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It is of great practical significance to manufacture ceramic membranes with good reusability. We used a macromolecular gel network for in situ enhancement of a reticulated skeleton ceramic (RSC) membrane. The prepared RSC membranes were firstly characterized to determine their physical and chemical properties. The sample calcined at 1400 °C has a porosity of 41.66 %, a pore size of 0.34 μm, a mechanical strength of 4.53 MPa, and a permeability of 63.92 L m−1 h−1 bar−1. This membrane can effectively reduce the content of total organic carbon (TOC) (80 %) and calcium ion (>85 %). In addition, the flux of RSC fouled by alginate, calcium ions, or their mixture is effectively recovered by simple chemical rinsing using sodium hydroxide and ethylenediaminetetraacetic acid.

Global warming is a major abiotic stress factor, which limit rice production. Exploiting the genetic basis of the natural variation in heat resistance at different reproductive stages among diverse exotic Oryza germplasms can help breeding heat-resistant rice cultivars. Here, we identified a stable quantitative trait locus (QTL) for heat tolerance at the heading stage on chromosome 5 (qHTH5) in O. rufipogon Griff. The corresponding gene, HTH5, pertains to the pyridoxal phosphate-binding protein PLPBP (formerly called PROSC) family, which is predicted to encode pyridoxal phosphate homeostasis protein (PLPHP) localized to the mitochondrion. Overexpression of HTH5 increased the seed-setting rate of rice plants under heat stress at the heading stage, whereas suppression of HTH5 resulted in greater susceptibility to heat stress. Further investigation indicated that HTH5 reduces reactive oxygen species accumulation at high temperatures by increasing the heat-induced pyridoxal 5'-phosphate (PLP) content. Moreover, we found that two SNPs located in the HTH5 promoter region are involved with its expression level and associated with heat tolerance diversity. These findings suggest that the novel gene HTH5 might have great potential value for heightening rice tolerance to heat stress to the on-going threat of global warming.

Microporous ceramics with slag gradient distribution were prepared by interlayer bonding methods, using silicon dioxide and silicon nitride as the main raw materials. The material performances of gradient ceramics and uniform ceramics were discussed, and the adsorption effects of Cd (Ⅱ), Pb (Ⅱ) between them were compared. The experimental results show a flexural strength of gradient ceramics of 10.67 MPa, bonding strength of the bonding layer of 15.28 MPa, and only a 0.89% difference in the line shrinkage of the gradient layer of different slag contents, indicating that it is feasible to utilize interlayer bonding methods to prepare gradient ceramics. The maximum adsorption quantity of Cd (II), Pb (II) of gradient ceramics can reach 3.48 mg/g and 4.40 mg/g, respectively. For an average slag content of 17.5 wt%, gradient ceramics exhibited high permeability flux equivalent to ceramic with 25 wt% slag content and heavy metal adsorption amount equivalent to ceramic with 20 wt% slag content. Overall, the gradient ceramics prepared by interlayer bonding method can effectively improve the removal efficiency of adsorbent and the overall filtration efficiency.

As the core of an irrigation system, microporous ceramic emitters (MPCEs) are closely related to the design, operation, and management of underground irrigation systems. In this study, computational fluid dynamics (CFD), an artificial neural network (ANN), and a multi-objective genetic algorithm (MOGA) were used to investigate the hydraulic performance of an MPCE and conduct parameter optimisation. A CFD software package was used to analyse the influence of the working parameters, structural parameters, and material properties on the flow characteristics of MPCE. Subsequently, an ANN and MOGA were used to optimise fabrication cost, flow rate, and flow index of the emitter. The results showed that a decrease in the bottom thickness or wall thickness of the MPCE increased the flow index of the emitter and the sensitivity of the flowrate to changes in pressure. Low working pressure was conducive to maintaining the active irrigation characteristic of the MPCE but the flowrate decreased. For crops with low water requirement, these conditions are ideal. The flow in the MPCE microchannel was mainly affected by the viscous resistance, whereas the inertial resistance only had an effect when the flow velocity was large. For field applications, the parameters can be optimised in the range obtained by the MOGA optimisation depending on the requirements of crop water demand, irrigation quality, and fabrication cost to achieve optimal irrigation performance. The results of this study provide references for the standardised fabrication of MPCEs.

