaline phosphatase (ALP). For most of the BPE-ECL biosensors, an effective signal amplification strategy was the key to enhance the sensitivity of the system. Herein, the signal amplification strategy of the enzyme catalysis was utilized in the BPE-ECL system. Au nanoparticles (NPs) were electrodeposited on the cathode surface of the ITO electrode to improve the stability and sensitivity of the signal. Compared with the previous BPE-ECL biosensors, the sensitivity was increased by at least 3 orders of magnitude. The biosensor showed high sensitivity and specificity of ALP detection with a detection limit of as low as 3.7 aM. Besides, it was further applied to the detection of ALP in different types of cells and successfully realized ALP detection in single Hep G2 cell, which had a huge application prospect in single biomolecule detection or single cell analysis.

Excitation and emission dual-wavelength confocal metalens designed directly in the biological tissue environment for two-photon micro-endoscopy.

With the advantages of completely controlling the phase, amplitude, and polarization in subwavelength range, metalenses have drawn intensive attentions in high resolution two-photon micro-endoscopic fluorescence imaging system. However, chromatic dispersion and severe scattering of biological tissue significantly reduce excitation-collection efficiency in the traditional two-photon imaging system based on traditional metalenses designed in the air background. Here, an excitation and emission dual-wavelength confocal and polarization-insensitive metalens designed in the biological tissue environment was proposed by adopting the composite embedding structure and spatial multiplexing approach. The metalens with numerical aperture (NA) of 0.895 can focus the excitation (915 nm) and emission (510 nm) beams to the same focal spot in the mouse cortex. According to the theoretical simulation of two-photon fluorescence imaging, the lateral resolution of the collected fluorescent spots via the proposed metalens can be up to 0.42 µm. Compared to the metalens designed in the air environment, the collection efficiency of fluorescent spot is improved from 5.92% to 14.60%. Our investigation has opened a new window of high resolution and minimally invasive imaging in deep regions of biological tissues.

Applied current thermoacoustic imaging for biological tissues.

BACKGROUND: The large differences of electrical characteristics can be used to reflect the physiological and pathological changes about biological tissues, and it can provide evidence for the early diagnosis and treatment of cancer in potential applications. OBJECTIVE: This paper describes a method called Applied Current Thermoacoustic Imaging (ACTAI) and explores the theory and demonstrates a low conductivity numerical simulation and fresh pork experimental studies. METHODS: In this paper, firstly, the principle of ACTAI is studied. In ACTAI, a target is applied with a microsecond width Gaussian pulse current. Then the target absorbs Joule heat and expands instantaneously, sending out thermoacoustic waves. The waves contain the conductivity information of the target. The waves received by sound transducers are processed by the time inversion method to reconstruct the sound source distribution of the target to illustrate the conductivity information of the target. Secondly, a square model with low conductivity was used as a target to conduct numerical simulation of ACTAI. Lastly, a fresh pork experiment study was conducted. RESULTS: The presented experimental results suggest that ACTAI can identify the conductivity changes information of the target with perfect imagery contrast and deep penetration. CONCLUSION: The ACTAI modality would benefit from the noncontact measurement and can be convenient for clinical application.

Enhanced removal of heavy metal ions from aqueous solution using manganese dioxide-loaded biochar: Behavior and mechanism.

In this study, a redox precipitation method was used to load manganese dioxide (MnO2) nanoparticles on biochar (BC) (BC@MnO2) pyrolyzed from the invasive water hyacinth, and the adsorption of Cd(II),Cu(II), Zn(II), and Pb(II) was investigated. Several techniques were used to characterize the adsorbents. The results revealed that the BC surface was covered by many intertwined thin amorphous MnO2 nanosheets, which significantly increased its specific surface area and pore volume. The adsorption of heavy metal ions by BC was negligible, whereas the MnO2-containing adsorbents exhibited a high capacity for adsorbing heavy metal ions. However, the MnO2-normalized adsorption amount decreased with increasing MnO2 load and was largely unchanged at MnO2 loads of 26.6% to 30.2%. The capacity for adsorbing heavy metal ions of BC@MnO2 was pH-dependent, but the adsorption affinity was unaffected by coexisting ions. Column tests revealed that BC@MnO2 with a load of 26.6% had a high capacity for removing heavy metal ions from simulated and real electroplating wastewater. Therefore, BC@MnO2 with a load of 26.6% shows promise as a regenerable adsorbent for removing heavy metal ions from water/wastewater. This study could lay an essential foundation to develop a win-win strategy for heavy metal ions removal from wastewater using biochar derived from water hyacinth.

Fluorescent carbon quantum dots synthesized using phenylalanine and citric acid for selective detection of Fe3+ ions.

