Exploring site-specific N application rate to reduce N footprint and increase crop production for green manure-rice rotation system in southern China.

Milk vetch (Astragalus sinicus L.) is leguminous green manure (GM) which produces organic nitrogen (N) for subsequent crops and is widely planted and utilized to simultaneously reduce the use of synthetic N fertilizer and its environmental costs in rice systems. Determination of an optimal N application rate specific to the GM-rice system is challenging because of the large temporal and spatial variations in soil, climate, and field management conditions. To solve this problem, we developed a framework to explore the site-specific N application rate for the low-N footprint rice production system in southern China based on multi-site field experiments, farmer field survey, and process-based model (WHCNS_Rice, soil water heat carbon nitrogen simulator for rice). The results showed that a process-based model can explain >83.3% (p < 0.01) of the variation in rice yield, aboveground biomass, crop N uptake, and soil mineral N. Based on the scenario analysis of the tested WHCNS_Rice model, the simple regression equation was developed to implement site-specific N application rates that considered variations in GM biomass, soil, and climatic conditions. Simulation evaluation on nine provinces in southern China showed that the site-specific N application rate reduced regional synthetic N fertilizer input by 29.6 ± 17.8% and 65.3 ± 23.0% for single and early rice, respectively; decreased their total N footprints (NFs) by 23.4% and 49.3%, respectively; and without reduction in rice yield, compared with traditional farming N practices. The reduction in total NF was attributed to the reduced emissions from ammonia volatilization by 35.2%, N leaching by 28.4%, and N runoff by 32.7%. In this study, we suggested a low NF rice production system that can be obtained by combining GM with site-specific N application rate in southern China.

Interfacial phenomenon and Marangoni convection of Fe-C melt on coke substrate under in situ observation.

The interfacial phenomenon between liqiuid iron and coke is important for determining the melting efficiency in the blast furnace iron-making process. In this study, the interaction observed in the case of the iron-carbon (Fe-C) melt on coke substrate was investigated using a high-temperature vacuum wettability test equipment. The Fe-C melt did not wet and spread on the coke substrate with different graphitization degrees (r0) at a high temperature of 1450 °C. The contact angles changed from 124.5° to 105.3°, and the r0 increased from 9.30 to 50.00%, thus indicating a nonwetting state. The deepening of graphitization decreased the contact angle. Thereby, increasing the contact area between liquid iron and the carbonaceous material, which facilitated carbon dissolution. The irregular movements of Fe-C melt were observed in situ during the wetting process. The horizontal force of the droplet caused by interfacial tension and the contact angle; the Marangoni convection owing to the gradient of carbon concentration; and the impulse force caused by the generation, aggregation, and release of SiO bubbles at the interface were attributed to the driving force.

Virus-Host Interactions Drive Contrasting Bacterial Diel Dynamics in the Ocean.

Marine organisms perform a sea of diel rhythmicity. Planktonic diel dynamics have been shown to be driven by light, energy resources, circadian rhythms, and the coordinated coupling of photoautotrophs and heterotrophic bacterioplankton. Here, we explore the diel fluctuation of viral production and decay and their impact on the total and active bacterial community in the coastal and open seawaters of the South China Sea. The results showed that the night-production diel pattern of lytic viral production was concurrent with the lower viral decay at night, contributing to the accumulation of the viral population size during the night for surface waters. The diel variations in bacterial activity, community composition, and diversity were found highly affected by viral dynamics. This was revealed by the finding that bacterial community diversity was positively correlated to lytic viral production in the euphotic zone of the open ocean but was negatively related to lysogenic viral production in the coastal ocean. Such distinct but contrasting correlations suggest that viral life strategies can not only contribute to diversifying bacterial community but also potentially piggyback their host to dominate bacterial community, suggesting the tightly synchronized depth-dependent and habitat-specific diel patterns of virus-host interactions. It further implies that viruses serve as an ecologically important driver of bacterial diel dynamics across the ocean, highlighting the viral roles in bacterial ecological and biogeochemical processes in the ocean.

Biogenic carbon pool production maintains the Southern Ocean carbon sink.