Oryza sativa ssp. javanica rice varieties exhibit a wide variation in the phenotypes of several important agronomic traits, including grain quality, grain shape, plant architecture, disease resistance, and high adaption to an unfavorable environment, indicating a great potential for rice improvement. DNA molecular markers are basic and critical tools in genetic analysis and gene mining. However, only a few whole-genome variation analyses have been performed in Oryza sativa ssp. Javanica (tropical japonica rice), and this has hampered the utilization of such an important resource. In this study, the length of insertions/deletions variation greater larger than 10 bp from 10 Oryza sativa ssp. indica rice and 10 Oryza sativa ssp. tropical japonica rice were extracted by using the Nipponbare genome as a reference. A total of 118 primer pairs which were almost evenly distributed on each chromosome corresponding to the loci of InDels were designed by the Primer 5 program. We confirmed 85 InDel markers from 60 rice varieties, including indica and tropical japonica, by running polyacrylamide gels. The InDel markers function like SSRs in identifying hybrids, calculating genetic distance, constructing the genetic linkage map, and gene mining. The InDel markers developed in this study might help in genetic studies and to investigate the tropical japonica rice varieties.

Developing an ultra-thin polyamide selective layer with sufficient mechanical robustness on a highly porous ceramic substrate is challenging for removing heavy metal ions from wastewater. We synthesized a reliable ceramic-polyamide membrane by assembling nanocomposite interlayers of alumina and carbon black on the kaolin substrate. The surface morphology, pore size distribution, and roughness of ceramic substrates were improved by introducing the nanocomposite interlayer. The corresponding optimized water flux, Pb(II), and Cd(II) removal efficiency are 2.75 L m

Application of Zinc (Zn) is considered an effective measure to reduce Cadmium (Cd) uptake and toxicity in Cd-contaminated soils for many plant species. However, interaction between Zn and Cd in rice plant is complex and uncertain. In this study, four indica rice cultivars were selected to evaluate the effect of Zn exposure in an EGTA-buffered nutrient solution under varying Zn activities and a field level of Cd activity to characterize the interaction between Zn and Cd in rice. Severe depression in shoots' biomass, tiller number, and SPAD (Soil and Plant Analyzer Development) value were found at both Zn deficiency and Zn phytotoxicity levels among four tested rice cultivars. There existed a strong antagonism interaction between Zn and Cd in both shoot and root from Zn deficiency to Zn phytotoxicity. The reduction of Cd accumulation in roots and shoots could be explained by the competition between Zn and Cd as well as the dilution effect of increasing biomass. The conflicting effect of Zn supply on Cd uptake may be attributed to the increasing transfer ratio of Cd from root to shoot with the increasing Zn2+ activities and the strong depression of Fe and Mn in shoots with the increasing Zn2+ activities as well as the variation of genotypes. Balance between Zn and Cd should be considered in field application.

In subsurface irrigation, emitter orifices can become clogged by root intrusion. Using the technologies of subsurface drip irrigation, porous ceramic moulding and 3D printing, a new ceramic patch type subsurface drip irrigation line (CP-SDIL) with a simple structure was developed. The CP-SDIL consists of a plastic pipe, a plastic patch, a porous ceramic water-seepage pad and a rubber leakage-proof gasket. The CP-SDIL discharge can be adjusted by changing the material of the ceramic water-seepage pad which is the core component. The CP-SDIL pressure–discharge relationship is linear, and the flow region index is one. The working pressure and the ceramic materials had a significant influence on the discharge of water from the CP-SDIL into the soil. The higher the ceramic porosity and the working pressure, the larger the discharge and the movement of the wetting front. Based on a theoretical analysis and using the reference value for the soil saturation zone radius, an equation for calculating the discharge from CP-SDIL into the soil was developed. The results of this study can be used as a reference for the promotion and application of CP-SDIL.