A facile, economical and one-step hydrothermal method was used to synthesize fluorescent carbon dots by utilizing citric acid as carbon source and phenylalanine to provide nitrogen. The as-prepared fluorescence carbon dots had strong blue light emission around 440 nm. As confirmed by UVvis absorption, X-ray photoelectron spectroscopic, Fourier transform infrared spectroscopy and transmission electron microscope characterization, the carbon dots were small and very stable in water for using as a fluorescent probe. It was also found that the fluorescence of the carbon dots could be quenched in the presence of Fe3+ ions, and the quenching rate was linear with the concentration of Fe3+ ions. We here proposed a static quenching mechanism about the fluorescence of the Phe-CDs could be selectively quenched by Fe3+ ions, which was because these Fe3+ ions could easily combine with the hydroxyl or carboxyl groups on the surface of Phe-CDs and induced aggregation. In addition, the pH had little effect on the fluorescence intensity of the Phe-CDs and maintained excellent fluorescence intensity even under extreme pH value conditions and could be used for the detection of Fe3+ ions. We have demonstrated that the method using the carbon dots for Fe3+ ions detection was rapid, reliable, and selective with a detection limit as low as 0.720 µM and a dynamic range from 5.0 to 500.0 µM. Moreover, the results of determination Fe3+ ions in tap water samples indicated that the presented method has potential for practical application in environmental metal analysis.

Response of denitrification in paddy soils with different nitrification rates to soil moisture and glucose addition.

Denitrification is one of the most important N loss pathways in paddy soil. The nitrification rate is a key natural feature for controlling denitrification N loss in paddy soil. However, the relationship between nitrification and denitrification under different conditions in paddy soil remains unknown. By using 15N tracing, we investigated the response of denitrification loss to soil moisture and glucose addition in six paddy soils, whose net nitrification rates ranged from 0.36 mg N kg-1 day-1 to 5.72 mg N kg-1 day-1. The soils were amended with or without glucose to simulate root exudates at rates of 100 mg kg-1 of soil and incubated under either 60% water holding capacity (WHC) or flooded (2 cm depth) at 25 °C for 15 days. Denitrification loss was calculated by the unrecovered 15NH4+. The results showed that the soil nitrification rate significantly affected the N recovery form and denitrification loss of the applied 15N. NH4+ was the main recovered N form of the applied 15N in soil with a low nitrification rates. Denitrification losses were higher in the high nitrification rate soil than soil with low nitrification rate in all treatments. The correlation between denitrification and nitrification rates was well fit by Michaelis-Menten kinetics during the incubation, irrespective of soil moisture and glucose addition, and the R2 ranged from 0.801 to 0.977 (P < 0.05). Glucose addition did not stimulate denitrification under either 60% WHC or flooded conditions. The results showed that nitrification rate, rather than labile organic supply, controlled denitrification in paddy soil.

Excessive application of pig manure increases the risk of P loss in calcic cinnamon soil in China.

Soil phosphorus (P) is a critical factor affecting crop yields and water environmental quality. To investigate the degree of loss risk and forms of soil P in calcic cinnamon soil, the P fraction activities in soils were analysed using chemical methods, combined with an in situ field experiment. Seven treatments were set in this study, including control (unfertilized), no P fertilizer (No-P), mineral P fertilizer (Min-P), low (L-Man) and high (H-Man) quantities of pig manure, Min-P+L-Man, and Min-P+H-Man. The results showed that manure fertilizer could not only significantly increase maize yield but could also enhance the accumulation of soil P in organic and inorganic forms. After 23years of repeated fertilization, the soil Olsen-P contents respectively showed 64.7-, 43.7- and 31.9-fold increases in the Min-P+H-Man, Min-P+L-Man and H-Man treatments, while the soil Olsen-P in Min-P treatment only increased 23.7-fold. The soil Olsen-P thresholds ranged from 22.59 to 32.48mgkg-1 in calcic cinnamon soil to maintain a higher maize yield as well as a lower risk of P loss. Therefore, long-term excessive manure application could obviously raise the content of soil Olsen-P and increase the risk of P loss in calcic cinnamon soil.

[Simulation research on magnetoacoustic effect and thermoacoustic effect of pulsed magnetic excitation].

According to the coupling relationship of electromagnetic field and acoustic field when electromagnetic field irradiates low conductivity objects, we carried out a study on the magnetoacoustic effect and thermoacoustic effect in pulsed magnetic excitation. In this paper, we provide the pressure wave equation in pulsed magnetic excitation based on the theory of electromagnetic field and acoustic wave propagation. A 2-dimensional coil carrying current and a circular thin sheet model were constructed to simulate the physical imaging environment. The transient electromagnetic field was simulated using finite element method. Numerical studies were conducted to simulate the pressures excited by magnetoacoustic effect and thermoacoustic effect according to the result of electromagnetic simulation. It was shown that the thermoacoustic effect played a leading role in the low conductivity objects on the microsecond Gauss pulsed magnetic excitation, and thermoacoustic effect and magnetoacoustic effect coexisted on the microsecond Gauss pulsed magnetic field and 0.2 T static magnetic field excitation. This study lays the foundation for the further application of magnetoacoustic tomography with magnetic induction and magnetically mediated thermoacoustic imaging.