Through biological activity, marine dissolved inorganic carbon (DIC) is transformed into different types of biogenic carbon available for export to the ocean interior, including particulate organic carbon (POC), dissolved organic carbon (DOC), and particulate inorganic carbon (PIC). Each biogenic carbon pool has a different export efficiency that impacts the vertical ocean carbon gradient and drives natural air-sea carbon dioxide gas (CO2) exchange. In the Southern Ocean (SO), which presently accounts for ~40% of the anthropogenic ocean carbon sink, it is unclear how the production of each biogenic carbon pool contributes to the contemporary air-sea CO2 exchange. Based on 107 independent observations of the seasonal cycle from 63 biogeochemical profiling floats, we provide the basin-scale estimate of distinct biogenic carbon pool production. We find significant meridional variability with enhanced POC production in the subantarctic and polar Antarctic sectors and enhanced DOC production in the subtropical and sea-ice-dominated sectors. PIC production peaks between 47°S and 57°S near the "great calcite belt." Relative to an abiotic SO, organic carbon production enhances CO2 uptake by 2.80 ± 0.28 Pg C y-1, while PIC production diminishes CO2 uptake by 0.27 ± 0.21 Pg C y-1. Without organic carbon production, the SO would be a CO2 source to the atmosphere. Our findings emphasize the importance of DOC and PIC production, in addition to the well-recognized role of POC production, in shaping the influence of carbon export on air-sea CO2 exchange.

Adding functional properties to beer with jasmine tea extract.

Hops provide the characteristic bitter taste and attractive aroma to beer; in this study, hops were replaced by jasmine tea extract (JTE) during late-hopping. The addition of JTE improved the beer foam stability 1.52-fold, and increased the polyphenol and organic acid contents. Linalool was the most important aroma compound in hopped (HOPB) and jasmine tea beer (JTB), but other flavor components were markedly different, including dimeric catechins, flavone/flavonol glycosides, and bitter acids and derivatives. Sensory evaluation indicated that addition of JTE increased the floral and fresh-scent aromas, reduced bitterness and improved the organoleptic quality of the beer. The antioxidant capacity of JTB was much higher than that of HOPB. The inhibition of amylase activity by JTB was 30.5% higher than that of HOPB. Functional properties to beer were added by substituting jasmine tea extract for hops during late hopping.

Impact of tea leaves categories on physicochemical, antioxidant, and sensorial profiles of tea wine.

Introduction: Tea is the main raw material for preparing tea wine. Methods: In this research, four types of tea wine were prepared using different categories of tea leaves, including green tea, oolong tea, black tea, and dark tea, and the comparative study looking their physicochemical, sensorial, and antioxidant profiles were carried out. Results: The dynamic changes of total soluble solids, amino acids and ethanol concentrations, and pH were similar in four tea wines. The green tea wine (GTW) showed the highest consumption of total soluble solids and amino acids, and produced the highest concentrations of alcohol, malic, succinic, and lactic acid among all tea wines. The analysis of volatile components indicated the number and concentration of esters and alcohols increased significantly after fermentation of tea wines. GTW presented the highest volatile concentration, while oolong tea wine (OTW) showed the highest number of volatile compounds. GTW had the highest total catechins concentration of 404 mg/L and the highest ABTS value (1.63 mmol TEAC/mL), while OTW showed the highest DPPH value (1.00 mmol TEAC/mL). Moreover, OTW showed the highest score of sensory properties. Discussion: Therefore, the types of tea leaves used in the tea wine production interfere in its bioactive composition, sensorial, and antioxidant properties.

Mass fluxes of dissolved arsenic discharging to the Meghna River are sufficient to account for the mass of arsenic in riverbank sediments.