Jujube (Ziziphus jujuba Mill.) is one of the most optimal fruit trees for economy and ecology in many semiarid regions. However, with water as a scarce resource, the strategy for irrigation and applied nitrogen (Napp) management need to be identified. The goal of this project was to determine the effects of irrigation and Napp on jujube yield, water use efficiency (WUE) and agronomic nitrogen use efficiency (ANUE), and the optimal level of soil water content (SWC) and Napp for jujube under surge-root irrigation (SRI) in a semiarid region. Experiments were conducted during the jujube growing seasons (May–October) of 2014 and 2015 in northern Shaanxi in China that included three levels of SWC, i.e. 60–85%θ (I1) (mass water content, simplified as %θ), 50–75%θ (I2), 40–65%θ (I3), and four levels of Napp, i.e. 0.75 (N1), 0.50 (N2), 0.25 (N3) and 0.00 kg N plant−1 (N4). The treatments were arranged in a strip-plot design with complete randomized blocks with three replications. For both years, irrigation and Napp had significant (P

High temperature (HT) stress is a major environmental stress that limits agricultural production worldwide. Discovery and application of genes promoting high temperature tolerance is essential to enhance crop tolerance to heat stress. Proteins associated with chaperone and protein folding plays an important role in the high temperature stress response of plants. MTH1745 (MtPDI), a disulfide isomerase-like protein (PDI) with a chaperone function and disulfide isomerase activity from Methanothermobacter thermautotrophicus delta H, was selected for studying the heat stress tolerance using an ectopic expression method in rice. Through molecular identification via quantitative real-time PCR and western blot, we demonstrated that the MtPDI gene was expressed stably in transgenic rice. Heat stress tolerance and survival ratio were significantly improved in seedling transgenic rice. At the same time, proline content, superoxide dismutase (SOD) and peroxidase (POD) activities were increased in MtPDI transgenic rice with a reduced malondialdehyde (MDA) content. Moreover, increased content of thiols group was discovered in transgenic plants. These results indicate that heterologous expression of MtPDI from extremophiles could confer heat stress tolerance of transgenic rice through the accumulation of proline content, the synergistic increase of the antioxidant enzymes activity and elevated production of more thiols group, which finally ameliorated the oxidative damage.

It is of great significance to develop a new gravity-driven filter to remove water pollutants, but it is still challenging. Here, a novel and simple strategy is demonstrated to manufacture fly ash (FA) ceramic foams showing a three-dimensional interconnected porous structure, with multiwalled carbon nanotubes (MWCNTs) implanted by combining carbamate grafting and polydimethylsiloxane coating. The polydimethylsiloxane formed a physical coating on the carbamate group, generating an effective thermal insulating layer on the outer side of the entire MWCNT. The FA foam, which shows a sufficient adsorption capacity for Pb(II) (51.67 ± 1.17 mg g−1) and Cd(II) (30.12 ± 0.37 mg g−1) at pH = 5, T = 25 °C, has a 96.33%, 95.12%, 89.50% removal efficiency for Cd(II), Pb(II), and particulate pollutants, and exhibits excellent recycling performance. This paper provides new opportunities to fabricate gravity-driven filters with low energy consumption for wastewater treatment.

Compared with root-associated habitats, little is known about the role of microbiota inside other rice organs, especially the rhizome of perennial wild rice, and this information may be of importance for agriculture. Oryza longistaminata is perennial wild rice with various agronomically valuable traits, including large biomass on poor soils, high nitrogen use efficiency, and resistance to insect pests and disease. Here, we compared the endophytic bacterial and archaeal communities and network structures of the rhizome to other compartments of O. longistaminata using 16S rRNA gene sequencing. Diverse microbiota and significant variation in community structure were identified among different compartments of O. longistaminata. The rhizome microbial community showed low taxonomic and phylogenetic diversity as well as the lowest network complexity among four compartments. Rhizomes exhibited less phylogenetic clustering than roots and leaves, but similar phylogenetic clustering with stems. Streptococcus, Bacillus, and Methylobacteriaceae were the major genera in the rhizome. ASVs belonging to the Enhydrobacter, YS2, and Roseburia are specifically present in the rhizome. The relative abundance of Methylobacteriaceae in the rhizome and stem was significantly higher than that in leaf and root. Noteworthy type II methanotrophs were observed across all compartments, including the dominant Methylobacteriaceae, which potentially benefits the host by facilitating CH4-dependent N2 fixation under nitrogen nutrient-poor conditions. Our data offers a robust knowledge of host and microbiome interactions across various compartments and lends guidelines to the investigation of adaptation mechanisms of O. longistaminata in nutrient-poor environments for biofertilizer development in agriculture.

Background Drought is a global environmental stress that limits crop yields. Microbial communities control many biogeochemical processes, and a predictive understanding of how crop microbial communities assemble in response to drought stress is central to addressing the challenges caused by drought. Little is known about the microbiome assembly processes in rice-ecosystems, particularly with regard to their environmental adaptation. Wild rice may serve as a source of superior drought tolerance candidate for rice breeding. There is an urgent need to explore wild rice resistance mechanisms to drought stress. Here, we evaluated the effect of drought stress on the microbial community recruitment and assembly in the endosphere (leaf, stem, and root) and rhizosphere of Oryza longistaminata. Results Species replacement was the dominant process shaping microbial community composition under drought stress. O. longistaminata recruited the phyla Actinobacteria and Fusobacteria, the genus Streptomyces, and phototrophic prokaryotes to improve its fitness. The host exerted strong effects on microbiome assembly, and the responses of the microbial community structure to the drought environment showed above- and belowground patterns. Drought reduced taxonomic α-diversity and destabilized co-occurrence network properties in the leaves and stems, but not in the roots and rhizosphere. Drought promoted the restructuring and strengthening of belowground network links to more strongly interconnect network properties. The drought response of the microbiome was phylogenetically conserved. Stochastic (neutral) processes acted on microbial community reassembly in response to drought stress across all four compartments. Conclusions Our results provide new insight into the mechanisms through which drought alters microbial community assembly in drought-tolerant wild rice and reveal a potential strategy for manipulating plant microbiomes to improve crop fitness.

Deploying deep learning models on embedded systems has been challenging due to limited computing resources. The majority of existing work focuses on accelerating image classification, while other fundamental vision problems, such as object detection, have not been adequately addressed. Compared with image classification, detection problems are more sensitive to the spatial variance of objects, and therefore, require specialized convolutions to aggregate spatial information. To address this need, recent work introduces dynamic deformable convolution to augment regular convolutions. However, this will lead to inefficient memory accesses of inputs with existing hardware. In this work, we harness the flexibility of FPGAs to develop a novel object detection pipeline with deformable convolutions. We show the speed-accuracy tradeoffs for a set of algorithm modifications including irregular-access versus limited-range and fixed-shape. We then Co-Design a Network CoDeNet with the modified deformable convolution and quantize it to 4-bit weights and 8-bit activations. With our high-efficiency implementation, our solution reaches 26.9 frames per second with a tiny model size of 0.76 MB while achieving 61.7 AP50 on the standard object detection dataset, Pascal VOC. With our higher accuracy implementation, our model gets to 67.1 AP50 on Pascal VOC with only 2.9 MB of parameters-20.9x smaller but 10% more accurate than Tiny-YOLO., Github repo: https://github.com/DequanWang/CoDeNet arXiv:2002.08357 is the preliminary version of this paper

Quantization is a promising approach for reducing the inference time and memory footprint of neural networks. However, most existing quantization methods require access to the original training dataset for retraining during quantization. This is often not possible for applications with sensitive or proprietary data, e.g., due to privacy and security concerns. Existing zero-shot quantization methods use different heuristics to address this, but they result in poor performance, especially when quantizing to ultra-low precision. Here, we propose ZeroQ , a novel zero-shot quantization framework to address this. ZeroQ enables mixed-precision quantization without any access to the training or validation data. This is achieved by optimizing for a Distilled Dataset, which is engineered to match the statistics of batch normalization across different layers of the network. ZeroQ supports both uniform and mixed-precision quantization. For the latter, we introduce a novel Pareto frontier based method to automatically determine the mixed-precision bit setting for all layers, with no manual search involved. We extensively test our proposed method on a diverse set of models, including ResNet18/50/152, MobileNetV2, ShuffleNet, SqueezeNext, and InceptionV3 on ImageNet, as well as RetinaNet-ResNet50 on the Microsoft COCO dataset. In particular, we show that ZeroQ can achieve 1.71\% higher accuracy on MobileNetV2, as compared to the recently proposed DFQ method. Importantly, ZeroQ has a very low computational overhead, and it can finish the entire quantization process in less than 30s (0.5\% of one epoch training time of ResNet50 on ImageNet). We have open-sourced the ZeroQ framework\footnote{https://github.com/amirgholami/ZeroQ}., Comment: CVPR 2020