Shallow (<30 m) reducing groundwater commonly contains abundant dissolved arsenic (As) in Bangladesh. We hypothesize that dissolved As in iron (Fe)-rich groundwater discharging to rivers is trapped onto Fe(III)-oxyhydroxides which precipitate in shallow riverbank sediments under the influence of tidal fluctuations. Therefore, the goal of this study is to compare the calculated mass of sediment-bound As that would be sequestered from dissolved groundwater As that discharges through riverbanks of the Meghna River to the observed mass of As trapped within riverbank sediments. To calculate groundwater discharge, a Boussinesq aquifer analytical groundwater flow model was developed and constrained by cyclical seasonal fluctuations in hydraulic heads and river stages observed at three sites along a 13 km reach in central Bangladesh. At all sites, groundwater discharges to the river year-round but most of it passes through an intertidal zone created by ocean tides propagating upstream from the Bay of Bengal in the dry season. The annualized groundwater discharge per unit width at the three sites ranges from 173 to 891 m2/yr (average 540 m2/yr). Assuming that riverbanks have been stable since the Brahmaputra River avulsed far away from this area 200 years ago and dissolved As is completely trapped within riverbank sediments, the mass of accumulated sediment As can be calculated by multiplying groundwater discharge by ambient aquifer As concentrations measured in 1969 wells. Across all sites, the range of calculated sediment As concentrations in the riverbank is 78-849 mg/kg, which is higher than the observed concentrations (17-599 mg/kg). This discovery supports the hypothesis that the dissolved As in groundwater discharge to the river is sufficient to account for the observed buried deposits of As along riverbanks.

Water Quality Assessment Bias Associated with Long-Screened Wells Screened across Aquifers with High Nitrate and Arsenic Concentrations.

Semi-arid regions with little surface water commonly experience rapid water table decline rates. To hedge against the falling water table, production wells in central Mexico are commonly installed to depths of several hundred meters below the present water table and constructed as open boreholes or perforated casings across their entire length. Such wells represent highly conductive pathways leading to non-negligible flow across chemically distinct layers of an aquifer-a phenomenon known as ambient flow. The objectives of this study were to estimate the rate of ambient flow in seven production wells utilizing an end-member mixing model that is constrained by the observed transient chemical composition of produced water. The end-member chemical composition of the upper and lower layers of an urban aquifer that overlies geothermal heat is estimated to anticipate the future quality of this sole source of water for a rapidly growing urban area. The comprehensive water chemistry produced by seven continuously perforated municipal production wells, spanning three geologically unique zones across the city of San Miguel de Allende in Guanajuato State, was monitored during one day of pumping. The concentration of conservative constituents gradually converged on steady-state values. The model indicates that, relative to the lower aquifer, the upper aquifer generally has higher specific conductance (SC), chloride (Cl), nitrate (NO3), calcium (Ca), barium (Ba) and magnesium (Mg). The lower aquifer generally has a higher temperature, sodium (Na), boron (B), arsenic (As) and radon (Rn). Ambient flow ranged from 33.1 L/min to 225.7 L/min across the seven wells, but this rate for a given well varied depending on which tracer was used. This new 3D understanding of the chemical stratification of the aquifer suggests that as water tables continue to fall, concentrations of geothermally associated contaminants of concern will increase in the near future, potentially jeopardizing the safety of municipal drinking water.

Feature pyramid self-attention network for respiratory motion prediction in ultrasound image guided surgery.

PURPOSE: The robot-assisted automated puncture system under ultrasound guidance can well improve the puncture accuracy in ablation surgery. The automated puncture system requires advanced definition of the puncture location, while the displacement of thoracic-abdominal tumors caused by respiratory motion makes it difficult for the system to locate the best puncture position. Predicting tumor motion is an effective way to help the automated puncture system output a more accurate puncture position. METHODS: In this paper, we propose a self-attention-based feature pyramid algorithm FPSANet for time-series forecasting, which can extract both linear and nonlinear dependencies of time series. Firstly, we use the temporal convolutional network as the backbone to extract different scale time-series features, and the self-attention module is followed to weigh more significant features to improve nonlinear prediction. Secondly, we use autoregressive models to perform linear prediction. Finally, we directly combine the above two kinds of predictions as the final prediction. RESULTS: FPSANet is trained and tested on our private datasets captured from clinical individuals, and we predict the target position after 50 ms, 150 ms, 300 ms and 400 ms. The result shows the evaluation criteria of the MAE is less than 1 mm at 50 ms and 150 ms, and less than 2 mm at 300 ms. Compared with the AR model, bidirectional LSTM and RVM, our method not only outperforms both models in accuracy (AR: ~ 7.7%; bidirectional LSTM: ~ 75.9%; RVM: ~ 76.5%) but is also more stable on different types of respiratory curves. CONCLUSION: Respiratory motion in the liver in actual clinical practice vary widely from person to person, while sometimes having less distinct periodic patterns. Under these conditions, our algorithm has the advantage of excellent stability for prediction on various sequences, and its running time of performing single sequence prediction can meet clinical requirements.