In remote agricultural areas, electrical energy is usually deficient for pumping water into greenhouses. Photovoltaic (PV) panels and wind generators are considered suitable options for power supply. The reliability of hybrid generation water pumping depends primarily on the number of system components, which should be adapted to the local climatic conditions and crop irrigation schedule. In this study, a universal size optimization model is established to optimize the configuration of a hybrid PV-wind-battery (PWB) generation system. The climatic conditions and crop irrigation schedule are parameterized in the model. Minimization of the annual cost of the hybrid PWB system is the objective function. The constraints include the battery state of charge (SOC) and the power supply reliability, which consists of the loss of power supply (δLPS) and the excess energy (δEX). The numbers of PV panels and batteries, as well as the rated power of the wind generator, are the decision variables. The optimization model of the PWB generation system is solved using a particle swarm optimization (PSO) algorithm based on penalty function. The model is then applied to determine the optimal configuration of a water pumping system for a greenhouse used to grow tomatoes. Measured climatic data are used in the optimization process, which is conducted in the month of maximum irrigation water requirement (August). The optimal results for this greenhouse are two PV panels and two batteries, and the rated power of the wind generator is 375 W. Furthermore, field experiments are performed to validate the optimization model. The field experiment results show that the total output power of the PV panels and wind generator during 15 d are 41.478 kW and 6.235 kW, respectively. The total load power of the pump is 36.965 kW. The field experiments demonstrate that the optimal results are able to meet the power requirements of the water pumping system and the sizing optimization model is appropriate.

Emitter discharge is one of the most important parameters considered in the design, operation, and management of subsurface irrigation systems. The emitter discharge, if properly chosen, can eliminate surface runoff and minimize deep percolation water losses. The discharge from a ceramic emitter depends on the working pressure head and the ceramic hydraulic conductivity, so it is important to determine the optimal working levels for these two design parameters. In this work, it is confirmed that the HYDRUS-2D predictions of the cumulative infiltration and the horizontal wetting front are in good agreement with experimental results, and that the Hydrus-2D model can be used to accurately simulate soil water movement under subsurface irrigation with ceramic emitters. Additional simulations with HYDRUS-2D were used to study the effects of various design parameters (i.e. working pressure head and ceramic hydraulic conductivity) on emitter discharges in soils, deep percolation and soil wetting fronts. Results show that both the working pressure head and ceramic hydraulic conductivity have significant impact on the discharge of emitters in soil, and the deep percolation water losses. The emitter discharge in soil decreases with time and finally stabilizes. When the working pressure head and ceramic hydraulic conductivity are higher, the stable discharge (emitter discharge in soil at 120 h) is greater, and this situation may increase the risk of deep percolation. The relationship between the working pressure head, ceramic hydraulic conductivity, and stable discharge is developed as a power function. To satisfy the water requirements of trees with an active layer of root systems down to about 0–100 cm in the Loess Plateau in China and reduce the risk of deep percolation, it is recommended that the working pressure head should be 20–50 cm of water and the ceramic hydraulic conductivity should be between 0.1 and 1.9 cm h−1.

The ubiquitin 26S proteasome system (UPS) is critical for enabling plants to alter their proteomes to integrate internal and external signals for the photoperiodic induction of flowering. We previously demonstrated that HAF1, a C3HC4 RING domain-containing E3 ubiquitin ligase, is essential to precisely modulate the timing of Heading Date1 accumulation and to ensure appropriate photoperiodic responses under short-day conditions in rice (Oryza sativa). However, how HAF1 mediates flowering under long-day conditions remains unknown. In this study, we show that OsELF3 (EARLY FLOWERING3) is the direct substrate of HAF1 for ubiquitination in vitro and in vivo. HAF1 is required for maintaining the circadian rhythm of OsELF3 accumulation during photoperiodic responses in rice. In addition, the haf1 oself3 double mutant headed as late as oself3 plants under long-day conditions. An amino acid variation (L558S) within the interaction domain of OsELF3 with HAF1 greatly contributes to the variation in heading date among japonica rice accessions. The japonica accessions carrying the OsELF3(L)-type allele are found at higher latitudes, while varieties carrying the OsELF3(S)-type allele are found at lower latitudes. Taken together, our findings suggest that HAF1 precisely modulates the diurnal rhythm of OsELF3 accumulation to ensure the appropriate heading date in rice.