A live-imaging protocol for tracking receptor dynamics in single cells.

Adjacent membrane receptors can show different cellular responses to ligand stimulation. Here, we describe a super-resolution microscopy imaging protocol for tracking the dynamics of two different membrane-bound receptors in single cells. We describe the transfection protocol by electroporation. We detail the imaging procedure for receptors in a single cell. We then outline the data analysis pipeline. We have applied this protocol to imaging of endocytosis of the LOX-1 and AT1 in CHO-K1 cells, but the protocol can be applied to a variety of membrane receptors in other cell lines. For complete details on the use and execution of this protocol, please refer to Takahashi et al. (2021).

PM2.5 induces pulmonary microvascular injury in COPD via METTL16-mediated m6A modification.

Fine particulate matter (PM2.5) exposure is a significant cause of chronic obstructive pulmonary disease (COPD), but the detailed mechanisms involved in COPD remain unclear. In this study, we established PM2.5-induced COPD rat models and showed that PM2.5 induced pulmonary microvascular injury via accelerating vascular endothelial apoptosis, increasing vascular permeability, and reducing angiogenesis, thereby contributing to COPD development. Moreover, microvascular injury in COPD was validated by measurements of plasma endothelial microparticles (EMPs) and serum VEGF in COPD patients. We then performed m6A sequencing, which confirmed that altered N6-methyladenosine (m6A) modification was induced by PM2.5 exposure. The results of a series of experiments demonstrated that the expression of methyltransferase-like protein 16 (METTL16), an m6A regulator, was upregulated in PM2.5-induced COPD rats, while the expression of other regulators did not differ upon PM2.5-induction. To clarify the regulatory effect of METTL16-mediated m6A modification induced by PM2.5 on pulmonary microvascular injury, cell apoptosis, permeability, and tube formation, the m6A level in METTL16-knockdown pulmonary microvascular endothelial cells (PMVECs) was evaluated, and the target genes of METTL16 were identified from a set of the differentially expressed and m6A-methylated genes associated with vascular injury and containing predicted sites of METTL16 methylation. The results showed that Sulfatase 2 (Sulf2) and Cytohesin-1 (Cyth1) containing the predicted METTL16 methylation sites, exhibited higher m6A methylation and were downregulated after PM2.5 exposure. Further studies demonstrated that METTL16 may regulate Sulf2 expression via m6A modification and thereby contribute to PM2.5-induced microvascular injury. These findings not only provide a better understanding of the role played by m6A modification in PM2.5-induced microvascular injury, but also identify a new therapeutic target for COPD.

Interleukin-15 receptor subunit alpha regulates interleukin-15 localization and protein expression in skeletal muscle cells.

NEW FINDINGS: What is the central question of this study? How are the dynamics of interleukin (IL)-15 and its receptors altered during the differentiation of myoblasts into myotubes, and how is IL-15 regulated? What is the main finding and its importance? The mRNA levels of IL-15 and interleukin-2 receptor subunits beta and gamma increase during skeletal muscle differentiation, whereas interleukin-15 receptor subunit alpha (IL-15RA) exhibits different kinetics. IL-15RA regulates the localization and expression of IL-15 at the protein level. ABSTRACT: Interleukin-15 (IL-15) is a myokine in the interleukin-2 (IL-2) family that is generated in the skeletal muscle during exercise. The functional effect of IL-15 involves muscle regeneration and metabolic regulation in skeletal muscle. Reports have indicated that interleukin-15 receptor subunit alpha (IL-15RA) acts by regulating IL-15 localization in immune cells. However, the dynamics of IL-15 and its receptors, which regulate the IL-15 pathway in skeletal muscle differentiation, have not yet been clarified. In this study, we investigated the mechanism of IL-15 regulation using a mouse skeletal muscle cell line, C2C12 cells. We found that the mRNA expression of IL-15, interleukin-2 receptor subunit beta (IL-2RB; CD122) and interleukin-2 receptor subunit gamma (IL-2RG; CD132) increased, but that IL-15RA exhibited different kinetics as differentiation progressed. We also found that IL-15, mainly present in the cytosol, pre-assembled with IL-15RA in the cytosol and fused to the plasma membrane. Moreover, IL-15RA increased IL-15 protein levels. Our findings suggest that genes involved in the IL-15 signalling complex are enhanced with the differentiation of myotubes and that IL-15RA regulates the protein kinetics of IL-15 signalling in skeletal muscle.

FPSN-FNCC: an accurate and fast motion tracking algorithm in 3D ultrasound for image-guided interventions.

The uncertain motions of a target caused by the breath, heartbeat and body drift of a patient can increase the target locating error during image-guided interventions, and that may cause additional surgery trauma. A surgery navigation system with accurate motion tracking is important for improving the operation accuracy and reducing trauma. In this work, we propose an accurate and fast tracking algorithm in three-dimensional (3D) ultrasound (US) sequences for US-guided surgery to achieve moving object tracking. The idea of this algorithm is as follows. Firstly, feature pyramid architecture is introduced into a Siamese network to extract multiscale convolutional features. Secondly, to improve the network discriminative power and the robustness to ultrasonic noise and gain variation, we use the normalized cross correlation (NCC) to calculate the similarity between template block and search block. Thirdly, a fast NCC (FNCC) is proposed, which can perform the real-time tracking. Finally, a density peaks clustering approach is used to compensate the motion of the target and further improve the tracking accuracy. The proposed algorithm is evaluated on a CLUST dataset that includes 22 sets of 3D US sequences, and the mean error of 1.60±0.97 mm compared with manual annotations is obtained. After comparing with other published works, the results show that our algorithm achieves the comparable performance. The ablation study proves that the results benefit from the feature pyramid architecture and FNCC. These findings show that our algorithm may improve the motion tracking accuracy in image-guided interventions.

The endocytosis of oxidized LDL via the activation of the angiotensin II type 1 receptor.

Arrestin-dependent activation of a G-protein-coupled receptor (GPCR) triggers endocytotic internalization of the receptor complex. We analyzed the interaction between the pattern recognition receptor (PRR) lectin-like oxidized low-density lipoprotein (oxLDL) receptor (LOX-1) and the GPCR angiotensin II type 1 receptor (AT1) to report a hitherto unidentified mechanism whereby internalization of the GPCR mediates cellular endocytosis of the PRR ligand. Using genetically modified Chinese hamster ovary cells, we found that oxLDL activates Gαi but not the Gαq pathway of AT1 in the presence of LOX-1. Endocytosis of the oxLDL-LOX-1 complex through the AT1-ß-arrestin pathway was demonstrated by real-time imaging of the membrane dynamics of LOX-1 and visualization of endocytosis of oxLDL. Finally, this endocytotic pathway involving GPCR kinases (GRKs), ß-arrestin, and clathrin is relevant in accumulating oxLDL in human vascular endothelial cells. Together, our findings indicate that oxLDL activates selective G proteins and ß-arrestin-dependent internalization of AT1, whereby the oxLDL-LOX-1 complex undergoes endocytosis.

Tracking 3D ultrasound anatomical landmarks via three orthogonal plane-based scale discriminative correlation filter network.

PURPOSE: In abdominal interventional therapy, accurate motion tracking of the target is regarded as crucial to minimize trauma and optimize dosage delivery. Meanwhile, three-dimensional (3D) ultrasound (US) is an attractive modality to show the real-time motion pattern of the target. In this work, we developed an accurate and robust landmark tracking algorithm for 3D US sequences. METHODS: The proposed algorithm introduces a three orthogonal planes (TOPs) based scale discriminative correlation filter network for 3D US landmarks tracking. First, we couple the fully convolutional network (FCN) with scale discriminative correlation filter (SDCF) to generate an effective tracker. And SDCF is reformulated as a differentiable layer, which ensures the network can perform scale learning and end-to-end training. Next, we train the end-to-end network on millions of natural images. Finally, we convert 3D US image to 2D three-channel image by TOP transformation and feed them to the proposed network for performing online tracking. RESULTS: Online tracking performance was evaluated on the Challenge of Liver Ultrasound Tracking (CLUST) dataset with 22 sets of 3D US sequences, obtaining mean error of 1.63 ± 1.04 mm and 95th percentile (95%ile) error of 3.37 mm, when compared with manual annotations annotated by surgeons. Ablation study indicates that the promising results benefit from SDCF and scale learning, which alleviates the influence from deformation. The findings of the clinical analysis support that the proposed algorithm can work well with different initial patch sizes, which means that our algorithm has potential to lighten the burden of surgeons. CONCLUSIONS: We propose a flexible, accurate and robust landmark tracking algorithm for the image-guided interventions, and our algorithm is comparable with the state-of-the-art approaches. The tracking accuracy and robustness show that our algorithm has potential in 3D US-guided abdominal interventional therapies. Furthermore, more researches are needed to improve the computing speed of the algorithm to achieve real-time tracking.