FPGAs provide a flexible and efficient platform to accelerate rapidly-changing algorithms for computer vision. The majority of existing work focuses on accelerating image classification, while other fundamental vision problems, including object detection and instance segmentation, have not been adequately addressed. Compared with image classification, detection problems are more sensitive to the spatial variance of objects, and therefore, require specialized convolutions to aggregate spatial information. To address this, recent work proposes dynamic deformable convolution to augment regular convolutions. Regular convolutions process a fixed grid of pixels across all the spatial locations in an image, while dynamic deformable convolutions may access arbitrary pixels in the image and the access pattern is input-dependent and varies per spatial location. These properties lead to inefficient memory accesses of inputs with existing hardware. In this work, we first investigate the overhead of the deformable convolution on embedded FPGA SoCs, and then show the accuracy-latency tradeoffs for a set of algorithm modifications including full versus depthwise, fixed-shape, and limited-range. These modifications benefit the energy efficiency for embedded devices in general as they reduce the compute complexity. We then build an efficient object detection network with modified deformable convolutions and quantize the network using state-of-the-art quantization methods. We implement a unified hardware engine on FPGA to support all the operations in the network. Preliminary experiments show that little accuracy is compromised and speedup can be achieved with our co-design optimization for the deformable convolution.

Subsurface irrigation has been achieved by using ceramic emitters, pitchers, pots and ceramic tubes, which have gained a certain degree of interest in arid regions due to their efficient use of water. Research on the formation of wetting patterns around the ceramic emitter is essential for the design of irrigation system. In this study, numerical simulations were carried out to investigate the effects of emitter installation method, emitter buried depth, emitter structural parameters, irrigation doses and initial soil water content on the wetting patterns in clay loam with Hydrus-2D. Finally, two field application experiments were conducted to test the practicality and reliability of simulation results. The simulation results were in good agreement with the experimental data. Results showed, emitter installation method had the least effect on the wetting pattern. A 25 cm buried depth would be suit for irrigating vegetables, a 45 cm deep buried depth would suit for irrigating fruit trees. The structure parameters had a significant effect on cumulative fluxes and horizontal wetting front, the structural parameters (emitter length is 7.00 cm, emitter external diameter is 1.25 cm, and emitter inner diameter is 0.60 cm) would be a better fabricate parameters for ceramic emitter. Wetting front increased with increasing irrigation doses and initial water content. To prevent percolation, when the initial water content was high, it should be better to cut down the irrigation duration of ceramic emitter. The field results indicated that Hydrus-2D could be used to investigate the suitable parameters for ceramic emitter in subsurface irrigation systems and determine the suitable arrangement and operation mode of ceramic emitter.

Low temperature is an environmental stress factor that is always been applied in research on improving crop growth, productivity, and quality of crops. Polyunsaturated fatty acids (PUFAs) play an important role in cold tolerance, so its genetic manipulation of the PUFA contents in crops has led to the modification of cold sensitivity. In this study, we over-expressed an &omega, 3 fatty acid desaturase from Glycine max (GmFAD3A) drove by a maize ubiquitin promoter in rice. Compared to the wild type (ZH11), ectopic expression of GmFAD3A increased the contents of lipids and total PUFAs. Seed germination rates in GmFAD3A transgenic rice were enhanced under low temperature (15 &deg, C). Moreover, cold tolerance and survival ratio were significantly improved in GmFAD3A transgenic seedlings. Malondialdehyde (MDA) content in GmFAD3A transgenic rice was lower than that in WT under cold stress, while proline content obviously increased. Meanwhile, the activities of superoxide dismutase (SOD), hydroperoxidase (CAT), and peroxidase (POD) increased substantially in GmFAD3A transgenic rice after 4 h of cold treatment. Taken together, our results suggest that GmFAD3A can enhances cold tolerance and the seed germination rate at a low temperature in rice through the accumulation of proline content, the synergistic increase of the antioxidant enzymes activity, which finally ameliorated the oxidative damage.