A pressor dose of angiotensin II has no influence on the angiotensin-converting enzyme 2 and other molecules associated with SARS-CoV-2 infection in mice.

In the early phase of the Coronavirus disease 2019 (COVID-19) pandemic, it was postulated that the renin-angiotensin-system inhibitors (RASi) increase the infection risk. This was primarily based on numerous reports, which stated that the RASi could increase the organ Angiotensin-converting enzyme 2 (ACE2), the receptor of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in rodents. RASi can theoretically antagonize the potential influence of angiotensin II (Ang II) on ACE2. However, while Ang II decreases the ACE2 levels in cultured cells, there is little evidence that supports this phenomenon in living animals. In this study, we tested whether Ang II or Ang II combined with its antagonist would alter the ACE2 and other molecules associated with the infection of SARS-CoV-2. Male C57BL6/J mice were administered vehicle, Ang II (400 ng/kg/min), or Ang II with losartan (10 mg/kg/min) for 2 weeks. ACE2 knockout mice were used as a negative control for the ACE2 assay. We found that both Ang II, which elevated blood pressure by 30 mm Hg, and Ang II with losartan, had no effect on the expression or protein activity of ACE2 in the lung, left ventricle, kidney, and ileum. Likewise, these interventions had no effect on the expression of Transmembrane Protease Serine 2 (TMPRSS2) and Furin, proteases that facilitate the virus-cell fusion, and the expression or activity of Tumor Necrosis Factor α-Convertase (TACE) that cleaves cell-surface ACE2. Collectively, physiological concentrations of Ang II do not modulate the molecules associated with SARS-CoV-2 infection. These results support the recent observational studies suggesting that the use of RASi is not a risk factor for COVID-19.

Rising arsenic concentrations from dewatering a geothermally influenced aquifer in central Mexico.

This study identifies causes of rising arsenic (As) concentrations over 17 years in an inter-montane aquifer system located just north of the Trans-Mexican-Volcanic-Belt in the Mesa central physiographic region that is extensively developed by long-screened production wells. Arsenic concentrations increased by more than 10 µg/L in 14% (3/22) of re-sampled wells. Similarly, in a larger scale analysis wherein As concentrations measured in 137 wells in 2016 were compared to interpolated, baseline concentrations from 246 wells in 1999, As concentrations rose more than 10 µg/L in 30% of wells. Between 1999 and 2016, the percentage of all wells sampled in each basin-wide sampling campaign exceeding the World Health Organization's 10 µg/L drinking water limit increased from 38 to 64%. Principal Components Analysis (PCA), step-wise multiple regression, and Random Forest modeling (RF) revealed that high As concentrations are closely associated with high pH and temperature, and high concentrations of fluoride (F), molybdenum (Mo), lithium (Li), sodium (Na) and silica (Si), but low calcium (Ca) and nitrate (NO3) concentrations. Pumping-induced mixing with hot, geothermally impacted groundwater generates alkaline water through hydrolysis of silicate minerals. The rising pH converts oxyanion sorption sites from positive to negative releasing As (and Mo) to pore waters. The negative correlation between nitrate and As concentrations can be explained by conservative mixing of shallow, young groundwater with geothermally influenced groundwater. Therefore water carrying an anthropogenic contaminant dilutes water carrying geogenic contaminants. This process is enabled by long well screens. Over-exploitation of aquifers in geothermal regions for agriculture can drive As concentrations in water from production wells to toxic levels even as the total dissolved solids remain low.

A Compact Convolutional Neural Network for Surface Defect Inspection.

The advent of convolutional neural networks (CNNs) has accelerated the progress of computer vision from many aspects. However, the majority of the existing CNNs heavily rely on expensive GPUs (graphics processing units). to support large computations. Therefore, CNNs have not been widely used to inspect surface defects in the manufacturing field yet. In this paper, we develop a compact CNN-based model that not only achieves high performance on tiny defect inspection but can be run on low-frequency CPUs (central processing units). Our model consists of a light-weight (LW) bottleneck and a decoder. By a pyramid of lightweight kernels, the LW bottleneck provides rich features with less computational cost. The decoder is also built in a lightweight way, which consists of an atrous spatial pyramid pooling (ASPP) and depthwise separable convolution layers. These lightweight designs reduce the redundant weights and computation greatly. We train our models on groups of surface datasets. The model can successfully classify/segment surface defects with an Intel i3-4010U CPU within 30 ms. Our model obtains similar accuracy with MobileNetV2 while only has less than its 1/3 FLOPs (floating-point operations per second) and 1/8 weights. Our experiments indicate CNNs can be compact and hardware-friendly for future applications in the automated surface inspection (ASI).

Methane and Nitrous Oxide Flux after Biochar Application in Subtropical Acidic Paddy Soils under Tobacco-Rice Rotation.

Biochar amendment is a good means of mitigating methane (CH4) and nitrous oxide (N2O) emissions. However, the effects of biochar amendment on N2O and CH4 reduction in soil under rotation with different soil moisture contents is not well understood. To understand CH4 and N2O flux from soil with biochar amendment under water-unsaturated and water-saturated conditions, a field experiment was conducted in a tobacco-rice rotation field in subtropical China to investigate N2O and CH4 emissions following soil amendment with tobacco straw biochar at rates of 0, 10, 40 and 80 t·ha-1 (B0, B10, B40 and B80, respectively). N2O and CH4 emissions were monitored by a closed-chamber method in the water-unsaturated tobacco (UT) and water-saturated rice (SR) seasons during the 2015 planting season. The soil pH increased from 5.4 in the control to 6.1 in the soil amended with biochar at 80 t·ha-1 in the UT season. During both the UT and SR seasons, with biochar amendment at 40 and 80 t·ha-1, the soil bulk density (BD) decreased, while the soil organic matter (SOM) and available potassium (Av. K) contents increased. N2O flux was significantly greater in UT than in SR in the controls but decreased with the application of biochar during both the UT and SR seasons. The cumulative CH4 emission decreased with the rate of biochar application and the methanotroph pmoA gene copy number in soils and increased with the methanogenic archaea 16Sr DNA gene copy number in soils during the rice-cropping season. These results indicated that biochar amendment could decrease methanogenic archaea and increase of methanotroph pmoA gene, which are the mechanistic origin for CH4 reduction.

Effects of increasing atmospheric CO2 on the marine phytoplankton and bacterial metabolism during a bloom: A coastal mesocosm study.

Increases of atmospheric CO2 concentrations due to human activity and associated effects on aquatic ecosystems are recognized as an environmental issue at a global scale. Growing attention is being paid to CO2 enrichment effects under multiple stresses or fluctuating environmental conditions in order to extrapolate from laboratory-scale experiments to natural systems. We carried out a mesocosm experiment in coastal water with an assemblage of three model phytoplankton species and their associated bacteria under the influence of elevated CO2 concentrations. Net community production and the metabolic characteristics of the phytoplankton and bacteria were monitored to elucidate how these organisms responded to CO2 enrichment during the course of the algal bloom. We found that CO2 enrichment (1000µatm) significantly enhanced gross primary production and the ratio of photosynthesis to chlorophyll a by approximately 38% and 39%, respectively, during the early stationary phase of the algal bloom. Although there were few effects on bulk bacterial production, a significant decrease of bulk bacterial respiration (up to 31%) at elevated CO2 resulted in an increase of bacterial growth efficiency. The implication is that an elevation of CO2 concentrations leads to a reduction of bacterial carbon demand and enhances carbon transfer efficiency through the microbial loop, with a greater proportion of fixed carbon being allocated to bacterial biomass and less being lost as CO2. The contemporaneous responses of phytoplankton and bacterial metabolism to CO2 enrichment increased net community production by about 45%, an increase that would have profound implications for the carbon cycle in coastal marine ecosystems.